Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries The most vulnerable trading nations on Earth – the Least Developed Countries and countries from sub-Saharan Africa – have long been Beggar-Thy-Poor-Neighbour: encouraged by Western donors, international development organisations, and economists to integrate their economies into world markets. This volume examines the extent to which such integration was frustrated by Crisis-Era Protectionism and protectionist measures taking since the onset of the Great Recession. Drawing upon the data compiled by Global Trade Alert, an independent Developing Countries protectionist monitoring service, the policy stance towards Least Developed Countries and sub-Saharan African nations – both beggar-thy-neighbour and liberalising – are characterised and their effects analysed by experts knowledgeable about both of these groups of developing countries. The 15th GTA Report Implications for policymaking at the national and international level, including at the G20, are explored. Edited by Simon J. Evenett

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Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries The 15th GTA Report Centre for Economic Policy Research (CEPR)

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Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

The 15th GTA Report

Edited by Simon J. Evenett

GLOB L TR DE a LERT About Global Trade Alert (GTA) Global Trade Alert provides information in real time on state measures taken during the current global economic downturn that are likely to discriminate against foreign commerce. Global Trade Alert is: Independent: GTA is a policy-oriented and research initiative of the Centre for Economic Policy Research (CEPR), an independent academic and policy research think-tank based in London, UK. Simon J. Evenett, the co-director of CEPR’s International Trade and Regional Economics Programme, is the coordinator of the GTA. Comprehensive: GTA complements and goes beyond the WTO, UNCTAD, and OECD’s monitoring initiatives by identifying those trading partners likely to be harmed by state measures. The GTA considers a broader range of policy instruments than other monitoring initiatives. Accessible: The GTA website allows policy-makers, exporters, the media, and analysts to search the posted government measures by implementing country, by trading partners harmed, and by sector. Third parties can report suspicious state measures and governments have the right to reply to any of their measures listed on the website. Transparent: The GTA website represents a major step forward in transparency of national policies, reporting not only the measures taken but identifies the implementing country, trading partners likely harmed, and product lines and sectors affected. Timely: The up-to-date information and informed commentary provided by Global Trade Alert will facilitates assessments of whether the G20 pledge not to “repeat the historic mistakes of protectionism of previous eras” is met, and the bite of multilateral trade rules. For further information, visit www.GlobalTradeAlert.org

About the Centre for Economic Policy Research (CEPR) The Centre for Economic Policy Research is a network of over 800 Research Fellows and Affiliates, based primarily in European universities. The Centre coordinates the research activities of its Fellows and Affiliates and communicates the results to the public and private sectors. CEPR is an entrepreneur, developing research initiatives with the producers, consumers and sponsors of research. Established in 1983, CEPR is a European economics research organization with uniquely wide-ranging scope and activities. The Centre is pluralist and non-partisan, bringing economic research to bear on the analysis of medium- and long-run policy questions. CEPR research may include views on policy, but the Executive Committee of the Centre does not give prior review to its publications, and the Centre takes no institutional policy positions. The opinions expressed in this report are those of the authors and not those of the Centre for Economic Policy Research. CEPR is a registered charity (No. 287287) and a company limited by guarantee and registered in England (No. 1727026). Chair of the Board Guillermo de la Dehesa President Richard Portes Director Richard Baldwin Research Director Kevin Hjortshøj O’Rourke Contents

Foreword vii

1. Beggar-thy-poor-neighbour: The incidence of protectionism in LDCs and Sub-Saharan Africa 1 Simon J. Evenett

Part One: The Impact of Protectionism on Developing Countries

2. Free trade, protectionism and the balance of trade: New empirical insights 13 Evans S. Osabuohien, Uchenna R. Efobi and Ibunkun Beecroft

3. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 25 Adugna Lemi

4. Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 47 Olayinka Idowu Kareem

5. SADC Crisis-era trade policy and its effects on intra-regional trade and investment 63 Albert Makochekanwa and Emson F. Chiwenga

6. The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 71 Bethuel K. Kinuthia, Remco H. Oostendorp and Jacob A. Jordaan

Part Two: Country Specific Data on the Incidence of Crisis-Era Protectionism on the Least Developed Countries and on Africa

Afghanistan 85 Angola 89 Bangladesh 93 Benin 98 Bhutan 102 Burkina Faso 104 Burundi 106 Cambodia 109 Central African Republic 112 Chad 114 Comoros 117 Democratic Republic of the Congo 120 Djibouti 124 Equatorial Guinea 126 vi Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Eritrea 129 Ethiopia 131 Gambia 136 Guinea 139 Guinea-Bissau 142 Haiti 144 Kiribati 146 Lao People’s Democratic Republic 148 Lesotho 150 Liberia 152 Madagascar 155 Malawi 158 Mali 162 Mauritania 165 Mozambique 169 Myanmar 173 Nepal 177 Niger 180 Rwanda 182 Samoa 185 Sao Tome and Principe 187 Senegal 189 Sierra Leone 193 Solomon Islands 197 Somalia 199 Sudan 201 Timor-Leste 206 Togo 208 Tuvalu 212 Uganda 214 United Republic of Tanzania 218 Vanuatu 223 Yemen 225 Zambia 228 Foreword

Global Trade Alert (GTA) was established in 2009 because of the widespread concern that governments would respond to the global financial crisis with 1930s-style across-the board tariff increases. Fortunately, such tariff increases have not materialised, but the work done by GTA has revealed very clearly the widespread implementation of a range of other discriminatory measures, for example industry-specific subsidies and bailouts. Such measures can have a significant impact on the exports, growth and employment levels of a country’s trading partners. For the developing and poor economies, the impact can be substantially greater. Supporting the integration of the poorest nations into the world economy has rightly been a long-standing objective of international development policy. Such integration would, it was argued, improve the allocation of resources, create opportunities to export and to participate in cross-border supply chains, encourage the upgrading of technology, improve productivity growth and reduce poverty. As the global economic crisis unfolded in 2008 and 2009 there were widespread fears that the clock would be turned back on the integration of developing countries into the global economy. It continues to be a cause of major concern today, and especially for many African economies and the least developed countries (LDCs) that have a weak capacity to absorb shocks from the outside, including those generated by trading partners tempted by protectionism. It is important to understand the impact of crisis-inspired protectionism on these countries. GTA has collected a large amount of information on government measures that affect (both beneficially as well as adversely) the commercial interests of African economies and LDCs. GTA also commissioned several studies by independent researchers that were presented at a conference involving policymakers in Accra in June 2012. Drawing upon the data collected by GTA, this volume includes original analyses of the impact of this protectionism on African economies and LDCs. The result is, we hope, an original and important analysis of the impact of crisis-inspired protectionism on African economies and LDCs. We are very grateful to the UK Department for International Development (DFID) for financing this component of GTA’s work and to the other financial supporters of the Global Trade Alert project, including the Canadian International Development Research Centre (IDRC) and the University of St. Gallen. The activities that led to this volume would not have been possible without the enthusiastic cooperation of the African Center for Economic Transformation (ACET), under the very able leadership of Dr. K.Y. Amoako. In addition, Dr. Nicolas Depetris Chauvin, Senior Adviser at ACET, provided crucial intellectual support for the project, and the conference in Ghana was expertly organised by Mrs. Sheila Ochugboju. Thanks are also due to colleagues at CEPR who have provided invaluable support throughout the project; in particular, Viv Davies, Susann Herring and

vii viii Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Anil Shamdasani. We are also grateful for the sustained work of the researchers in the GTA team based at St. Gallen and at various institutions around the world. Phil Thornton helped considerably in getting this manuscript into shape with his superb copy-editing skills. And last but not least, we are again indebted to Simon Evenett for his inclusive approach, unflagging energy and single-minded commitment to the work and development of the GTA initiative. Trade policies and other government policies that are likely to affect foreign commerce are of crucial importance for the poorest nations in the world. This volume adds to the information available on contemporary protectionism and its effects on developing countries and, in so doing, makes it more difficult for anyone to argue that the beggar-thy-neighbour policies inspired by the crisis are inconsequential.

Stephen Yeo Chief Executive Officer, CEPR 2 February 2014 1 Beggar-thy-poor-neighbour: The incidence of protectionism in LDCs and Sub-Saharan Africa

Simon J. Evenett1 University of St. Gallen and CEPR

For the past 30 years, policymakers in developing countries have been encouraged to integrate their economies into world markets by their counterparts in industrialised countries and by officials from international organisations. Much academic research backed up this policy recommendation. If trade in its various forms is so beneficial for development, then it is of interest how the commercial interests of developing countries have fared since the onset of the global economic crisis. This chapter surveys the latest information on the incidence of protectionism in the least developed countries (LDCs) and Sub-Saharan Africa (SSA).

The recent global economic crisis, which spread quickly from the financial sectors of certain industrialised economies throughout the rest of the world economy, did not spare the least developed countries (LDCs) and Sub-Saharan Africa (SSA). While there are differences between and within these two groups2, there is considerable interest in how the countries have fared, not least because they are thought to be particularly vulnerable to external shocks. LDCs and SSA are the focus of many countries’ aid and development policies. Hence, interest comes not only from the legitimate concern for the wellbeing of fellow humans, but also from the desire to enhance the effectiveness of aid policy. A concern often raised in this regard is one of coherence, namely, whether the effectiveness of some of a government’s policies are undermined by other actions taken by that same government. The purpose of this chapter is to assess, using the latest available data from the recently updated Global Trade Alert database, the frequency with which the commercial interests of the LDCs and SSA nations have been affected by foreign beggar-thy-neighbour policies since November 2008, when the G20 (and many other) nations announced that they would eschew protectionism during the crisis. The information presented here not only has implications for assessments of the coherence of other countries’ policies towards the poorest nations on

1 I thank Christina Tzogiou for help in assembling the data for this chapter. All errors are mine. 2 Moreover, there is some overlap with 17 jurisdictions being located in Sub-Saharan Africa and being Least Developed Countries according to the classification of the United Nations. For a list ofthe countries classified as LDCs see http://www.unohrlls.org/en/ldc/25/

1 2 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries earth, but also helps identify which international fora would be most relevant for any initiative to unwind crisis-era protectionism that has likely harmed the LDCs and SSA. Subsequent chapters in this volume examine the determinants of policy choices that affect the commercial interests of the LDCs and SSA and estimate the consequences of these crisis-era policy decisions. Much is at stake for these countries. Together, the least developed countries have a population of 844 million, more than in Western Europe and the US combined. Per capita incomes in the LDCs are much lower, however, than their Western counterparts. According to the World Bank’s World Development Indicators, in 2011 the per-capita income of the LDCs was US$824 in current dollars and, once corrections for differences in the cost of living are made, the per- capita purchasing power adjusted income is US$1,572. The comparable figures for the Sub-Saharan African nations are 876 million, US$1,469, and US$2,363, respectively. In addition to generating, on average, low incomes for their populations, the LDCs and SSA are exposed to the changing fortunes of the world economy. In recent years, exports of goods and services in SSA consistently accounted for around a third of national income. For LDCs the contribution is smaller, but the comparable fraction is not below a quarter. Recessions abroad, then, may well trigger falls in demand for the produce of the LDCs and SSA, thereby jeopardising living standards in those countries as well. Demand shocks are not the only means by which developments abroad can affect the commercial interests of the LDCs and SSA. Attempts by foreign governments to tilt the playing field in favour of domestic commercial interests can erode the profitability and ability of firms in LDCs and SSA to compete in world markets. In what follows, information on the frequency of such beggar- thy-neighbour policies is presented, drawing upon a substantial update of the Global Trade Alert database that was completed in May 2013. The Global Trade Alert (GTA) database contains reports on state measures taken since November 2008 that alter the relative treatment – for better or for worse – of foreign commercial interests in a sector vis-à-vis domestic rivals. Employing the relative treatment standards avoids the pitfalls of defining protectionism in terms of specific government policies, such as tariffs and quotas. This feature is particularly desirable during crises when governments tend to find new ways to tilt the commercial playing field. That the GTA considers all types of commercial interests is important for countries that have substantial expatriate populations working in other jurisdictions, as some LDCs and SSA countries do. The incidence of protectionism in LDCs and Sub-Saharan Africa 3

Figure 1 During 2009-12, Sub-Saharan African commercial interests were hit more often by foreign protectionism than comparable LDC interests 125

100

75

50

25

0 Nov-Dec 2009 2010 2011 2012 Jan-22 May 2008 2013 LDC SSA Source data: Global Trade Alert. May 2013. One indication of the harm done to LDCs’ and SSA’commercial interests is given by Figure 1, which plots the number of times each group of countries have seen their exporters, investors, and overseas workers harmed each year.3 The fact that there is some delay in reporting less transparent protectionist measures may account for the tapering off of the totals over time.4 Still, Figure 1 does show that LDCs and SSA countries were harmed most often in 2009 and 2010, very much in line with when the global incidence of protectionism was highest. If anything, even though both groupings include roughly the same number of members, the incidence of harm to SSA commercial interests is higher than that for LDCs, in particular in 2009 through to 2012. Of course, counts of the number of harmful measures may provide a misleading indication of the extent of harm done. Still, such numbers speak to the fact that the poorest trading nations did not emerge unscathed from crisis-era protectionism. These nations exported products in the same tariff lines affected by foreign policy measures, for example. Indeed, in 2009 of all of the protectionist measures implemented worldwide, 225 adversely affected at least one Sub-Saharan African country.5 As the crisis continued the incidence of harm mounted up, as shown in Tables 1 and 2. In principle, foreign governments could have unwound the beggar- thy-neighbour policies, but this rarely happened. For example, at the time of writing, only 17% of all the protectionist measures faced by the LDC nations and imposed since November 2008 have been removed. A total of 246 protectionist measures affecting the LDCs remain in place. The situation is broadly the same for the SSA nations. The key facts are summarised in Figure 2.

3 These totals include instances when a LDC country adopts a protectionist measure that likely harms another LDC country; likewise, the totals for SSA include harm done by one jurisdiction in that region to another trading partner in that region. Given the interest in South-South trade this choice seems appropriate. 4 Indeed, as a comparison of its reports shows, the first estimates by the Global Trade Alert of each quarter’s protectionist totals have tended to be substantially revised upwards over time. 5 The comparable percentage for the LDCs was 15%. 4 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Figure 2 Plenty of crisis-era protectionism harming LDCs and Sub-Saharan Africa needs to be unwound 350 35

300 30

250 25

200 20

150 15

100 10

Number of measures still in force 50 5 Percentage of harmful measures unwound 0 0 End 2008 End 2009 End 2010 End 2011 End 2012 22-May-13 LDC still in force SSA still in force Source data: Global Trade Alert, May 2013.

Tables 1 and 2 also include information on liberalisation by trading partners that may have benefited SSA and LDCs. In both cases, over 100 foreign measures have been implemented that likely benefit these countries, however the total number of liberalising measures never exceeded 40% of the total number of harmful measures. Put another way, the latter outnumber the former at least 2.5-to-1. The contribution of the G20 nations to the incidence of protectionism and liberalisation affecting LDCs and SSA is roughly the same.6 G20 nations account for around 60-65% of all the measures harming their poorest trading partners. Meanwhile, the G20 nations are responsible for 70-75% of all measures benefiting those trading partners. A mixed record, then, that is definitely worth exploring further. Indeed, Brazil, China, and India alone account for 45 of the 116 liberalising measures that benefited LDCs, an indication of the extent of liberalisation by the “South” that benefits the “South.”

6 Further information on the countries that have harmed SSA and LDC interests the most is given in the appendix to this chapter in Tables 3 and 4. The incidence of protectionism in LDCs and Sub-Saharan Africa 5 G20 72.4 73.5 71.4 63.3 61.5 20.0 of ever of ever beneficial Percentage Percentage measures by measures by implemented G20 G20 61.3 62.3 62.8 61.1 58.8 66.7 of ever of ever harmful Percentage Percentage measures by measures by Measures implemented by the Measures implemented by implemented 0.39 0.38 0.35 0.27 0.27 0.33 Ratio of beneficial to harmful implemented by given date given by measures ever measures ever 5 77 49 26 commercial interests commercial 116 102 Total Total given date given number ever number ever Measures likely to benefit LDC implemented at 17.2 17.9 20.6 23.9 24.7 33.3 given time given Percentage Percentage of measures unwound at unwound h calendar year that implicate LDC commercial interests that implicate LDC commercial h calendar year 73 10 246 220 177 137 given date given Total number Total still in force at still in force commercial interests commercial 97 15 297 268 223 180 Total Total given date given number ever number ever Measures that likely or almost certainly harm LDC implemented at Measures in effect at the end of eac

22/05/2013 31/12/2012 31/12/2011 31/12/2010 31/12/2009 31/12/2008 Date Table 1. Table database. Data extracted 22 May 2013 GTA Source: 6 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries G20 76.0 77.7 78.7 73.2 75.0 25.0 of ever of ever beneficial Percentage Percentage measures by measures by implemented G20 G20 64.7 64.7 65.3 63.7 62.3 62.5 of ever of ever harmful Percentage Percentage measures by measures by Measures implemented by the Measures implemented by implemented 0.38 0.36 0.36 0.30 0.20 0.25 Ratio of beneficial to harmful implemented by given date given by measures ever measures ever interests 4 71 28 146 130 108 Total Total given date given Saharan Africa’s commercial Africa’s Saharan number ever number ever Measures likely to benefit Sub- implemented at 15.1 15.7 18.3 21.5 22.5 25.0 given time given Percentage Percentage of measures unwound at unwound h calendar year that implicate Sub-Saharan Africa’s commercial interests. commercial Africa’s that implicate Sub-Saharan h calendar year 12 327 301 245 186 107 given date given Total number Total still in force at still in force Saharan Africa’s commercial interests commercial Africa’s Saharan 16 385 357 300 237 138 Total Total given date given number ever number ever Measures that likely or almost certainly harm Sub- implemented at Measures in effect at the end of eac

22/05/2013 31/12/2012 31/12/2011 31/12/2010 31/12/2009 Date 31/12/2008 Table 2. Table database. Data extracted 22 May 2013 GTA Source: The incidence of protectionism in LDCs and Sub-Saharan Africa 7

Figure 3 Types of beggar-thy-neighbour measures affecting LDC and SSA commercial interests, percent for each group of total number of times harmed.

9.8 Migration restrictions 8.1

12.1 Export subsidies 8.8

11.1 Non tariff barriers (not otherwise specified) 10.9

13.8 State aid (except export subventions) 14.8

18.9 Export taxes and restrictions 16.4

23.9 Tariff increases 24.9

0 5 10 15 20 25 30 Harming LDCs Harming SSA Source data: Global Trade Alert. May 2013.

Turning now to the types of beggar-thy-neighbour policies that harmed the commercial interests of LDCs and SSA, the main findings are summarised in Figure 3. For each group of nations, this figure reproduces the percentage of the total number of protectionist measures affecting a group that fall into six types of policy instrument. For both LDCs and SSA, export taxes and restrictions and tariff increases together account for more than 40% of measures taken. Interestingly, antidumping, countervailing duty, and safeguard actions (the so- called trade defence measures) by trading partners are not among the top six policy instruments that harmed LDCs and SSA. Subsidies of different types (export and other) account for a quarter of the harmful measures and migration restrictions and non-tariff barriers (not specified elsewhere) account for about a tenth of measures each. This diverse range of policy instruments harming the commercial interests of the LDCs and SSA is significant, as several prevalent categories are not well covered by WTO rules. Even tariffs, the most basic international trade obligation, are not completely covered by multilateral trade agreements – some countries bind less than 100% of their tariffs and many can raise their applied tariffs substantially without hitting their maximum allowable levels. Such findings must call into question the extent to which the LDCs and SSA nations’ commercial interests have actually been protected by binding multilateral trade rules. There is plenty of wiggle room built into the existing patchwork of international rules. Some of the policy instruments that harm LDC and SSA interests are typically not included in regional trade agreements either. Migration measures are particularly politically sensitive in many jurisdictions. Regional trade agreements have tended not to be an effective vehicle for disciplining the resort to subsidies either.7

7 Even the European Union, which on paper has a tough regime on subsidies and state aids, suspended important elements of that regime during the recent global economic crisis. 8 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Ultimately, then, what type of international intiative might benefit the LDCs and SSA? Assuming that further liberalisation by trading partners that specifically benefits the LDCs and SSA is unlikely, then there is always unwinding the crisis- era protectionist measures that have been implemented to date. As noted earlier, less than 18% of such measures affecting the LDCs and SSA have been unwound. Much more, then, could be done. But in what forum? This is where Tables 3 and 4 in the Appendix are helpful, for they identify which countries have implemented the most measures that harm the LDCs and SSA. Initiatives by the G8 countries to unwind their protectionist measures would no doubt help, but would omit countries such as India that have implemented many measures that harm the LDCs and SSA. An initiative by the BRICS countries would leave out plenty of European nations whose crisis-era policies have harmed the LDCs and SSA. Bearing in mind that the EU is a member of the G20, as well as several of its member states, then it is telling that every country listed in Tables 3 and 4 is a G20 member. One option, then, is for the G20 to begin a programme of unwinding its crisis-era measures that harmed the LDCs and SSA. A weaker alternative would be for the G20 to, wherever possible, alter the implementation of its crisis-era measures so as to exclude harm to the LDCs and SSA. In the absence of such an initiative, questions should be raised as to the coherence of G20 aid and development policies with their crisis-era policy responses. For example, how much aid money has been spent on projects that bolster export competitiveness in the LDCs and SSA that now face greater trade restrictions than before the crisis began?

The organisation of the rest of this volume

This volume is split into two parts. The first part includes five analyses of either the choice of policy during the crisis era that has some bearing on the commercial interests of the LDCs or SSA, or the consequences of those policy decisions. Evans S. Osabuhien, Uchenna R. Efobi, and Ibunkun Beecroft present a cross-country analysis of industrialised country crisis-era protectionism on the trade balances of developing countries. Adugna Lemi examines the contribution of foreign protectionism on African exports. Olayinka Idowu Kareem documents and contrasts EU-African and US-African trade relations during the crisis era. The focus then shifts from North-South trade relations to South-South trade, first with Albert Makochekenwa and Emson F. Chiwenga examining the crisis- era policy choices of several Southern African Development Community (SADC) members. Finally, Bethuel K. Kinuthia, Remco H. Oostendorp, and Jacob A. Jordaan estimate the consequences of a high profile Malaysian measure that involved firing foreign workers before domestic ones. Given the substantial number of foreign workers from developing countries that work in Malaysia, full implementation of this policy would not only harm industrialised countries’ commercial interests. Together, these chapters add to the limited body of The incidence of protectionism in LDCs and Sub-Saharan Africa 9 knowledge about the causes and effects of beggar-thy-neighbour measures that harmed developing countries during the crisis-era. The second part of this volume contains detailed data on the resort to protectionism by least developed countries and nations in Sub-Saharan Africa as well as information on the incidence of foreign protectionism harming these nations’ commercial interests. This information was compiled from the Global Trade Alert database and can be updated “in real time” from GTA’s website.8 The tables in Part Two of this volume were assembled by the GTA team based at the University of St. Gallen.

8 Specifically, go to the “Statistics” page of the GTA website and extract information about the jurisdictions of interest. That page allows for searches of the database by affected jurisdiction and implementing jurisdiction. The URL for the Statistics page is http://www.globaltradealert.org/site-statistics 10 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Appendix Tables on jurisdictions responsible for harming LDC and SSA commerical interests most often

Table 3. Top 11 countries that have imposed the most protectionist measures on the Least Developed Countries since November 2008 Number of protectionist measures Jurisdiction imposed by given jurisdiction that harm LDC commercial interests India 48 Indonesia 19 China 18 Argentina 17 France 16 Russian Federation 13 Germany 12 Netherlands 12 United Kingdom of Great Britain and 12 Northern Ireland Italy 11 Poland 11 Source: GTA database. Data extracted 22 May 2013.

Table 4. Top 11 countries that have imposed the most protectionist measures on the sub-Saharan African Countries since November 2008 Number of protectionist measures Jurisdiction imposed by given jurisdiction that harm Sub-Saharan Africa commercial interests India 44 Russian Federation 33 Argentina 29 China 24 Indonesia 22 United Kingdom of Great Britain and 21 Northern Ireland France 18 Brazil 15 Italy 15 Netherlands 12 Spain 12 Source: GTA database. Data extracted 22 May 2013. Part One The Impact of Protectionism on Developing Countries

2 Free trade, protectionism and the balance of trade: New empirical insights

Evans S. Osabuohien, Uchenna R. Efobi and Ibunkun Beecroft Covenant University, Nigeria

Protectionism reverberated around the world in the wake of the recent global financial crises despite the stance of the WTO and various regional trade agreements, which preached the gospel of reducing trade restrictions. This study explores the nature of recent protectionism and its impact on per capita income and trade balances both globally and in Africa. It observes that between 2009 and 2011, trade defence mechanisms and bailouts accounted for 25% of the protectionist measures, while tariffs and non-tariff measures were also frequently used, jointly constituting about 28%. The study reveals that a country’s per capita income growth was significantly and adversely affected by protectionism. Beggar-thy-neighbour state measures impacted negatively on trade balances and the effect was significant for African countries.

1. Introduction

Cooperation between countries to enhance growth and development through has been one of the major preoccupations of the World Trade Organization (WTO). The growth in the world trade system (WTS), which was based on a consensus in favour of free trade in goods and services and cooperation to enhance countries’ trading capacity, can also be seen as a cause of the drive towards regional economic cooperation by countries (UNECA, 2006). However, for several decades, the debate over free trade and protectionism has not led to an agreement. Proponents of free trade advocate minimising restrictions on international trade in favour of openness and “seamless” access to the global market. This is evidenced by the number of regional trade agreements (RTAs) across the world, which more than tripled between 1990 and 2011 (WTO, 2012). These agreements are expected to increase cross-border commerce by enhancing trading capacities of member countries. Protectionists, on the other hand, advocate national macroeconomic objectives and seeking economic welfare through regulating imports and market entry of other countries, especially when there is a perceived need to tackle a particular threat, such as unemployment or poverty. For instance, countries implemented

13 14 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

1,593 protectionist actions in the three years to November 2011 (Evenett, 2011). An example is the complaint by the European Union (EU) over Argentina’s import restrictions and the “controversial expropriation of a Spanish-owned oil company.” Another example is the China-US dispute regarding 22 countervailing measures that were applied to Chinese imports, which are argued to affect about US$7.3 billion of Chinese exports to the US (ICTSD, 2012a,b). The arguments for free trade or protectionism have their pros and cons, but the tendency of countries to favour one or the other often depends on national issues. This argument is not new, as similar issues emerged after the economic depression of the 1930s (Eichengreen and Irwin, 2009). However, the 2008 global economic crisis has brought a new dimension to the debate, as policymakers had been advocating nations remove impediments to trade in the run-up to the crisis. This can be seen in the formation of numerous regional economic communities (RECs) (Osabuohien and Efobi, 2011). This study examines the extent of protectionist actions and the implications on per capita income and trade balance based on a sample of 105 countries, including 25 African nations. The rest of the study is organised as follows: Section Two presents insights from the existing literature, methods of analysis and discussion of results are in Sections Three and Four, while the Section Five concludes with some policy implications.

2. Insights from existing literature

Free trade may be referred to as the absence or reduction of restrictions on trade between countries. It requires the integration of nations through a common market for the exchange of goods and services (Maruping, 2005). Trade is generally viewed as essential for a country’s growth and, to some extent, its economic development. Krugman (1983) and Bhagwati (2004) highlighted other benefits of trade such as its role in driving employment generation, poverty reduction, income redistribution and economic growth. Solow (1956) likewise notes that market-centred trade liberalisation accelerates economic growth and development. Winters (2004) finds that a reduction in barriers to trade improves total factor productivity via a rise in import competition. Conflicting evidence has been put forward in the study of the relationship between trade liberalisation, economic growth and development (Ackah and Morrissey, 2010). Osabuohien and Egwakhe (2011) found that, although Africa was becoming increasingly more integrated via trade and had reduced its tariffs consistently and remarkably, the continent had experienced less economic development. They submit that increases in trade integration had not translated into economic development in Africa. Despite evidence of the positive effects of international trade, most countries still engage in some sort of protectionism. Protectionism can be described as an attempt by a government to impose restrictions on the exchange of goods and services with other countries (George, 1949). The philosophy underlining protectionism is that the regulation of international trade is vital for ensuring that Free trade, protectionism and the balance of trade: New empirical insights 15 markets function properly and that there is a need to provide ways of mitigate market inefficiencies (Investopedia.com, 2012)1. The implication is that these market inefficiencies andloss of faith in free trade will culminate in the persistence of protectionism (Bhagwati, 2009). Some of the instruments used for protectionism include: tariffs, export subsidies, quotas, embargoes, exchange controls, import licensing, voluntary export restraint arrangements, and intellectual property laws such as patents and copyrights (Datt et al., 2011; Evenett, 2011; GTA, 2012). The justifications for employing protectionist measures include: infant industry promotion, dumping of imports, externalities, market failures, import controls, and other non-economic reasons. It has been asserted that protectionism has more unfavourable effects on developing than developed countries. The United Nations has claimed that EU protectionism deprived developing countries of nearly US$700 billion in export income a year (Landis, 2010). There is also an on-going dispute between the US and Russia over the linking of human rights violations to trade restrictions, as the US Congress opposes plans to regularise trade relations due to Russia’s human rights record (ICTSD, 2012c). Similarly, the WTO’s highest court ruled that the US “dolphin-safe” label violates the WTO’s Agreement on Technical Barriers to Trade (TBT), as it discriminates against Mexican tuna by banning a fishing practice known as “purse-seine” nets (encircling nets used almost exclusively by Mexican fisheries) (ICTSD, 2012d). The implication is that such a label increases the market share for the dolphin-safe US industries, while decreasing that of the non-dolphin-safe Mexican fish farmers. However, there is a dearth of empirical studies on the impact of recent protectionism on per capita income and trade balance, especially when looking at African countries. As Global Trade Alert observed, the instruments of protectionism have evolved, which will likely have an impact on these countries (GTA 2012). This study contributes in this regard.

3. Methods of analysis and data sources

The study used descriptive analysis to explore the extent of the protective/free trade measures. Two econometric models were formulated to examine the impact of protective actions on per capita GDP growth and trade balance with a view to investigating the response of macroeconomic and external sector performance2. The econometric models were based on the endogenous growth model and the new trade theory and presented in explicit form as:

Yit = β0 + β1Protctit + β2Labit + β3Kapit + β4inflation + 1ite (1) Trdit = λ0 + λ1Protctit + λ2Exrit + λ3Kapit + λ4Labit + e2it (2)

Where: Y: per capita income growth rate.

1 Available at www.investopedia.com/articles/03/112503.ap#axzz1uVPIdXIS (Accessed 10th May, 2012) 2 Possible factors such as institutional quality that could influence countries’ tendency to protect are not covered in this paper for focus and brevity sake. This is taken up elsewhere. 16 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Trd: trade balance (measured as export minus import divided GDP). Protct: resort to protectionist measures proxied by the proportion of red to total measures as reported in the GTA dataset3. Lab: total labour force. Exr: exchange rate Kap: capital captured as the annual growth rate of the gross fixed capital formation. Inflation: consumer prices (annual %). e: error term. it: country and time dimensions (105 countries from 2009-2010). β, and λ: coefficients of the explanatory variables in models.

The study engaged data for 105 countries and an African sample comprising of 25 countries as informed by the GTA dataset4. Another source of data was the World Development Indicators (World Bank 2012). This study employed the weighted least squares (WLS) technique, which is a type of generalised least squares suitable for handling the problem of heteroscedasticity in a short panel data (Gujarati and Porter, 2009)5. The analysis was performed with the aid of STATA 11.1 software.

