1
Chinese Official Finance and Africa’s Pariah States
Roudabeh Kishi†
Clionadh Raleigh†
† Department of Geography, University of Sussex
(Rough draft. Please do not cite without permission.)
Abstract: Chinese official finance to Africa has been increasing. China’s ‘official finance’ encapsulates all aid, debt forgiveness, export credits, grants and technical assistance, etc. It is intentionally distinct from other ‘traditional’ (Western) donors due to its ‘non-interference policy’ –
China claims to avoid imposing political views, ideals, or principles onto recipient countries, meaning it does not require any specific governance conditions on the part of recipients in order to receive official finance. This results in a complete lack of accountability mechanisms associated with
China’s current official finance; this ‘unconditional’ assistance is more fungible, and has left local communities at an increased risk. As a result of such policies, Chinese finance has inadvertently supported an increase in state-based violence, repression, civilian targeting, and expansiveness. Such increases do not follow official finance by ‘traditional’, often Western, donors. These effects are similar across multiple regime types, states with and without primary resources, and histories of conflict. Hence, though China isn’t specifically giving official finance to ‘pariah states’, it contributes to transforming states into pariahs through providing resources to state leaders who are unafraid to use repression as a means to quell competition. Using newly available data mapping Chinese official finance in Africa (Strange et al. forthcoming) and state violence data from the public, real-time
Armed Conflict Location and Event Data (ACLED) Project, variations in state violence mechanisms are assessed. 2
As one of the continent’s largest commercial partners, China exerts a great impact on African economies. China is increasing its economic expansion into Sub-Saharan Africa (Adisu, Sharkey, and
Okoroafo 2010; Kaplinsky, McCormick, and Morris 2007), and has become a significant provider of official finance across African states.1 Aggregated Chinese official finance to Africa since 2000 – including all aid, debt forgiveness, export credits, grants and technical assistance, etc. – account for, on average, 10% of overall amounts of official finance. Consequentially, China’s influence on
African governments continues to grow.
A persistent question amongst donors, academics, and policy communities is whether the effects of
Chinese economic assistance will result in ‘good governance’? Specifically, will recipient states use this finance in ways that increase stability and human rights adherence in Africa? If not, what types of violence may increase, in what contexts, and for what reasons? The analysis and data presented here find that Chinese official finance does increase the likelihood of African state repression upon its citizens and competitors. This is not the intent of China or Chinese assistance; African regimes use fungible and unaccountable funding streams to bolster their authority and capacity, and increased levels of repression follow from those regime priorities.
Public perceptions – and misperceptions – about Chinese official finance continue to ‘delegitimize’ this form of economic assistance. China is often accused of providing ‘rogue aid’ by supporting
African regimes with significant human rights abuse records (Naim 2009). Many claim its motives are resource extraction or favorable international ties and access (for example, see Foster,
Butterfield, Chen, and Pushak 2008). Others suggest that by cultivating closer ties with states accused of poor human rights records, China intends to bolster its league of international defenders
1 In this study, ‘official finance’ refers to all ODA-like, OOF-like, and vague official finance (i.e. ODA-like or OOF-like activities that cannot be specifically assigned to either category). This is “regardless of its developmental, commercial, or 3 through ‘buying’ support and sympathizers (see Samy 2010). China’s relationship with other donor states is also marred by negative allegations regarding its own domestic policy.
Scenes of African leaders courting China while being condemned by the West further upset traditional donors (e.g. Zimbabwean President Mugabe’s visit to Beijing;2 Kenyan President
Kenyatta’s warm reception in 2014) who contend that the longer-term benefits from conditions that have been cultivated by traditional donors for the receipt of official finance are diminished (for example, see McGreal 2007). But Chinese official finance is not directed towards pariah states, and human rights records have no bearing on its choices (Brautigam 2009; Dreher and Fuchs 2011).
China sends official finance to many different institutional contexts: Ghana and Kenya receive large shares, as do Sudan and Zimbabwe. Indeed across Africa, only Burkina Faso, Swaziland and the
Gambia3 did not receive Chinese official finance from 2000-2013, owing to their stance in support of Taiwan.
Yet, there are significant differences between Chinese and more ‘traditional’ official finance from the
West. ‘Western’ official finance includes recipient conditions for disbursement including governance reform, democratization, human rights adherence, transparency, and anti-corruption measures.