3 The GTA dataset provides information on contemporary protectionism actions and these actions are categorised into three colours (red, amber and green). Red refers to measures that have been implemented and almost certainly restrict trade. Amber relates to measures that are implemented/ already announced and if implemented are likely to cause harm. Green measures have announced and either liberalise commerce or improve transparency of a national trading regime (GTA, 2012). 4 The countries include: Afghanistan, Algeria, Angola, Argentina, Armenia, Australia, Austria, Bangladesh, Belarus, Belgium, Bolivia, Bosnia, Botswana ,Brazil, Bulgaria, Cameroon, Canada, Chile, China, Colombia, Costa Rica, Croatia, Cyprus, Czech Republic, Democratic Republic of Congo, Denmark, Dominican Republic, Ecuador, Egypt, Estonia, Ethiopia, Finland, France, Gabon, Gambia, Germany, Ghana, Greece, Hungary, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Korea, Kuwait, and Kyrgyz Republic. Other are: Latvia, Lebanon, Lithuania, Luxemburg, Malawi, Malaysia, Malta, Mauritania, Mexico, Mongolia, Morocco, Mozambique, Namibia, Netherlands, New Zealand, Nigeria, Pakistan, Paraguay, Peru, Philippine, Poland, Portugal, Romania, Russia, Saudi Arabia, Sierra Leone, Singapore, Slovakia, Slovenia, South Africa, Spain, Sri Lanka, Sudan, Sweden, Switzerland, Syria, Tanzania, Thailand, Togo, Trinidad and Tobago, Turkey, United Arab Emirate, Uganda, United Kingdom, Ukraine, United States of America, Uzbekistan, Venezuela, Vietnam, Zambia and Zimbabwe. African countries are underlined and they represent more than 75% of the continent’s population and economic size. 5 The WLS is appropriate when the variance of the error term of the sampled countries (i) for the period (t) is not constant. And in this case, the countries included as sample will have their explanatory variables assuming diverse values. Thus, the problem of heteroscedasticity will arise. Furthermore, the WLS is an efficient method used for short panel data. This study employed WLS for the estimation process. Efforts were made to use a dynamic panel data model with a view to handling the issue of endogeneity but it was observed that the process would considerably reduce the degree of freedom given the short time dimension. Each term in the WLS method includes an additional weight that determines the extent each observation in the data set can influence the final parameter estimates. Therefore, using weights that are inversely proportional to the variance at each level of the explanatory variables yields the most precise parameter estimates. The study used the per unit error variances of the series as automatically generated the system, thereby reducing the possibility of the problem of heteroscedasticity. The mathematical representation of the WLS is: n 2 n * * 2 Σi=1(yi-a-b.xi) Σi=1(y -a.zi-b.xi ) = (3) i hi

* * yi is the dependent variable, xi are the sets of explanatory variables, while zi is a vector. The WLS will involve the minimisation of equation (3) by scaling the squared residuals for the observations with proportion to the variances. With this, a best linear unbiased estimate and correct standard errors for coefficient estimates are expected. Free trade, protectionism and the balance of trade: New empirical insights 17

4. Results and discussion

4.1. The trade-protectionism contradiction

From the global perspective, there has been a substantial increase in the number of RTAs between 1948 and 2011, as shown in Figure 2.1. This suggests that “freer trade” is being advocated “in principle.” This is because RTAs are expected to inter alia, enhance trade by improving the opportunities for market access by member countries. The reason for the increased number of RTAs may be that member countries hope to increase their trade flows, at least among members (intra-regional trade), by reducing or removing trade barriers. Figure 2.1 Regional trade agreements notified, 1948–2011

Source: WTO (2011).

Even though many countries are members of various RTAs, their governments have resorted to protectionism in recent years. This became more apparent after the 2008 global financial crisis as countries struggled to contend with its consequences, such as macroeconomic imbalances. This study presents the categories of actions (trade liberalising and protectionist) engaged by countries as a percentage of total measures for the period 2009-2011 in Figure 2.2. From Figure 2.2, the proportion of measures that can liberalise trade (green) implemented by countries increased from 18.21% in 2009 to 27.48% in 2010, but decreased to 26.63% in 2011. Measures where the effects on trade are less certain (amber) ranged from 21.90% to 30.47% over the same period. The percentage of measures that are almost certainly protectionist (red) remained considerably higher than other measures. It was close to 60% in 2009, about 50% in 2010 and 42.90% in 2011. However, it is important to note that in any given year, the number of measures is higher than those reported in Figure 2.2, as previous years’ measures have a cumulative effect. For instance, a “face value” of 50% observed for 2010 for protectionist measures is actually higher, as measures implemented in 2009 will also be effective in 2010. 18 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Figure 2.2 Trade liberalising and protectionist measures as a percentage of total (2009-2011) 70 60 50 40 30 20 10 0 2009 2010 2011 red amber green Source: Authors’ computation frm the GTA database. Details of the protectionist measures undertaken during 2009-2011 are given in Figure 2.3, which shows that trade defence mechanisms and bailouts remained popular. For instance, in 2009 and 2011, trade defence measures constituted up to 25% of the total protectionist measures. Other important measures were tariff and non-tariff measures, which accounted for about 14.23% and 13.88% of the total measures in 2011. Figure 2.3 Protectionist Measures, by type and year 30 25 20 15 2009 10 2010 5 2011 0

Tariff bailout others Non TariffMigration Import Ban export taxes Export SubsidyTrade Defence

Public Procurementother service sectorInvestment measure

local content requirement Note: ‘Others’ in the graph include: Sanitary and phyto-sanitary; Consumption subsidy; Intellectual property protection; Technical barriers to trade; State trading enterprise; Import licences; Quota; Competitive devaluation; Trade finance; Import subsidy; and Sub-national government measure. Source: Authors’ computation from the GTA database.

Other protectionist instruments less frequently used include other service sector measures, import bans, migration policies, local content requirements and public procurement. After establishing that protectionist actions by countries have increased after 2008, the study also examined the different instruments of protectionism in the first quarter of 2012. Table 2.1 shows that countries used 67 protectionist instruments in that quarter. The most common measures reported were bailout and trade defence actions, which accounted for over 74% of the total number of protectionist measures. Free trade, protectionism and the balance of trade: New empirical insights 19

Table 2.1 Protectionist measures adopted in 1st quarter 2012

Type of Non- Export Tariff OSS TDM TBT STE Bailout Total Measure Tariff taxes No. of 1 3 2 28 2 6 3 22 67 Measures % of Total 1.49 4.48 2.99 41.79 2.99 8.96 4.48 32.84 100.00

Note: OSS: other service sector; TDM: Trade defence measure; TBT: Technical barriers to trade; STE: State trading enterprise. Source: Authors’ computation from the GTA database.

Based on the finding that countries have employed protectionist measures (red) to a greater extent than other measures (amber and green), this study examines the impact of those measures on per capita income and trade balances.

4.2. Impact of protectionist measures6

The results of the estimation for the sampled countries and African country sub-sample are shown in Table 2.2. The reliability of the estimations was tested using the probability value of the F-statistics, which was statistically significant at 1% showing that the results are of good fit and represent the best linear unbiased estimates. Focusing on the independent variables of interest, Table 2.2 reveals that the number of protectionist measures implemented by countries (independent variable Prop_red) had a negative and significant impact on per-capita incomes, both for the entire sample and for African countries. This finding becomes stronger given the inclusion of another explanatory variable – growth rate of capital formation – which had a surprisingly negative outturn for the period (2009-10). The latter might have been driven by capital flight and by the crash in stock markets, as most economic activities were negative over the period. The impact of protectionist actions on the trade balance was mixed. It was not statisitically significant and negative for the entire sample, but it was for the African countries at the 5% level. Contemporary protectionism adversely affects African countries as it inhibits these economies’ trade (especially export) flows. This is relevant given the structural problems of most African economies with their export baskets dominated by unprocessed raw materials and commodities, which suffered a price crash after the crisis. African economies are thus more vulnerable to adverse external trade policies and global market developments. Related matters include a weak supply chain and low value addition on unprocessed raw materials and commodities in the world market. Moreover, given the fact that most African countries import finished products, any crisis-era increase in import bills was accompanied by reduced exports, thereby amplifying the negative impact on the trade balance. The policy recommendation from this study is that African countries must diversify their export base in order to mitigate the adverse effect of global

6 The impact of protectionist actions on unemployment rate was attempted but there were data constraints. 20 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries protectionism. This will involve processing raw materials, boosting domestic efficiency by promoting infrastructure provisions, and improving transport systems. In other words, African countries need to reduce export constraints, as most do not have the technical and financial wherewithal to cope with developed countries’ protectionist actions. It is rare to see African countries (apart from South Africa) initiate trade disputes against developed countries that contravene the WTO rules. Improving the domestic effectiveness of African economies is a better policy option than crying foul at protectionist actions. The role of Africa’s RTAs in this regard cannot be overemphasised. This concurs with the finding of Osabuohien and Efobi (2011) that aiding improved institution qualities by African RTAs is germane to improving the continent’s trade outcome. Table 2.2 Impact of protectionism on per capita income and trade balance

Sample All African countries Dependent Per capita Per capita Trade Balance Trade Balance variable Income Income Cap -1.2469a 0.0555a -0.8975a 0.0725a (0.0000) (0.0000) (0.0003) (0.0000) Labour 2.0295a 0.0392a 0.7606b 0.0158 (0.0000) (0.0000) (0.0211) (0.3538) Prop_red -0.0222a -0.0001 -0.0131a -0.0006b (0.0000) (0.5751) (0.0040) (0.0255) Inflation -0.1231a -0.1372a (0.0000) (0.0048) Exr 0.0001a 0.0001a (0.0011) (0.0001) Const 0.2724 -0.7316a 12.7470a 12.9650a (0.8446) (0.0000) (0.0000) (0.0070) R2 0.9843 0.9762 0.6421 0.7268 F-test P-value (0.0000)a (0.0000)a (0.0000)a (0.0000)a

Note: Probability values are in parenthesis. Superscripts a,b and c represent significant at 1, 5 and 10%. Source: Authors’ computation.

Table 2.2 also shows that price changes (inflation) had a significant and inverse relationship with per capita income. This follows economic theory that price changes in the basket of goods purchased by the consumer will exert pressure on their level of income. Labour variables had a positive impact on per capita income but a negative impact on trade. The exchange rate had a positive and significant impact on trade balance. This might also be interpreted to mean that depreciation will not be an effective trade policy instrument during economic Free trade, protectionism and the balance of trade: New empirical insights 21 crises. However, given the findings on the trade balance, the effect might have also resulted from increased prices of imported goods following depreciation.

5. Summary and concluding remarks

One of the core aims of cooperation between countries is to boost the mutual benefits, especially with respect to trade, as encapsulated in WTO and various RTAs protocols. This is evidenced by the fact that the number of RTAs across the world tripled between the 1990s and 2011. However, Global Trade Alert reported numerous protectionist measures that have been initiated by many countries that are signatories to both the WTO and many RTAs. This contradiction formed the key motivation for this study, which was to explore the extent of recent protectionism and how it has impacted on per capita incomes and trade balances using a sample of 105 countries and a sub-sample involving 25 African countries. Descriptive and econometric analyses were used to examine these matters. The study found that the number of protectionist measures put in place was much higher than trade liberalising measures. Between 2009 and 2011, the trade defence instruments and trade-distorting bailouts represented about 25% of the total measures, while other commonly used protectionist measures, including tariff and non-tariff barriers, amounted to 14% and 13% of the total measures, respectively. The econometric results show that protectionist measures exert a significant and adverse impact on per capita incomes. Protectionist measures also had negative effects on national trade balances, but statistically significant effects were only found in the sample of African countries. Crisis-era trade protectionism adversely impacted the trade of African countries, as most export principally unprocessed raw materials. This suggests the need for African countries to diversify their export capacities by putting in place mechanisms that will facilitate the processing of raw materials and enhancing trade infrastructure. The study concludes that the debate surrounding free trade protectionism will persist with grave implications for developing countries, in particular for Africa.

References

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About the authors

Evans Osabuohien is a lecturer in the Department of Economics and Development Studies, Covenant University and currently an Alexander von Humboldt Postdoctoral Fellow, Germany. He started teaching and researching in the University System since 2004 with research interest in International Economics, Institutional Economics, and Development. He has successfully executed a number of team funded research projects and has won severa; individual research grants/awards. He has over 30 scholarly papers in referred journals and edited books. He currently serves as reviewer to some international journals such as World Development; African Development Review; South African Journal of Economics; Pakistan Economic and Social Review; Journal of Environmental Policy and Planning; The Journal of Developing Areas, Journal of Sustainable Development, among others. He is also an editorial board member of some journals. He is a member of a number of learned societies, namely the Royal Economic Society; Nigerian Economic Society; CODESRIA; AERC; UNCTAD Virtual Institute; International Society of New Institutional Economics; African Growth and Development Policy Modeling Consortium (AGRODEP). He has participated in conferences, workshops, specialized courses and summer schools across the world. He has writing, reading and travelling as hobbies. He is married with two children.

Uchenna Efobi is a Doctoral candidate and a lecturer in the School of Business, Covenant University. He is also a qualified Chartered Accountant. His research focus is on development, institutions and international economics. He has publications in journals and book chapters such as South African Journal of Economics, African Development Bank Working Paper, Emerald Book Series, IGI- Global Book Series, Petroleum-Gas University of Ploiesti Economic Sciences Series. He has participated in conferences/workshops such as Centre for European Economic Research-ZEW, Germany, April 2013; African Institute for Economic Development and Planning, Senegal, November 2012; Centre for Economic Policy Research (CEPR), in collaboration with Global Trade Alert (GTA) and the 24 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

African Centre for Economic Transformation (ACET), Ghana, June 2012; United Nations University-Institute for Natural Resources in Africa (UNU-INRA), Ghana, 2011, December 2011; Indira Gandhi National Open University Conference on Diaspora and Remittances, New Delhi, India, September, 2011; International Conference on ‘Economic Development in Africa’ by the Centre for the Study of African Economies (CSAE), Oxford University, United Kingdom, March 19-21, 2011.

Ibukun Beecroft is a Doctoral Student, Assistant Lecturer and Researcher in the Department of Economics and Development Studies, Covenant University, Ota, Ogun State, Nigeria. She holds a B.Sc. in Economics from Covenant University and an M.Sc. in Finance and Development from the School of Oriental and African Studies (SOAS), University of London, United Kingdom. Before joining Covenant University, she worked with the Office for National Statistics, London, United Kingdom as well as with Zenith International Bank, Lagos, Nigeria. She has won various research and travel grants to conduct economic research, some of which include: Free Trade Versus Protectionism in Africa: The Unending Contradiction, 2012 (with Osabuohien, E. and Efobi, U.), funded by the Centre for Economic Policy Research (CEPR) in collaboration with Global Trade Alert (GTA) and African Centre for Economic Transformation (ACET), Ghana; UNU- WIDER Conference on L2C-Learning to Compete: Industrial Development and Policy in Africa, Helsinki, Finland, 2013. Her research paper (with two others) also won first place in the FLACSO-WTO Chairs Award, 2012. She is currently a reviewer for the Journal of Environment, Development and Sustainability. Her main teaching areas are mathematical economics, applied statistics, introductory econometrics and introductory microeconomics. Her research interests include: international economics, public finance and economic development. She has participated in conferences and workshops within and outside Nigeria. 3 Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible?

Adugna Lemi University of Massachusetts Boston

1. Introduction

The growing number of trade measures that OECD countries have implemented during the recent global economic crisis, under pressure from domestic interest groups, has raised serious concerns, especially among developing countries. This is despite repeated pledges by the advanced countries not to engage in trade- distorting measures. Least developed counties, especially those in Africa, have seen their total export values decline – but less so for export volumes – during the recent years of crisis. However, it is not clear whether the decline in export values is due to the crisis-era protectionism, a decline in demand resulted from the global economic crisis, or other factors. As a result of the 2008-09 global financial crisis, the global flow of goods and services has faced setbacks, to say the least. Some label it a trade crisis while others just call it a trade collapse (Behrens et al., 2010). Whatever label one likes to assign to it, the current consensus is that the world is in a recovery mode of some sort. Since the onset of the recent global financial crisis and the resulting trade downturn, there have been efforts to understand the channels through which the financial crisis has affected global trade and to explain the overall welfare impact of the crisis. Most of the studies focus on finding the key factors that link the financial crisis to the trade crisis. Limited access to trade credit, murky protectionism, behind-the-border measures, border measures, and fluctuations in demand components are all implicated as leading contributors to the downturn. The limited literature mainly focuses on descriptions of the extent of the trade crisis in order to establish stylised facts and suggest some possible explanation for the downturn (Balwin and Evenett, 2009; Freund, 2009), forecasts for the future course of the global trade (Freund, 2009), and recommendations for the need

25 26 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries for tightening multilateral agreements by completing the Doha round (Gregory et al., 2010). Given the brief history of the recent crisis, it is to be expected that rigorous empirical studies are limited in number. Of those available studies, most either picked only one of their favourite contributing factors or attempted a global analysis and ran into aggregation bias. When existing literature has gone beyond description of the events and presentation of professional guesses on the future direction, the conclusions are all too often vague or too general. Some have only considered the bigger picture (Erixon and Sally, 2010), perhaps scared by data limitations. In between the two extremes, there are few others that ventured deep in their analysis to look for a statistically and economically significant explanation for the downturn in trade flow during the crisis years. Most empirical studies fall within the latter, in that they attempt to look into one or two of these suspected factors that link the financial crisis to the trade crisis. Some studies focus only on lack of access to trade credit (Bastos and Pindado, 2013) and others on the demand components (Anderson and Tewolde, 2011). Others went further into detail and looked not only at the downturn in import value, but also at the significance of the changes in the intensive and extensive trade margins as well as prices (Haddad et al., 2010), the impact on intermediate inputs trade (Levchenko et. al., 2010), and the need to distinguish between the production and trade of durable and non-durable goods (McKibbin and Stoeckel, 2009) in explaining the contraction in trade and GDP. Anderson and Tewolde (2011) and Henn and McDonald (2011) are the closest in spirit to the present study. The former looks at the role of demand components while the latter investigates the importance of trade measures during the crisis years. The contribution of the present study is to combine both factors (demand components and trade measures) and empirically test for their importance in the context of imports of OECD countries from African countries and hence fill this gap by investigating this issue empirically for the sample countries. The significance of this study is, therefore, threefold. First, it makes an important contribution to the ongoing discussion as to how much trade barriers hinder flow of trade, ceterius paribus. Second, it sheds light on what to expect during crises from trading partners severely affected by the crisis and how to prepare oneself accordingly. Finally, for international organisations, such as the World Trade Organization, that serve as a platform for setting global trade rules, the results from this study will provide insights about the future negotiation agenda and applicability of safeguard mechanisms, which define what countries are allowed to do during times of crisis. The results presented here confirm that OECD countries’ demand components played a relatively minor role in the downturn of imports from African countries, whereas trade measures, especially tariffs, quotas, and the so-called “trade defence measures” had significant negative effects on OECD imports from African countries. Global Trade Alert’s (GTA) assessment of trade measures, based as it is on changes in relative treatment of foreign commercial interests, does not carry over into impact on trade flows, at least according to the results presented in this chapter. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 27

To address the above issues, this study uses information on trade measures reported by GTA together with a very detailed and rich OECD commodity-level trade dataset to study the impacts of the crisis-years trade measures and demand components of OECD countries on exports of African countries. In particular, the study will further evaluate the impact of implemented trade measures that almost certainly discriminate against foreign commercial interests (coded red) to those implemented trade measures that were expected to further liberalise trade flows (coded green) as well as trade measures with less certain but likely harmful effects (coded amber). Combining the OECD and GTA datasets allows for assessments of the impact of crisis-era policy measures at the (two-digit) commodity level. In addition to the total number of implemented measures, I have identified nine types of measures that are of great significance for African countries in particular, and less developed countries in general. Of these nine1, export subsidies, import subsidies, non-tariff barriers, tariff measures, trade defence measures, and quotas are found to be the most important in terms of the number of affected tariff lines and sectors for exports of African countries.

2. Crisis-era exports of African countries to the OECD

The OECD commodity-level trade flow data shows that African countries faced a significant decline in exports in 2009. While there was a sign of recovery in 2010, the recovery was mostly noticeable for oil exporting countries, as the figures below indicate. In 2008, South Africa, Zambia and Tunisia were the top exporters of goods to the OECD countries2. Figures 3.1-3.3 below report commodity- weighted average trade flows between African and OECD countries for 2008, 2009 and 2010, respectively.

1 These are export subsidy, import subsidies, import ban, non-tariff barriers, tariff measures, trade defence measures, technical measures, quota, sanitary and phyto-sanitary measures, and local content requirements. 2 Note that the blue coloured bars are exports for African countries (or imports for OECD countries from African countries) and the brown coloured bars are imports of African countries from OECD countries. 28 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Figure 3.1 Mean import and export levels in African-OECD trade in 2008, by African nation

Zambia South Africa Tunisia Nigeria Ghana Uganda Guinea Sierra Leone Liberia Madagascar Cameroon Congo Swaziland Niger Egypt Equatorial Guinea Senegal Libya Mauritania Gabon Burkina Faso Angola Mauritius Mali Djibouti Namibia Kenya Malawi Chad Benin Sudan Eritrea Togo Central African Republic Zimbabwe

0 50 100 150 200

mean of import mean of export Note: average commodity-level exports of these countries were typically in the range $0 million to $50 million in 2008. For those countries with no blue bars, it means that their average commodity exports are negligible, but may not necessarily be zero.

Figure 3.2 Mean import and export levels in African-OECD trade in 2009, by African nation

Tunisia South Africa Angola Equatorial Guinea Egypt Mozambique Nigeria Libya Liberia Zambia Cameroon Guinea Lesotho Mauritius Kenya Ethiopia Madagascar Chad Swaziland Sierra Leone Senegal Djibouti Namibia Congo Ghana Niger Gabon Eritrea Sudan Burkina Faso Uganda Mali Togo Rwanda Cape Verde Guinea−Bissau Botswana Zimbabwe Mauritania Gambia Benin Central African Republic Malawi Burundi

0 20 40 60 80

mean of import mean of export Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 29

In 2009, South Africa and Tunisia still dominated the list although their average exports fell to half of what they were in 2008 (see Figure 3.2). It is important to note that despite lower exports to OECD countries, African countries’ imports from OECD countries in fact increased or at least remained constant. This could either be as a result of the export promotion efforts that the OECD countries had instituted during the crisis years and/or as a result of the structure of the imports (i.e. necessities) of African countries. In 2010, there was a shake-up in the ranking of countries in terms of average exports to OECD countries. In addition to South Africa and Tunisia, four additional countries near the top of the list are oil exporters: Libya, Nigeria, Angola and Sudan. In fact, one can claim that the expected recovery was really not across the board for all goods and all countries. Therefore, it is not far- fetched to claim that the crisis is not over for non-oil-exporting countries of Africa. Could this pattern be explained by the impact of the new trade measures? Figure 3.3 Mean import and export levels in African-OECD trade in 2010, by African nation

Libya Angola Sudan Nigeria South Africa Congo Tunisia Equatorial Guinea Egypt Gabon Chad Mauritius Liberia Mozambique Djibouti Cameroon Zimbabwe Botswana Ethiopia Mali Kenya Uganda Swaziland Sierra Leone Namibia Zambia Madagascar Senegal Niger Ghana Guinea Gambia Togo Lesotho Eritrea Mauritania Cape Verde Benin Guinea−Bissau Malawi Burkina Faso Rwanda Central African Republic Burundi

0 100 200 300

mean of import mean of export

3. Types of crisis-era protectionism

The total numbers of colour-coded (i.e. red, green and amber) trade measures, as per the GTA classification scheme, may have the expected impact. However, during the years of crisis, trade flows could also be affected by demand conditions in an importing country as well as supply conditions in an exporting country. Having discussed the trade flow data in the previous paragraphs, it is now time to turn to the trade measures data from GTA. 30 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Note that in this study, I have used only those measures implemented between 2008 and 2010, excluding measures not implemented during these years. After cleaning up the data, I have been left with 1,140 trade measures between 2008 and 2010 (57 in 2008, 674 in 2009 and 409 in 2010). During these years, there were about 20 different types of trade measure reported by GTA. Out of the 20 types, trade defence measures (455 cases) top the list, followed by bail-out/state aid measures (233 cases) and tariff measures (162 cases) (see Table 3.1). Among these measures, 73 were amber, 804 were red, and 264 were green.3 Figure 3.4 below reports the sum of amber trade measures by commodity, the other two types of trade measures (red and green) have too many commodities to present here in graphs. OECD countries have imposed amber measures on fewer commodities compared to red and green measures; red (or trade limiting) measures were used by far the most and were also imposed on more commodities compared to green and amber measures. Table 3.1 Types of trade measures implemented by OECD+ countries between 2008 and 2010 Measure Type 2008 2009 2010 Total Bail out / state aid measure 32 142 59 233 Consumption subsidy 1 3 1 5 Consumption subsidy, Export subsidy 1 1 Consumption subsidy, Public procurement 1 1 Consumption subsidy, Sub-national 1 1 government Export subsidy 5 20 12 37 Export subsidy, Export taxes or restrict 5 5 Export subsidy, Import subsidy, Trade finance 1 1 Export subsidy, Public procurement, Tariff 1 1 Export taxes or restriction 2 10 11 23 Import ban 1 4 5 Import ban, Local content requirement 1 1 Import ban, Sanitary and Phytosantiary 1 1 2 Measures Import subsidy 17 17 Intellectual property protection, Local 1 1 Intellectual property protection, Migration 1 1 Investment measure 14 20 34 Investment measure, Local content 1 1 requirement Investment measure, Migration measure 1 1 Investment measure, Non-tariff barrier 1 1 Investment measure, Other service sector 1 1

3 See Table 3.2 in the Appendix which lists trade measures by implementing OECD+ countries [sample countries] during the crisis years. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 31

Measure Type 2008 2009 2010 Total Investment measure, Public procurement 1 1 Local content requirement 3 3 6 Local content requirement, Public 3 3 procurement Migration measure 1 19 14 34 Non-tariff barrier (not otherwise specified) 1 13 16 30 Non-tariff barrier (not otherwise specified) 1 1 Non-tariff barrier (not otherwise specified) 1 1 Non-tariff barrier (not otherwise specified) 1 1 Other service sector measure 3 2 5 Public procurement 5 10 2 17 Public procurement, Tariff measure 1 1 Quota (including tariff rate quotas) 1 3 23 27 Sanitary and Phytosantiary Measures 4 4 Tariff measure 4 79 79 162 Technical Barrier to Trade 1 2 3 Trade defence measure (AD, CVD, safeguard) 3 333 119 455 Trade finance 1 5 9 15 Total 56 674 409 1,139

Of the top three commodity categories (beverages, spirits, and vinegar, vehicles other than railway or train, mineral fuels, mineral oils and products of their distillation) that faced amber measures during the crisis years, two are of significant importance for African countries’ exports. This may be the reason why only amber trade measures turn out to be significant in influencing African exports to OECD countries. Figure 3.4 Amber coded trade measures by OECD country 2008-10, by commodity Trade Measures with uncertian effects by Commodity

22 : BEVERAGES, SPIRITS AND VINEGAR

87 : VEHICLES OTHER THAN RAILWAY OR TRAM

27 : MINERAL FUELS, MINERAL OILS AND PRO

52 : COTTON

88 : AIRCRAFT, SPACECRAFT, AND PARTS THE

85 : ELECTRICAL MACHINERY AND EQUIPMENT

84 : NUCLEAR REACTORS, BOILERS, MACHINER

73 : ARTICLES OF IRON OR STEEL

72 : IRON AND STEEL

30 : PHARMACEUTICAL PRODUCTS

26 : ORES, SLAG AND ASH

20 : PREPARATIONS OF VEGETABLES, FRUIT,

15 : ANIMAL OR VEGETABLE FATS AND OILS A

04 : DAIRY PRODUCE; BIRDS’ EGGS; NATURAL

02 : MEAT AND EDIBLE MEAT OFFAL

0 5 10 15 sum of amber Data Source: Global Trade Alert 32 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Merging the trade flow and the trade measures data, I have estimated the import demand equations for OECD countries with different specifications to show the robustness of the results. From the trade measures, the two key variables are GTA’s evaluation colour codes and the types of the trade measures as reported to GTA. I have used the GTA evaluation variable to create three separate variables for the evaluation codes: trade-limiting measures (red); trade-liberalising measures (green); and measures with uncertain effects (amber)4. In addition to these colour-related variables, I have also created variables for major types of trade measure that might be important for African trade. As such, I have created six dummy variables for the following trade measure types: export subsidy; import subsidy; quota; non-tariff barriers; trade defence measures; and tariff measures. I have estimated two separate import demand specifications: one including aggregated (GTA’s colour-coded) trade measures; and the other including the six individual trade measure types. Both specifications include the demand components and the (gravity) control variables 5

4. Results and discussion6

The overall message from the various specifications is that both demand components and trade measures played a role in affecting imports of OECD countries from African countries during the crisis years. The results also show that the demand components played a relatively smaller role compared with trade measures in affecting imports from Africa. The new trade measures, especially tariffs and trade defence measures, were significant in explaining the downturn of African countries exports to OECD markets.

4.1 Crisis-era trade measures played a much bigger than the decline in OECD demand

Demand component variables have the expected positive signs on imports, with the exception of investment, which shows a significantly negative association with OECD imports in at least one specification. The positive signs of the demand components are expected and in line with previous studies. It implies that a decline in OECD countries’ demand is associated with a decline in imports from African countries. The exception with investment may have to do with the incentives provided by governments of OECD countries to source locally

4 Since red and green trade measures are highly correlated, separate import demand equations are estimated for red and green measures. As a robustness test, I estimated the equations after dropping bailouts and state aids from the list of measures assuming that these measures may not be relevant for the case of Africa and they may not qualify as protectionism measures in the textbook definition of protectionist measures. However, the results remained the same. 5 The gravity control variables include factors that link the trading partners in Africa and OECD (i.e. distance between trading partners, dummies for common language, and colonial tie) and are obtained from Mayer et al. (2011). 6 Results from the standard panel data estimation techniques and from the robustness test estimations are more or less similar. Although the results from each specification are not contradictory, there are slight variations in the size and significance of some of the key variables. Note that I have tried estimation with levels and with proportions of imports and exports variables, the results remain the same. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 33 to benefit from any bailout or domestic investment incentive programmes that governments provided during the crisis years. Unlike investment spending, shares of government spending and exports had consistent and significant positive impacts (more so for exports) on import demand from Africa. This implies that during the crisis years, increases in the share of government spending and exports resulted in an increase in imports from Africa. As indicated in Anderson and Tewolde (2011), OECD exports are one of the demand components with high import intensity and therefore, one expects that as exports increase (using more imported goods and services), imports would increase as well. As we will see below, it is not far-fetched to state that the negative effects of investment spending could be because of the direct impact of murky protectionism, which were felt mainly by the private sector as a result of incentives to divert their spending to local or favoured sources. One may wonder that since most of African countries’ exports are not investment goods, how could an increase in investment in OECD countries result in a decline in imports from Africa countries? This may have to do with the vertical specialisation of global production networks where exports from African countries often end up being intermediate goods for the final goods processed in OECD countries. The positive signs on direct consumption spending (i.e. household consumption) and government spending in a country also imply that exports of African countries in fact benefit from this non-investment spending. These results are consistent with the expectation that higher spending in OECD countries results in higher imports. But these demand components did not have a strong impact on African exports as predicted by proponents of this argument. Given the weak significance of these spending components, one could argue that in fact, exports of African countries are immune from the severe shock of a global financial crisis to the extent that it is manifested in the demand decline. Freund (2009) alluded to this and stated that food and beverages were the least-affected traded goods during the crisis years. Whether the same logic carries over to the impact of trade measures, as Freund (2009) suggested, remains to be seen in the following results. The next results look into the impact of totals of (GTA colour-coded) trade measures on exports of African countries. The results presented here do not support the evaluation that GTA assigned to each trade measure (i.e. red, green and amber). It was expected that red and green trade measures would affect imports negatively and positively, respectively, whereas amber trade measures would not have any significant impact on trade flows. Contrary to this expectation, the results of the study indicate that only amber trade measures are found to have positive and significant effects on imports of OECD countries from Africa. One could argue that this should not be taken as a GTA evaluation error, since this study is focused only on African countries’ trade, which accounts for a smaller world trade share and only limited commodities. Second, it may be the case that these trade measures (coded amber) exempt African countries’ imports following the general preferential treatment of imports from Africa. Finally, a look back at the amber measures (see Table 3.2) reveals that, in fact, the amber measures were almost entirely implemented in 2009 and 2010 and the countries 34 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries that implemented these amber measures were mostly the BRIC countries, which often give special favour to countries in Africa. Although the semi-aggregated trade measures result shows unexpected significant effects for amber trade measures, the results for the individual trade measures are mostly as expected. Most of the six trade measures selected by their coverage and importance for Africa (i.e. export subsidy, import subsidy, non-tariff measures, quota, tariffs, and trade defence measures) turn out to be statistically significant in negatively affecting OECD imports from Africa. Except export subsidies of OECD countries, the other five trade measures all had negative impacts on imports from Africa countries. This is to be expected, except for the negative effect of import subsidy. One expects that import subsidies would promote more imports, not reduce them. In a further sensitivity analysis, this negative effect disappeared (see Tables 3.3-3.5 in Appendix).

4.2 Border measures were more important than behind-the-border measures

As expected, most of the crisis-era trade measures which are in principle trade- limiting were found to impede trade between OECD and African countries during the crisis years. Imports of OECD countries that imposed one of these five trade measures declined by about US$20 million compared to OECD countries that did not impose such measures. On the other hand, the impacts of demand components, especially government spending and exports, were only of a factor of between 0.37 to a little over 9. That means, for instance, that a one unit increase in the exports of an OECD country only resulted in an increase of less than US$1 million (in fact, US$370,000) in imports from African countries. The results of this study also show that, unlike results from Henn and McDonald (2011) who found that behind-the-border measures (subsidies and bailouts) were more important than the border measures, the border measures (tariffs, trade defence measures, quotas) turn out to be significant in the context of imports from Africa. This does not mean that behind-the-border measures were not important for the case of imports from Africa; in fact, export subsidies are one of the factors limiting imports although to a lesser degree than the border measures listed above. These results clearly demonstrate that trade measures, especially border measures, were harmful and had limited imports of OECD countries from Africa.

5. Conclusions

One of the results of this study highlights the importance of murky protectionism in explaining the downturn in exports from African countries to their OECD partners. In fact, the results confirm that, unlike results from overall global trade flows, a fall in demand and its components are less important compared with the impact of trade measures in explaining the declines in exports of African countries. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 35

This empirical finding raises two issues: First, there are still open loopholes that even those OECD countries could use to limit trade, possibly on a global scale. Second, these measures affect even those countries that are supposed to be protected under special privileges given their development status in the world economic standing. As a result, Gregory, et al. (2010) suggested that fixing these loopholes through tightened multilateral trade commitments by completing the Doha round negotiations might help to mitigate the root causes of these issues in the future. To better understand the global nature of the contending explanations of the downturn in global trade, future studies should look into the importance of most of the alternative explanations (trade credits, demand and its components and trade measures, etc.), not just one at a time, to paint a clearer picture of the events right after the crisis and to rank the alternative explanations. Only then is it possible for multilateral organisations to close the loopholes often used by otherwise free-market-friendly countries.

References

Anderson, R. and T. Tewolde (2011), “The Global Financial Crisis: Understanding the Global Trade Downturn and Recoverty”, The World Economy 34(5): 741- 763. Baldwin, R. and S. J. Evenett (2009), “Introduction and recommendations for the G20”, in R. Baldwin and S. J. Evenett (eds), The Collapse of global trade, murky protectionism, and the crisis: Recommendations for the G20, A VoxEU.org publication, CEPR. Bastos, R. and J. Pinodado (2013), “Trade credit during a financial crisis: A panel data analysis”, Journal of Business Research 66(5): 614-620. Behrens, K., G. Corcos, and G. Mion (2010), “Trade Crisis? What trade crisis?”, National Bank of Belgium Working Paper no. 195. Erixon, F. and S. Razeen. (2010), “Trade, globalization and emerging protectionism since the crisis”, ECIPE Working Paper no 02/2010. Freund, C. (2009), “The trade response to global downturns : historical evidence”, Policy Research working paper no. WPS 5015. Gregory, R., C. Henn, B. McDonald, and M. Saito. (2010), “Trade and the Crisis: Protect or Recover”, IMF Staff Position Note 10-07. Haddad, M., A. Harrison and C. Hausman (2010), “Decomposing the Great Trade Collapse: Products, Prices, and Quantities in the 2008–2009 Crisis”, National Bureau of Economic Research Working Paper 16253. Henn, C. and B. McDonald (2011), “Protectionist Responses to the Crisis: Damage Observed in Product-Level Trade”, IMF Working Papers 11/139. Levchenko, A., L. Lewis and L. Tesar (2010), “The Collapse of International Trade During the 2008-2009 Crisis: In Search of the Smoking Gun”, NBER Working Paper No.16006. McKibbin, W. J. and A. Stoeckel (2009), “The Potential Impact of the Global Financial Crisis on World Trade”, World Bank Policy Research Working Paper 36 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

No. 5134. Mayer, T. and S. Zignago (2011), “Notes on CEPII’s distances measures: The GeoDist database”, CEPII WP No 2011 – 25. Willenbockel, D. and S. Robinson (2009), “Assessing the Impact of the Global Financial Crisis on World Prices and Trade in Developing Countries: Analysis with a World Trade Model”, Institute of Development Studies at the University of Sussex.

About the author

Adugna Lemi is an Associate Professor at the Department of Economics, University of Massachusetts Boston. Previously, he was an Assistant Professor at Winona State University in Winona, Minnesota. Since 2007, he has held Visiting Professorship positions at various times both at Addis Ababa University in Ethiopia and at the Joint Elective Facility (JEF) of the African Economic Research Consortium (AERC) in Nairobi, Kenya. Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 37

Appendix: Data sources and description of variables

OECD countries trade and demand variables (Source: OECD International Trade by Commodities Statistics online version, 2011) 1. Imports: value of imports of an OECD country from AFRICA countries 2. Exports: value of total exports of an OECD country 3. Household consumption: Share of household consumption spending out of total spending in an OECD country. 4. Investment: share of gross fixed capital formation out of total spending in an OECD country. 5. Government spending: share of gross government spending out of total spending in an OECD country.

GTA Trade measures variables (Source: Global Trade Alert, Statistics available at http://www.globaltradealert. org/site-statistics) (Note that some of the variables listed below are constructed from the raw data and are not readily available from the link indicated above.) 6. Red: Trade measure that has been implemented and almost certainly discriminates against foreign commercial interests. 7. Green: Trade measure that has been announced and involves liberalisation on a non-discriminatory (i.e., most favoured nation) basis; or that has been implemented and is found (upon investigation) not to be discriminatory or that has been implemented, involves no further discrimination, and improves the transparency of a jurisdiction’s trade-related policies. 8. Amber: Trade measure that has been implemented and may involve discrimination against foreign commercial interests; or that has been announced or is under consideration and would (if implemented) almost certainly involves discrimination against foreign commercial interests.

The remaining variables are dummy variables that take value 1 when trade measure type is as listed below and takes value 0 otherwise (see export subsidy, for instance.)

9. Export Subsidy: is a dummy variable constructed from the trade measures which takes value 1 if type of trade measure is export subsidy and takes value 0 otherwise. 10. Import Subsidy 11. Tariff measures 12. Quota 13. Non-tariff barriers 14. Trade defence measures 15. Quota 38 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Gravity control variables The variables listed below are readily available for each country and no adjustments are made to the variables. (Source: Thierry Mayer and Soledad Zignago (2011). Notes on CEPII’s distances measures: The GeoDist database. CEPII, WP No 2011 – 25) 16. Distance: I have used two alternative distance variables. The first is calculated following the great circle formula, which uses latitudes and longitudes of the most important cities/agglomerations (in terms of population) and the second distance variable used the geographic coordinates of the capital cities of trading partners. 17. Common Language: Dummy variable indicating whether the two countries share a common language 18. Colony: Dummy variable indicating whether the two countries ever had a colonial link Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 39 1 1 1 3 4 1 1 1 1 1 5 6 3 3 18 24 3 3 4 8 12 1 1 5 7 1 5 15 21 6 18 24 1 1 6 8 1 7 25 33 6 12 18 1 1 6 8 1 7 18 26 6 14 20 1 1 4 6 1 7 20 28 6 18 24 3 1 7 11 3 8 29 40 7 27 34 1 1 9 11 1 8 40 49 6 18 24 1 1 7 9 1 7 26 34 6 15 21 1 1 6 8 1 7 22 30 6 18 24 1 1 5 7 1 7 24 32 2 9 13 24 3 22 24 49 5 31 37 73 1 4 12 17 2 4 4 10 3 8 16 27 2 3 7 12 1 2 9 12 3 5 16 24 2 2 1 3 22 26 2 4 35 41 3 7 59 69 2 2 1 1 3 3 1 7 12 20 1 1 6 8 2 8 21 31 3 3 4 5 22 31 5 6 9 20 9 11 34 54 2 2 4 4 1 1 1 1 1 1 1 1 3 2 12 17 1 4 5 1 2 4 7 1 16 28 45 6 8 16 30 8 26 48 82 2008 2009 2010 Total Amber Green Red Total Amber Green Red Total Amber Green Red Total Amber Green Red Total ade measures implemented by OECD+ countries between 2008 and 2010 ade measures implemented by Coded tr

Country Argentina Austia Australia Austria Belgium Brazil Canada China Denmark Finland France Germany Greece India Ireland Israel Italy Japan Korea Table 3.2 Table 40 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries 1 1 3 4 3 4 1 5 9 14 10 9 19 1 3 4 1 1 1 3 5 8 1 2 1 1 1 1 1 2 1 1 3 5 1 3 4 7 1 3 9 13 1 4 5 1 2 3 4 5 5 3 8 1 2 6 14 20 1 1 4 6 1 7 19 27 2 2 1 6 13 19 1 1 6 8 1 8 20 29 4 4 8 6 21 27 2 1 10 13 2 7 34 43 1 13 14 1 2 8 11 1 3 22 26 6 14 20 1 1 4 6 1 7 19 27 6 15 21 1 1 4 6 1 7 23 31 1 6 15 22 1 2 6 9 2 8 21 31 1 6 7 2 6 8 16 2 7 14 23 1 2 3 1 1 1 1 1 1 6 14 56 76 2 5 39 46 8 19 96 123 4 4 1 6 14 21 1 1 7 9 2 7 25 34 1 1 1 1 1 3 3 1 1 1 1 2 1 3 4 4 2 2 1 1 1 2 1 6 50 57 27 170 478 675 45 88 276 409 73 264 804 1,141 2008 2009 2010 Total Amber Green Red Total Amber Green Red Total Amber Green Red Total Amber Green Red Total Amber- Trade measures with uncertain effects on Trade flow, Red- Trade measures with certain trade limiting effect, Green – Trade measures with trade liberalising effect liberalising trade with measures Trade – Green effect, limiting trade certain with measures Trade Red- flow, Trade on effects uncertain with measures Trade Amber- Country Luxembourg Mexico Netherlands New Zealand Poland Portugal Russia Singapore South Africa Spain Sweden Switzerland Taiwan Turkey Tunisia Ukraine UAE UK US Total Note: Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 41 b/se 1.26 -7.07 -9.58 -0.00 -1.00 (7.52) (5.34) (0.03) (9.07) (0.00) (6.13) -15.54 (10.35) 317.62

0.45*** (11.10) (11.44) 3415.00 29.86*** 63.30*** Hausman- Taylor Hausman- Taylor b/se 1.26 1.00 -7.07 -9.58 -0.00 (7.52) (5.34) (0.03) (9.07) (0.00) (6.13) -15.54 (10.35) 317.62 0.45*** (11.10) (12.36) 3415.00 29.86*** 64.30*** b/se 0.01 0.06 -0.01 -0.46 -0.80 -0.38 0.00* (0.07) (0.14) (0.11) (0.01) (1.10) (0.00) (0.70) (1.98) (1.91) 635.03 0.23*** 5.51*** 3415.00 ade measures and demand components as explanatory b/se 0.01 0.06 0.38 -0.01 -0.46 -0.80 0.00* (0.07) (0.14) (0.11) (0.01) (1.10) (0.00) (1.98) (0.70) (1.94) 635.03 0.23*** 5.89*** 3415.00 b/se 5.21 0.07 0.37 0.07 -0.00 -2.66 0.73* (0.39) (0.56) (0.77) (0.12) (6.56) (0.00) 23.30 (2.71) 1.29** 1.58** -12.82 62.77* 0.46*** (10.38) (32.52) 3415.00 Standard Heteroscedastic Heteroscedastic Hausman-Taylor b/se 5.21 0.07 0.37 0.07 2.66 -0.00 (0.39) (0.56) (0.77) (0.12) (6.56) (0.00) 23.30 (2.71) 1.29** 1.58** -12.82 0.46*** (10.38) (32.52) 65.43** 3415.00 Standard variables variables Estimations of import demand equations with colour–coded aggregate tr

N Independent variable Household Consumption 0.73* Business Investment Government Spending Government Exports Common Language Distance from Capital Colonial tie chi2 Amber measures Liberalising measures r2_overall Restrictive measures r2_between r2_within Table 3.3 Table 42 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries b/se -0.47 -8.41 (7.54) (5.27) (0.03) (9.08) (0.00) -0.00* -15.64 -52.31 (10.64) (11.12) (34.79) (22.75) (15.61) (33.34) 0.45*** -61.92* -47.37** 33.18*** -13.93*** -48.08*** Hausman-Taylor Hausman-Taylor b/se 0.20 1.19 1.12 0.00 -2.04 -9.36 (0.49) (1.00) (0.89) (0.03) (7.08) (0.00) (9.39) -44.89 (34.36) (22.11) (14.85) (31.14) ade measure types and components of demand as explanatory 0.45*** -62.23* -53.63** -55.13*** Heteroscedastic b/se 0.20 -2.04 -9.36 -0.00 (0.46) (0.19) (0.57) (0.12) (6.50) (0.00) (9.51) 1.19** 1.12** (25.85) (24.54) (24.48) (24.73) 0.45*** -44.89* -62.23** -53.63** -55.13** Standard variables Estimations of import demand equations with specific tr

Business Investment Spending Government Household Consumpt~n Exports Common Langauage Colonial Tie Export Subsidy Distance from Capi~l Import Subsidy Quota Non-Tariff M Non-Tariff Table 3.4 Table Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 43 b/se (9.89) (11.38) 316.29 3415.00 -53.57*** -51.97*** Hausman-Taylor Hausman-Taylor b/se (9.07) (10.42) 634.56 3415.00 -61.30*** -57.56*** Heteroscedastic b/se 0.08 0.68 0.07 28.57 (25.24) (25.41) 3415.00 -61.30** -57.56** Standard Trade Defence M Trade Tariff Measures Tariff N chi2 r2_overall r2_between r2_within Note: Numbers in parenthesis are standard errors. 44 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries b/se 2.54 9.66 -6.29 -5.44 -0.00 (6.48) (4.13) (7.47) (0.02) (8.10) (9.94) (0.00) -15.67 -26.71 -21.17 -19.42 (32.43) 0.37*** (20.55)

Heteroscedastic b/se 2.54 -5.44 -0.00 9.66* (3.07) (2.40) (5.04) (0.09) (7.36) (0.00) -15.67 (12.49) (11.13) 0.37*** (10.86) -19.42* -6.29*** -26.71** -21.17** b/se 4.13 7.39 0.23 -1.42 -6.69 -0.00 (6.47) (4.13) (7.28) (0.02) (8.08) (9.91) (0.00) (9.35) (5.57) -15.43 0.37*** 49.63*** b/se 4.13 7.39 -1.42 -6.69 -0.00 -0.23 (6.47) (4.13) (7.28) (0.02) (8.08) (9.91) (0.00) (5.57) -15.43 (10.32) 0.37*** 49.40*** ade measures and demand components as explanatory variables and ade measures and demand components as explanatory variables b/se 4.13 7.39 0.23 -1.42 -6.69 -0.00 (3.60) (1.56) (4.50) (0.09) (7.72) (0.00) (3.28) -15.43 49.63* (12.28) (26.57) 0.37*** Standard Heteroscedastic Heteroscedastic Standard b/se 4.13 7.39 -1.42 -6.69 -0.23 (3.60) (1.56) (4.50) (0.09) (7.72) (0.00) (3.28) -15.43 49.40* (12.28) (27.44) 0.37*** Standard accounting for commodity effects in addition to country Estimations of import demand equations with tr

Household Consumption Business Investment Government Spending Government Exports Common Language Colonial Tie Distance from Capital -0.00 Amber Measures Quota Restrictive Measures Restrictive Measures Liberalizing Export Subsidy Import Subsidy Table 3.5 Table Trade measures of OECD countries and the decline in exports of African countries: Is murky protectionism responsible? 45 b/se (8.36) (6.40) -23.48 309.48 (30.86) (13.17) 3906.00 -20.41** -23.70***

Heteroscedastic b/se 0.07 0.14 0.06 74.56 (9.89) -23.48 (11.11) (17.46) (10.10) -20.41* 3906.00 -23.70** b/se 324.99 3906.00 b/se 324.99 3906.00 b/se 0.08 0.13 0.07 70.96 3906.0 Standard Heteroscedastic Heteroscedastic Standard b/se 0.08 0.13 0.07 70.96 3906.00 Standard chi2 N Tariff measures Tariff Trade defence M Trade r2_overall r2_between r2_within Non-Tariff M Non-Tariff Note: Numbers in parenthesis are standard errors.

4 Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations

Olayinka Idowu Kareem Federal University of Agriculture, Abeokuta, Nigeria

1. Introduction

The sudden negative shocks that characterised the recent global economic crisis left policymakers with a range of policies they could use to mitigate the unprecedented macroeconomic instability that pervaded many countries. The tools available to these countries, such as members of the EU and the US, included injecting funds into the financial system, depreciating their currencies and/or control of trade. Some countries, such as the US, chose the first option, which had negative consequences. Many of the developed countries, especially within the EU and the US, adopted the latter policy and imposed trade-restricting measures. The adoption of such policies by the EU, for example, affected many trade partners, including African countries. This led to strong feelings in African governments that following the global economic crisis most of their exports were prevented from fully accessing developed markets. Several protectionist trade policies were used by the EU and the US, especially non-tariff measures such as subsidies, export incentives and public procurement. These trade policies were meant to reduce spending on imported products and to stimulate domestic production through stimulus packages, and revenue from higher tariffs. However, these protectionist trade policies greatly affected Africa’s foreign exchange earnings from trade and their quest for sustainable development (Kareem 2011). In the light of this finding, the objective of this study is to test the Eichengreen and Irwin hypothesis that the flexibility of macroeconomic policies and exchange rate regimes provided alternatives to crisis-era protectionism.

47 48 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

2. Trends in Africa’s exports

Table 4.1 shows Africa’s share of world trade between 1980 and 2009. Africa’s share of world exports is relatively low. In 1980, African countries exported about US$119 billion worth of commodities, representing about 6% of world exports. However, by 1990, the value of exports dropped to about US$107 billion, or 3% of world exports. The continent’s exports regained an upward trend in 1995; it recorded up to over US$112 billion, but against a background of growing world trade this represented just 2% of world exports. Africa’s exports value increased to US$231 billion in 2004 and later rose to US$397.4 billion in 2007, which is 2.5% and about 3.0%, respectively, of global exports. Africa’s share of global exports rose to about 3.5% in 2008 before dropping to 3.0% in 2009. Thus, the share of Africa’s exports in world exports is not only very low but has no stable trend. The trend in Africa’s exports to the EU and US is presented in Figures 4.1 and 4.2. Figure 4.1 indicates that in 1990, Africa exported over US$36 billion worth of commodities to the EU. After the crises that engulfed most African countries in the 1990s, Africa’s exports to the EU dropped to about US$31 billion in 1993. However, by 2000, such exports had risen to about US$54 billion. This increasing trend continued and nine years later, Africa’s recorded exports to the EU reached around US$98 billion. However, it can be seen from the figures that African exports to the EU dropped sharply in 2009 due to the global economic meltdown. Figure 4.1 also shows that there has been a negative balance of trade in Africa’s trade with the EU. Figure 4.1 Africa’s trade with the EU, 1990-2009 180

160

140

120

100 Export 80 US$ Billion Import 60

40

20

0 1990 1991 1992 1993 1996 1997 1998 1999 2000 2001 2002 2003 2006 2007 2008 2009 1995 2005 1994 2004 Source: IMF Direction of Trade (several years). Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 49

Figure 4.2 Africa’s trade with the US, 1990-2009 120

100

80

60 Export

US$ Billion Import 40

20

0 1990 1991 1992 1993 1995 1996 1997 1998 1999 2000 2001 2002 2003 2005 2006 2007 2008 2009 1994 2004 Source: IMF Direction of Trade (several years)

Table 4.1 Share of exports by region (%)

Region 1980 1985 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 World 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 US 14.5 15.7 15.0 15.0 16.4 16.0 14.6 13.3 12.3 12.1 12.0 11.4 10.9 11.1 EU 42.9 41.9 47.0 44.5 40.1 42.0 42.7 43.8 42.8 40.8 40.1 40.5 39.0 39.1 Africa 5.9 4.2 3.1 2.1 2.3 2.2 2.3 2.4 2.5 2.9 3.0 2.9 3.45 3.1

Source: Author’s compilation from UNCTAD Handbook of Statistics (2010) Figure 4.2 shows that the total value of Africa’s exports to the US was US$14 billion in 1990, which later dropped to about US$13 billion in 1993. However by 2000, Africa’s exports to the US had increased to about US$23 billion due to relative political and macroeconomic stability in many of the countries. Although Africa’s exports to the US fell to US$18 billion in 2002, this picked up in the following year (2003) to about US$27 billion and increased through to 2008 when they were US$99 billion, before they fell to US$54 billion due to the global economic meltdown. The continent recorded positive trade balance in its trade with the US throughout those years.

2.1 Trade policy measures during the global economic crisis

Several trade policy measures were put in place during the global economic crisis (GEC) in order to protect, and at times enhance, trade between countries1. Table 4.2 shows trade policy measures put in place during the crisis by developed countries. The EU had a total of 333 measures as reported by March 2012, of which 34 encouraged trade with its partners (coded green), including African countries. There were 40 measures that were implemented and harmful, or under

1 The Global Trade Alert Statistics (2012) shows that there are three categories of this trade policy measures: the measures that encourage trade (green coded); measures that could discriminate trade against foreign interest if implemented; and measures that have been implemented and almost certainly will restrict trade against foreign trade partners, are coded in amber and red, respectively. 50 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries consideration and if implemented would almost certainly lead to protectionist policy measures (coded amber). Some 259 measures were coded red, which almost certainly harmed their trading partners, including Africa. These protectionist trade policy measures by the EU affected 552 tariff lines (of which some were of relative importance to Africa), 185 trading partners and 53 sectors of the EU economy. The US had a total of 127 measures, of which 19 encouraged trade. 80 of the measures announced would almost certainly restrict trade if implemented, while 26 were either in the works or likely protected domestic commercial interests. Put together, the US had 106 trade policy measures that hindered or had the potential to restrict trade flows to its market. There were 15 tariff lines affected by these measures implemented during the crisis, and 43 sectors and 124 trading partners were affected,. Table 4.3 presents sectors that were affected by the trade policy measures. The selected sectors are based on the sectors of interest and importance to Africa. The basic chemical sector had the highest number measures with 273, of which about 210 were protectionist. Agriculture, horticulture and market gardening products recorded 22 measures and over 76% of those were used to restrict trade flow. A total of 154 measures were used on grain mill products, starches and starch products, and other food products, of which 71% were protectionist trade measures and 29% encouraged trade. About 83% of the total measures on yarn and thread, woven and tufted textile fabric were restrictive, while 81% and 82% of rubber and plastic products and glass and glass product, other non-metallic product n.e.c, were protectionist. Table 4.2 Trade policy measures2 by implementing jurisdiction during the global economic crisis Trading Tariff lines Sectors partners Total Green Amber Red affected affected Jurisdiction affected measures measures measures measures by red by red by red measures measure measures EU27 333 34 40 259 552 53 185 USA 127 19 80 26 150 43 124 G8 643 129 164 345 668 66 196 G20 1521 345 396 775 1084 69 214 Source: Compiled from Global Trade Alert (accessed May, 2012)

2 Evenett (2010) defined these measures as follows: The red measure indicates that the measure has been implemented and almost certainly discriminates against foreign commercial interests. The amber measure shows that the measure has been implemented and may involve discrimination against foreign commercial interests; or the measure has been announced or is under consideration and would (if implemented) almost certainly involve discrimination against foreign commercial interests. While green measure has been announced and involves liberalisation on a non-discriminatory (i.e., most favoured nation) basis; or the measure has been implemented and is found (upon investigation) not to be discriminatory: or the measure has been implemented, involves no further discrimination, and improves the transparency of a jurisdiction’s trade-related policies. Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 51

African commercial interests were harmed by numerous US and EU trade measures. For example, a US local content requirement implemented in 2011 affected 113 product lines in Africa that cut across 13 sectors and 16 countries. In addition, EU state aid and export subsidy affected 10 African products that cut across three sectors and 17 countries. Morever, if the US passes and implements a bill to ban imports of goods for which there is no registered domestic agent, it will affect 886 product lines, 19 sectors and 44 African countries. The new requirements on food safety by the US, if implemented, will hinder the flow of 125 products in 18 sectors across 20 countries in Africa. Finally, if the bill to strengthen customs enforcement for apparel is finally passed and implemented then it will certainly hinder trade in 150 African products across one sector in 13 countries. In contrast, the relaxation of American standards for defence procurement will enhance 11 African product lines, two sectors and one country if fully implemented. The temporary suspension of import tariffs for the CXI concessions sugar, which is an import subsidy, will enhance trade in 17 African countries in a single sector and product. Likewise, the renewal of the US preferential trade programmes that was proposed in 2009 will lead to market access in 44 African countries across 30 sectors.

3. Methodology and empirical results

This study tests the hypothesis as put forward by Eichengreen and Irwin (2009) that other macroeconomic instruments can substitute for protectionism. Eichengreen and Irwin’s approach is adapted in this study to examine the extent to which a change in Africa’s trade is related to domestic economic activities in the EU and US and to determine the relationship between changes in tariffs and exchange rates. The result of the estimated relationship between a change in import and change in real GDP3 indicates that the euro and US dollar exchange rate movements during this period were an import-inhibiting factor for African products. This factor remained significant after employing instrumental variables in the dynamic panel analysis, and confirmed the findings of Eichengreen and Irwin (2009). In addition, real GDP is an import-enhancing factor as it significantly enhances EU imports of African products by about 17%. The comparable factor raised US imports of African goods by about 57%.

3 See Table 4.A in the appendix. 52 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries 0 3 8 9 68 56 41 40 14 10 52 57 17 53 23 50 55 52 56 10 in jurisdictions Red measures implemented 4 6 7 9 6 8 5 1 22 10 15 12 25 40 25 26 91 28 32 57 Pending Pending measures 1 97 45 50 41 11 24 30 33 70 26 69 65 98 21 114 115 108 measures Implemented 2 0 2 0 556553 615 9 9 12 342 18 21 37 11 9 38 32 22 17 3 77 191 14 11 10 20 27 21 2926 39 42 5 7 14 3037 695 6 11 18 18 13 23 13 54 119 18 25 76 154 44 37273136 73 130 66 26 24 95 39 48 111 71 58 182 222 53 46 123 165 Total Total Green Amber Red rade policy measures by affected sector during the global economic crisis measures by policy rade T

Live animals & animal products Live & logging products Forestry & other fishing products Fish gas Crude petroleum & natural & thorium ores Uranium Metal ores & starch mill products, starches Grain products, other food products products Tobacco & tufted textile fabrics & thread, woven Yarn Leather & leather products; footwear 140Pulp, paper & products; printed matter & related article Basic Chemicals 24Rubber & plastics products Glass & glass products other non metallic 43products n.e.c Agriculture, mining & manufacturing services 73 Agriculture, Forestry & Fishing products & Fishing Agriculture, Forestry Agriculture, horticulture & Products of marketing gardening Coal & lignite; peat Stone, sand & clay Dairy products Affected Sector : Compiled from Global Trade Alert (Accessed May, 2012) Alert (Accessed May, : Compiled from Global Trade Source Table 4.3 Table Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 53

In terms of the relationship between change in tariffs and exchange rate in the EU, the econometric estimates4 imply that the exchange rate is significant and has a direct relationship with changes in tariffs in almost all the models. According to Eichengreen and Irwin (2009), exchange rates are endogenous not least because of sharp changes in monetary policy. Using instrumental variables indicates a different pattern in terms of the magnitude of the change in tariff, which has reduced to about 80% from 108% in the OLS estimate, although still statistically significant at the 1% level. The inclusion of price level as an additional independent variable gave similar results to the exchange rate terms. This means that depreciated currencies were associated with smaller tariff increases. By and large, the results of both African-EU and African-US trade confirm the hypothesis of Eichengreen and Irwin (2009).

4. Conclusions

Analysis of the GTA data shows that many African agricultural product lines were affected by the protectionist trade policy instruments, many of which were implemented by the US. Having said that, some trade preference initiatives were instituted by the US from which Africa benefited. Our empirical analysis also shows that exchange rate policies in both the EU and US have had a significant negative impact on the flow of Africa’s agricultural exports. Furthermore, such policies indirectly affected changes in tariffs on Africa’s agricultural products in both markets. Depreciating currencies tend to encourage a rise in tariffs. Meanwhile, changes in the consumer price indices in both markets have differential impacts on African trade. While an increase in the price level in the EU reduces its imports, the reverse is the case for the US. These findings support the argument that there is substitutability between trade policies and other macroeconomic instruments. Thus, Africa’s trading partners need not necessarily make use of protectionist trade policy instruments in regulating the flow of trade, especially during economic crises. Other macroeconomic instruments could serve the same purpose without directly restricting access to their markets.

References

Eichengreen, B. and D. Irwin (2009), “The Slide To Protectionism In The Great Depression: Who Succumbed and Why?”, NBER Working Paper No. 15142. Evenett, S. J. (2010), “Global Developments Since the G20 Summit in Toronto, June 2010”, in S. J. Evenett (ed.), Tensions Contained... For Now: The 8th GTA Report, Global Trade Alert. Global Trade Alert (2012) Online Database, accessed in May. Kareem, O.I. (2011) “The European Union Trade Policies and Africa’s Exports,” World Economics 12(2).

4 See Table 4.B in the appendix 54 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

About the author

Olayinka Idowu Kareem specializes in the area of trade, trade policies and development. He has written several articles in these fields of economics. He was a research fellow of the Centre for the Public – Private Cooperation (CPPC), associate member of United Nations Conference for Trade and Development (UNCTAD) Virtual Institute and a member of the International Economic Relations Network (IERN), University of Barcelona, Spain. He was a fellow of the Journal of African Economies, Centre for the Study of African Economies (CSAE), Department of Economics, University of Oxford and Senior Member of St’ Anthony’s College University of Oxford, Oxford, the United Kingdom. Dr. Kareem was formerly an Impact Evaluation Consultant at the World Bank Nigeria Country Office on Commercial Agriculture Development Project (CADP). He has taught at the Federal University of Agriculture, Abeokuta, Nigeria before becoming a Global South Scholar at the Graduate Institute of International and Development Studies, Geneva, Switzerland. Currently, he is a Postdoctoral fellow at the Robert Schuman Centre for Advanced Studies, European University Institute, Florence, Italy. Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 55

Appendix

Table 4.A Relationship between change in imports and change in real GDP EU US Variable OLS Dynamic OLS Dynamic Exchange -1.6664 -2.7240 -1.1105 -2.2740 Control (0.18) (0.06)* (0.05)** (0.07)* 0.1676 0.0965 0.5689 0.0685 lnCRGDP (0.01)*** (0.12) (0.00)*** (0.22) 6.1192 5.8354 Constant - - (0.00)*** (0.00)*** R2 0.25 - 0.43 - Source: Computed Note that the figures in parentheses are the probability values while *, ** and *** indicate significant at 10%, 5% and 1%, respectively.

Table 4.B Average tariff and exchange rate result for EU OLS Dynamic OLS Dynamic OLS Dynamic Exchange 0.0071 0.0119 -1.0878 -0.8034 -1.1892 -1.1134 Rate (0.00)*** (0.22) (0.00)*** (0.00)*** (0.22) (0.13) Exchange 0.113 0.0111 0.0081 0.0097 - - Control (0.00)*** (0.00)*** (0.04)** (0.00)*** -0.1018 -0.1174 Price Level - - - - (0.03)** (0.00)*** R2 0.72 - 0.91 - 0.84 - Source: Computed Note that the figures in parentheses are the probability values while *, ** and *** indicate significant at 10%, 5% and 1%, respectively.