There are accountability provisions and regulations surrounding the fungibility of assistance built into traditional official finance distribution; and disbursement is often based on need. Chinese donors have varied agendas that do not conform to mandates around present and future institutional change (Dreher and Fuchs 2011). These agendas include accessing resources, creating new markets, and building international coalitions through creating closer ties with non-Western
2 Upon his return from China, President Mugabe reportedly explained that he preferred Chinese official finance as China does not insist that he ‘support homosexuality’ in order to access it (Thornycroft 2014). 3 As of 2013, however, the Gambia has severed diplomatic ties with Taiwan (Al Jazeera 2013). 4 states, such as those in Africa (Tull 2006; Adisu et al. 2010). China insists that relationships with
African states are forged for mutual benefit, and it emphatically does not seek to influence the domestic politics of recipient states (Guimei 2010). Chinese official finance is characterized by overt regime support, where large and growing proportions of official finance come without conditionality. This principle is ‘non-interference’.
What role international donors should play in fostering or supporting institutional change is an ongoing debate. Even amongst ‘traditional’ donors, various countries and regimes engaged in undemocratic practices are supported: many donors – e.g. Scandinavian states – spend significantly more in ‘good’ country cases in order to promote ongoing institutional change, yet there are indeed examples of assistance from Western donors going to countries with military dictatorships or rampant corruption.4 However, accepting conditions for necessary change, and evidence of successful change, is often the minimum entry standard to access official finance from traditional donors. Yet these changes often constitute a raised and inaccessible bar for African states, and
African leaders have often complained of the strict conditions and ‘interference’ found with Western official finance. As a result, the lack of ulterior motives found in China’s distribution (Halakhe 2014) is attractive. Due to the lack of obvious conditionality as well as accountability, African leaders can use Chinese official finance in the ways they see fit and suited to their political, economic, and social needs.
States may use repression as a tactic to enforce their hold on power and to reaffirm their authority.
The use of repression tactics helps regimes to remain in power (Escriba-Folch 2013); intimidating,
4 Despite routine torture, official murder, and arbitrary arrests (Dellios 1997), Mobutu of Zaire benefitted from much military and economic assistance from various supporters during his tenure (Snyder 1992), largely from the US (Lamb 1987); much of this was embezzled, amassing Mobutu a fortune of billions of dollars (Fantaye 2004). 5 targeting, and/or killing potential opposition is effective in quelling threats from organized groups
(Hafner-Burton, Hyde, and Jablonski 2010). These tactics are common across many regimes. While repression may be seen more readily under autocratic regimes, there are differences in the level of repression seen within autocracies (Davenport 2007a), and across democracies (Davenport 2007b).
African regimes often use repression to eradicate competition and subordinate civilian reform and revolt in order to ensure their survival (see Clapham 1996); how different income flows facilitate a regime to bolster its authority, capacity, and ability to repress to remain in power is under-addressed.
Access to resources with ‘no strings attached’ means that regimes can choose to use these resources toward entrenching, defending, and expanding their powers.
An ongoing debate within conflict studies suggests that traditional official finance encourages insurgent or anti-state violence through supporting the economic ‘prize’ for state capture (for example, see: Grossman 1992; Arcand and Chauvet 2001). Few studies consider the effects of official finance on a state’s likelihood to use repression, or varied armed competition against regimes.
This articles tests the effects of Chinese official finance on subsequent conflict rates within states, and whether domestic political violence rates by governments are affected by official finance. The findings are that states in receipt of higher rates of unconditional, Chinese official finance actively engage in more violence against their citizens relative to states with more conditional, ‘traditional’ official finance profiles (see Figure 1). Political violence is employed by states willing to engage in repressive action against competitors and civilians, in order to secure continued dominance.
This article proceeds as follows: we begin by reviewing the relationship between official finance and violence, and the accountability and fungibility mechanisms through which increased political violence is related to official finance and changes in these amounts. The similarities and differences Figure 1. Chinese Official Finance vs. Traditional Official Finance and State Conflict Events in Africa.