Table 4.C Average tariff and exchange rate result for USA OLS Dynamic OLS Dynamic OLS Dynamic

Exchange 0.0076 0.0185 -0.8034 -1.6490 -0.3544 -0.7429 Rate (0.00)*** (0.16) (0.00)*** (0.05)** (0.01)*** (0.11) Exchange 0.0111 0.0147 0.0650 0.0081 - - Control (0.00)*** (0.15) (0.05)** (0.01)*** 0.0717 0.2628 Price Level - - - - (0.22) (0.04)** R2 0.18 - 0.23 - 0.39 - Source: Computed Note that the figures in parentheses are the probability values while *, ** and *** indicate significant at 10%, 5% and 1%, respectively. 56 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Trade policy measures by implementing jurisdiction during the global economic crisis Trading Tariff lines Sectors partners Total Green Amber Red affected affected Jurisdiction affected measures measures measures measures by red by red by red measures measures measures EU27 333 34 40 259 552 53 185 USA 127 19 80 26 150 43 124 G8 643 129 164 345 668 66 196 G20 1521 345 396 775 1084 69 214 Algeria 11 2 1 8 476 62 63 Angola 4 1 1 2 15 2 7 Botswana 4 0 2 2 33 3 3 Cameroon 2 1 0 1 1 1 11 Cote 2 1 0 1 0 1 3 d’lvoire Egypt 24 8 5 11 112 11 71 Ethiopia 4 1 0 3 347 32 74 Gabon 1 0 0 1 1 1 0 Ghana 5 1 1 3 120 41 34 Kenya 14 5 7 2 3 2 2 Lesotho 0 0 0 0 0 0 0 Mauritius 1 1 0 0 0 0 0 Nigeria 22 4 5 13 599 45 114 Senegal 1 0 0 1 0 1 3 South 56 20 12 24 59 18 134 Africa Tunisia 2 0 0 2 356 31 58 Source: Compiled from Global Trade Alert (Accessed May 2012) Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 57

Trade policy measures by type during the global economic crisis Red measures Implemented Pending Measure Total Green Amber Red implemented measures measures in jurisdictions Bail out/State aid 355 3 42 310 283 72 49 Competitive 5 0 0 5 5 0 5 devaluation Consumption 18 4 6 8 13 5 6 subsidy Export subsidy 60 3 19 38 55 5 42 Export taxes or 151 36 29 86 117 34 55 restrictions Import ban 49 7 15 27 37 12 21 Import subsidy 13 3 9 1 11 2 1 Intellectual property 9 1 5 3 3 6 3 protection Investment 144 57 41 46 113 31 29 measures Local content 52 4 23 25 34 18 14 requirement Migration measure 95 28 18 49 85 10 25 NTB not specified 154 12 33 109 135 19 26 Other service 41 8 20 13 24 17 7 sector measure Public 73 3 31 39 50 23 21 Procurement Quota (including 41 11 12 18 31 10 11 tariff rate quota) Sanitary Phytosanitary 29 6 8 15 19 10 12 Measure State trading 9 1 0 8 8 1 3 enterprise State controlled 22 2 4 16 19 3 4 company Sub-national government 6 0 5 1 4 2 1 measure Tariff measure 505 247 93 164 377 128 68 Technical barrier 37 12 13 12 24 13 7 to trade Trade defence measure (AD, 577 92 241 243 308 269 59 CVD, SG) Trade finance 32 0 11 23 29 3 7 Source: Compiled from Global Trade Alert (Accessed May 2012) 58 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Aggregate trade policy Measures by all countries during the global economic crisis Total measures excluding trade Total measures defence measures Statistic May, September, June, May, September, June, 2012 2010 2010 2012 2010 2010 Total of all measures 2236 1226 175 1661 872 140 Total green measures 513 246 71 421 209 69 Total amber 544 342 20 304 166 17 measures Total red measures 1174 638 84 932 497 54 Source: Compiled from Global Trade Alert (accessed May 2012) and Evenett (2010). Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 59 1 1 2 6 5 10 24 30 125 113 Number products of affected 1 3 1 1 1 8 1 3 30 16 13 Number of affected sectors 4 1 1 2 8 3 13 41 17 20 16 Number of jurisdictions affected African Export subsidy, Export Export subsidy, taxes or restriction Bail out / state aid measure, Export subsidy Tariff measure Tariff Sanitary and Phytosantiary Measure Bail out / state aid measure Local content requirement, Public procurement Local content requirement, Public procurement Export subsidy Yes Yes Yes Yes Yes Yes Implemented Measure type Red Red Red Red Red GTA GTA Green Amber No measure Tariff Amber No Amber No measure Tariff Amber No Amber No Public procurement evaluation EU: Additional out-of-quota sugar exports United States of America: Renewal of preferential trade programs EU: Reclassification of DMB mobile phones for tariff purposes. EU: Measures to “stabilise” markets for certain dairy products United States of America: New food safety requirements United States of America: Support for General Motors and Chrysler. United States of America: Possible imposition of a fee on imported dairy products United States of America: Buy American provisions in school construction bill. United States of America: Buy American provisions in stimulus package United States of America: Dairy Export Incentive Program USA: Water Quality Improvement USA: Water Act of 2009 2010 2009 2009 2009 2009 2009 2009 2009 2009 2009 Year Measure title 2009 Selected EU and USA measures that have a direct impact on Africa a direct impact on Selected EU and USA measures that have 60 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries 2 1 1 1 11 17 886 150 Number products of affected 1 1 1 2 1 1 1 1 19 Number of affected sectors 7 1 1 1 2 2 11 42 44 13 Number of jurisdictions affected African Tariff measure Tariff Technical Barrier to Technical Trade Quota (including tariff rate quotas) Other service sector measure measure, Tariff Local content requirement Bail out / state aid measure Technical Barrier to Technical Trade Bail out / state aid measure measure, Tariff Local content requirement Yes Yes Implemented Measure type Red GTA GTA Green Green No Amber No measure Tariff Amber No Amber No Amber No Amber No Amber No Amber No evaluation EU: Additional import duties for certain products in the sugar sector United States of America: Additional sugar import quota for 2010 remainder of Fiscal Year United States of America: Expiration and renewal of trade preferences and other programs United States of America: Bill to ban imports of goods for which there is no registered domestic agent United States of America: Bill to tax and discourage the use of foreign call-centers United States of America: Relaxation of Buy-American standards in defense procurement United States of America: Subsidy to tuna canner United States of America: Bill to strengthen customs enforcement for apparel United States of America: Using revenue from apparel imports to fund program for domestic wool industry United States of America: U.S. for biofuel requirements citizenship subsidies 2011 2010 2010 2010 2010 2010 2010 2010 2010 Year Measure title 2010 Protectionist trade policy instruments in the global economic crisis: An impact analysis from Africa-EU and Africa-US trade relations 61 1 1 1 8 2 4 1 1 1 47 Number products of affected 1 1 1 2 3 1 1 2 1 1 Number of affected sectors 1 1 1 2 4 4 17 11 11 16 Number of jurisdictions affected African Bail out / state aid measure Import subsidy Local content requirement Tariff measure Tariff Export subsidy Export subsidy Non tariff barrier (not otherwise specified) Export subsidy Yes Yes Yes Yes Yes Implemented Measure type Red GTA GTA Green Green No Green No measure Tariff Green No Green Green Amber Amber No measure Tariff Amber No evaluation EU: Temporary suspension EU: Temporary of import tariffs for the CXL concessions sugar quota during the market year 2010/2011 United States of America: Initiative to eliminate subsidy on mohair production United States of America: Initiative to end subsidies and tariffs on ethanol United States of America: Failed attempt to enact Buy-American requirements EU: Suspension of import duties for certain products in the cereals sector EU: opening to tender export refunds on certain milk products United States of America: Increase and expand scope of fee on imported cotton products EU: Reduction of the export refunds for beef and veal EU: Fixing the export refunds for poultry meat United States of America: Reduced excise taxes for domestic but not imported micro-brewery beer 2011 2011 2011 2011 2011 2011 2011 2011 2011 Year Measure title 2011 62 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries 6 6 8 2 1 55 Number products of affected 6 1 1 1 1 1 Number of affected sectors 1 1 1 1 1 1 41 15 Number of jurisdictions affected African Local content requirement Bail out / state aid measure, Export subsidy Quota (including tariff rate quotas) Non tariff barrier (not otherwise specified) Quota (including tariff rate quotas) Yes Implemented Measure type GTA GTA Green Green No measure Tariff Amber No Amber No Amber No Amber No Amber No Public procurement Amber No measure Tariff evaluation United States of America: Buy- American provisions in the Department of Homeland Security appropriations bill United States of America: Repeal the Dairy Export Incentive Program United States of America: Increase in fee for milk TRQ United States of America: Bill to increase security against piracy United States of America: Buy- American provisions in the proposed American Jobs Act EU: Temporary suspension of EU: Temporary import tariffs for an exceptional tariff quota of sugar United States of America: increase in Reauthorization of GSP, import fee, and expansion of Trade Adjustment Assistance EU: Temporary suspension of EU: Temporary customs duties on certain cereal products for the 2010/2011 marketing year 2011 2011 2011 2011 2011 2011 2011 Year Measure title 2011 Computed from Global Trade Alert Database Computed from Global Trade Source: Note: The sectors and products considered are in 2-digit 4-digit, respectively. 5 SADC Crisis-era trade policy and its effects on intra-regional trade and investment

Albert Makochekanwa and Emson F. Chiwenga Southern Africa Trade Hub; Ministry of Labour and Social Services, Zimbabwe

1. Introduction

Since its creation in 1995, the WTO (and its predecessor, the General Agreement on Tariffs and Trade) has been at the forefront of promoting free trade among participating member states. The role of free trade on the global scale at large, and in rapid socio-economic development of Southern Africa countries, cannot be over-emphasised. It is a major source of the strong economic performance of most Southern African countries in recent times. However, the recent global and financial crises (which began at the end of 2008) have led to a proliferation of both liberal and protectionist trade policies being adopted by Southern African countries, among others. Liberal polices present possible opportunities for enhancing intra-regional trade and investments in the Southern African Development Community (SADC)1 region, while restrictive measures threaten the foundation of the success recorded by this region in trade expansion, cross- border investments, market access and economic progress. The crisis has resulted in numerous countries taking diverse policies including industrial, trade and exchange-rate measures and these policies have a bearing on regional integration. These measures have had mixed effects, with measures having impacted positively on these economies through increased exports, imports of critical inputs, domestic employment creation and increased investment opportunities, while some have had severe adverse effects on the economy. These negative effects include sharp declines in exports, foreign direct investment (FDI), private capital flows, national savings, rises in unemployment,

1 The current 15 Member States (MS) are: Angola, Botswana, Democratic Republic of Congo (DRC), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe.

63 64 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries worsened terms of trade, and impacts on the current account balance (Ogunleye 2010). Although there is evidence of a plethora of post-crisis policies that have been implemented by both developed and developing countries, most of the impact studies since the crisis began have focused on the North-South relationship, where the studies investigated the extent to which policies adopted by the North (developed countries) impacted on the South (developing countries) mostly through the trade channel. Unfortunately, limited attention has been given to the impact of South-South relationship in the aftermath of the crisis. There are no studies that analyse the extent to which policies adopted by developing countries impact on other developing countries. Such studies are even scant in the regional trading bloc context. It is this gap that this paper addresses by zeroing in on the SADC region. Thus, this chapter examines selected specific discriminatory policy measures (trade and investment) adopted by three SADC countries – Botswana, South Africa and Zimbabwe – and summarises their impacts on their respective economies, most importantly on the other SADC regional members. This study articulates the nature of post-crisis trade and investment measures adopted and implemented by Botswana, South Africa and Zimbabwe in three broad areas: (a) exchange rate/investments measures; (b) local content requirement on government procurement and/or buy national product campaigns; and (c) import/export duty changes. It further investigates the extent to which the measures of these three countries either encourage or discourage SADC intra- trade and intra- or cross-border investment. The Global Trade Alert (GTA) database is used to itemise all the policy measures that the three countries have adopted in response to the global financial crisis. These measures were analysed to infer the extent to which they either encourage or discourage intra-SADC trade and intra-SADC investment, and as such, how the same measures are in line with, or oppose the two SADC Protocols – the Protocol on Trade, and the Protocol on Finance and Investment. Furthermore, trade data from the United Nations Commodity Trade Statistics Database (UN Comtrade) were, where applicable, employed in the analysis of the various measures to get possible impacts.

2. Impact of Botswana’s policy measures on SADC regional integration

All of the measures that have been announced and adopted by the government of Botswana since the financial crisis began aim to encourage government agencies to procure locally produced goods from citizen-owned enterprises. Such policies are tantamount to discrimination against SADC- (foreign-)owned companies, thus working against the spirit of both the Protocol on Trade and the Protocol on Finance and Investment, as they will discourage government entities from importing from SADC countries. Such measures will hinder trade integration. SADC Crisis-era trade policy and its effects on intra-regional trade and investment 65

Table 5.1 lists four policy measures that have been announced by Botswana after the financial crisis to buttress its attempts to encourage purchases of goods and services by government from local and citizen-owned enterprises. Table 5.1 Botswana’s policy measures Potential impact on SADC intra- Policy initiative Date announced trade and investment Budget statement and Discourage SADC exports to 8 Feb 2010 procurement discrimination Botswana Government bodies urged Discourage SADC exports to 25 Feb 2010 to buy local. Botswana Proposed changes in Discourage SADC exports to procurement law to favour 13 Nov 2009 Botswana local companies Give advance to local firm which Subsidies and loans for may translate to cheaper price January 2010 textile sector than similar products from SADC countries

2.1 Budget statement and procurement discrimination

In analysing the policies implemented by Botswana, it is important to note that the government is the largest consumer of goods and services, accounting for nearly a third of the country’s GDP by expenditure in 20092. The most frequently purchased products and services by government ministries’ departments, local government departments, parastatals and councils are cleaning materials and services, food stuffs, office furniture, protective clothing, stationery and printing services, building materials, fuels and lubricants and vehicle spare parts (LEA 2009). Botswana’s official statements support the notion of preferential procurement of government departments and parastatals from locally and citizen-owned enterprises, thus discriminating against products and services from SADC countries. Currently, most of the goods and services procured by government departments in Botswana, such as food stuffs, protective clothing, stationery and vehicle parts, are mostly supplied by South African firms. On the other hand, some services, especially in the construction industry including design, building, electrical, etc., are supplied by companies that are registered in Botswana, but are owned by other SADC nationals, mainly Zimbabweans. Thus the measures implemented by Botswana work against the spirit of regional integration as they discourage exports from SADC countries.

2 Calculated using Botswana Central Statistical Office (CSO) figures. 66 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

3. Impact of South African policy measures on SADC regional integration

The global financial crisis has had a severe impact on South Africa. The economy went into recession in 2008-09 for the first time in 17 years. Powell and Steytler (2010) claim that nearly a million people lost their jobs in 2009 alone, while even more jobs were lost in 2010 and 2011. Growth has resumed, but the recovery is fragile, and another recession is possible. Rising unemployment and poverty have placed greater demands on state resources even as revenues contracted, and there is mounting political pressure on the government to review its economic policy. Various measures have been announced and/or implemented since 2008. For ease of analysis, here the measures are grouped together as follows: (i) those dealing with changes in export taxes and import duties including bans; (ii) measures which aim to encourage government and firms to buy their goods and services from local (Black Economic Empowerment (BEE)) firms or buy national campaigns; and (iii) policies which deal with exchange rate and investment changes. The measures relating to changes in export and import duties show that most of them have a positive impact on SADC integration. For instance, “Increase in rate of duty on wheat and wheaten flour from the EU and EFTA” will mean that SADC countries exporting wheat and wheaten flour products to South Africa will have an advantage as their products will enter duty free, hence giving them a price advantage when compared to those from EU and EFTA. In this case, there will be a potential increase in exports into South Africa from SADC members, namely Botswana, Lesotho, Malawi, Mozambique, Namibia, Swaziland and Zambia. The beneficiary countries have been chosen on the basis that they had been exporting the same products to South Africa before the introduction of this new measure. Similarly an “Automotive Investment Scheme (AIS)” provides taxable cash grants to approved applicants for the main purpose of increasing production, introducing new components, introducing intermediate products, and creating new markets will mean that recipient South African firms will be able to produce and export more to SADC countries. This measure will result in more South African car exports to all SADC countries3. This measure impacts positively on SADC integration as it results in more trade. Furthermore, the same measure encourages investments mostly to local South African firms involved in the automobile industry. The third measure type, “New preferential procurement regulations for public entities”, which encourages the South African government and its departments to buy goods and services from local producers, discriminates against foreign firms including those from the SADC region. This measure ensures that priority is given to South Africa firms producing locally. Thus, government entities will have a reduced interest in importing from SADC countries. This measure

3 UNCOMTRADE does not show separate data for South African and other Southern African Customs Union (SACU) Member States of Botswana, Lesotho, Namibia and Swaziland. SADC Crisis-era trade policy and its effects on intra-regional trade and investment 67

therefore works against regional integration, as it will discourage exports from SADC countries of the products in question or covered by this measure.

4. Impact of Zimbabwe’s policy measures on SADC regional integration

The measures which were announced (and/or implemented) by Zimbabwe fall into two groups: (i) those dealing with changes in export taxes and import duties including bans; and (ii) policies which deal with exchange rate and investment changes. The credit facility to importers introduced in 2009 was meant to encourage imports of goods into the country. This measure had the potential for increasing intra-SADC trade by encouraging exports from SADC countries into Zimbabwe. South Africa is one of the countries that are likely to benefit the most, given that Zimbabwe sources more than 50% of its total imports from South Africa. Major changes to the foreign exchange regulations resulted in a 143% increase in remittances from the diaspora in 2009 compared with 2008 (with over 53% coming from the SADC region). A further increase of 32% was registered in 2010. The growth rates primarily reflected the markets’ confidence in the formal channel of remitting funds (GoZ 2011). Given that three million (or 75%) of the four million Zimbabweans in the diaspora reside in South Africa, and a further sizeable number in Botswana, this measure has resulted in increased intra- regional trade in the services sector. Imports of vehicles from the SADC region grew by 25% despite a ban on the importation of used vehicles more than five years old, which was later suspended4. This was not surprising given that most second hand vehicles affected by the ban are from Japan, while imports from SADC countries (see the list in Table 5) are normally new. Thus, this growth in imports from SADC was mostly of new cars. The reduction in duty on selected food and clothing items introduced to counter the food crisis in 2009 seems to have benefited selected countries within the SADC region. For instance, the measure resulted in countries such as South Africa exporting more food and live animals, while countries such as Botswana, Mauritius and Zambia increased their exports of blankets to Zimbabwe. Contrary to one of the objectives of the SADC Protocol on Finance and Investment which states that that “ …any changes to financial and investment policies in one state party do not necessitate an undesirable adjustments in other state parties,” the 51% ownership measure has a direct impact on the member states with investments in Zimbabwe or those who intent to invest. Thus, while the impact of the proposed 51% ownership on SADC countries cannot be fully ascertained because it has not been fully implemented, the inability of Zimbabwe to attract meaningful investments from the region in the post-crisis period can be viewed as being partially a result of this indigenisation drive. The country has

4 Government has indefinitely suspended the ban on used car imports that are five-years-old and above while the importation of left-hand drive vehicles was not be allowed from 1 November 2010, see http:// www.herald.co.zw/index.php?option=com_content&view=article&id=22967. 68 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries failed to attract meaningful investment from the SADC region despite numerous promises.

5. Conclusion

This chapter sets out the nature of post-crisis trade and investment measures adopted and implemented by Botswana, South Africa and Zimbabwe, with the intention of teasing out the potential impacts of such measures on intra-SADC trade and investment. Overall, it can be concluded that some of the measures taken by SADC countries disregard some provisions of the SADC Protocol on Trade and the SADC Protocol on Finance and Investment, thereby discouraging intra-regional trade. For Botswana, all of the measures that have been announced and/or implemented by the government to date are a hindrance to intra-SADC trade, as they discourage imports from the region for government procurement and, at the same time, they also discourage procurement from locally registered entities that are not citizen-owned. In the case of South Africa, measures implemented to limit the impact of the global financial crisis have resulted in mixed impacts on SADC intra-regional trade and investment. Some measures, especially those dealing with changes in export taxes and import duties, have been beneficial (or are likely to be beneficial) to SADC countries that export goods that are covered by the various import duty change measures. On the other hand, measures dealing with government procurement are a hindrance to intra-SADC trade as they discourage imports from the region for government procurement. Lastly, most of the export/import duty changes measures which were implemented by Zimbabwe support regional integration of the SADC, while measures relating to company ownership (although not yet fully implemented) have already set in motion a trend which discourages investment ventures by businesses from the SADC. As to policy recommendations, the SADC must ultimately adopt a customs union (as indicated in its long-term regional strategic goals) to reduce the impact of negative measures on intra-regional trade. This requires serious political will from member countries, especially in refraining from implementing new measures that restrain regional trade. Second, investment measures that take account of the regional bloc are critical since an undesirable measure in one country may disadvantage investment in the whole region. Thus, countries should strive to implement investor-friendly measures, nationally and on a region-wide basis.

References

Afari-Gyan, N. A. (2010), “Transforming Africa’s Structure and Composition of Trade after the GlobalEconomic Crisis”, in S. J. Evenett (ed), Africa Resists the Protectionist Temptation: The 5th GTA Report, Global Trade Alert. SADC Crisis-era trade policy and its effects on intra-regional trade and investment 69

Evenett, S. J. (2010.), “The landscape of crisis-era protectionism three years since the first G20 Summit in November 2008”, in S. J. Evenett (ed.),The Unrelenting Pressure of Protectionism: The 3rd GTA Report, Global Trade Alert. Evenett, S. J. (2010), “The harm done to the commercial interests of the LDCs: An update”, in S. J. Evenett (ed.), Tensions Contained... For Now: The 8th GTA Report, Global Trade Alert. Government of Zimbabwe (GoZ) (2011), Monetary Policy Statement (MPS). Local Enterprise Authority (LEA) (2009), Packaged government and parastatals procurement from SMEs study. Ogunley, E. K. (2010), “Effects of post-crisis foreign trade policy measures on economic and trade performance in Africa”, in S. J. Evenett (ed), Africa Resists the Protectionist Temptation: The 5th GTA Report, Global Trade Alert. N’zue, F. F. (2010), “Impact of the global financial crisis on trade and economic policy making in Africa”, in S. J. Evenett (ed), Africa Resists the Protectionist Temptation: The 5th GTA Report, Global Trade Alert. Powell, D and N. Steytler (2010), “The impact of the global financial crisis on decentralized government in South Africa”, Community Law Centre University of the Western Cape. Prepared for delivery at the annual conference of the International Association of Centers or Federal Studies, 16-18 September, Philadelphia SADC Secretariat (2006), Protocol on Finance and Investment, Gaborone, Botswana SADC Secretariat (2000), Protocol on Trade, Gaborone, Botswana

Websites visited http://globaltradealert.org www.sadc.int

About the authors

Albert Makochekanwa is an economist with close to 10 years of experience in economics and social science issues. He has worked extensively in Africa, specifically, Zimbabwe, South Africa, Botswana and Ethiopia. Dr. Makochekanwa has published several papers and contributed to several studies on economic issues in Southern Africa. Dr. Makochekanwa holds a Ph.D. in Economics Degree (University of Pretoria, South Africa), a Master of Science (MSc) in Economics Degree (University of Zimbabwe, Zimbabwe) and an Honours in Economics Degree (University of Zimbabwe, Zimbabwe). Over the years, Dr. Makochekanwa has also been a consultant to the following organizations with which he has produced technical and policy documents: (1) World Bank Institute (WIB) Washington DC, USA; (2) United Nations Conference on Trade and Development Virtual Institute (UNCATDVi), Geneva, Switzerland; (3) Trade and Industrial Strategies (TIPS of South Africa) and AusAID, (4) Center for Global Development 70 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

(CGD), Washington DC, USA; (5) United Nations Children’s Fund (UNICEF), Harare, Zimbabwe; (6) African Economic Research Consortium (AERC), Kenya; (7) Centre for International Governance Innovation (CIGI), Canada; (8) Namibia Chamber of Commerce and Industry (NCCI), Namibia, (9) Underhill Capital Solutions, South Africa, (10) University of Mauritius (UoM), Mauritius; and (11) Trade and Development Studies Centre, Zimbabwe, among others.

Emson F Chiwenga is a Principal Economic Economist in the Ministry of Regional Integration and International Cooperation. He holds a Masters degree in Trade Policy and Trade Law from Lund University and a Bachelor Of Science Honours in Economics from the University Of Zimbabwe. Before joining the Ministry Emson was an Executive Researcher at Southern Africa Trade and Development Trust. Emson has also worked as an Exchange Control Officer with the Reserve Bank Of Zimbabwe, an Economist with the Competition & Tariff Commission and Ministry of Industry and international Trade as well as a Revenue trainee with the Zimbabwe Revenue Authority. He has previously been involved in research for AERC and other related institutions relating to trade issues. 6 The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector

Bethuel K. Kinuthia, Remco H. Oostendorp and Jacob A. Jordaan Leiden University and University of Nairobi; VU University Amsterdam, Tinbergen Institute Oxford University; VU University Amsterdam

In response to the recent global economic crisis, many governments have implemented a variety of restrictive trade and labour policies. A good example of this is in Malaysia where the government has implemented a controversial Foreign Workers First Out policy, promoting the dismissal of foreign workers and the substitution of Malaysian for non-Malaysian labour. The introduction of this policy offers a unique opportunity to study the effectiveness and economic effects of restrictive labour policies. Using manufacturing industry-level data for the period 2005-09 that distinguish between domestic and foreign workers, we investigate the effectiveness of the Foreign Workers First Out policy and its economic effects. We find that this policy has led to a significant decrease in the use of foreign workers, especially in industries with high pre-crisis industry shares of foreign labour. Furthermore, we identify significant positive productivity effects from the use of both high-skilled and low-skilled foreign workers. These positive effects are particularly pronounced in important segments within the manufacturing sector. The decrease in the use of foreign workers will generate important productivity losses in these segments, weakening the role of the manufacturing sector as main driver of the Malaysian economy.

71 72 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

1. The Foreign Workers First Out policy in Malaysia

The global economic crisis is posing a challenge for many developing economies (UN, 2010). A good example of the severity of the impact of the crisis is Malaysia, which experienced a large decrease in industrial production, a collapse of manufacturing exports, a substantial slowdown in inward foreign direct investment and an increase in unemployment. The manufacturing sector, responsible for about 80% of Malaysia’s total export revenues, was particularly hard hit1. In response to the crisis, the Malaysian government started a Foreign Workers First Out (FWFO) policy at the end of 2008 and beginning of 20092. The policy includes measures such as increased fees to hire foreign workers, the introduction of mandatory health insurance for foreign labour and government programmes labelled “Train to Replace,” aimed at improving skills of domestic workers to facilitate the substitution of domestic for foreign workers. Most recently, the introduction of a mandatory minimum wage in 2012 that applies to all workers irrespective of nationality is also expected to act as a deterrent to using foreign workers. The FWFO policy has raised fierce protests from many organisations within Malaysia that argue that the policy promotes a premature dismissal of foreign workers in breach of their employment contracts. Approximately 1.8 million foreign-born workers live in Malaysia. Migrants from South and Southeast Asian developing countries are heavily represented, and so the FWFO policy implications those nations’ commercial interests. Internationally, the policy has attracted the attention of the Global Trade Alert database, which reports and monitors restrictive government policies that are implemented in response to the economic crisis, policies that are expected to have a detrimental effect on international commerce3. Importantly, the WTO lacks comprehensive provisions and obligations on labour migration. Also, there is very little evidence on the effectiveness and the actual economic effects that may arise in countries that adopt such restrictive labour policies. The introduction of the FWFO policy presents us with a unique opportunity to study the effectiveness and the economic effects of this case of restrictive labour policy. The Department of Statistics in Malaysia provided us with annual 5-digit manufacturing industry level data for the period 2005-09. This dataset contains information on industry output and inputs. Importantly, the dataset distinguishes between Malaysian and non-Malaysian workers. Our focus is on two related questions. First, we estimate the effect of the restrictive labour policy on the use of foreign workers. As our dataset contains data from before and after the implementation of the labour policy, we can identify statistically the effect of the policy. Second, we estimate production functions to

1 Bussiere et al. (2011) provide an overview of government responses to the recent crisis. See also Henn and McDonald (2011). 2 The goal of the policy is to cut the number of foreign workers in the Malaysian economy to 1.8 million in 2009, followed by an additional decrease of 300,000 in 2015. 3 www.globaltradealert.org The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 73 investigate whether the use of foreign workers is related to industry productivity. It may be the case that foreign workers incorporate certain skills, knowledge, experience or a work ethos that are different from domestic workers. If this is the case, the decrease in the use of foreign workers may affect productivity of Malaysian manufacturing firms. Furthermore, we assess whether these effects differ across industries.

2. The Foreign Workers First Out policy and the use of foreign labour

Table 6.1 presents information on the use of foreign workers in the years before and during the economic crisis. There was a strong upward trend in the industry share of foreign labour in the pre-crisis period 2005-07, from 16% to 23%. This trend was discontinued and even reversed with a large fall to 19% in 2008, and 20% in 2009. Table 6.1 also distinguishes between industries with low and high industry shares of foreign workers. The strongest reduction in the use of foreign labour is reported in industries with a relative high pre-crisis industry share of foreign workers4. To link the decrease in use of foreign workers to the introduction of the FWFO policy, we adopt a quasi-experimental modelling strategy, exploiting the feature that some industries were more affected by the introduction of the restrictive labour policy than others5. Industries that have been “more affected” are industries with a relatively high pre-crisis level of use of foreign workers. We calculate the change in the industry share of foreign workers for the periods 2006-07, 2007-08 and 2007-09. We use the period 2006-07 as the pre-crisis period, 2007-08 as the initial crisis period and 2007-09 as the full crisis period6. We expect that industries with higher pre-crisis industry shares of foreign labour show larger declines in their use of foreign workers than industries with lower pre-crisis use of foreign labour.