7 between Chinese and traditional official finance to African states are evident through their domestic purposes. By comparing the rates of political violence – and distinguishing between violence by the state, by non-state actors, and violence against civilians from 2001-2014 – this study illuminates the possibilities and pitfalls of official finance policies in patronage states and the different agenda of domestic and international political communities.5
Compared to traditional official finance, Chinese official finance is more closely associated with increased state violence against civilians and competitors (see Figure 1). But these observed effects of political violence should hold for any unconditional and unaccountable official finance, regardless of the donor. This deviates from other debates, which contend that official finance impacts violence through its effect on insurgence against the state through rent capture, rather than violence by the state (for example, see: Grossman 1992; Arcand and Chauvet 2001).
Linking Official Finance and Political Violence
Studies find that high levels of official finance in recipient states increase the occurrence of civil war through its allocative and distributive effects (Grossman 1992). Conflict is found in areas with high fungible finance6 distribution; for example, civil wars in Sierra Leone, Angola, and Mozambique occurred in peripheral areas where distribution-related grievances were highest (Findley, Powell,
Strandow, and Tanner 2011). Further case studies suggest that the Rwandan genocide (Uvin 1998) and the Kenyan 2007-2008 election violence (Wrong 2010) were ‘fueled’ by international official finance. Yet, other research suggests that official finance reduces the duration of active civil conflicts
5 This analysis is facilitated by new information on Chinese official finance in Africa provided by AidData (Strange, Dreher, Fuchs, Parks, and Tierney forthcoming). 6 ‘Fungible’ official finance refers to amounts that are not allocated directly to programs. The definition used by Findley et al. states that these flows relate to “money originally intended for development purposes but that can easily diverted to other purposes” (2011:1998). In other parlance, these are ‘state rents’. 8 and exerts no effect on civil war onset rates (De Ree and Nillesen 2009), and that following economic shocks, official finance is central to mitigating violence risk (Savun and Tirone 2011).
Particular forms of official finance may affect conflict rates more than others: for example, food aid may increase the rate of civil conflict incidences, onset and duration (Nunn and Qian 2014), though when accounting for political contexts, this relationship is not evident (Huth and Backer 2014).
The debate surrounding the utility and unintended consequences of official finance has employed several mechanisms to explain the effect of this finance on fueling conflict. ‘Rent capture’ studies suggest that official finance in Africa from traditional (i.e. Western) donors affects the onset or duration of civil war specifically through the attraction of the state to rebel competitors (Collier and
Hoeffler 2002). Official finance functions as ‘state rent’, and ‘fungible’ finance can be reallocated based on the needs of the regime (for example, see Findley et al. 2011). The hoarding of this official finance benefits select areas and communities, and can be used to support regimes’ patronage networks (for example, see Mwenda and Tangri 2005).
But traditional explanations linking official finance and violence do not account for all violent agents within an environment. It is equally plausible that official finance increases the capacity of the state to repress both competitors and civilian populations who may oppose the regime. These effects of official finance may be found in and outside of civil war periods. This increase in capacity and ability to repress should be especially evident when states can determine how this finance is spent or when official finance programs are designed to support the state (e.g. ‘statebuilding’, ‘institution building support’, or for public goods distribution). These policies may directly impact the ability of a regime to control territory and manage internal violence effectively, while bolstering the dominance of the 9 central regime. The proposed linkages between the distribution of official finance and conflict are hence partially explained by how the finance is used, and by whom.
Through the mechanisms of accountability and fungibility associated with conditions imposed by differing donors, official finance may influence the extent to, and ease with which, the state is able to determine the distribution of official finance and secure its regime. Both the role of state violence more generally in response to this finance, as well as the varying effect of official finance from different donors, is yet to be interrogated in this literature.
Fungibility and Accountability of Official Finance
The international community often enforces constraints on governments to whom they give funds.
One clear example is how Western donors began to enforce democratic reforms during and after the
Cold War period; this ‘condition’ was largely regarded as effective in cultivating institutional reform
(Goldsmith 2001; Dunning 2004). Despite the focus on how bilateral official finance ‘forced’ or
‘encouraged’ democratic reforms, research suggests that official finance conditions and restrictions are largely ineffective in contributing to meaningful political reforms in recipient countries, due to the weakness of imposed conditional measures rather than by the strength of the recipient governments (Crawford 1997; Brown 2005, 2011; Van Cranenburgh 2011).
In response to the official finance quagmire, evidence of ‘good governance’ has become a precondition – rather than a goal – for particular Western official finance packages, especially those emanating from the International Monetary Fund, the World Bank, and the United States (Nanda
2006). While there are few agreed upon indicators of ‘good governance’, the evidence of poor 10 governance is well documented: De Maria (2008) reports that corruption costs African economies more that US 148 billion dollars a year.
To improve the impact and defend the purpose of official development finance, accountability mechanisms have become central to the relationships between donors, recipient states, and communities. Accountability is “a moral or institutional relation in which one agent (or group of agents) is accorded entitlements to question, direct, sanction or constrain the actions of another – particularly where these actions involve the exercise of public power or authority within a governance system” (Macdonald 2014:428). They have largely emerged from a growing development and civil society community who demand that official finance and its recipients be accountable for its use, employ finance to improve the lives of citizens, and display transparent and defendable practices.
The accountability mechanism has both up and down scales: in terms of bilateral official finance relationships, it concerns whether the receiving regime is accountable to both funders/donors (up) and proposed beneficiaries/citizens (down). Accountability to funders/donors means being able to fulfill a policy, to deliver a specific public good, etc.; accountability to beneficiaries/citizens ensures that affected communities and populations are not (further) harmed as a result of new funding initiatives. In response to both international and domestic requests, development-financing institutions acknowledge the need to explain and report on their actions to a variety of internal and external ‘stakeholders’, and increase the transparency, communication stakeholders, and ‘adherence to internal policies’ (Macdonald and Miller-Dawkins 2015a: 429). Accountability mechanisms are more prevalent in multilateral and bilateral development banks and export credit agencies; for bilateral development finance, accountability practices answer to their own domestic political 11 constituencies and to recipient governments. These processes place less emphasis on citizens
(Macdonald and Miller-Dawkins 2015a: 431).
Accountability targets have several benefits: Balaton-Chrimes and Haines (2015) note that communities affected by development initiatives can negotiate concessions, and that these more limited ‘internal’ accountability mechanisms are used to challenge how projects continue,
(Macdonald and Miller-Dawkins 2015a). But the influence of internal accountability is more limited
(Park 2015), as is the potential to redress harm as a result of large projects. Further, corruption – such as embezzlement of funds, and the use of state funds for purposes others than they are intended – is expected to be rampant in the absence of accountability. Fiscal corruption is indeed high where the fungibility of official finance is high and accountability is low (see Kolstad, Fritz, and
O’Neil 2008).
The main difference between conditional and unconditional official finance is the lack of accountability associated with the latter. New donors from emerging, non-Development Assistance
Committee (DAC) donors – e.g. the BRICs (Brazil, Russia, India, China) – “de-prioritize accountability principles focused on the rights of affected citizens, in favour of state-centric principles of noninterference and mutual benefit” (Macdonald and Miller-Dawkins 2015a: 431; see also: Dreher, Nunnenkamp, and Thiele 2011; Kragelund 2011; Zimmermann and Smith 2011;
Quadir 2013; Tilak 2014).
Across African states, the symbolic or economic burden of donor conditions or preconditions for accessing official finance are stated reasons why Chinese official finance is positively regarded
(Economy and Monaghan 2006). In contrast to traditional donors, China practices a clear ‘non- 12 interference’ policy with regard to its official finance by not requiring any specific governance conditions in order to receive official finance.7 China’s recent history with Africa suggests that the relationship stems from a ‘South-South’ movement (Adisu et al. 2010:3) where China’s support of
African independence displayed its opposition to colonialism (Taylor 1998; Qiang 2007; Davies,
Edinger, Tay, and Naidu 2008; Samy 2010). Yet, China’s domestic development strategy also plays an important role in shaping policy towards Africa (Zweig and Jianhai 2005; Adisu et al. 2010).
China has now entered a ‘pragmatic’ period focused on domestic market-orientated reforms, and its official finance to Africa increased in line with ‘buying’ the support of international sympathizers
(Samy 2010). During this period, support from the Chinese government allowed Chinese construction, mining, and oil extraction companies to move into African countries (Broadman 2007;
Mohan and Kale 2007; Adisu et al. 2010). With the establishment of the Forum on China-Africa
Cooperation (FOCAC), China’s finance behavior expanded beyond project-based finance (Samy
2010).
Chinese official finance is therefore intentionally distinct from traditional donors in multiple ways.