4 See World Bank (2011) for information on the overall use of foreign labour in the Malaysian economy. 5 This approach is similar to the approach that has been developed in the literature that analyses the impact of changes in minimum wages (see Card, 1992; Stewart, 2002; Draca et al., 2011). 6 Although the FWFO policy was formally announced in the beginning of 2009, more stringent foreign labour policies may have actually already been in force with the onset of the crisis in 2008, and therefore policy-induced changes in the use of foreign labour might already be detectable in the initial crisis period 2007-2008. 74 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 6.1 Share of foreigners in industry employment (levels and changes), 2005- 2009 Level Change Pre- Crisis crisis 2005- 2007- 2007- 2005 2006 2007 2008 2009 2007 2008 2009 Overall 0.16 0.18 0.23 0.19 0.20 0.07 -0.04 -0.03 Manufacturing Industries with low 0.09 0.10 0.13 0.13 0.14 0.04 0.00 0.01 share of foreigners Food products 0.10 0.09 0.13 0.14 0.14 0.03 0.01 0.01 Tobacco products 0.02 0.04 0.03 0.03 0.03 0.01 0.00 0.00 Paper and paper 0.07 0.08 0.10 0.11 0.11 0.03 0.01 0.01 products Printing and services activities 0.07 0.07 0.11 0.16 0.12 0.04 0.05 0.01 related Petroleum products 0.02 0.01 0.05 0.08 0.03 0.03 0.03 -0.02 Chemical products 0.08 0.08 0.09 0.05 0.13 0.01 -0.04 0.04 Fabricated metal 0.10 0.16 0.20 0.18 0.21 0.10 -0.02 0.01 products Rubber products 0.08 0.11 0.12 0.18 0.11 0.04 0.06 -0.01 Transport 0.09 0.09 0.13 0.12 0.14 0.04 -0.01 0.01 equipment Industries with high 0.19 0.20 0.26 0.21 0.23 0.07 -0.05 -0.03 share of foreigners Wood and wood 0.43 0.44 0.45 0.42 0.43 0.02 -0.03 -0.02 products Glass and non- metallic mineral 0.11 0.12 0.20 0.15 0.23 0.09 -0.05 0.03 products Basic metals 0.10 0.16 0.14 0.16 0.13 0.04 0.02 -0.01 Machinery and 0.21 0.24 0.22 0.22 0.20 0.01 0.00 -0.02 equipment Medical, optical and scientific 0.07 0.15 0.17 0.12 0.17 0.10 -0.05 0.00 instruments Non-metal furniture 0.31 0.34 0.38 0.35 0.33 0.07 -0.03 -0.05 Other 0.18 0.21 0.26 0.22 0.24 0.08 -0.04 -0.02 Textile and 0.20 0.23 0.19 0.19 0.19 -0.01 0.00 0.00 footwear Electrical and 0.13 0.13 0.21 0.16 0.16 0.08 -0.05 -0.05 electronic products Note: Industries with below (above) median share of foreign workers in 2007 are classified as having a low (high) share of foreign workers in the above table. The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 75

Figure 6.1 shows the findings from locally weighted regressions of the changes in the industry-level share of foreign workers with respect to the pre-crisis industry share of foreign workers for the periods 2006-07, 2007-08 and 2007-09. We define the pre-crisis share of foreign workers in an industry as the mean share of foreign labour during the pre-crisis years 2005-07. Figure 1 clearly shows that changes in the share of foreign labour in the pre-crisis period 2006-07 have a very different pattern from those in the crisis periods 2007-08 and 2007-09. This is especially the case for industries with shares of foreign labour exceeding 10%; industries with lower shares of foreign labour show similar patterns for all three periods. This confirms our quasi-experimental modelling strategy that industries with larger pre-crisis shares of foreign labour are more affected by the FWFO policy. Figure 6.1 Changes in industry-level shares of foreign labour

Change in share of all foreign workers .1 .05 0 −.05 −.1 0 .2 .4 .6 Share all foreign workers pre−crisis

2006−2007 2007−2008 2007−2009

Next, we estimate the changes in the industry shares of foreign labour in a difference-in-difference regression framework for the entire period 2005-09. We estimate the following equation separately for foreign white- and blue-collar workers:

2009 pre pre pre shareit = αi + ∑t=2005 δtYt + γTt * sharei + ψ1 Y2008 * sharei + ψ2 Y2009 * sharei +εit (2.1) where i and t are subscripts for industry and year, αi is an industry-specific effect, pre Yt are time dummies, Tt is a trend variable, sharei is the mean share of foreign labour in the pre-crisis years 2005-07 and εit is a random error. The term Tt * pre sharei is included to allow changes in the trend of the share of foreign labour to vary across industries, depending on their current use of foreign workers. The regression corrected difference-in-difference (DD) estimates of the changes in the industry share of foreign labour are ψ1 and ψ2, they are expected to be negative as a result of the FWFO policy. Table 6.2 show the regression results. For white-collar workers, we find no increasing overall trend in the use of foreign labour (δt). However, industries with 76 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries a high pre-crisis share of foreign white collar workers show a strong increase in their use of foreign skilled labour (γ is positive). For blue-collar workers, the trend is increasing overall and industries with a relatively high pre-crisis share of low skilled foreign workers show an increase in their use of this type of foreign labour. Most importantly, the DD estimates are all negative and jointly significant, showing that the use of foreign workers was strongly reduced in industries that were most affected by the policy. The DD estimates for foreign white- collar workers are individually insignificant, but this reflects the fact that the industry share of foreign white-collar workers in total white-collar employment is typically small (2.9% on average), and they are not statistically different from the estimated blue-collar DD coefficients (p-value 0.88)7. The size of the DD coefficients suggests that the FWFO policy reduced the use of foreign white- and blue-collar workers by about 25% in the period 2007-09. We have verified that this decline in foreign labour use cannot be attributed to the crisis itself, as the estimated reduction in the use of foreign labour is the same when we control for industry changes in the total labour force and sales as possible determinants of the change in foreign labour use. Table 6.2 Difference-in-difference (DD) estimates for white and blue collar workers Estimate (1) (2) White collar Blue collar

δ2006 -0.01 (2.54) 0.00 (0.27) δ2007 -0.01 (2.47) 0.03 (1.65) δ2008 -0.01 (2.06) 0.05 (3.03) δ2009 -0.01 (2.76) 0.07 (4.75) γ 0.18 (2.90) 0.09 (2.89)

ψ1 (DD) -0.24 (1.45) -0.17 (2.15) ψ2 (DD) -0.25 (1.16) -0.32 (3.03) Industry fixed effects Yes Yes Number of observations 505 505 R2 0.69 0.88 Note: Absolute t-values in parentheses

3. Foreign labour and productivity effects

It is clear that the FWFO policy has lowered the use of foreign workers. To get an indication of the economic effects of this, we conduct an econometric analysis to determine whether foreign workers generate productivity effects among Malaysian firms. It important to consider that there is no clear theoretical prediction of the nature of these effects. It may be the case that foreign workers create positive productivity effects. A firm may hire a worker from abroad with

7 The share of foreign blue-collar workers in blue-collar employment was 22.2% on average over the 2005-2009 period. The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 77 specific skills or knowledge that is difficult to find among domestic workers (Markusen and Trofimenko, 2009). Also, foreign workers may be characterised by a favourable work ethos or possess skills that are complementary to those possessed by domestic workers (Lazear, 1999; Peri, 2009). However, it may also be the case that foreign workers lack certain skills or experience, which may result in a decrease in productivity among domestic firms (see Paserman, 2009). Of course, it may also be the case that foreign and domestic workers are perfect substitutes, in which case no productivity effects will materialise. To identify productivity effects from using foreign workers, we use a standard Cobb Douglas production function framework. The log linearised specification is as follows: lnYit = lnAit + alnKit +γlnLit + ϑlnHit + dlnMit + Ii + Tt + εit (3.1)

Y is total sales, A is the productivity parameter, K is capital measured as the net book value of total capital, L is employment measured as total number of employees, H captures human capital measured as the share of white-collar employees in total employees, M is the value of raw materials, I and T are industry and year effects and i and t capture the industry and time dimensions of the dataset. To identify productivity effects from the use of foreign workers, we replace the productivity parameter with the industry share of foreign workers in industry employment. To see whether productivity effects depend on type of worker, we also estimate the regression model controlling for the shares of foreign white- collar workers and foreign blue- collar workers in industry white- collar employment and industry blue- collar employment. The findings from estimating regression model (3.1) are presented inthe first part of Table 6.3. The estimated effect of the variable capturing the share of foreign labour in industry employment carries a positive but insignificant coefficient, suggesting that there are no productivity effects from using foreign workers. However, the results are different when we distinguish between the use of foreign high- skilled and foreign low- skilled workers. The variable capturing the use of foreign white-collar workers carries a positive and significant coefficient, indicating that Malaysian firms experience positive productivity effects from using high-skilled foreign workers. This suggests that this type of foreign worker possesses certain skills, experience and knowledge that benefit Malaysian firms. The estimated effect of the use of low-skilled foreign workers carries an insignificant coefficient, suggesting that the use of this type of foreign labour does not affect productivity of Malaysian firms. To study further the productivity effects of foreign workers, we consider the possibility that productivity effects are not constant across industries. Whether productivity effects vary across industries is especially relevant when considering that the restrictive FWFO labour policy applies equally to all types of workers and industries. To test for industry heterogeneity, we estimate the regression model 78 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries separately for different sets of industries. We separate industries into high- and low- productivity industries and capital- and labour-intensive industries8. The second part of Table 6.3 presents the findings from estimating the regression model for the different types of industries. The findings from distinguishing between high- and low-productivity industries contain two important features. First, positive productivity effects from foreign high skilled workers only materialise in high productivity industries. This suggests that this type of foreign worker possesses certain skills, knowledge and experience that are particularly suited for this type of industry. Table 6.3 Productivity effects from the use of foreign labour High Low Capital Labour (1) (2) productivity productivity intensive intensive 1.53 1.59 1.76 1.66 2.08 1.00 Constant (0.18)a (0.18)a (0.37)a (0.30)a (0.40)a (0.20)a 0.02 0.02 0.004 0.03 0.01 0.006 Log Capital (0.007)a (0.007)a (0.01) (0.01)a (0.01) (0.009) 0.19 0.20 0.18 0.25 0.25 0.11 Log Labour (0.02)a (0.02)a (0.03)a (0.03)a (0.04)a (0.02)a 0.39 0.39 0.63 Human Capital 0.34 (0.10)a (0.09)a (0.12)a 0.63 -0.22 (0.20) (0.15)a (0.14) 0.78 0.78 0.78 0.72 0.72 0.88 Log Raw Materials (0.02)a (0.02)a (0.03)a (0.03)a (0.03)a (0.02)a Share foreign workers in 0.12 industry (0.09) employees Share foreign white collar 0.56 0.47 -0.19 0.79 -0.20 workers in (0.19)a (0.24)b (0.44) (0.28)a (0.31) industry white collar employees Share blue collar foreign workers 0.03 -0.19 0.30 -0.19 0.28 in industry blue (0.07) (0.09)b (0.13)b (0.15) (0.09)b collar employees R2 0.93 0.94 0.92 0.94 0.91 0.96 Prob > Chi 2 0.00 0.00 0.00 0.00 0.00 0.00 Number of 505 505 205 199 204 200 observations Note: All estimations are fixed effects specification; a and b indicate significance levels of 1% and5%. Heteroscedasticity-robust standard errors are reported between brackets. Estimations for high and low productivity and capital- and labour-intensive industries use one year lagged values for foreign white collar and foreign blue collar variables. Industries with above (below) median values of industry productivity or capital intensity are classified as high (low) productivity and capital- (labour-) ntensivei industries.

8 Productivity is the ratio sales/employment; capital versus labour intensive is based on the ratio net book value capital/employment. The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 79

Second, the use of foreign low- skilled workers is now also linked to significant productivity effects. Foreign blue- collar workers create negative productivity effects in high productivity industries, indicating that their skills are less suited for this type of industry. In contrast, foreign low-skilled workers generate positive productivity effects in low-productivity industries. This important distinction between the effects of white- and blue-collar foreign workers is confirmed by the findings for capital- and labour-intensive industries. Foreign high-skilled workers create positive productivity effects in capital-intensive industries, whereas foreign blue-collar workers create positive productivity effects in labour-intensive industries9. These findings that identify industry heterogeneity of the productivity impact of the use of foreign high- skilled and low-w skilled workers indicate that negative productivity effects from the decrease in use of foreign workers will be especially marked in certain segments within the Malaysian manufacturing sector.

4. Summary and conclusions

At the end of 2008 and the beginning of 2009, the Malaysian government responded to the economic crisis by implementing a Foreign Workers First Out policy, promoting the dismissal of foreign workers and the substitution of domestic for foreign workers. This restrictive labour policy is controversial, receiving a “red” designation in the Global Trade Alert database. In our study, we analyse the effectiveness and economic effects of this restrictive labour policy. We use industry level data for the period 2005-09 that distinguishes between Malaysian and non-Malaysian workers. Our findings are three-fold. First, we find robust evidence that the policy has been effective, as the level of use of foreign workers has decreased significantly. This applies especially to industries with relatively high pre-crisis levels of use of foreign labour. Second, we identify significant productivity effects that result from the use of foreign labour. Our estimations for the entire sample of manufacturing industries indicate that the use of foreign high- skilled labour generates positive productivity effects among Malaysian firms. Third, when we distinguish between different types of industries, we find positive productivity effects from both foreign high-skilled and foreign low-skilled workers. The feature that these productivity effects are not the same across all industries indicates that negative effects from the decrease in the use of foreign workers are concentrated in segments within the Malaysian manufacturing sector. The policy implications of our findings are two-fold. First, the implementation of the FWFO policy has created negative knock-on effects, as the decrease in the use of foreign workers will inevitably have created negative productivity effects among Malaysian manufacturing firms. Second, these negative effects

9 We also estimated the regression model distinguishing between industries with high or low levels of export and research and development (R&D) intensity. The findings indicate that positive productivity effects from foreign high skilled workers exist in industries with high levels of export and R&D intensity. The estimated effect of the use of low skilled foreign labour is insignificant in these estimations. 80 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries are particularly pronounced in certain segments of the manufacturing sector. Negative effects from lowering the use of low- skilled foreign workers will be most pronounced in low- productivity and labour- intensive industries. Negative effects from lowering the use of high skilled foreign workers are concentrated in high-productivity, capital-intensive, export- and R&D-intensive industries. Given the importance of these industries for the generation of export revenues and the modernisation and technological development of manufacturing activities, the Foreign Workers First Out policy will weaken the role of the manufacturing sector as the main driver of the Malaysian economy.

References

Bussiere, M., E. P. Barriero, P. Straub, P. and D. Taglioni (2011), “Protectionist responses to the crisis: Global trends and implications”, The World Economy 34: 826-852. Card, D. (1992), “Using Regional variation in Wages to Measure the Effects of the Federal Minimum Wage”, Industrial and Labour Relations Review 46: 22-37. Draca, M., S. Machin and J. Van Reenen (2011), “Minimum Wages and Firm Profitability”,American Economic Journal: Applied Economics 3: 129-151. Henn, C. and B. J. McDonald (2011), “Protectionist responses to the crisis: Damage observed in product-level trade”, IMF Working Paper Series no. WP/11/139, Washington, DC: International Monetary Fund. Lazear, E. P. (1999), “Globalisation and the market for team-mates”, Economic Journal 109: 15-40. Markusen, J. R. and N. Trofimenko, N. (2009), “Teaching locals new tricks: Foreign exports as a channel of knowledge transfers”, Journal of Development Economics 88: 120-131. Paserman, M. D. (2008), “Do high skill immigrants raise productivity? Evidence from Israeli manufacturing firms, 1990-1999”, CEPR Discussion Paper No. 6896, London: Centre for Economic Policy Research. Peri, G. (2011), “The effect of immigration on productivity: Evidence from US states”, NBER Working Paper Series No. 15507, Massachusetts: National Bureau of Economic Research. Stewart, M. (2002), “Estimating the Impact of the Minimum Wage Using Geographical Wage Variation”, Oxford Bulletin of Economics and Statistics 64: 583-605. UN (2010), World Economic Situation and Prospects 2010, New York: United Nations. World Bank (2011), Malaysia Economic Monitor: Brain Drain, Washington, DC: World Bank. The economic crisis and the protection of domestic workers: The case of the Foreign Workers First Out policy in Malaysia’s manufacturing sector 81

About the authors

Bethuel Kinyanjui Kinuthia is a lecturer at the School of Economics, University of Nairobi, Kenya. He is also a member of the Africa Economic Research Consortium (AERC) network and the African Econometric Society. His main areas of interests include microeconomics analysis, comparative studies, migration and issues related to trade and poverty in developing countries.

Remco Oostendorp is currently Associate Professor in Development Economics at the VU University Amsterdam. He is also a Research Fellow of the Tinbergen Institute (TI), Fellow of the Amsterdam Institute for International Development (AIID), Research Associate of the Centre for the Study of African Economies (CSAE, University of Oxford), and Resource Person for the African Economic Resource Consortium (AERC). His research interests include empirical microeconomics, globalization, labor markets, manufacturing, agricultural intensification, and survey methodology in developing countries.

Jacob Jordaan (MA International Economics and Economic Geography, 1994, Utrecht University; PhD Economic Geography, 1998, London School of Economics) is currently Assistant Professor in International Economics at the VU University. He is also a Research Fellow of the Tinbergen Institute (TI). His research interests include globalization, FDI, externalities, international trade, economic geography and economic development.

PART TWO Country Specific Data on the Incidence of Crisis-Era Protectionism on the Least Developed Countries and on Africa

Table notes:

[1] These measures are classified “green” in the Global Trade Alert database. [2] These measures are classified “amber” in the Global Trade Alert database. [3] These measures are classified “red” in the Global Trade Alert database. * These measures are classified “red” in the Global Trade Alert database

Country-Specific Data 85

Afghanistan

Table 7.1. Foreign state measures affecting Afghanistan’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Afghanistan’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Afghanistan’s 67 66 commercial interests. Total number of foreign measures found to benefit or involve no 14 14 change in the treatment of Afghanistan’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Afghanistan’s commercial interests or 16 16 (ii) that have been announced but not implemented and which would almost certainly discriminate against Afghanistan’s interests. [2] Total number of foreign measures that have been implemented and 37 36 which almost certainly discriminate against Afghanistan’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Afghanistan’s 52 52 commercial interests Total number of implemented measures affecting Afghanistan’s 39 39 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Afghanistan’s 28 28 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Afghanistan’s 5 5 commercial interests Total number of pending measures that, if implemented, are likely to 5 5 harm Afghanistan’s commercial interests. AFGHANISTAN MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Afghanistan’s 10 9 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Afghanistan’s 9 8 commercial interests. Total number of implemented, but no longer enforced measures that 9 8 were almost certainly harmful to Afghanistan’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 13 13 currently in force and that harm Afghanistan’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Afghanistan” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 86 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.2. Afghanistan’s state measures affecting other jurisdictions’ commercial interests.

All measures except Summary statistic of Afghanistan’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Afghanistan’s measures affecting other 1 1 jurisdictions’ commercial interests. Total number of Afghanistan’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Afghanistan’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Afghanistan’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Afghanistan’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Afghanistan’s measures that have been implemented and are likely to harm foreign 1 1 commercial interests. Total number of Afghanistan’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Afghanistan that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Afghanistan that harm foreign none none commercial interests. Total number of trading partners affected by measures implemented by Afghanistan that harm foreign none none commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Afghanistan” in the “Affecting Trading Partner” and clicking the button “Get Stats”. AFGHANISTAN Country-Specific Data 87

Table 7.3 Frequency with which trading partners’ state measures have almost certainly harmed* Afghanistan’s commercial interests

Jurisdiction Number of measures China 6 India 5 Indonesia 3 Kazakhstan 3 Argentina 2 Iran 2 Italy 1 Netherlands 1 Nigeria 1 Republic of Korea 1 Russian Federation 1 United Kingdom of Great Britain and Northern Ireland 1 Uzbekistan 1

Table 7.4 Implemented measures that harm* Afghanistan’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 15 28.85% Export taxes or restriction 8 15.38% Migration measure 5 9.62% Trade finance 5 9.62% Tariff measure 4 7.69% Bail out / state aid measure 2 3.85% Local content requirement 2 3.85% Non-tariff barrier (not otherwise specified) 2 3.85% Other service sector measure 2 3.85% Competitive devaluation 1 1.92% Import ban 1 1.92% Import subsidy 1 1.92%

Public procurement 1 1.92% AFGHANISTAN Quota (including tariff rate quotas) 1 1.92% Sanitary and Phytosanitary Measure 1 1.92% Technical Barrier to Trade 1 1.92% Total 52 100.00% 88 Not Just Victims: Latin America and Crisis-Era Protectionism

Table 7.5 Afghanistan’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Public procurement 1 100% Total 1 100%

Foreign jurisdictions’ commercial interests affected by Afghanistan’s state measures No measures have been reported for this jurisdiction in the GTA database. AFGHANISTAN Country-Specific Data 89

Angola

Table 7.6. Foreign state measures affecting Angola’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Angola’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Angola’s 84 83 commercial interests. Total number of foreign measures found to benefit or involve no 18 17 change in the treatment of Angola’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Angola’s commercial interests or 28 28 (ii) that have been announced but not implemented and which would almost certainly discriminate against Angola’s interests. [2] Total number of foreign measures that have been implemented and 38 38 which almost certainly discriminate against Angola’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Angola’s 63 62 commercial interests Total number of implemented measures affecting Angola’s 48 48 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Angola’s 31 31 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Angola’s commercial 10 10 interests Total number of pending measures that, if implemented, are likely 9 9 to harm Angola’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Angola’s 11 11 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Angola’s 9 9 commercial interests. ANGOLA Total number of implemented, but no longer enforced measures 7 7 that were almost certainly harmful to Angola’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 39 39 are currently in force and that harm Angola’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Angola” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 90 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.7. Angola’s state measures affecting other jurisdictions’ commercial interests.

All measures except Summary statistic of Angola’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Angola’s measures affecting other 4 4 jurisdictions’ commercial interests. Total number of Angola’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Angola’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Angola’s measures that have been implemented and which almost certainly discriminate 3 3 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Angola’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Angola’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Angola’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 17 17 implemented by Angola that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Angola that harm foreign commercial 4 4 interests. Total number of trading partners affected by measures implemented by Angola that harm foreign commercial 7 7 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Angola” in the “Affecting Trading Partner” and clicking the button “Get Stats”. ANGOLA Country-Specific Data 91

Table 7.8. Frequency with which trading partners’ state measures have almost certainly harmed* Angola’s commercial interests

Jurisdictions Number of measures China 7 Argentina 5 Indonesia 5 India 4 Italy 2 Netherlands 2 Portugal 2 United Kingdom of Great Britain and Northern Ireland 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Nigeria 1 Poland 1 Republic of Korea 1 Romania 1 Slovakia 1 Slovenia 1 South Africa 1 Spain 1 Sri Lanka 1

Sweden 1 ANGOLA Thailand 1 Viet Nam 1 92 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.9. Frequency with which Angola’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures Burundi 1 Congo 1 Ethiopia 1 Kenya 1 Rwanda 1 Uganda 1 United Republic of Tanzania 1

Table 7.10. Implemented measures that harm* Angola’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 16 28.07% Export taxes or restriction 14 24.56% Tariff measure 9 15.79% Trade finance 4 7.02% Non-tariff barrier (not otherwise specified) 3 5.26% Bail out / state aid measure 2 3.51% Competitive devaluation 2 3.51% Migration measure 2 3.51% Import ban 1 1.75% Import subsidy 1 1.75% Investment measure 1 1.75% Public procurement 1 1.75% Quota (including tariff rate quotas) 1 1.75% Total 57 100.00%

Table 7.11. Angola’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Sanitary and Phytosanitary Measure 1 50.00% Tariff measure 1 50.00% Total 2 100.00% ANGOLA Country-Specific Data 93

Bangladesh

Table 7.12. Foreign state measures affecting Bangladesh’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Bangladesh’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Bangladesh’s 202 198 commercial interests. Total number of foreign measures found to benefit or involve no 53 51 change in the treatment of Bangladesh’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Bangladesh’s commercial interests or 49 48 (ii) that have been announced but not implemented and which would almost certainly discriminate against Bangladesh’s interests. [2] Total number of foreign measures that have been implemented and 100 99 which almost certainly discriminate against Bangladesh’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Bangladesh’s 152 155 commercial interests Total number of implemented measures affecting Bangladesh’s 111 110 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Bangladesh’s 79 78 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Bangladesh’s 17 16 commercial interests Total number of pending measures that, if implemented, are likely to 13 12 harm Bangladesh’s commercial interests.

MEASURES NO LONGER IN FORCE BANGLADESH Total number of implemented measures that affected Bangladesh’s 30 30 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Bangladesh’s 25 25 commercial interests. Total number of implemented, but no longer enforced measures that 21 21 were almost certainly harmful to Bangladesh’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 55 55 currently in force and that harm Bangladesh’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Bangladesh” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 94 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.13. Bangladesh’s state measures affecting other jurisdictions’ commercial interests.

All measures except Summary statistic of Bangladesh’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Bangladesh’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of Bangladesh’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Bangladesh’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Bangladesh’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Bangladesh’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Bangladesh’s measures that have been implemented and are likely to harm foreign 1 1 commercial interests. Total number of Bangladesh’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 5 5 implemented by Bangladesh that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Bangladesh that harm foreign 1 1 commercial interests. Total number of trading partners affected by measures implemented by Bangladesh that harm foreign 2 2 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Bangladesh” in the “Affecting Trading Partner” and clicking the button “Get Stats”. BANGLADESH Country-Specific Data 95

Table 7.14. Frequency with which trading partners’ state measures have almost certainly harmed* Bangladesh’s commercial interests

Jurisdictions Number of measures India 14 Argentina 9 China 8 Indonesia 7 Saudi Arabia 6 Germany 4 United Kingdom of Great Britain and Northern Ireland 3 Viet Nam 3 Brazil 2 France 2 Italy 2 Japan 2 Poland 2 Ukraine 2 United Arab Emirates 2 Algeria 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Egypt 1 Estonia 1 Ethiopia 1 European Communities 1 Finland 1 Greece 1 Hong Kong 1 Hungary 1 Iran 1 Ireland 1 Jordan 1 BANGLADESH Kazakhstan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Myanmar 1 Netherlands 1 Nigeria 1 Oman 1 Portugal 1 96 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Jurisdictions Number of measures Romania 1 Russian Federation 1 Slovakia 1 Slovenia 1 South Africa 1 Spain 1 Sri Lanka 1 Sudan 1 Sweden 1 Thailand 1 United States of America 1

Table 7.15. Frequency with which Bangladesh’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures China 1 Japan 1

Table 7.16. Implemented measures that harm* Bangladesh’s commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 24 19.20% Tariff measure 22 17.60% Export subsidy 21 16.80% Migration measure 15 12.00% Non-tariff barrier (not otherwise specified) 10 8.00% Bail out / state aid measure 9 7.20% Competitive devaluation 4 3.20% Quota (including tariff rate quotas) 4 3.20% Trade finance 4 3.20% Import subsidy 2 1.60% Investment measure 2 1.60% Local content requirement 2 1.60% Public procurement 2 1.60% Import ban 1 0.80% Other service sector measure 1 0.80% Technical Barrier to Trade 1 0.80% Trade defence measure (AD, CVD, safeguard) 1 0.80% Total 125 100.00% BANGLADESH Country-Specific Data 97

Table 7.17. Bangladesh’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 2 66.67% Export taxes or restriction 1 33.33% Total 3 100.00% BANGLADESH 98 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Benin

Table 7.18. Foreign state measures affecting Benin’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Benin’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Benin’s 68 66 commercial interests. Total number of foreign measures found to benefit or involve no 13 12 change in the treatment of Benin’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Benin’s commercial interests or 20 19 (ii) that have been announced but not implemented and which would almost certainly discriminate against Benin’s interests [2] Total number of foreign measures that have been implemented and 35 35 which almost certainly discriminate against Benin’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Benin’s 51 50 commercial interests Total number of implemented measures affecting Benin’s 41 41 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Benin’s 29 29 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Benin’s commercial 8 7 interests Total number of pending measures that, if implemented, are likely 7 6 to harm Benin’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Benin’s 9 9 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Benin’s 7 7 commercial interests. Total number of implemented, but no longer enforced measures 6 6 that were almost certainly harmful to Benin’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 38 38 are currently in force and that harm Benin’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Benin” in the “Affecting Trading Partner” and clicking the button “Get Stats”. BENIN Country-Specific Data 99

Table 7.19. Benin’s state measures affecting other jurisdictions’ commercial interests.

All measures except Summary statistic of Benin’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Benin’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of Benin’s measures found to benefit or involve no change in the treatment of other 1 1 jurisdictions’ commercial interests. [1] Total number of Benin’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Benin’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Benin’s measures found to benefit 1 1 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Benin’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Benin’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Benin that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Benin that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Benin that harm foreign commercial none none interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Benin” in the “Affecting Trading Partner” and clicking the button “Get Stats”. BENIN 100 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.20. Frequency with which trading partners’ state measures have almost certainly harmed* Benin’s commercial interests

Jurisdictions Number of measures India 8 China 6 Indonesia 6 France 3 Italy 3 Austria 2 Belgium 2 Bulgaria 2 Cyprus 2 Czech Republic 2 Denmark 2 Estonia 2 European Communities 2 Finland 2 Germany 2 Greece 2 Hungary 2 Ireland 2 Latvia 2 Lithuania 2 Luxembourg 2 Malta 2 Netherlands 2 Poland 2 Portugal 2 Romania 2 Slovakia 2 Slovenia 2 Spain 2 Sweden 2 United Kingdom of Great Britain and Northern Ireland 2 Argentina 1 Egypt 1 Malaysia 1 Nigeria 1 South Africa 1 Thailand 1 Viet Nam 1 BENIN Country-Specific Data 101

Frequency with which Benin’s state measures have almost certainly harmed foreign commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.21. Implemented measures that harm* Benin’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 17 35.42% Tariff measure 11 22.92% Export taxes or restriction 8 16.67% Non-tariff barrier (not otherwise specified) 3 6.25% Trade finance 3 6.25% Bail out / state aid measure 2 4.17% Competitive devaluation 2 4.17% Import subsidy 1 2.08% Public procurement 1 2.08% Total 48 100.00%

Benin’s implemented measures that harm foreign commercial interests, by type. No measures have been reported for this jurisdiction in the GTA database. BENIN 102 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Bhutan

Table 7.22. Foreign state measures affecting Bhutan’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Bhutan’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Bhutan’s 23 22 commercial interests. Total number of foreign measures found to benefit or involve no 7 7 change in the treatment of Bhutan’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Bhutan’s commercial interests or 10 9 (ii) that have been announced but not implemented and which would almost certainly discriminate against Bhutan’s interests [2] Total number of foreign measures that have been implemented and 6 6 which almost certainly discriminate against Bhutan’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Bhutan’s 17 17 commercial interests Total number of implemented measures affecting Bhutan’s 11 11 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Bhutan’s 6 6 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Bhutan’s commercial 5 4 interests Total number of pending measures that, if implemented, are likely 5 4 to harm Bhutan’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Bhutan’s 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Bhutan’s none none commercial interests. Total number of implemented, but no longer enforced measures none none that were almost certainly harmful to Bhutan’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 3 3 are currently in force and that harm Bhutan’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Bhutan” in the “Affecting Trading Partner” and clicking the button “Get Stats”. BHUTAN Country-Specific Data 103

Bhutan’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.23. Frequency with which trading partners’ state measures have almost certainly harmed* Bhutan’s commercial interests

Jurisdictions Number of measures India 4 China 1 Italy 1

Frequency with which Bhutan’s state measures have almost certainly harmed foreign commercial interests.

No measures have been reported for this jurisdiction in the GTA database.

Table 7.24. Implemented measures that harm* Bhutan’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 4 26.67% Tariff measure 4 26.67% Trade finance 3 20.00% Non-tariff barrier (not otherwise specified) 2 13.33% Export taxes or restriction 1 6.67% Import subsidy 1 6.67% Total 15 100.00%

Bhutan’s implemented measures that harm foreign commercial interests, by type. No measures have been reported for this jurisdiction in the GTA database. BHUTAN 104 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Burkina Faso

Table 7.25. Foreign state measures affecting Burkina Faso’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Burkina Faso’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Burkina Faso’s 27 26 commercial interests. Total number of foreign measures found to benefit or involve no 4 3 change in the treatment of Burkina Faso’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Burkina Faso’s commercial interests or 9 9 (ii) that have been announced but not implemented and which would almost certainly discriminate against Burkina Faso’s interests [2] Total number of foreign measures that have been implemented and which almost certainly discriminate against Burkina Faso’s interests 14 14 [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Burkina Faso’s 17 16 commercial interests Total number of implemented measures affecting Burkina Faso’s 14 14 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Burkina Faso’s 10 10 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Burkina Faso’s 6 6 commercial interests Total number of pending measures that, if implemented, are likely to 5 5 harm Burkina Faso’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Burkina Faso’s 4 4 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Burkina Faso’s 4 4 commercial interests. Total number of implemented, but no longer enforced measures that 4 4 were almost certainly harmful to Burkina Faso’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 7 7 currently in force and that harm Burkina Faso’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting BURKINA FASO BURKINA “Burkina Faso” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 105

Burkina Faso’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.26. Frequency with which trading partners’ state measures have almost certainly harmed* Burkina Faso’s commercial interests

Jurisdictions Number of measures China 3 France 2 India 1 Italy 1 Japan 1 Senegal 1 Viet Nam 1

Frequency with which Burkina Faso’s state measures have almost certainly harmed foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.27. Implemented measures that harm* Burkina Faso’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 5 33.33% Non-tariff barrier (not otherwise specified) 4 26.67% Bail out / state aid measure 2 13.33% Trade finance 2 13.33% Competitive devaluation 1 6.67% Import subsidy 1 6.67% Total 15 100.00% BURKINA FASO Burkina Faso’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. 106 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Burundi

Table 7.28. Foreign state measures affecting Burundi’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Burundi’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Burundi’s 22 21 commercial interests. Total number of foreign measures found to benefit or involve no 4 3 change in the treatment of Burundi’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Burundi’s commercial interests or 9 9 (ii) that have been announced but not implemented and which would almost certainly discriminate against Burundi’s interests [2] Total number of foreign measures that have been implemented and 9 9 which almost certainly discriminate against Burundi’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Burundi’s 14 13 commercial interests Total number of implemented measures affecting Burundi’s 10 10 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Burundi’s 6 6 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Burundi’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Burundi’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Burundi’s 4 4 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Burundi’s 3 3 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Burundi’s commercial 3 3 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 5 5 that are currently in force and that harm Burundi’s commercial interests.

BURUNDI Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Burundi” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 107

Table 7.29. Burundi’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Burundi’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Burundi’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of Burundi’s measures found to benefit or involve no change in the treatment of other 2 2 jurisdictions’ commercial interests. [1] Total number of Burundi’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Burundi’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Burundi’s measures found to benefit 2 2 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Burundi’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Burundi’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Burundi that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Burundi that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Burundi that harm foreign commercial none none interests. BURUNDI Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Burundi” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 108 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.30. Frequency with which trading partners’ state measures have almost certainly harmed* Burundi’s commercial interests

Jurisdictions Number of measures China 2 Angola 1 Italy 1 Nigeria 1 South Africa 1

Frequency with which Burundi’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.31. Implemented measures that harm Burundi’s commercial interests, by type Number of As percentage of Type of measure measures measures Bail out / state aid measure 2 18.18% Export subsidy 2 18.18% Trade finance 2 18.18% Competitive devaluation 1 9.09% Non-tariff barrier (not otherwise specified) 1 9.09% Other service sector measure 1 9.09% Sanitary and Phytosanitary Measure 1 9.09% Tariff measure 1 9.09% Total 11 100.00%

Burundi’s implemented measures that harm foreign commercial interests, by type. No measures have been reported for this jurisdiction in the GTA database. BURUNDI Country-Specific Data 109

Cambodia

Table 7.32. Foreign state measures affecting Cambodia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Cambodia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Cambodia’s 89 88 commercial interests. Total number of foreign measures found to benefit or involve no 20 19 change in the treatment of Cambodia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Cambodia’s commercial interests or 31 31 (ii) that have been announced but not implemented and which would almost certainly discriminate against Cambodia’s interests. [2] Total number of foreign measures that have been implemented and 38 38 which almost certainly discriminate against Cambodia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Cambodia’s 62 61 commercial interests Total number of implemented measures affecting Cambodia’s 46 46 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Cambodia’s 32 32 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Cambodia’s commercial 15 15 interests Total number of pending measures that, if implemented, are likely to 14 14 harm Cambodia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Cambodia’s 12 12 commercial interests but are no longer in force.