While the ‘Washington consensus’ may be seen as “a neo-liberal paradigm that takes into consideration democracy, good governance, and poverty reduction” (Adisu et al. 2010:4; Fine and
Jomo 2005; Sautman and Hairong 2007), the ‘Beijing consensus’ “values the political and international relations concept of multilateralism, consensus and peaceful co-existence” (Adisu et al.
2010:4; Wenping 2007). Chinese emphasis on ‘South-South’ relations includes a ‘respect for sovereignty’, which is practiced as ‘non-interference’: “China is not imposing its political views,
7 Along with China, Brazil too emphasizes “principles of non-interference in partner countries’ domestic affairs” (Macdonald and Miller-Dawkins 2015a:431-2; see also: Cabral and Leite 2015). However, “[Brazil’s] development cooperation is increasingly vulnerable to scrutiny and pressure from civil society, media and other domestic actors, generating pressures for citizen-centred accountability reforms that exceed those in most other non-DAC and some DAC donor countries,” such as China (Macdonald and Miller-Dawkins 2015a:431-2; see also: Cabral and Leite 2015). 13 ideals nor principles onto recipient countries” (Davies et al. 2008:57). While Western donors tend to develop country-specific strategies, China’s official finance programs are based on high-level discussions, which has the effect of feeding ‘prestige’ products and/or patronage flows, since it is not tied to specific outcomes to the degree other donors’ are (Brautigam 2011). Examples of such a policy in action include the Chinese government’s silence on the role of the Sudanese government in
Darfur, especially when indicating, “it was not interested in issues beyond its own economic interests” (Samy 2010:85).
Commonalities do exist between the ‘Beijing’ and ‘Washington’ consensuses. Official finance is delivered in similar ways – including project support, technical assistance, food aid, debt relief, humanitarian assistance – and Chinese principles emphasize ownership, alignment with country priorities, and results, similar to the 2005 Paris Declaration on Aid Effectiveness (Brautigam 2011:9).
All donors give official finance for a variety of reasons, not least important of which are political and strategic incentives (see Alesina and Dollar 2000; Berthelemy and Tichit 2004). Understanding donor intent in official finance is important, especially when ultimately interested in notions of aid efficacy. In comparison to other international donors, Chinese economic and commercial considerations are priorities (Dreher and Fuchs 2011). China’s need for natural resources to sustain economic growth and interest in accessing resources (e.g. oil, bauxite), is complemented by the desire to develop new markets through trade and investment (Zafar 2007; Adisu et al. 2010; Samy
2010), engage in symbolic diplomacy and development, and forge strategic partnerships, in line with its ‘one China’ policy (Alden 2005; Adisu et al. 2010).
14
African leaders see Chinese official finance in a largely positive light, citing “a new approach to development and increased potential for meaningful South–South cooperation” (Samy 2010:75) and
“China as the ideal model for their countries and economies” (Adisu et al. 2010:7). This may be because the ‘Chinese model’ allows leaders to maintain a strong grip on political power (Brooks and
Shin 2006). For African states, Chinese official finance is an attractive source of funding because it allows – relative to ‘traditional’, conditional, unpredictable, volatile official finance – for continued growth on a sustainable basis (Samy 2010). In general, the ‘no strings attached’ model allows support of initiatives not attended to by the West, and limits reports, targets, and meetings that burden the overstretched capacities of many African states (Adisu et al. 2010:4; Sautman and Hairong 2007;
Brautigam 2011). Chinese official finance has brought significant and needed improvements including relatively high economic growth in Africa, debt cancellation, and needed infrastructure
(e.g. roads, bridges, dams). China has also built health and educational capacity through student exchanges in universities and training centers (Adisu et al. 2010).
However, African civil society has warned of a growing neo-colonial relationship (De Lorenzo 2007) and remains cautious and worried about “the possible negative repercussions on governance, the environment, human rights and overall economic development” (Samy 2010:75). There are a number of potential development drawbacks to Chinese official finance. Some have claimed that the
Chinese official finance model has negatively impacted local African trade, commerce and labor.
Increased competition has also been harmful to African enterprises and exports, both in internal markets for domestically oriented manufacturers as well as in external markets (Alden 2005; Adisu et al. 2010). Additionally, Chinese environmental and social standards have been cited as potentially problematic for Africa (Moss and Rose 2006). ‘Traditional’ donors have arguably been more sensitive to social and cultural differences as well as power relations in Africa; China often 15
“depend[s] on local governments to sort these things out,” which means they often are not resolved
(Brautigam 2009; 2011:10).
More fundamental are the possible effects on political violence. While China, and its official finance, is not intentionally fueling violence, many suggest that Chinese official finance policies have indirectly propped up dictatorships and tyranny, citing Sudan, Chad, and Zimbabwe as examples
(Askouri 2007; Samy 2010). This may be the result of unintended policies: Chinese official finance is easier to direct towards areas of a leader’s choosing, regardless of need (Dreher, Fuchs, Hodler,
Parks, Raschky, and Tierney 2014); traditional donor economic and political conditions are actively undermined by the unconditionality of Chinese official finance (Brautigam 2011); and a lack of conditionality has “emboldened the governments to limit their progress towards political and economic reform” (Adisu et al. 2010:5).
The Effects of Fungible Official Finance on Conflict
Is there a clear difference in government behavior when it receives Chinese official finance? China distributes money widely across both violent and non-violent states (see Figure 1). Yet, state violence in countries with significant Chinese official finance may be a function of the countries to which China gives assistance: some evidence suggests that China chooses ‘pariah cases’ as recipients, and those with significant resources (and hence higher likelihoods of autocratic or corrupt rule)
(Naim 2009). Resource dependent states have a higher than average rate of political violence due to economic corruption, inequality, poor governance and competition for state control (Collier and
Hoeffler 2005). Yet Dreher and Fuchs (2011) do not find that China’s pre-condition for finance is a history of ‘bad governance’ or resource dependence; indeed, there is no standard institutional form that China supports more than others (see Brautigam 2009). 16
A high level of conjecture regarding Chinese distribution practices also affects the discussion on violence: typical studies on the relationship between aid and conflict have focused on the appeal of
‘state rents’ to rebel regime challengers. The levels of state violence toward citizens and a variety of political challengers remain unaddressed, despite being a crucial component of governance practice and quality (De Waal 2015; Davenport 2007b).
Chinese official finance may disproportionately increase state violence in comparison to other official finance as governments can use these monies to funnel into their military and paramilitary forces to ‘assist’ in repression against competitors and civilians. African state military funding is determined by internal and external challenges as well as neighboring contexts (Dunne and Perlo-
Freeman 2003). Challenges to African leaders are often domestically based, and increasingly challengers are political elites within formal government as opposed to external rebel coalitions
(Raleigh 2014). In addition, riots, protests and civilian challenges are increasing within states, and regimes have often used violence to dispel popular uprisings (Branch and Mampilly 2015).
Despite Chinese finance being ‘ear-marked’ for specific areas, the lack of accountability means that funds can be funneled into other areas with relative ease. Often, no reliable public records are available to note where money has gone – both for traditional or Chinese official finance. The link between Chinese assistance and repression is in the outcomes: the avenues for increased violence are tested to differentiate between contexts where China may invest and assist more – such as those with resources for China’s consumption – and cases where the mechanism of non-conditionality allows for states to use official finance where they see fit. This is a key distinction: a resource wealthy state – such as Sudan – may receive Chinese official finance and engage in conflict on multiple 17 fronts. Yet, in order to isolate and establish a link between repression and Chinese assistance, increases in the amount of finance received should result in states becoming more pronounced in their use of repression and violence against opponents and civilians.
By testing this relationship at the state-level, how recipients choose to distribute finance in line with challenges and opportunities throughout its territory is clear. There is no presumption that China would direct the subnational distribution or concentration of finance in a specific way to increase violence; rather, official finance without conditions bolsters the capacity of states to increase violence against challengers and citizens.
This argument leads to the following hypotheses:
Hypothesis 1: Increases in Chinese official finance lead to an increase in all levels of armed
violence, relative to the effects of official finance from traditional donors.
Hypothesis 2A: Increases in Chinese official finance lead to an increase in state-involved
violence, relative to the effects of official finance from traditional donors.
Hypothesis 2B: Increases in Chinese official finance lead to an increase in state violence
against civilians, relative to the effects of official finance from traditional donors.
Hypothesis 2C: Increases in Chinese official finance lead to an increase in the
expansiveness of state violence, relative to the effects of official finance from traditional
donors.