Total number of implemented, but no longer enforced measures that CAMBODIA were harmful or almost certainly harmful to Cambodia’s commercial 9 9 interests. Total number of implemented, but no longer enforced measures that 6 6 were almost certainly harmful to Cambodia’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 39 39 currently in force and that harm Cambodia’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Cambodia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 110 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Cambodia’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.33. Frequency with which trading partners’ state measures have almost certainly harmed* Cambodia’s commercial interests

Jurisdictions Number of measures China 8 India 8 Argentina 4 Viet Nam 4 Indonesia 2 Italy 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Japan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Republic of Korea 1 Romania 1 Slovakia 1 Slovenia 1 South Africa 1 Spain 1 Sweden 1 Thailand 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 CAMBODIA Country-Specific Data 111

Frequency with which Cambodia’s state measures have almost certainly harmed* foreign commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.34. Implemented measures that harm* Cambodia’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 16 29.09% Tariff measure 12 21.82% Export taxes or restriction 6 10.91% Non-tariff barrier (not otherwise specified) 5 9.09% Trade finance 5 9.09% Bail out / state aid measure 3 5.45% Public procurement 2 3.64% Competitive devaluation 1 1.82% Import subsidy 1 1.82% Intellectual property protection 1 1.82% Investment measure 1 1.82% Local content requirement 1 1.82% Migration measure 1 1.82% Total 55 100.00%

Cambodia’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. CAMBODIA 112 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Central African Republic

Table 7.35. Foreign state measures affecting Central African Rep.’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Central African Rep.’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Central African Rep.’s 18 17 commercial interests. Total number of foreign measures found to benefit or involve no change in 2 1 the treatment of Central African Rep.’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Central African Rep.’s commercial interests or 7 7 (ii) that have been announced but not implemented and which would almost certainly discriminate against Central African Rep.’s interests [2] Total number of foreign measures that have been implemented and which 9 9 almost certainly discriminate against Central African Rep.’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Central African Rep.’s 11 10 commercial interests Total number of implemented measures affecting Central African Rep.’s 9 9 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Central African Rep.’s 7 7 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Central African Rep.’s 5 5 commercial interests Total number of pending measures that, if implemented, are likely to harm 5 5 Central African Rep.’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Central African 2 2 Rep.’s commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Central African Rep.’s commercial 2 2 interests. Total number of implemented, but no longer enforced measures that were 2 2 almost certainly harmful to Central African Rep.’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 5 5 currently in force and that harm Central African Rep.’s commercial interests.

CENTRAL AFRICAN REPUBLIC CENTRAL AFRICAN Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Central African Republic” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 113

Central African Republic’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.36. Frequency with which trading partners’ state measures have almost certainly harmed* Central African Republic’s commercial interests

Jurisdictions Number of measures China 3 Italy 1 Nigeria 1 South Africa 1 Viet Nam 1

Frequency with which Central African Republic’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.37. Implemented measures that harm* Central African Republic’s commercial interests, by type CENTRAL AFRICANREPUBLIC Number of As percentage of Type of measure measures measures Export subsidy 3 30.00% Competitive devaluation 2 20.00% Tariff measure 2 20.00% Bail out / state aid measure 1 10.00% Export taxes or restri9ction 1 10.00% Trade finance 1 10.00% Total 10 100.00%

Central African Republic’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. 114 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Chad

Table 7.38. Foreign state measures affecting Chad’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Chad’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Chad’s 28 27 commercial interests. Total number of foreign measures found to benefit or involve no 5 4 change in the treatment of Chad’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Chad’s commercial interests or 11 11 (ii) that have been announced but not implemented and which would almost certainly discriminate against Chad’s interests [2] Total number of foreign measures that have been implemented and 12 12 which almost certainly discriminate against Chad’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Chad’s 15 14 commercial interests Total number of implemented measures affecting Chad’s 12 12 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Chad’s 8 8 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Chad’s commercial 7 7 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Chad’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Chad’s 6 6 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Chad’s 5 5 commercial interests. Total number of implemented, but no longer enforced measures 4 4 that were almost certainly harmful to Chad’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 4 4 are currently in force and that harm Chad’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Chad” in the “Affecting Trading Partner” and clicking the button “Get Stats”. CHAD Country-Specific Data 115

Table 7.39. Chad’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Chad’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Chad’s measures affecting other 1 1 jurisdictions’ commercial interests. Total number of Chad’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Chad’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Chad’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Chad’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Chad’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Chad’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 2 2 implemented by Chad that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Chad that harm foreign commercial 1 1 interests. Total number of trading partners affected by measures implemented by Chad that harm foreign commercial none none interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Chad” in the “Affecting Trading Partner” and clicking the button “Get Stats”. CHAD 116 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.40. Frequency with which trading partners’ state measures have almost certainly harmed* Chad’s commercial interests

Jurisdictions Number of measures China 5 Argentina 1 Italy 1 Nigeria 1

Frequency with which Chad’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.41. Implemented measures that harm* Chad’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 7 46.67% Tariff measure 3 20.00% Export taxes or restriction 2 13.33% Competitive devaluation 1 6.67% Public procurement 1 6.67% Trade finance 1 6.67% Total 15 100.00%

Chad’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. CHAD Country-Specific Data 117

Comoros

Table 7.42. Foreign state measures affecting Comoros’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Comoros’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Comoros’ 20 20 commercial interests. Total number of foreign measures found to benefit or involve no 5 5 change in the treatment of Comoros’ commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Comoros’ commercial interests or 6 6 (ii) that have been announced but not implemented and which would almost certainly discriminate against Comoros’s interests. [2] Total number of foreign measures that have been implemented and 9 9 which almost certainly discriminate against Comoros’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Comoros’ 14 14 commercial interests Total number of implemented measures affecting Comoros’s 10 10 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Comoros’ 9 9 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Comoros’ commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Comoros’ commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Comoros’ 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that COMOROS were harmful or almost certainly harmful to Comoros’ commercial none none interests. Total number of implemented, but no longer enforced measures that none none were almost certainly harmful to Comoros’ commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 32 32 are currently in force and that harm Comoros’ commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Comoros” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 118 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Comoros’ state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.43. Frequency with which trading partners’ state measures have almost certainly harmed* Comoros’ commercial interests

Jurisdictions Number of measures Indonesia 3 China 2 Italy 2 Algeria 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Nigeria 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 United Kingdom of Great Britain and Northern Ireland 1

Frequency with which Comoros’ state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database. COMOROS Country-Specific Data 119

Table 7.44. Implemented measures that harm* Comoros’ commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 4 50.00% Competitive devaluation 1 12.50% Investment measure 1 12.50% Non-tariff barrier (not otherwise specified) 1 12.50% Trade finance 1 12.50% Total 8 100.00%

Comoros’ implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. COMOROS 120 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Democratic Republic of the Congo

Table 7.45. Foreign state measures affecting DR Congo’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting DR Congo’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting DR Congo’s 51 50 commercial interests. Total number of foreign measures found to benefit or involve no 11 10 change in the treatment of DR Congo’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm DR Congo’s commercial interests or 13 13 (ii) that have been announced but not implemented and which would almost certainly discriminate against DR Congo’s interests [2] Total number of foreign measures that have been implemented and 27 27 which almost certainly discriminate against DR Congo’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting DR Congo’s 32 31 commercial interests Total number of implemented measures affecting DR Congo’s 23 23 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting DR Congo’s 18 18 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting DR Congo’s 7 7 commercial interests Total number of pending measures that, if implemented, are likely 7 7 to harm DR Congo’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected DR Congo’s 12 12 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to DR Congo’s 10 10 commercial interests. Total number of implemented, but no longer enforced measures that 9 9 were almost certainly harmful to DR Congo’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 34 34 that are currently in force and that harm DR Congo’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting DEMOCRATIC REPUBLIC OF THE CONGO REPUBLIC OF DEMOCRATIC “DR Congo” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 121

Table 7.46. DR Congo’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of DR Congo’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of DR Congo’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of DR Congo’s measures found to benefit or involve no change in the treatment of other none none

jurisdictions’ commercial interests. [1] DEMOCRATIC REPUBLIC OF THE CONGO Total number of DR Congo’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of DR Congo’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of DR Congo’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of DR Congo’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of DR Congo’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 4 4 implemented by DR Congo that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by DR Congo that harm foreign 2 2 commercial interests. Total number of trading partners affected by measures implemented by DR Congo that harm foreign 16 16 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “DR Congo” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 122 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.47. Frequency with which trading partners’ state measures have almost certainly harmed* DR Congo’s commercial interests

Jurisdictions Number of measures China 6 Indonesia 3 Belgium 2 Italy 2 Russian Federation 2 United Kingdom of Great Britain and Northern Ireland 2 Austria 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 South Africa 1 Spain 1 Sweden 1 Ukraine 1 Zimbabwe 1 DEMOCRATIC REPUBLIC OF THE CONGO REPUBLIC OF DEMOCRATIC Country-Specific Data 123

Table 7.48. Frequency with which DR Congo’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures Belgium 1 Brazil 1 Canada 1 China 1 France 1 Germany 1 Italy 1 Japan 1 Netherlands 1 DEMOCRATIC REPUBLIC OF THE CONGO Republic of Korea 1 Rwanda 1 South Africa 1 Uganda 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 Zambia 1

Table 7.49. Implemented measures that harm* DR Congo’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 8 30.77% Bail out / state aid measure 3 11.54% Export taxes or restriction 3 11.54% Non-tariff barrier (not otherwise specified) 3 11.54% Tariff measure 3 11.54% Migration measure 2 7.69% Import ban 1 3.85% Other service sector measure 1 3.85% Public procurement 1 3.85% Trade finance 1 3.85% Total 26 100.00%

Table 7.50. DR Congo’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Import ban 1 100.00% Total 1 100.00% 124 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Djibouti

Table 7.51. Foreign state measures affecting Djibouti’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Djibouti’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Djibouti’s 52 51 commercial interests. Total number of foreign measures found to benefit or involve no 10 9 change in the treatment of Djibouti’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Djibouti’s commercial interests or 17 17 (ii) that have been announced but not implemented and which would almost certainly discriminate against Djibouti’s interests [2] Total number of foreign measures that have been implemented and 25 25 which almost certainly discriminate against Djibouti’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Djibouti’s 38 38 commercial interests Total number of implemented measures affecting Djibouti’s 30 30 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Djibouti’s 20 20 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Djibouti’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Djibouti’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Djibouti’s 8 8 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Djibouti’s 7 7 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Djibouti’s commercial 5 5 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 11 11 that are currently in force and that harm Djibouti’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the DJIBOUTI numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Djibouti” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 125

Djibouti’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.52. Frequency with which trading partners’ state measures have almost certainly harmed* Djibouti’s commercial interests

Jurisdictions Number of measures China 6 India 4 Indonesia 4 Algeria 1 Ethiopia 1 Italy 1 Japan 1 Malaysia 1 Sudan 1 Thailand 1 Ukraine 1

Frequency with which Djibouti’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.53. Implemented measures that harm* Djibouti’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 12 34.29% Export taxes or restriction 5 14.29% Non-tariff barrier (not otherwise specified) 4 11.43% Tariff measure 4 11.43% Trade finance 3 8.57% Bail out / state aid measure 1 2.86% Competitive devaluation 1 2.86% Import ban 1 2.86% Import subsidy 1 2.86% Investment measure 1 2.86% DJIBOUTI Other service sector measure 1 2.86% Public procurement 1 2.86% Total 35 100.00%

Djibouti’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. 126 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Equatorial Guinea

Table 7.54. Foreign state measures affecting Equatorial Guinea’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Equatorial Guinea’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Equatorial Guinea’s 39 39 commercial interests. Total number of foreign measures found to benefit or involve no change in 5 5 the treatment of Equatorial Guinea’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Equatorial Guinea’s commercial interests or 19 19 (ii) that have been announced but not implemented and which would almost certainly discriminate against Equatorial Guinea’s interests [2] Total number of foreign measures that have been implemented and which 15 15 almost certainly discriminate against Equatorial Guinea’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Equatorial Guinea’s 20 20 commercial interests Total number of implemented measures affecting Equatorial Guinea’s 17 17 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Equatorial Guinea’s 10 10 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Equatorial Guinea’s 10 10 commercial interests Total number of pending measures that, if implemented, are likely to harm 10 10 Equatorial Guinea’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Equatorial Guinea’s 9 9 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Equatorial Guinea’s commercial 7 7 interests. Total number of implemented, but no longer enforced measures that were 5 5 almost certainly harmful to Equatorial Guinea’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 30 30 currently in force and that harm Equatorial Guinea’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Equatorial Guinea” in the “Affecting Trading Partner” and clicking the button “Get Stats”. EQUATORIAL GUINEA EQUATORIAL Country-Specific Data 127

Equatorial Guinea’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.55. Frequency with which trading partners’ state measures have almost certainly harmed* Equitorial Guinea’s commercial interests

Jurisdictions Number of measures China 6 Italy 2 Netherlands 2 Argentina 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 EQUATORIAL GUINEA Malta 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 United Kingdom of Great Britain and Northern Ireland 1

Frequency with which Equitorial Guinea’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database. 128 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.56. Implemented measures that harm* Equatorial Guinea’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 9 52.94% Tariff measure 3 17.65% Export taxes or restriction 2 11.76% Bail out / state aid measure 1 5.88% Non-tariff barrier (not otherwise specified) 1 5.88% Trade finance 1 5.88% Total 17 100.00%

Equatorial Guinea’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. EQUATORIAL GUINEA EQUATORIAL Country-Specific Data 129

Eritrea

Table 7.57. Foreign state measures affecting Eritrea’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Eritrea’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Eritrea’s 27 27 commercial interests. Total number of foreign measures found to benefit or involve no 6 6 change in the treatment of Eritrea’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Eritrea’s commercial interests or 9 9 (ii) that have been announced but not implemented and which would almost certainly discriminate against Eritrea’s interests. [2] Total number of foreign measures that have been implemented and 12 12 which almost certainly discriminate against Eritrea’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Eritrea’s 18 18 commercial interests Total number of implemented measures affecting Eritrea’s 13 13 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Eritrea’s 9 9 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Eritrea’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Eritrea’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Eritrea’s 4 4 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Eritrea’s 3 3 commercial interests.

Total number of implemented, but no longer enforced measures ERITREA 3 3 that were almost certainly harmful to Eritrea’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 5 5 are currently in force and that harm Eritrea’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Eritrea” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 130 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Eritrea’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.58. Frequency with which trading partners’ state measures have almost certainly harmed* Eritrea’s commercial interests

Jurisdictions Number of measures China 5 Algeria 1 Italy 1 Sudan 1 United Kingdom of Great Britain and Northern Ireland 1

Frequency with which Eritrea’s state measures have almost certainly harmed foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.59. Implemented measures that harm* Eritrea’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 6 40.00% Migration measure 2 13.33% Tariff measure 2 13.33% Trade finance 2 13.33% Import ban 1 6.67% Import subsidy 1 6.67% Investment measure 1 6.67% Total 15 100.00%

Eritrea’s implemented measures that harm foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. ERITREA Country-Specific Data 131

Ethiopia

Table 7.60. Foreign state measures affecting Ethiopia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Ethiopia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Ethiopia’s 82 82 commercial interests. Total number of foreign measures found to benefit or involve no 13 13 change in the treatment of Ethiopia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Ethiopia’s commercial interests or 24 24 (ii) that have been announced but not implemented and which would almost certainly discriminate against Ethiopia’s interests. [2] Total number of foreign measures that have been implemented and 45 45 which almost certainly discriminate against Ethiopia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Ethiopia’s 54 54 commercial interests Total number of implemented measures affecting Ethiopia’s 46 46 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Ethiopia’s 33 33 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Ethiopia’s commercial 10 10 interests Total number of pending measures that, if implemented, are likely 9 9 to harm Ethiopia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Ethiopia’s 18 18 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Ethiopia’s commercial 14 14

interests. ETHIOPIA Total number of implemented, but no longer enforced measures that 12 12 were almost certainly harmful to Ethiopia’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 20 20 are currently in force and that harm Ethiopia’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Ethiopia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 132 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.61. Ethiopia’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Ethiopia’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Ethiopia’s measures affecting other 6 6 jurisdictions’ commercial interests. Total number of Ethiopia’s measures found to benefit or involve no change in the treatment of other 1 1 jurisdictions’ commercial interests. [1] Total number of Ethiopia’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Ethiopia’s measures that have been implemented and which almost certainly discriminate 5 5 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Ethiopia’s measures found to benefit 1 1 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Ethiopia’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Ethiopia’s measures that have been implemented and which almost certainly discriminate 5 5 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by 347 347 measures implemented by Ethiopia that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Ethiopia that harm foreign 33 32 commercial interests. Total number of trading partners affected by measures implemented by Ethiopia that harm foreign 74 74 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Ethiopia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. ETHIOPIA Country-Specific Data 133

Table 7.62. Frequency with which trading partners’ state measures have almost certainly harmed* Ethiopia’s commercial interests

Jurisdictions Number of measures China 7 India 4 Indonesia 3 Ukraine 3 Angola 1 Argentina 1 France 1 Germany 1 Israel 1 Italy 1 Japan 1 Kazakhstan 1 Netherlands 1 South Africa 1 Sri Lanka 1 Sudan 1 Switzerland 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 Viet Nam 1

Table 7.63. Frequency with which Ethiopia’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures United Arab Emirates 3 Brazil 2 India 2 Oman 2 Pakistan 2 Saudi Arabia 2 Thailand 2 Turkey 2 United States of America 2 Yemen 2 Albania 1 ETHIOPIA Australia 1 Austria 1 Bahrain 1 Bangladesh 1 Belgium 1 Belize 1 Bulgaria 1 Canada 1 134 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Jurisdictions affected Number of measures China 1 Cyprus 1 Czech Republic 1 Democratic People's Republic of Korea 1 Denmark 1 Djibouti 1 Ecuador 1 Egypt 1 Finland 1 France 1 Germany 1 Greece 1 Hong Kong 1 Hungary 1 Indonesia 1 Iran 1 Ireland 1 Israel 1 Italy 1 Japan 1 Jordan 1 Kazakhstan 1 Kenya 1 Kuwait 1 Lebanon 1 Libya 1 Lithuania 1 Luxembourg 1 Malaysia 1 Mauritius 1 Mexico 1 Morocco 1 Netherlands 1 New Zealand 1 Norway 1 Poland 1 Portugal 1 Qatar 1 Republic of Korea 1 Republic of Moldova 1 Romania 1 Russian Federation 1 Singapore 1 Somalia 1 South Africa 1 Spain 1 Sudan 1 ETHIOPIA Country-Specific Data 135

Jurisdictions affected Number of measures Swaziland 1 Sweden 1 Switzerland 1 Syrian Arab Republic 1 Tunisia 1 Ukraine 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1

Table 7.64. Implemented measures that harm* Ethiopia’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 14 35.90% Export taxes or restriction 6 15.38% Bail out / state aid measure 5 12.82% Migration measure 4 10.26% Non-tariff barrier (not otherwise specified) 4 10.26% Competitive devaluation 2 5.13% Local content requirement 2 5.13% Import ban 1 2.56% Import subsidy 1 2.56% Total 39 100.00%

Table 7.65. Ethiopia’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Competitive devaluation 1 20.00% Export taxes or restriction 1 20.00% Migration measure 1 20.00% Non-tariff barrier (not otherwise specified) 1 20.00% Other service sector measure 1 20.00% Total 5 100.00% ETHIOPIA 136 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Gambia

Table 7.66. Foreign state measures affecting Gambia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Gambia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Gambia’s 39 38 commercial interests. Total number of foreign measures found to benefit or involve no 10 9 change in the treatment of Gambia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Gambia’s commercial interests or 11 11 (ii) that have been announced but not implemented and which would almost certainly discriminate against Gambia’s interests [2] Total number of foreign measures that have been implemented and 18 18 which almost certainly discriminate against Gambia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Gambia’s 27 26 commercial interests Total number of implemented measures affecting Gambia’s 20 20 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Gambia’s 14 14 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Gambia’s commercial 7 7 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Gambia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Gambia’s 5 5 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Gambia’s 4 4 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Gambia’s commercial 4 4 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 5 5 that are currently in force and that harm Gambia’s commercial interests.

GAMBIA Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Gambia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 137

Table 7.67. Gambia’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Gambia’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Gambia’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of Gambia’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Gambia’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Gambia’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Gambia’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Gambia’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Gambia’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 1 1 implemented by Gambia that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Gambia that harm foreign commercial 1 1 interests. Total number of trading partners affected by measures implemented by Gambia that harm foreign commercial 7 7 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting GAMBIA “Gambia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 138 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.68. Frequency with which trading partners’ state measures have almost certainly harmed* Gambia’s commercial interests

Jurisdictions Number of measures China 5 India 4 Indonesia 1 Italy 1 Viet Nam 1

Table 7.69. Frequency with which Gambia’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures Belgium 1 France 1 Germany 1 Japan 1 United Arab Emirates 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1

Table 7.70. Implemented measures that harm* Gambia’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 10 43.48% Trade finance 4 17.39% Tariff measure 3 13.04% Export taxes or restriction 2 8.70% Competitive devaluation 1 4.35% Import subsidy 1 4.35% Non-tariff barrier (not otherwise specified) 1 4.35% Public procurement 1 4.35% Total 23 100.00%

Table 7.71. Gambia’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Non-tariff barrier (not otherwise specified) 1 100.00% Total 1 100.00% GAMBIA Country-Specific Data 139

Guinea

Table 7.72. Foreign state measures affecting Guinea’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Guinea’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Guinea’s 57 56 commercial interests. Total number of foreign measures found to benefit or involve no 12 11 change in the treatment of Guinea’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Guinea’s commercial interests or 18 18 (ii) that have been announced but not implemented and which would almost certainly discriminate against Guinea’s interests. [2] Total number of foreign measures that have been implemented and 27 27 which almost certainly discriminate against Guinea’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Guinea’s 40 39 commercial interests Total number of implemented measures affecting Guinea’s 30 30 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Guinea’s 19 19 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Guinea’s commercial 6 6 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Guinea’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Guinea’s 11 11 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Guinea’s 9 9 commercial interests.

Total number of implemented, but no longer enforced measures GUINEA that were almost certainly harmful to Guinea’s commercial 8 8 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 36 36 are currently in force and that harm Guinea’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Guinea” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 140 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Guinea’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.73. Frequency with which trading partners’ state measures have almost certainly harmed* Guinea’s commercial interests

Jurisdictions Number of measures China 6 India 4 Italy 2 Nigeria 2 Algeria 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Indonesia 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Romania 1 Russian Federation 1 Slovakia 1 Slovenia 1 Spain 1 Sri Lanka 1 Sweden 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1 GUINEA Country-Specific Data 141

Frequency with which Guinea’s state measures have almost certainly harmed* foreign commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.74. Implemented measures that harm* Guinea’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 14 37.84% Tariff measure 7 18.92% Export taxes or restriction 4 10.81% Trade finance 4 10.81% Competitive devaluation 2 5.41% Public procurement 2 5.41% Bail out / state aid measure 1 2.70% Import ban 1 2.70% Import subsidy 1 2.70% Technical Barrier to Trade 1 2.70% Total 37 100.00%

Guinea’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. GUINEA 142 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Guinea-Bissau

Table 7.75. Foreign state measures affecting Guinea-Bissau’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Guinea-Bissau’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Guinea-Bissau’s 21 20 commercial interests. Total number of foreign measures found to benefit or involve no 6 5 change in the treatment of Guinea-Bissau’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Guinea-Bissau’s commercial interests or 9 9 (ii) that have been announced but not implemented and which would almost certainly discriminate against Guinea-Bissau’s interests [2] Total number of foreign measures that have been implemented and which almost certainly discriminate against Guinea-Bissau’s 6 6 interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Guinea-Bissau’s 14 13 commercial interests Total number of implemented measures affecting Guinea-Bissau’s 9 9 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Guinea-Bissau’s 5 5 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Guinea-Bissau’s 5 5 commercial interests Total number of pending measures that, if implemented, are likely 5 5 to harm Guinea-Bissau’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Guinea- 2 2 Bissau’s commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Guinea-Bissau’s 1 1 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Guinea-Bissau’s commercial 1 1 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 5 5 are currently in force and that harm Guinea-Bissau’s commercial interests. GUINEA-BISSAU

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Guinea-Bissau” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 143

Guinea-Bissau’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.76. Frequency with which trading partners’ state measures have almost certainly harmed* Guinea-Bissau’s commercial interests

Jurisdictions Number of measures China 1 Indonesia 1 Italy 1 Portugal 1 Viet Nam 1

Frequency with which Guinea-Bissau’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.77. Implemented measures that harm* Guinea-Bissau’s commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 3 25.00% Export subsidy 2 16.67% Export taxes or restriction 2 16.67% Competitive devaluation 1 8.33% Import ban 1 8.33% Migration measure 1 8.33% Non-tariff barrier (not otherwise specified) 1 8.33% Trade finance 1 8.33% Total 12 100.00% GUINEA-BISSAU Guinea-Bissau’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. 144 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Haiti

Table 7.78. Foreign state measures affecting Haiti’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Haiti’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Haiti’s 55 54 commercial interests. Total number of foreign measures found to benefit or involve no 10 9 change in the treatment of Haiti’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Haiti’s commercial interests or 23 23 (ii) that have been announced but not implemented and which would almost certainly discriminate against Haiti’s interests [2] Total number of foreign measures that have been implemented and 22 22 which almost certainly discriminate against Haiti’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Haiti’s 32 31 commercial interests Total number of implemented measures affecting Haiti’s 25 25 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Haiti’s 18 18 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Haiti’s commercial 17 17 interests Total number of pending measures that, if implemented, are likely 15 15 to harm Haiti’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Haiti’s 6 6 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Haiti’s 5 5 commercial interests. Total number of implemented, but no longer enforced measures 4 4 that were almost certainly harmful to Haiti’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 10 10 are currently in force and that harm Haiti’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Haiti” in the “Affecting Trading Partner” and clicking the button “Get Stats”. HAITI Country-Specific Data 145

Haiti’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.79. Frequency with which trading partners’ state measures have almost certainly harmed* Haiti’s commercial interests

Jurisdictions Number of measures China 6 Indonesia 3 Argentina 2 United States of America 2 Italy 1 Japan 1 Puerto Rico 1 United States Virgin Islands 1 Venezuela 1 Viet Nam 1

Frequency with which Haiti’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.80. Implemented measures that harm* Haiti’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 9 30.00% Export taxes or restriction 6 20.00% Tariff measure 4 13.33% Bail out / state aid measure 2 6.67% Competitive devaluation 2 6.67% Trade finance 2 6.67% Import subsidy 1 3.33% Local content requirement 1 3.33% Non-tariff barrier (not otherwise specified) 1 3.33% Public procurement 1 3.33% Sub-national government measure 1 3.33% Total 30 100.00%

Haiti’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. HAITI 146 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Kiribati

Table 7.81. Foreign state measures affecting Kiribati’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Kiribati’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Kiribati’s 8 8 commercial interests. Total number of foreign measures found to benefit or involve no 2 2 change in the treatment of Kiribati’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Kiribati’s commercial interests or 4 4 (ii) that have been announced but not implemented and which would almost certainly discriminate against Kiribati’s interests [2] Total number of foreign measures that have been implemented and 2 2 which almost certainly discriminate against Kiribati’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Kiribati’s 5 5 commercial interests Total number of implemented measures affecting Kiribati’s 3 3 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Kiribati’s 2 2 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Kiribati’s commercial 3 3 interests Total number of pending measures that, if implemented, are likely 3 3 to harm Kiribati’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Kiribati’s none none commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Kiribati’s none none commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Kiribati’s commercial none none interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 2 2 are currently in force and that harm Kiribati’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting KIRIBATI “Kiribati” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 147

Kiribati’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.82. Frequency with which trading partners’ state measures have almost certainly harmed* Kiribati’s commercial interests

Jurisdictions Number of measures China 1 Japan 1

Frequency with which Kiribati’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.83. Implemented measures that harm* Kiribati’s commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 1 33.33% Non-tariff barrier (not otherwise specified) 1 33.33% Tariff measure 1 33.33% Total 3 100.00%

Kiribati’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. KIRIBATI 148 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Lao People’s Democratic Republic

Table 7.84. Foreign state measures affecting Laos’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Laos’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Laos’s 48 48 commercial interests. Total number of foreign measures found to benefit or involve no 11 11 change in the treatment of Laos’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Laos’s commercial interests or 20 20 (ii) that have been announced but not implemented and which would almost certainly discriminate against Laos’s interests [2] Total number of foreign measures that have been implemented and 17 17 which almost certainly discriminate against Laos’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Laos’s 35 35 commercial interests Total number of implemented measures affecting Laos’s 24 24 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Laos’s 15 15 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Laos’s commercial 9 9 interests Total number of pending measures that, if implemented, are likely 9 9 to harm Laos’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Laos’s 4 4 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Laos’s commercial 4 4 interests. Total number of implemented, but no longer enforced measures 2 2 that were almost certainly harmful to Laos’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 9 9 are currently in force and that harm Laos’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Laos” in the “Affecting Trading Partner” and clicking the button “Get Stats”. LAO PEOPLE’S DEMOCRATIC REPUBLIC PEOPLE’S DEMOCRATIC LAO Country-Specific Data 149

Lao People’s Democratic Republic’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.85. Frequency with which trading partners’ state measures have almost certainly harmed* Lao People’s Democratic Republic commercial interests

Jurisdictions Number of measures China 7 Japan 2 Viet Nam 2 Argentina 1

Indonesia 1 LAO PEOPLE’S DEMOCRATIC REPUBLIC Italy 1 Malaysia 1 Thailand 1 United States of America 1

Frequency with which Lao People’s Democratic Republic’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.86. Implemented measures that harm* Lao People’s Democratic Republic’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 7 21.88% Tariff measure 7 21.88% Export taxes or restriction 4 12.50% Non-tariff barrier (not otherwise specified) 4 12.50% Trade finance 2 6.25% Bail out / state aid measure 1 3.13% Competitive devaluation 1 3.13% Import subsidy 1 3.13% Investment measure 1 3.13% Local content requirement 1 3.13% Public procurement 1 3.13% Quota (including tariff rate quotas) 1 3.13% Sub-national government measure 1 3.13% Total 32 100.00%

Lao People’s Democratic Republic’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. 150 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Lesotho

Table 7.87. Foreign state measures affecting Lesotho’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Lesotho’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Lesotho’s 30 29 commercial interests. Total number of foreign measures found to benefit or involve no 7 6 change in the treatment of Lesotho’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Lesotho’s commercial interests or 10 10 (ii) that have been announced but not implemented and which would almost certainly discriminate against Lesotho’s interests [2] Total number of foreign measures that have been implemented and 13 13 which almost certainly discriminate against Lesotho’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Lesotho’s 22 21 commercial interests Total number of implemented measures affecting Lesotho’s 17 17 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Lesotho’s 13 13 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Lesotho’s commercial 7 7 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Lesotho’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Lesotho’s 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Lesotho’s none none commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Lesotho’s commercial none none interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 5 5 are currently in force and that harm Lesotho’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting LESOTHO “Lesotho” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 151

Lesotho’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.88. Frequency with which trading partners’ state measures have almost certainly harmed* Lesotho’s commercial interests

Jurisdictions Number of measures China 6 India 4 Nigeria 1 South Africa 1 United States of America 1

Frequency with which Lesotho’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.89. Implemented measures that harm* Lesotho’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 10 47.62% Tariff measure 3 14.29% Public procurement 2 9.52% Bail out / state aid measure 1 4.76% Competitive devaluation 1 4.76% Local content requirement 1 4.76% Non-tariff barrier (not otherwise specified) 1 4.76% Other service sector measure 1 4.76% Trade finance 1 4.76% Total 21 100.00%

Lesotho’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. LESOTHO 152 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Liberia

Table 7.90. Foreign state measures affecting Liberia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Liberia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Liberia’s 47 47 commercial interests. Total number of foreign measures found to benefit or involve no 11 11 change in the treatment of Liberia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Liberia’s commercial interests or 15 15 (ii) that have been announced but not implemented and which would almost certainly discriminate against Liberia’s interests [2] Total number of foreign measures that have been implemented and 21 21 which almost certainly discriminate against Liberia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Liberia’s 33 33 commercial interests Total number of implemented measures affecting Liberia’s 26 26 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Liberia’s 17 17 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Liberia’s commercial 6 6 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Liberia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Liberia’s 8 8 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Liberia’s 5 5 commercial interests. Total number of implemented, but no longer enforced measures 4 4 that were almost certainly harmful to Liberia’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 8 8 are currently in force and that harm Liberia’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Liberia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. LIBERIA Country-Specific Data 153

Table 7.91 Liberia’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Liberia’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Liberia’s measures affecting other 4 4 jurisdictions’ commercial interests. Total number of Liberia’s measures found to benefit or involve no change in the treatment of other 4 4 jurisdictions’ commercial interests. [1] Total number of Liberia’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Liberia’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Liberia’s measures found to benefit 3 3 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Liberia’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Liberia’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Liberia that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Liberia that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Liberia that harm foreign commercial none none interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting

“Liberia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. LIBERIA 154 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.92. Frequency with which trading partners’ state measures have almost certainly harmed* Liberia’s commercial interests

Jurisdictions Number of measures China 7 Indonesia 4 Argentina 1 Italy 1 Nigeria 1 Republic of Korea 1 Russian Federation 1 Viet Nam 1

Frequency with which Liberia’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.93. Implemented measures that harm* Liberia’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 9 32.14% Export taxes or restriction 7 25.00% Tariff measure 6 21.43% Non-tariff barrier (not otherwise specified) 3 10.71% Competitive devaluation 2 7.14% Trade finance 1 3.57% Total 28 100.00%

Liberia’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. LIBERIA Country-Specific Data 155

Madagascar

Table 7.94. Foreign state measures affecting Madagascar’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Madagascar’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Madagascar’s 73 72 commercial interests. Total number of foreign measures found to benefit or involve no 15 14 change in the treatment of Madagascar’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Madagascar’s commercial interests or 20 20 (ii) that have been announced but not implemented and which would almost certainly discriminate against Madagascar’s interests. [2] Total number of foreign measures that have been implemented and 38 38 which almost certainly discriminate against Madagascar’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Madagascar’s 55 54 commercial interests Total number of implemented measures affecting Madagascar’s 44 44 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Madagascar’s 32 32 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Madagascar’s 7 7 commercial interests Total number of pending measures that, if implemented, are likely to 7 7 harm Madagascar’s commercial interests.

MEASURES NO LONGER IN FORCE MADAGASCAR Total number of implemented measures that affected Madagascar’s 11 11 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Madagascar’s 7 7 commercial interests. Total number of implemented, but no longer enforced measures that 6 6 were almost certainly harmful to Madagascar’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 36 36 currently in force and that harm Madagascar’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Madagascar” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 156 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Madagascar’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.95. Frequency with which trading partners’ state measures have almost certainly harmed* Madagascar’s commercial interests

Jurisdictions Number of measures China 8 India 7 France 5 Indonesia 5 Italy 2 South Africa 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Japan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Nigeria 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 Viet Nam 1 MADAGASCAR Country-Specific Data 157

Frequency with which Madagascar’s state measures have almost certainly harmed* foreign commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.96. Implemented measures that harm* Madagascar’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 17 32.08% Export taxes or restriction 7 13.21% Tariff measure 7 13.21% Bail out / state aid measure 6 11.32% Non-tariff barrier (not otherwise specified) 4 7.55% Trade finance 4 7.55% Public procurement 2 3.77% Competitive devaluation 1 1.89% Import ban 1 1.89% Import subsidy 1 1.89% Local content requirement 1 1.89% Quota (including tariff rate quotas) 1 1.89% State-controlled company 1 1.89% Total 53 100.00%

Madagascar’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. MADAGASCAR 158 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Malawi

Table 7.97. Foreign state measures affecting Malawi’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Malawi’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Malawi’s 62 61 commercial interests. Total number of foreign measures found to benefit or involve no 10 9 change in the treatment of Malawi’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Malawi’s commercial interests or 21 21 (ii) that have been announced but not implemented and which would almost certainly discriminate against Malawi’s interests [2] Total number of foreign measures that have been implemented and 31 31 which almost certainly discriminate against Malawi’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Malawi’s 43 42 commercial interests Total number of implemented measures affecting Malawi’s 38 38 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Malawi’s 25 25 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Malawi’s commercial 10 10 interests Total number of pending measures that, if implemented, are likely 8 8 to harm Malawi’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Malawi’s 9 9 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Malawi’s 6 6 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Malawi’s commercial 6 6 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 40 40 are currently in force and that harm Malawi’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting MALAWI “Malawi” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 159

Table 7.98. Malawi’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Malawi’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Malawi’s measures affecting other 1 1 jurisdictions’ commercial interests. Total number of Malawi’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Malawi’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Malawi’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Malawi’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Malawi’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Malawi’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Malawi that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Malawi that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Malawi that harm foreign commercial none none interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting MALAWI “Malawi” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 160 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.99. Frequency with which trading partners’ state measures have almost certainly harmed* Malawi’s commercial interests

Jurisdictions Number of measures China 6 India 4 Australia 2 Italy 2 South Africa 2 United Kingdom of Great Britain and Northern Ireland 2 Argentina 1 Austria 1 Belarus 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Indonesia 1 Ireland 1 Japan 1 Kazakhstan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Nigeria 1 Poland 1 Portugal 1 Romania 1 Russian Federation 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 United States of America 1 MALAWI Country-Specific Data 161

Frequency with which Malawi’s state measures have almost certainly harmed* foreign commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.100. Implemented measures that harm* Malawi’s commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 12 28.57% Export subsidy 10 23.81% Non-tariff barrier (not otherwise specified) 4 9.52% Public procurement 3 7.14% Trade finance 3 7.14% Bail out / state aid measure 2 4.76% Competitive devaluation 2 4.76% Export taxes or restriction 2 4.76% Investment measure 1 2.38% Local content requirement 1 2.38% Migration measure 1 2.38% Other service sector measure 1 2.38% Total 42 100.00%

Malawi’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. MALAWI 162 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Mali

Table 7.101. Foreign state measures affecting Mali’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Mali’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Mali’s 49 48 commercial interests. Total number of foreign measures found to benefit or involve no 6 5 change in the treatment of Mali’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Mali’s commercial interests or 15 15 (ii) that have been announced but not implemented and which would almost certainly discriminate against Mali’s interests [2] Total number of foreign measures that have been implemented and 28 28 which almost certainly discriminate against Mali’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Mali’s 35 34 commercial interests Total number of implemented measures affecting Mali’s 30 30 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Mali’s 21 21 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Mali’s commercial 7 7 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Mali’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Mali’s 7 7 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Mali’s commercial 7 7 interests. Total number of implemented, but no longer enforced measures 7 7 that were almost certainly harmful to Mali’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 38 38 are currently in force and that harm Mali’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Mali” in the “Affecting Trading Partner” and clicking the button “Get Stats”. MALI Country-Specific Data 163

Mali’s state measures affecting other jurisdictions’ commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.102. Frequency with which trading partners’ state measures have almost certainly harmed* Mali’s commercial interests

Jurisdictions Number of measures China 6 India 4 France 2 Italy 2 Argentina 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 Germany 1 Ghana 1 Greece 1 Hungary 1 Indonesia 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Nigeria 1 Poland 1 Portugal 1 Romania 1 Senegal 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 Switzerland 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 MALI Viet Nam 1 164 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Frequency with which Mali’s state measures have almost certainly harmed* foreign commercial interests No measures have been reported for this jurisdiction in the GTA database.

Table 7.103. Implemented measures that harm* Mali’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 15 38.46% Bail out / state aid measure 5 12.82% Tariff measure 5 12.82% Trade finance 4 10.26% Competitive devaluation 2 5.13% Local content requirement 2 5.13% Public procurement 2 5.13% Export taxes or restriction 1 2.56% Import subsidy 1 2.56% Investment measure 1 2.56% Non-tariff barrier (not otherwise specified) 1 2.56% Total 39 100.00%

Mali’s implemented measures that harm* foreign commercial interests, by type No measures have been reported for this jurisdiction in the GTA database. MALI Country-Specific Data 165

Mauritania

Table 7.104. Foreign state measures affecting Mauritania’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Mauritania’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Mauritania’s 52 51 commercial interests. Total number of foreign measures found to benefit or involve no 8 7 change in the treatment of Mauritania’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Mauritania’s commercial interests or 16 16 (ii) that have been announced but not implemented and which would almost certainly discriminate against Mauritania’s interests. [2] Total number of foreign measures that have been implemented and 28 28 which almost certainly discriminate against Mauritania’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Mauritania’s 38 37 commercial interests Total number of implemented measures affecting Mauritania’s 31 31 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Mauritania’s 22 22 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Mauritania’s 6 6 commercial interests Total number of pending measures that, if implemented, are likely to 6 6 harm Mauritania’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Mauritania’s 8 8 MAURITANIA commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Mauritania’s 7 7 commercial interests. Total number of implemented, but no longer enforced measures that 6 6 were almost certainly harmful to Mauritania’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 11 11 that are currently in force and that harm Mauritania’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Mauritania” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 166 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.105. Mauritania’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Mauritania’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Mauritania’s measures affecting other 1 1 jurisdictions’ commercial interests. Total number of Mauritania’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Mauritania’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Mauritania’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Mauritania’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Mauritania’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Mauritania’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 1 1 implemented by Mauritania that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Mauritania that harm foreign 1 1 commercial interests. Total number of trading partners affected by measures implemented by Mauritania that harm foreign 7 7 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Mauritania” in the “Affecting Trading Partner” and clicking the button “Get Stats”. MAURITANIA Country-Specific Data 167

Table 7.106. Frequency with which trading partners’ state measures have almost certainly harmed* Mauritania’s commercial interests

Jurisdictions Number of measures China 6 India 4 Indonesia 3 Argentina 2 Algeria 1 France 1 Italy 1 Nigeria 1 Russian Federation 1 Ukraine 1 Viet Nam 1

Table 7.107. Frequency with which Mauritania’s state measures have almost certainly harmed* foreign commercial interests. Jurisdictions affected Number of measures Belgium 1 France 1 Japan 1 Netherlands 1 Senegal 1 Spain 1 United Arab Emirates 1

Table 7.108. Implemented measures that harm* Mauritania’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 14 37.84% Export taxes or restriction 6 16.22% Tariff measure 5 13.51%

Trade finance 4 10.81% MAURITANIA Bail out / state aid measure 2 5.41% Competitive devaluation 2 5.41% Import subsidy 1 2.70% Investment measure 1 2.70% Non-tariff barrier (not otherwise specified) 1 2.70% Public procurement 1 2.70% Total 37 100.00% 168 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.109. Mauritania’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Non-tariff barrier (not otherwise specified) 1 100.00% Total 1 100.00% MAURITANIA Country-Specific Data 169

Mozambique

Table 7.110. Foreign state measures affecting Mozambique’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Mozambique’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Mozambique’s 90 89 commercial interests. Total number of foreign measures found to benefit or involve no 17 16 change in the treatment of Mozambique’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Mozambique’s commercial interests or 31 31 (ii) that have been announced but not implemented and which would almost certainly discriminate against Mozambique’s interests. [2] Total number of foreign measures that have been implemented and which almost certainly discriminate against Mozambique’s interests 42 42 [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Mozambique’s 63 62 commercial interests Total number of implemented measures affecting Mozambique’s 51 51 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Mozambique’s 33 33 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Mozambique’s 12 12 commercial interests Total number of pending measures that, if implemented, are likely to 11 11 harm Mozambique’s commercial interests. MOZAMBIQUE MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Mozambique’s 15 15 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Mozambique’s 11 11 commercial interests. Total number of implemented, but no longer enforced measures that 9 9 were almost certainly harmful to Mozambique’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 40 40 currently in force and that harm Mozambique’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Mozambique” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 170 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.111. Mozambique’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Mozambique’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Mozambique’s measures affecting 1 1 other jurisdictions’ commercial interests. Total number of Mozambique’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Mozambique’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Mozambique’s measures that have been implemented and which almost certainly none none discriminate against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Mozambique’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Mozambique’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Mozambique’s measures that have been implemented and which almost certainly none none discriminate against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Mozambique that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Mozambique that harm foreign none none commercial interests. Total number of trading partners affected by measures implemented by Mozambique that harm foreign none none commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Mozambique” in the “Affecting Trading Partner” and clicking the button “Get Stats”. MOZAMBIQUE Country-Specific Data 171

Table 7.112. Frequency with which trading partners’ state measures have almost certainly harmed* Mozambique’s commercial interests

Jurisdictions Number of measures Indonesia 7 China 6 India 4 Argentina 3 South Africa 3 France 2 Italy 2 Japan 2 Zimbabwe 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Romania 1

Russian Federation 1 MOZAMBIQUE Slovakia 1 Slovenia 1 Spain 1 Sweden 1 Thailand 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1 Zambia 1 172 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Frequency with which Mozambique’s state measures have almost certainly harmed* foreign commercial interests. No measures have been reported for this jurisdiction in the GTA database. Table 7.113. Implemented measures that harm* Mozambique’s commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 15 25.00% Export subsidy 14 23.33% Export taxes or restriction 9 15.00% Non-tariff barrier (not otherwise specified) 7 11.67% Trade finance 4 6.67% Bail out / state aid measure 3 5.00% Public procurement 2 3.33% Competitive devaluation 1 1.67% Import subsidy 1 1.67% Investment measure 1 1.67% Other service sector measure 1 1.67% Sanitary and Phytosanitary Measure 1 1.67% Sub-national government measure 1 1.67% Total 60 100.00%

Mozambique’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. MOZAMBIQUE Country-Specific Data 173

Myanmar

Table 7.114. Foreign state measures affecting Myanmar’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Myanmar’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Myanmar’s 85 83 commercial interests. Total number of foreign measures found to benefit or involve no 23 22 change in the treatment of Myanmar’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Myanmar’s commercial interests or 22 22 (ii) that have been announced but not implemented and which would almost certainly discriminate against Myanmar’s interests. [2] Total number of foreign measures that have been implemented and 40 39 which almost certainly discriminate against Myanmar’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Myanmar’s 74 72 commercial interests Total number of implemented measures affecting Myanmar’s 53 52 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Myanmar’s 36 35 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Myanmar’s 3 3 commercial interests Total number of pending measures that, if implemented, are likely 3 3 to harm Myanmar’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Myanmar’s 8 8 commercial interests but are no longer in force.

Total number of implemented, but no longer enforced measures MYANMAR that were harmful or almost certainly harmful to Myanmar’s 6 6 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Myanmar’s commercial 4 4 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 14 14 that are currently in force and that harm Myanmar’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Myanmar” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 174 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.115. Myanmar’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Myanmar’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Myanmar’s measures affecting other 3 3 jurisdictions’ commercial interests. Total number of Myanmar’s measures found to benefit or involve no change in the treatment of other 2 2 jurisdictions’ commercial interests. [1] Total number of Myanmar’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Myanmar’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Myanmar’s measures found to 1 1 benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Myanmar’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Myanmar’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by 2 2 measures implemented by Myanmar that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Myanmar that harm foreign 2 2 commercial interests. Total number of trading partners affected by measures implemented by Myanmar that harm foreign 8 8 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Myanmar” in the “Affecting Trading Partner” and clicking the button “Get Stats”. MYANMAR Country-Specific Data 175

Table 7.116. Frequency with which trading partners’ state measures have almost certainly harmed* Myanmar’s commercial interests

Jurisdictions Number of measures China 9 India 7 Indonesia 7 Argentina 3 Japan 2 Italy 1 Malaysia 1 Republic of Korea 1 South Africa 1 Sri Lanka 1 Thailand 1 Ukraine 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1

Table 7.117. Frequency with which Myanmar’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures Bangladesh 1 China 1 India 1 Malaysia 1 Pakistan 1 Singapore 1 Thailand 1 Viet Nam 1 MYANMAR 176 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.118. Implemented measures that harm* Myanmar’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 17 25.00% Tariff measure 14 20.59% Export taxes or restriction 11 16.18% Non-tariff barrier (not otherwise specified) 6 8.82% Trade finance 5 7.35% Import subsidy 2 2.94% Investment measure 2 2.94% Migration measure 2 2.94% Public procurement 2 2.94% Quota (including tariff rate quotas) 2 2.94% Bail out / state aid measure 1 1.47% Competitive devaluation 1 1.47% Local content requirement 1 1.47% Sanitary and Phytosanitary Measure 1 1.47% Trade defence measure (AD, CVD, safeguard) 1 1.47% Total 68 100.00%

Table 7.119. Myanmar’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 1 100.00% Total 1 100.00% MYANMAR Country-Specific Data 177

Nepal

Table 7.120. Foreign state measures affecting Nepal’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Nepal’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Nepal’s 65 60 commercial interests. Total number of foreign measures found to benefit or involve no 18 16 change in the treatment of Nepal’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Nepal’s commercial interests or 24 21 (ii) that have been announced but not implemented and which would almost certainly discriminate against Nepal’s interests. [2] Total number of foreign measures that have been implemented and 23 23 which almost certainly discriminate against Nepal’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Nepal’s 51 49 commercial interests Total number of implemented measures affecting Nepal’s 34 34 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Nepal’s 21 21 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Nepal’s commercial 11 11 interests Total number of pending measures that, if implemented, are likely 11 11 to harm Nepal’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Nepal’s 3 3 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Nepal’s 2 2 commercial interests. Total number of implemented, but no longer enforced measures 2 2 that were almost certainly harmful to Nepal’s commercial interests NEPAL TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 9 9 are currently in force and that harm Nepal’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Nepal” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 178 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.121. Nepal’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Nepal’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Nepal’s measures affecting other 1 1 jurisdictions’ commercial interests. Total number of Nepal’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Nepal’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Nepal’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Nepal’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Nepal’s measures that have been implemented and are likely to harm foreign 1 1 commercial interests. Total number of Nepal’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures none none implemented by Nepal that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Nepal that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Nepal that harm foreign commercial none none interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Nepal” in the “Affecting Trading Partner” and clicking the button “Get Stats”. NEPAL Country-Specific Data 179

Table 7.122. Frequency with which trading partners’ state measures have almost certainly harmed* Nepal’s commercial interests

Jurisdictions Number of measures India 9 China 6 Japan 2 Indonesia 1 Italy 1 Malaysia 1 Thailand 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1

Frequency with which Nepal’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.123. Implemented measures that harm* Nepal’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 13 31.71% Tariff measure 9 21.95% Export taxes or restriction 6 14.63% Trade finance 3 7.32% Bail out / state aid measure 2 4.88% Migration measure 2 4.88% Public procurement 2 4.88% Import ban 1 2.44% Import subsidy 1 2.44% Local content requirement 1 2.44% Non-tariff barrier (not otherwise specified) 1 2.44% Total 41 100.00%

Table 7.124. Nepal’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Bail out / state aid measure 1 25.00% Export subsidy 1 25.00% Import subsidy 1 25.00% NEPAL Tariff measure 1 25.00% Total 4 100.00% 180 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Niger

Table 7.125. Foreign state measures affecting Niger’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Niger’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Niger’s 45 44 commercial interests. Total number of foreign measures found to benefit or involve no 7 6 change in the treatment of Niger’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Niger’s commercial interests or 13 13 (ii) that have been announced but not implemented and which would almost certainly discriminate against Niger’s interests [2] Total number of foreign measures that have been implemented and 25 25 which almost certainly discriminate against Niger’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Niger’s 32 31 commercial interests Total number of implemented measures affecting Niger’s 27 27 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Niger’s 19 19 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Niger’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Niger’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Niger’s 8 8 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Niger’s 6 6 commercial interests. Total number of implemented, but no longer enforced measures 6 6 that were almost certainly harmful to Niger’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 9 9 are currently in force and that harm Niger’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Niger” in the “Affecting Trading Partner” and clicking the button “Get Stats”. NIGER Country-Specific Data 181

Niger’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.126. Frequency with which trading partners’ state measures have almost certainly harmed* Niger’s commercial interests

Jurisdictions Number of measures China 5 India 4 Argentina 3 Nigeria 2 Ghana 1 Indonesia 1 Italy 1 Russian Federation 1 Viet Nam 1

Frequency with which Niger’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.127. Implemented measures that harm* Niger’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 11 33.33% Tariff measure 4 12.12% Trade finance 4 12.12% Bail out / state aid measure 3 9.09% Competitive devaluation 2 6.06% Export taxes or restriction 2 6.06% Non-tariff barrier (not otherwise specified) 2 6.06% Public procurement 2 6.06% Import subsidy 1 3.03% Investment measure 1 3.03% Other service sector measure 1 3.03% Total 33 100.00%

Niger’s implemented measures that harm* foreign commercial interests, by type NIGER No measures have been reported for this jurisdiction in the GTA database. 182 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Rwanda

Table 7.128. Foreign state measures affecting Rwanda’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Rwanda’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Rwanda’s 31 30 commercial interests. Total number of foreign measures found to benefit or involve no 6 5 change in the treatment of Rwanda’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Rwanda’s commercial interests or 8 8 (ii) that have been announced but not implemented and which would almost certainly discriminate against Rwanda’s interests [2] Total number of foreign measures that have been implemented and 17 17 which almost certainly discriminate against Rwanda’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Rwanda’s 21 20 commercial interests Total number of implemented measures affecting Rwanda’s 17 17 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Rwanda’s 12 12 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Rwanda’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 3 3 to harm Rwanda’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Rwanda’s 5 5 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Rwanda’s 5 5 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Rwanda’s commercial 5 5 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 7 7 that are currently in force and that harm Rwanda’s commercial interests.

RWANDA Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Rwanda” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 183

Table 7.129. Rwanda’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Rwanda’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Rwanda’s measures affecting other 5 5 jurisdictions’ commercial interests. Total number of Rwanda’s measures found to benefit or involve no change in the treatment of other 4 4 jurisdictions’ commercial interests. [1] Total number of Rwanda’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Rwanda’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Rwanda’s measures found to benefit 4 4 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Rwanda’s measures that have been implemented and are likely to harm foreign 1 1 commercial interests. Total number of Rwanda’s measures that have been implemented and which almost certainly discriminate none none against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by none none measures implemented by Rwanda that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Rwanda that harm foreign commercial none none interests. Total number of trading partners affected by measures implemented by Rwanda that harm foreign commercial none none interests. RWANDA

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Rwanda” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 184 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.130. Frequency with which trading partners’ state measures have almost certainly harmed* Rwanda’s commercial interests

Jurisdictions Number of measures China 5 South Africa 2 Angola 1 Democratic Republic of the Congo 1 Italy 1 Russian Federation 1 Sudan 1

Frequency with which Rwanda’s state measures have almost certainly harmed* foreign commercial interests.

No measures have been reported for this jurisdiction in the GTA database.

Table 7.131. Implemented measures that harm* Rwanda’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 6 30.00% Trade finance 3 15.00% Bail out / state aid measure 2 10.00% Import ban 2 10.00% Non-tariff barrier (not otherwise specified) 2 10.00% Import subsidy 1 5.00% Investment measure 1 5.00% Other service sector measure 1 5.00% Public procurement 1 5.00% Sanitary and Phytosanitary Measure 1 5.00% Total 20 100.00%

Rwanda’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. RWANDA Country-Specific Data 185

Samoa

Table 7.132. Foreign state measures affecting Samoa’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Samoa’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Samoa’s 22 22 commercial interests. Total number of foreign measures found to benefit or involve no 6 6 change in the treatment of Samoa’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Samoa’s commercial interests or 7 7 (ii) that have been announced but not implemented and which would almost certainly discriminate against Samoa’s interests. [2] Total number of foreign measures that have been implemented and 9 9 which almost certainly discriminate against Samoa’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Samoa’s 17 17 commercial interests Total number of implemented measures affecting Samoa’s 12 12 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Samoa’s 8 8 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Samoa’s commercial 4 4 interests Total number of pending measures that, if implemented, are likely 3 3 to harm Samoa’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Samoa’s 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Samoa’s 1 1 commercial interests. Total number of implemented, but no longer enforced measures

1 1 SAMOA that were almost certainly harmful to Samoa’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 5 5 are currently in force and that harm Samoa’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Samoa” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 186 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Samoa’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.133. Frequency with which trading partners’ state measures have almost certainly harmed* Samoa’s commercial interests

Jurisdictions Number of measures Indonesia 3 China 2 Italy 1 Nigeria 1 Russian Federation 1

Frequency with which Samoa’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.134. Implemented measures that harm* Samoa’s commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 3 23.08% Tariff measure 3 23.08% Export subsidy 2 15.38% Trade finance 2 15.38% Bail out / state aid measure 1 7.69% Competitive devaluation 1 7.69% Import subsidy 1 7.69% Total 13 100.00%

Samoa’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. SAMOA Country-Specific Data 187

Sao Tome and Principe

Table 7.135. Foreign state measures affecting Sao Tome and Principe’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Sao Tome and Principe’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Sao Tome & Principe’s 8 8 commercial interests. Total number of foreign measures found to benefit or involve no change in 2 2 the treatment of Sao Tome & Principe’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Sao Tome & Principe’s commercial interests or 4 4 (ii) that have been announced but not implemented and which would almost certainly discriminate against Sao Tome & Principe’s interests. [2] Total number of foreign measures that have been implemented and which 2 2 almost certainly discriminate against Sao Tome & Principe’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Sao Tome & Principe’s 4 4 commercial interests PRINCIPE SAO TOMEAND Total number of implemented measures affecting Sao Tome & Principe’s 3 3 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Sao Tome & Principe’s 2 2 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Sao Tome & Principe’s 3 3 commercial interests Total number of pending measures that, if implemented, are likely to harm 3 3 Sao Tome & Principe’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Sao Tome & 1 1 Principe’s commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Sao Tome & Principe’s commercial none none interests. Total number of implemented, but no longer enforced measures that were none none almost certainly harmful to Sao Tome & Principe’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 2 2 currently in force and that harm Sao Tome & Principe’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Sao Tome and Principe” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 188 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Sao Tome and Principe’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.136. Frequency with which trading partners’ state measures have almost certainly harmed* Sao Tome and Principe’s commercial interests

Jurisdictions Number of measures Italy 1 Portugal 1

Frequency with which Sao Tome and Principe’s state measures have almost certainly harmed* foreign commercial interests.

No measures have been reported for this jurisdiction in the GTA database.

Table 7.137. Implemented measures that harm* Sao Tome and Principe’s commercial interests, by type Number of As percentage of Type of measure measures measures Trade finance 2 66.67% Migration measure 1 33.33% Total 3 100.00%

Sao Tome and Principe’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. SAO TOME TOME AND SAO PRINCIPE Country-Specific Data 189

Senegal

Table 7.138. Foreign state measures affecting Senegal’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Senegal’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Senegal’s 90 88 commercial interests. Total number of foreign measures found to benefit or involve no 15 14 change in the treatment of Senegal’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Senegal’s commercial interests or 30 29 (ii) that have been announced but not implemented and which would almost certainly discriminate against Senegal’s interests. [2] Total number of foreign measures that have been implemented and 45 45 which almost certainly discriminate against Senegal’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Senegal’s 63 62 commercial interests Total number of implemented measures affecting Senegal’s 51 51 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Senegal’s 34 34 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Senegal’s commercial 11 10 interests Total number of pending measures that, if implemented, are likely 10 9 to harm Senegal’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Senegal’s 16 16 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Senegal’s 14 14 commercial interests. SENEGAL Total number of implemented, but no longer enforced measures that were almost certainly harmful to Senegal’s commercial 11 11 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 38 38 are currently in force and that harm Senegal’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Senegal” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 190 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.139. Senegal’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Senegal’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Senegal’s measures affecting other 3 3 jurisdictions’ commercial interests. Total number of Senegal’s measures found to benefit or involve no change in the treatment of other 1 1 jurisdictions’ commercial interests. [1] Total number of Senegal’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Senegal’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Senegal’s measures found to benefit 1 1 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Senegal’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Senegal’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 1 1 implemented by Senegal that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Senegal that harm foreign commercial 2 2 interests. Total number of trading partners affected by measures implemented by Senegal that harm foreign commercial 5 5 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Senegal” in the “Affecting Trading Partner” and clicking the button “Get Stats”. SENEGAL Country-Specific Data 191

Table 7.140. Frequency with which trading partners’ state measures have almost certainly harmed* Senegal’s commercial interests

Jurisdictions Number of measures China 6 India 6 Indonesia 6 France 5 Argentina 3 Italy 2 South Africa 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 Germany 1 Greece 1 Hungary 1 Iran 1 Ireland 1 Japan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Mauritania 1 Netherlands 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sri Lanka 1 Sweden 1

United Kingdom of Great Britain and Northern Ireland 1 SENEGAL Viet Nam 1 192 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.141. Frequency with which Senegal’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures Belgium 2 Burkina Faso 1 China 1 Mali 1 Netherlands 1

Table 7.142. Implemented measures that harm* Senegal’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 19 31.15% Export taxes or restriction 11 18.03% Bail out / state aid measure 8 13.11% Tariff measure 8 13.11% Non-tariff barrier (not otherwise specified) 4 6.56% Trade finance 4 6.56% Competitive devaluation 1 1.64% Import subsidy 1 1.64% Investment measure 1 1.64% Local content requirement 1 1.64% Migration measure 1 1.64% Public procurement 1 1.64% State-controlled company 1 1.64% Total 61 100.00%

Table 7.143. Senegal’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Import ban 1 50.00% Non-tariff barrier (not otherwise specified) 1 50.00% Total 2 100.00% SENEGAL Country-Specific Data 193

Sierra Leone

Table 7.144. Foreign state measures affecting Sierra Leone’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Sierra Leone’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Sierra Leone’s 46 45 commercial interests. Total number of foreign measures found to benefit or involve no 16 15 change in the treatment of Sierra Leone’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Sierra Leone’s commercial interests or 14 14 (ii) that have been announced but not implemented and which would almost certainly discriminate against Sierra Leone’s interests. [2] Total number of foreign measures that have been implemented and which almost certainly discriminate against Sierra Leone’s interests 16 16 [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Sierra Leone’s 34 33 commercial interests Total number of implemented measures affecting Sierra Leone’s 22 22 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Sierra Leone’s 13 13 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Sierra Leone’s 6 6 commercial interests Total number of pending measures that, if implemented, are likely to 5 5

harm Sierra Leone’s commercial interests. SIERRA LEONE MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Sierra Leone’s 6 6 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Sierra Leone’s 3 3 commercial interests. Total number of implemented, but no longer enforced measures that 3 3 were almost certainly harmful to Sierra Leone’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 31 31 currently in force and that harm Sierra Leone’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Sierra Leone” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 194 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.145. Sierra Leone’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Sierra Leone’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Sierra Leone’s measures affecting other 3 3 jurisdictions’ commercial interests. Total number of Sierra Leone’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Sierra Leone’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Sierra Leone’s measures that have been implemented and which almost certainly 3 3 discriminate against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Sierra Leone’s measures found to none none benefit or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Sierra Leone’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Sierra Leone’s measures that have been implemented and which almost certainly 3 3 discriminate against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 17 17 implemented by Sierra Leone that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Sierra Leone that harm foreign 7 7 commercial interests. Total number of trading partners affected by measures implemented by Sierra Leone that harm foreign 9 9 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Sierra Leone” in the “Affecting Trading Partner” and clicking the button “Get Stats”. SIERRA LEONE Country-Specific Data 195

Table 7.146. Frequency with which trading partners’ state measures have almost certainly harmed* Sierra Leone’s commercial interests.

Jurisdictions Number of measures China 6 Indonesia 3 Italy 2 United Kingdom of Great Britain and Northern Ireland 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 Viet Nam 1 SIERRA LEONE 196 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.147. Frequency with which Sierra Leone’s state measures have almost certainly harmed* foreign commercial interests. Jurisdictions affected Number of measures Algeria 1 Belgium 1 China 1 Estonia 1 Republic of Korea 1 Russian Federation 1 Turkey 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1

Table 7.148. Implemented measures that harm* Sierra Leone’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 8 32.00% Export taxes or restriction 5 20.00% Tariff measure 5 20.00% Bail out / state aid measure 2 8.00% Trade finance 2 8.00% Competitive devaluation 1 4.00% Consumption subsidy 1 4.00% Migration measure 1 4.00% Total 25 100.00%

Table 7.149. Sierra Leone’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 2 66.67% Tariff measure 1 33.33% Total 3 100.00% SIERRA LEONE Country-Specific Data 197

Solomon Islands

Table 7.150. Foreign state measures affecting Solomon Islands’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Solomon Islands’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Solomon Islands’s 17 17 commercial interests. Total number of foreign measures found to benefit or involve no 4 4 change in the treatment of Solomon Islands’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Solomon Islands’s commercial interests or 5 5 (ii) that have been announced but not implemented and which would almost certainly discriminate against Solomon Islands’s interests. [2] Total number of foreign measures that have been implemented and which almost certainly discriminate against Solomon Islands’s interests 8 8 [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Solomon Islands’s 14 14 commercial interests Total number of implemented measures affecting Solomon Islands’s 10 10 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Solomon Islands’s 7 7 commercial interests that are almost certainly harmful. SOLOMON ISLANDS PENDING MEASURES Total number of pending measures affecting Solomon Islands’s 2 2 commercial interests Total number of pending measures that, if implemented, are likely to 2 2 harm Solomon Islands’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Solomon 1 1 Islands’s commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Solomon Islands’s 1 1 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Solomon Islands’s commercial 1 1 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 4 4 are currently in force and that harm Solomon Islands’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Solomon Islands” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 198 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Solomon Islands’ state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.151. Frequency with which trading partners’ state measures have almost certainly harmed* Solomon Island’s commercial interests.

Jurisdictions Number of measures Indonesia 3 China 2 Japan 1 Viet Nam 1

Frequency with which Solomon Island’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.152. Implemented measures that harm* Solomon Islands’ commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 4 36.36% Export taxes or restriction 3 27.27% Export subsidy 2 18.18% Competitive devaluation 1 9.09% Non-tariff barrier (not otherwise specified) 1 9.09% Total 11 100.00%

Solomon Islands’ implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. SOLOMON ISLANDS Country-Specific Data 199

Somalia

Table 7.153. Foreign state measures affecting Somalia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Somalia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Somalia’s 38 38 commercial interests. Total number of foreign measures found to benefit or involve no 9 9 change in the treatment of Somalia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Somalia’s commercial interests or 12 12 (ii) that have been announced but not implemented and which would almost certainly discriminate against Somalia’s interests. [2] Total number of foreign measures that have been implemented and 17 17 which almost certainly discriminate against Somalia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Somalia’s 29 29 commercial interests Total number of implemented measures affecting Somalia’s 21 21 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Somalia’s 14 14 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Somalia’s commercial 5 5 interests Total number of pending measures that, if implemented, are likely 5 5 to harm Somalia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Somalia’s 4 4 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Somalia’s 3 3

commercial interests. SOMALIA Total number of implemented, but no longer enforced measures that were almost certainly harmful to Somalia’s commercial 3 3 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 10 10 that are currently in force and that harm Somalia’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Somalia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 200 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Somalia’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.154. Frequency with which trading partners’ state measures have almost certainly harmed* Somalia’s commercial interests

Jurisdictions Number of measures China 4 Indonesia 2 Algeria 1 Ethiopia 1 India 1 Italy 1 Netherlands 1 Norway 1 Ukraine 1 United Kingdom of Great Britain and Northern Ireland 1

Frequency with which Somalia’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.155. Implemented measures that harm* Somalia’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 5 23.81% Migration measure 5 23.81% Export taxes or restriction 3 14.29% Tariff measure 3 14.29% Non-tariff barrier (not otherwise specified) 2 9.52% Competitive devaluation 1 4.76% Investment measure 1 4.76% Trade finance 1 4.76% Total 21 100.00%

Somalia’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. SOMALIA Country-Specific Data 201

Sudan

Table 7.156. Foreign state measures affecting Sudan’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Sudan’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Sudan’s 94 93 commercial interests. Total number of foreign measures found to benefit or involve no 16 16 change in the treatment of Sudan’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Sudan’s commercial interests or 28 27 (ii) that have been announced but not implemented and which would almost certainly discriminate against Sudan’s interests. [2] Total number of foreign measures that have been implemented and 50 50 which almost certainly discriminate against Sudan’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Sudan’s 69 69 commercial interests Total number of implemented measures affecting Sudan’s 57 57 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Sudan’s 37 37 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Sudan’s commercial 6 5 interests Total number of pending measures that, if implemented, are likely 6 5 to harm Sudan’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Sudan’s 19 19 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Sudan’s 15 15 commercial interests. Total number of implemented, but no longer enforced measures 13 13 that were almost certainly harmful to Sudan’s commercial interests SUDAN TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 45 45 are currently in force and that harm Sudan’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Sudan” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 202 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.157. Sudan’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Sudan’s state measures anti-dumping, affecting other jurisdictions’ commercial interests All measures anti-subsidy, and safe-guard actions ALL MEASURES Total number of Sudan’s measures affecting other 4 4 jurisdictions’ commercial interests. Total number of Sudan’s measures found to benefit or involve no change in the treatment of other 1 1 jurisdictions’ commercial interests. [1] Total number of Sudan’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Sudan’s measures that have been implemented and which almost certainly discriminate 3 3 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Sudan’s measures found to benefit 1 1 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Sudan’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Sudan’s measures that have been implemented and which almost certainly discriminate 3 3 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 67 67 implemented by Sudan that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Sudan that harm foreign commercial 18 18 interests. Total number of trading partners affected by measures implemented by Sudan that harm foreign commercial 22 22 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Sudan” in the “Affecting Trading Partner” and clicking the button “Get Stats”. SUDAN Country-Specific Data 203

Table 7.158. Frequency with which trading partners’ state measures have almost certainly harmed* Sudan’s commercial interests

Jurisdictions Number of measures China 6 India 4 Italy 4 Germany 3 Indonesia 3 Poland 3 United Kingdom of Great Britain and Northern Ireland 3 Algeria 2 Argentina 2 Austria 2 Belgium 2 Bulgaria 2 Cyprus 2 Czech Republic 2 Denmark 2 Egypt 2 Estonia 2 European Communities 2 Finland 2 France 2 Greece 2 Hungary 2 Ireland 2 Latvia 2 Lithuania 2 Luxembourg 2 Malta 2 Netherlands 2 Portugal 2 Romania 2 Slovakia 2 Slovenia 2 Spain 2 Sweden 2 Ukraine 2 Viet Nam 2 Ethiopia 1 Iran 1 SUDAN Japan 1 Malaysia 1 Nigeria 1 Republic of Korea 1 Russian Federation 1 Thailand 1 204 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Jurisdictions Number of measures United Arab Emirates 1

Table 7.159. Frequency with which Sudan’s state measures have almost certainly harmed* foreign commercial interests. Jurisdictions affected Number of measures Egypt 2 Saudi Arabia 2 Bangladesh 1 China 1 Czech Republic 1 Djibouti 1 Eritrea 1 Ethiopia 1 Germany 1 India 1 Iran 1 Italy 1 Japan 1 Malaysia 1 Republic of Korea 1 Rwanda 1 Syrian Arab Republic 1 Thailand 1 Turkey 1 United Arab Emirates 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1 SUDAN Country-Specific Data 205

Table 7.160. Implemented measures that harm* Sudan’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 16 24.62% Tariff measure 14 21.54% Export taxes or restriction 11 16.92% Non-tariff barrier (not otherwise specified) 7 10.77% Bail out / state aid measure 4 6.15% Trade finance 4 6.15% Competitive devaluation 3 4.62% Migration measure 2 3.08% Import subsidy 1 1.54% Public procurement 1 1.54% Quota (including tariff rate quotas) 1 1.54% Technical Barrier to Trade 1 1.54% Total 65 100.00%

Table 7.161. Sudan’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Import ban 1 33.33% Sanitary and Phytosanitary Measure 1 33.33% Tariff measure 1 33.33% Total 3 100.00% SUDAN 206 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Timor-Leste

Table 7.162. Foreign state measures affecting Timor-Leste’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Timor-Leste’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Timor-Leste’s 19 19 commercial interests. Total number of foreign measures found to benefit or involve no 5 5 change in the treatment of Timor-Leste’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Timor-Leste’s commercial interests or 5 5 (ii) that have been announced but not implemented and which would almost certainly discriminate against Timor-Leste’s interests [2] Total number of foreign measures that have been implemented and 9 9 which almost certainly discriminate against Timor-Leste’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Timor-Leste’s 15 15 commercial interests Total number of implemented measures affecting Timor-Leste’s 11 11 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Timor-Leste’s 9 9 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Timor-Leste’s commercial 3 3 interests Total number of pending measures that, if implemented, are likely to 3 3 harm Timor-Leste’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Timor-Leste’s 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Timor-Leste’s commercial none none interests. Total number of implemented, but no longer enforced measures that none none were almost certainly harmful to Timor-Leste’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that are 3 3 currently in force and that harm Timor-Leste’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Timor-Leste” in the “Affecting Trading Partner” and clicking the button “Get Stats”. TIMOR-LESTE Country-Specific Data 207

Timor-Leste’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.163. Frequency with which trading partners’ state measures have almost certainly harmed* Timor-Leste’s commercial interests

Jurisdictions Number of measures Indonesia 7 Australia 1 Viet Nam 1

Frequency with which Timor-Leste’s state measures have almost certainly harmed* foreign commercial interests.

No measures have been reported for this jurisdiction in the GTA database.

Table 7.164. Implemented measures that harm* Timor-Leste’s commercial interests, by type Number of As percentage of Type of measure measures measures Export taxes or restriction 5 45.45% Tariff measure 4 36.36% Competitive devaluation 1 9.09% Non-tariff barrier (not otherwise specified) 1 9.09% Total 11 100.00%

Timor-Leste’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. TIMOR-LESTE 208 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Togo

Table 7.165. Foreign state measures affecting Togo’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Togo’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Togo’s 58 57 commercial interests. Total number of foreign measures found to benefit or involve no 11 10 change in the treatment of Togo’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Togo’s commercial interests or 17 17 (ii) that have been announced but not implemented and which would almost certainly discriminate against Togo’s interests [2] Total number of foreign measures that have been implemented and 30 30 which almost certainly discriminate against Togo’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Togo’s 47 46 commercial interests Total number of implemented measures affecting Togo’s 37 37 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Togo’s 27 27 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Togo’s commercial 6 6 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Togo’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Togo’s 5 5 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Togo’s commercial 4 4 interests. Total number of implemented, but no longer enforced measures 3 3 that were almost certainly harmful to Togo’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 38 38 are currently in force and that harm Togo’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Togo” in the “Affecting Trading Partner” and clicking the button “Get Stats”. TOGO Country-Specific Data 209

Table 7.166. Togo’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Togo’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Togo’s measures affecting other 2 2 jurisdictions’ commercial interests. Total number of Togo’s measures found to benefit or involve no change in the treatment of other none none jurisdictions’ commercial interests. [1] Total number of Togo’s measures that (i) have been implemented and are likely to harm foreign commercial interests or none none (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Togo’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Togo’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Togo’s measures that have been implemented and are likely to harm foreign none none commercial interests. Total number of Togo’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 6 6 implemented by Togo that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Togo that harm foreign commercial 2 2 interests. Total number of trading partners affected by measures implemented by Togo that harm foreign commercial 13 13 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Togo” in the “Affecting Trading Partner” and clicking the button “Get Stats”. TOGO 210 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.167. Frequency with which trading partners’ state measures have almost certainly harmed* Togo’s commercial interests

Jurisdictions Number of measures China 6 India 5 Indonesia 5 France 3 Spain 3 Italy 2 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 Germany 1 Ghana 1 Greece 1 Hungary 1 Ireland 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Netherlands 1 Nigeria 1 Poland 1 Portugal 1 Romania 1 Russian Federation 1 Slovakia 1 Slovenia 1 Sri Lanka 1 Sweden 1 Thailand 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1 TOGO Country-Specific Data 211

Table 7.168. Frequency with which Togo’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures China 2 Belgium 1 Canada 1 France 1 Germany 1 Ghana 1 India 1 Japan 1 Netherlands 1 Switzerland 1 United Arab Emirates 1 United Kingdom of Great Britain and Northern Ireland 1 United States of America 1

Table 7.169. Implemented measures that harm* Togo’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 15 32.61% Tariff measure 10 21.74% Export taxes or restriction 8 17.39% Public procurement 3 6.52% Trade finance 3 6.52% Bail out / state aid measure 2 4.35% Competitive devaluation 2 4.35% Import subsidy 1 2.17% Non-tariff barrier (not otherwise specified) 1 2.17% Other service sector measure 1 2.17% Total 46 100.00%

Table 7.170. Togo’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Import ban 1 50.00% Non-tariff barrier (not otherwise specified) 1 50.00% Total 2 100.00% TOGO 212 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Tuvalu

Table 7.171. Foreign state measures affecting Tuvalu’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Tuvalu’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Tuvalu’s 7 7 commercial interests. Total number of foreign measures found to benefit or involve no none none change in the treatment of Tuvalu’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Tuvalu’s commercial interests or 4 4 (ii) that have been announced but not implemented and which would almost certainly discriminate against Tuvalu’s interests [2] Total number of foreign measures that have been implemented and 3 3 which almost certainly discriminate against Tuvalu’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Tuvalu’s 3 3 commercial interests Total number of implemented measures affecting Tuvalu’s 3 3 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Tuvalu’s 3 3 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Tuvalu’s commercial 4 4 interests Total number of pending measures that, if implemented, are likely 4 4 to harm Tuvalu’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Tuvalu’s none none commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Tuvalu’s none none commercial interests. Total number of implemented, but no longer enforced measures none none that were almost certainly harmful to Tuvalu’s commercial interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 1 1 are currently in force and that harm Tuvalu’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Tuvalu” in the “Affecting Trading Partner” and clicking the button “Get Stats”. TUVALU Country-Specific Data 213

Tuvalu’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.172. Frequency with which trading partners’ state measures have almost certainly harmed* Tuvalu’s commercial interests

Jurisdictions Number of measures China 3

Frequency with which Tuvalu’s state measures have almost certainly harmed* foreign commercial interests.

No measures have been reported for this jurisdiction in the GTA database.

Table 7.173. Implemented measures that harm* Tuvalu’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 2 66.67% Export taxes or restriction 1 33.33% Total 3 100.00%

Tuvalu’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. TUVALU 214 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Uganda

Table 7.174. Foreign state measures affecting Uganda’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Uganda’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Uganda’s 75 74 commercial interests. Total number of foreign measures found to benefit or involve no 16 15 change in the treatment of Uganda’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Uganda’s commercial interests or 17 17 (ii) that have been announced but not implemented and which would almost certainly discriminate against Uganda’s interests [2] Total number of foreign measures that have been implemented and 42 42 which almost certainly discriminate against Uganda’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Uganda’s 52 51 commercial interests Total number of implemented measures affecting Uganda’s 41 41 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Uganda’s 30 30 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Uganda’s commercial 8 8 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Uganda’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Uganda’s 15 15 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Uganda’s 12 12 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Uganda’s commercial 12 12 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 43 43 that are currently in force and that harm Uganda’s commercial interests.

UGANDA Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Uganda” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 215

Table 7.175. Uganda’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Uganda’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Uganda’s measures affecting other 8 8 jurisdictions’ commercial interests. Total number of Uganda’s measures found to benefit or involve no change in the treatment of other 3 3 jurisdictions’ commercial interests. [1] Total number of Uganda’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 3 3 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Uganda’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Uganda’s measures found to benefit 3 3 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Uganda’s measures that have been implemented and are likely to harm foreign 2 2 commercial interests. Total number of Uganda’s measures that have been implemented and which almost certainly discriminate 2 2 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 6 6 implemented by Uganda that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Uganda that harm foreign commercial 4 4 interests. Total number of trading partners affected by measures implemented by Uganda that harm foreign commercial 10 10 interests. UGANDA

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Uganda” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 216 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.176. Frequency with which trading partners’ state measures have almost certainly harmed* Uganda’s commercial interests

Jurisdictions Number of measures China 6 India 4 Italy 2 Kenya 2 Russian Federation 2 South Africa 2 Ukraine 2 United Kingdom of Great Britain and Northern Ireland 2 Angola 1 Argentina 1 Australia 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Democratic Republic of the Congo 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Indonesia 1 Ireland 1 Japan 1 Latvia 1 Lithuania 1 Luxembourg 1 Malta 1 Netherlands 1 Oman 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 Spain 1 Sweden 1 Switzerland 1 Viet Nam 1 UGANDA Country-Specific Data 217

Table 7.177. Frequency with which Uganda’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures South Africa 2 United Arab Emirates 2 United Kingdom of Great Britain and Northern Ireland 2 China 1 India 1 Japan 1 Kenya 1 Netherlands 1 Singapore 1 United States of America 1

Table 7.178. Implemented measures that harm* Uganda’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 13 27.08% Bail out / state aid measure 6 12.50% Tariff measure 6 12.50% Export taxes or restriction 5 10.42% Non-tariff barrier (not otherwise specified) 5 10.42% Trade finance 4 8.33% Competitive devaluation 1 2.08% Import ban 1 2.08% Import subsidy 1 2.08% Investment measure 1 2.08% Local content requirement 1 2.08% Migration measure 1 2.08% Other service sector measure 1 2.08% Public procurement 1 2.08% Sanitary and Phytosanitary Measure 1 2.08% Total 48 100.00%

Table 7.179. Uganda’s implemented measures that harm* foreign commercial interests, by type

Number of As percentage of UGANDA Type of measure measures measures Non-tariff barrier (not otherwise specified) 2 50.00% Import ban 1 25.00% Tariff measure 1 25.00% Total 4 100.00% 218 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

United Republic of Tanzania

Table 7.180. Foreign state measures affecting Tanzania’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Tanzania’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Tanzania’s 93 92 commercial interests. Total number of foreign measures found to benefit or involve no 17 16 change in the treatment of Tanzania’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Tanzania’s commercial interests or 30 30 (ii) that have been announced but not implemented and which would almost certainly discriminate against Tanzania’s interests [2] Total number of foreign measures that have been implemented and 46 46 which almost certainly discriminate against Tanzania’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Tanzania’s 65 64 commercial interests Total number of implemented measures affecting Tanzania’s 52 52 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Tanzania’s 32 32 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Tanzania’s commercial 9 9 interests Total number of pending measures that, if implemented, are likely 8 8 to harm Tanzania’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Tanzania’s 19 19 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Tanzania’s 16 16 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Tanzania’s commercial 14 14 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 43 43 that are currently in force and that harm Tanzania’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the UNITED REPUBLIC OF TANZANIA UNITED REPUBLIC OF numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Tanzania” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 219

Table 7.181. Tanzania’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Tanzania’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Tanzania’s measures affecting other 8 8 jurisdictions’ commercial interests. Total number of Tanzania’s measures found to benefit or involve no change in the treatment of other 3 3 jurisdictions’ commercial interests. [1] Total number of Tanzania’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 1 1 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Tanzania’s measures that have been implemented and which almost certainly discriminate 4 4 UNITED REPUBLIC OF TANZANIA against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Tanzania’s measures found to benefit 3 3 or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Tanzania’s measures that have been implemented and are likely to harm foreign 1 1 commercial interests. Total number of Tanzania’s measures that have been implemented and which almost certainly discriminate 3 3 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by 9 9 measures implemented by Tanzania that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Tanzania that harm foreign 8 8 commercial interests. Total number of trading partners affected by measures implemented by Tanzania that harm foreign 14 14 commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Tanzania” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 220 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.182. Frequency with which trading partners’ state measures have almost certainly harmed* Tanzania’s commercial interests

Jurisdictions Number of measures China 7 Indonesia 7 India 5 Italy 2 Nigeria 2 Angola 1 Argentina 1 Austria 1 Belgium 1 Bulgaria 1 Cyprus 1 Czech Republic 1 Denmark 1 Estonia 1 European Communities 1 Finland 1 France 1 Germany 1 Greece 1 Hungary 1 Ireland 1 Japan 1 Kazakhstan 1 Kenya 1 Latvia 1 Lithuania 1 Luxembourg 1 Malaysia 1 Malta 1 Netherlands 1 Poland 1 Portugal 1 Romania 1 Slovakia 1 Slovenia 1 South Africa 1 Spain 1 Sweden 1 Thailand 1 Ukraine 1 United Kingdom of Great Britain and Northern Ireland 1 Viet Nam 1 Zambia 1 UNITED REPUBLIC OF TANZANIA UNITED REPUBLIC OF Country-Specific Data 221

Table 7.183. Frequency with which Tanzania’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures South Africa 3 United Arab Emirates 3 India 2 Belgium 1 China 1 Hong Kong 1 Israel 1 Kenya 1 Kuwait 1 Luxembourg 1 Netherlands 1 Spain 1 Thailand 1 United States of America 1 UNITED REPUBLIC OF TANZANIA Table 7.184. Implemented measures that harm* Tanzania’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 16 25.00% Export taxes or restriction 13 20.31% Tariff measure 13 20.31% Bail out / state aid measure 5 7.81% Non-tariff barrier (not otherwise specified) 5 7.81% Trade finance 4 6.25% Competitive devaluation 2 3.13% Import ban 1 1.56% Import subsidy 1 1.56% Other service sector measure 1 1.56% Public procurement 1 1.56% Quota (including tariff rate quotas) 1 1.56% Sanitary and Phytosanitary Measure 1 1.56% Total 64 100.00% 222 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.185. Tanzania’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Investment measure 2 33.33% Export taxes or restriction 1 16.67% Local content requirement 1 16.67% Non-tariff barrier (not otherwise specified) 1 16.67% Tariff measure 1 16.67% Total 6 100.00% UNITED REPUBLIC OF TANZANIA UNITED REPUBLIC OF Country-Specific Data 223

Vanuatu

Table 7.186. Foreign state measures affecting Vanuatu’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Vanuatu’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Vanuatu’s 14 14 commercial interests. Total number of foreign measures found to benefit or involve no 3 3 change in the treatment of Vanuatu’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Vanuatu’s commercial interests or 6 6 (ii) that have been announced but not implemented and which would almost certainly discriminate against Vanuatu’s interests. [2] Total number of foreign measures that have been implemented and 5 5 which almost certainly discriminate against Vanuatu’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Vanuatu’s 9 9 commercial interests Total number of implemented measures affecting Vanuatu’s 6 6 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Vanuatu’s 4 4 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Vanuatu’s commercial 4 4 interests Total number of pending measures that, if implemented, are likely 4 4 to harm Vanuatu’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Vanuatu’s 1 1 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Vanuatu’s 1 1 VANUATU commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Vanuatu’s commercial 1 1 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures 2 2 that are currently in force and that harm Vanuatu’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Vanuatu” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 224 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Vanuatu’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.187. Frequency with which trading partners’ state measures have almost certainly harmed* Vanuatu’s commercial interests

Jurisdictions Number of measures China 3 Japan 1

Frequency with which Vanuatu’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.188. Implemented measures that harm* Vanuatu’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 2 28.57% Tariff measure 2 28.57% Export taxes or restriction 1 14.29% Import subsidy 1 14.29% Non-tariff barrier (not otherwise specified) 1 14.29% Total 7 100.00%

Vanuatu’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. VANUATU Country-Specific Data 225

Yemen

Table 7.189. Foreign state measures affecting Yemen’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Yemen’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Yemen’s 106 105 commercial interests. Total number of foreign measures found to benefit or involve no 21 21 change in the treatment of Yemen’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Yemen’s commercial interests or 27 26 (ii) that have been announced but not implemented and which would almost certainly discriminate against Yemen’s interests. [2] Total number of foreign measures that have been implemented and 58 58 which almost certainly discriminate against Yemen’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Yemen’s 84 84 commercial interests Total number of implemented measures affecting Yemen’s 67 67 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Yemen’s 48 48 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Yemen’s commercial 8 7 interests Total number of pending measures that, if implemented, are likely 7 6 to harm Yemen’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Yemen’s 14 14 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Yemen’s 11 11 commercial interests. Total number of implemented, but no longer enforced measures 10 10

that were almost certainly harmful to Yemen’s commercial interests YEMEN TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 47 47 are currently in force and that harm Yemen’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Yemen” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 226 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Yemen’s state measures affecting other jurisdictions’ commercial interests. No measures have been reported for this jurisdiction in the GTA database.

Table 7.190. Frequency with which trading partners’ state measures have almost certainly harmed* Yemen’s commercial interests

Jurisdictions Number of measures China 7 Saudi Arabia 7 India 6 Indonesia 6 Italy 3 United Kingdom of Great Britain and Northern Ireland 3 Algeria 2 Argentina 2 Armenia 2 Austria 2 Belgium 2 Bulgaria 2 Cyprus 2 Czech Republic 2 Denmark 2 Estonia 2 Ethiopia 2 European Communities 2 Finland 2 France 2 Germany 2 Greece 2 Hungary 2 Ireland 2 Latvia 2 Lithuania 2 Luxembourg 2 Malta 2 Netherlands 2 Poland 2 Portugal 2 Romania 2 Slovakia 2 Slovenia 2 Spain 2 Sweden 2 Ukraine 2 Egypt 1 Iran 1 Kazakhstan 1 YEMEN Country-Specific Data 227

Jurisdictions Number of measures Malaysia 1 Nigeria 1 Republic of Korea 1 Russian Federation 1 Thailand 1 United Arab Emirates 1 Viet Nam 1

Frequency with which Yemen’s state measures have almost certainly harmed* foreign commercial interests

No measures have been reported for this jurisdiction in the GTA database.

Table 7.191. Implemented measures that harm* Yemen’s commercial interests, by type Number of As percentage of Type of measure measures measures Export subsidy 21 28.00% Export taxes or restriction 13 17.33% Tariff measure 10 13.33% Migration measure 8 10.67% Bail out / state aid measure 5 6.67% Competitive devaluation 4 5.33% Trade finance 4 5.33% Non-tariff barrier (not otherwise specified) 3 4.00% Investment measure 2 2.67% Import ban 1 1.33% Import subsidy 1 1.33% Local content requirement 1 1.33% Public procurement 1 1.33% Quota (including tariff rate quotas) 1 1.33% Total 75 100.00%

Yemen’s implemented measures that harm* foreign commercial interests, by type

No measures have been reported for this jurisdiction in the GTA database. YEMEN 228 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Zambia

Table 7.192. Foreign state measures affecting Zambia’s commercial interests

All measures except anti- Summary statistic of foreign state measures All dumping, affecting Zambia’s commercial interests measures anti-subsidy, and safeguard actions ALL MEASURES Total number of measures affecting Zambia’s 76 75 commercial interests. Total number of foreign measures found to benefit or involve no 15 14 change in the treatment of Zambia’s commercial interests. [1] Total number of foreign measures that (i) have been implemented and are likely to harm Zambia’s commercial interests or 27 27 (ii) that have been announced but not implemented and which would almost certainly discriminate against Zambia’s interests [2] Total number of foreign measures that have been implemented and 34 34 which almost certainly discriminate against Zambia’s interests [3] MEASURES STILL IN FORCE Total number of implemented measures affecting Zambia’s 54 53 commercial interests Total number of implemented measures affecting Zambia’s 44 44 commercial interests that are harmful or almost certainly harmful. Total number of implemented measures affecting Zambia’s 25 25 commercial interests that are almost certainly harmful. PENDING MEASURES Total number of pending measures affecting Zambia’s commercial 7 7 interests Total number of pending measures that, if implemented, are likely 6 6 to harm Zambia’s commercial interests. MEASURES NO LONGER IN FORCE Total number of implemented measures that affected Zambia’s 15 15 commercial interests but are no longer in force. Total number of implemented, but no longer enforced measures that were harmful or almost certainly harmful to Zambia’s 11 11 commercial interests. Total number of implemented, but no longer enforced measures that were almost certainly harmful to Zambia’s commercial 9 9 interests TRADING PARTNERS RESPONSIBLE Total number of trading partners that have imposed measures that 38 38 are currently in force and that harm Zambia’s commercial interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting ZAMBIA “Zambia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. Country-Specific Data 229

Table 7.193. Zambia’s state measures affecting other jurisdictions’ commercial interests

All measures except Summary statistic of Zambia’s state measures anti-dumping, All measures affecting other jurisdictions’ commercial interests anti-subsidy, and safe-guard actions ALL MEASURES Total number of Zambia’s measures affecting other 4 4 jurisdictions’ commercial interests. Total number of Zambia’s measures found to benefit or involve no change in the treatment of other 1 1 jurisdictions’ commercial interests. [1] Total number of Zambia’s measures that (i) have been implemented and are likely to harm foreign commercial interests or 2 2 (ii) that have been announced but not implemented and which would almost certainly discriminate against foreign interests. [2] Total number of Zambia’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. [3] MEASURES STILL IN FORCE Total number of Zambia’s measures found to benefit none none or involve no change in the treatment of other jurisdictions’ commercial interests. Total number of Zambia’s measures that have been implemented and are likely to harm foreign 2 2 commercial interests. Total number of Zambia’s measures that have been implemented and which almost certainly discriminate 1 1 against foreign commercial interests. COMMERCE AFFECTED Total number of 4-digit tariff lines affected by measures 1 1 implemented by Zambia that harm foreign commercial interests. Total number of 2-digit sectors affected by measures implemented by Zambia that harm foreign commercial 1 1 interests. Total number of trading partners affected by measures implemented by Zambia that harm foreign commercial 10 10 interests.

Note: As the Global Trade Alert database is updated frequently, the above data will change. Updates on the ZAMBIA numbers in this table can be found by going to http://www.globaltradealert.org/site-statistics, and selecting “Zambia” in the “Affecting Trading Partner” and clicking the button “Get Stats”. 230 Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries

Table 7.194. Frequency with which trading partners’ state measures have almost certainly harmed* Zambia’s commercial interests

Jurisdictions Number of measures China 6 India 4 Italy 4 United Kingdom of Great Britain and Northern Ireland 4 Austria 3 Belgium 3 Bulgaria 3 Cyprus 3 Czech Republic 3 Denmark 3 Estonia 3 European Communities 3 Finland 3 France 3 Germany 3 Greece 3 Hungary 3 Ireland 3 Latvia 3 Lithuania 3 Luxembourg 3 Malta 3 Netherlands 3 Poland 3 Portugal 3 Romania 3 Slovakia 3 Slovenia 3 Spain 3 Sweden 3 Nigeria 2 Zimbabwe 2 Democratic Republic of the Congo 1 Indonesia 1 Kenya 1 Russian Federation 1 South Africa 1 Viet Nam 1 ZAMBIA Country-Specific Data 231

Table 7.195. Frequency with which Zambia’s state measures have almost certainly harmed* foreign commercial interests Jurisdictions affected Number of measures British Virgin Islands 1 France 1 India 1 Mozambique 1 Portugal 1 South Africa 1 United Arab Emirates 1 United Kingdom of Great Britain and Northern Ireland 1 United Republic of Tanzania 1 Zimbabwe 1

Table 7.196. Implemented measures that harm* Zambia’s commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 15 28.30% Export subsidy 14 26.42% Bail out / state aid measure 4 7.55% Non-tariff barrier (not otherwise specified) 4 7.55% Trade finance 4 7.55% Import ban 3 5.66% Competitive devaluation 2 3.77% Export taxes or restriction 2 3.77% Import subsidy 2 3.77% Migration measure 1 1.89% Other service sector measure 1 1.89% Public procurement 1 1.89% Total 53 100.00%

Table 7.197. Zambia’s implemented measures that harm* foreign commercial interests, by type Number of As percentage of Type of measure measures measures Tariff measure 3 60.00% Export taxes or restriction 1 20.00%

Investment measure 1 20.00% ZAMBIA Total 5 100.00% Beggar-Thy-Poor-Neighbour: Crisis-Era Protectionism and Developing Countries The most vulnerable trading nations on Earth – the Least Developed Countries and countries from sub-Saharan Africa – have long been Beggar-Thy-Poor-Neighbour: encouraged by Western donors, international development organisations, and economists to integrate their economies into world markets. This volume examines the extent to which such integration was frustrated by Crisis-Era Protectionism and protectionist measures taking since the onset of the Great Recession. Drawing upon the data compiled by Global Trade Alert, an independent Developing Countries protectionist monitoring service, the policy stance towards Least Developed Countries and sub-Saharan African nations – both beggar-thy-neighbour and liberalising – are characterised and their effects analysed by experts knowledgeable about both of these groups of developing countries. The 15th GTA Report Implications for policymaking at the national and international level, including at the G20, are explored. Edited by Simon J. Evenett

GLOB L Centre for Economic Policy Research TR DE 77 BASTWICK STREET • LONDON EC1V 3PZ • UK a a TEL: +44 (0)20 7183 8801 • FAX: +44 (0)20 7183 8820 • EMAIL: [email protected] LERT www.cepr.org CEPR Press CEPR Press