18
Research Design
Chinese and traditional official finance are recorded by AidData. AidData’s ‘Chinese Official
Finance to Africa Dataset (2000-2013, Version 1.2)’ (Strange et al. forthcoming) represents a new frontier in aid and finance studies, and captures official finance flows – including Official
Development Assistance, or ODA-like flows; other official flows, or OOF-like flows; and “vague official finance” flows8 – based on origin, intent, and recipient.9,10 All three types are combined for annual ‘official finance’ flow totals to all African countries. Chinese official finance data are compared to traditional official finance using AidData’s ‘Research Release 2.1 (1997-2012)’ (Tierney et al. 2011). Data are aggregated by country-year for each state in Africa, resulting in 676 units for analysis, across 49 countries. Both official finance variables are logged11 to normalize and lagged to distinguish the direction of the effect.12
Information on armed, organized conflict events is from ACLED – the Armed Conflict Location and Event Data project (Raleigh, Linke, Hegre, and Karlsen 2010). ACLED collects information on a range of political violence, distinguished by event characteristics, type of group(s) participating,
8 Vague official finance refers to “loans and grants that are either ODA-like or OOF-like, but for which there is insufficient information to assign the flows to either the ODA-like or OOF-like category” (Strange et al. forthcoming:6). 9 As suggested by AidData, pledges or cancelled/suspended projects are removed from the aggregate amounts of Chinese official financing. 10 “Open-source data collection, while limited in knowable ways, can provide a stronger empirical foundation for research on development finance” (Muchapondwa, Nielson, Parks, Strange, and Tierney 2015). Muchapondwa et al. (2015) find support for this after ground-truthing in Uganda and South Africa to verify the accuracy between AidData’s Tracking Underreported Financial Flows (TUFF) methodology of leveraging open-source information surrounding Chinese official finance to Africa and reality. 11 To ensure that country-years not receiving official finance (variables equal to 0) are not dropped from analysis after logging (given that the log of zero is not defined), the official finance variables were first amended before logging. In line with Sherlund, Barrett, and Adesina (2002), in order to maintain the original order in the distribution, we first divided by ten the smallest observation in our sample for each official finance variable; this value was then substituted for all zero- values of the official finance variable, respectively, before logging. 12 Chinese official finance data are available for 2000-2013; given these data are lagged, analysis using these data are conducted for 2001-2014. Traditional official finance data are available as far back as the 1940s; the Research Release 2.1 is “a snapshot of the AidData's entire project-level database from February 2012.” Given our conflict data are available from 1997 to present (outlined in further detail below), and the official finance data are lagged, analysis using these traditional official finance data are conducted for 1998-2013 (allowing for conflict data from 1997 to be used as a lagged armed conflict value for 1998, and so forth). 19 with geolocation information and date.13 These data are available from 1997 into real-time.
Information from 1997-2014 is integrated into this analysis. The occurrence and frequency of violent events between organized, named armed groups (e.g. rebels, state forces, political militias, communal militias, external forces), and attacks by those groups on civilians, are extracted by country-year. The groups involved in each attack are distinguished, as is the number of discrete, unique locations in which attacks took place by country-year.14 In total, conflict variables include country-year occurrence counts of all violent events,15 state events in total, state battles against challengers, state actions against civilians, unique locations of state events, and rebel events in total.16
A lagged count of organized, armed events in total in each given state is included, as is a spatial lag variable measuring the number of organized, armed events occurring the previous year in all bordering African states.
Several actor types are included to distinguish the goals of challengers relative to that of the state.
The typical study of official finance and ‘rent capture’ in conflict concentrates on civil wars; rebel groups are isolated to consider the effects of Chinese official finance on groups with a goal of state capture.
13 Extensive information regarding ACLED’s sourcing, methodology, and practices can be found at www.acleddata.com/methodology. 14 Using the number of discrete conflict locations (cities/towns/villages) where conflict involving the state occurred during the year tests whether state forces extended their reach of violence over the study period. Locations are distinguished by name and latitude/longitude (with two degrees in detail). 15 This incudes battles, remote violence, and violence against civilians involving state forces, rebel groups, political militias, ethnic and communal militias, and external forces. 16 ACLED interaction codes are used to distinguish events based on actors involved. All battles, remote violence, and violence against civilians event types in a given country-year denote all ‘armed events’. For all violent ‘state events’, interactions codes 11, 12, 13, 14, 17 and 18 are aggregated. For all ‘state violence against civilians’, entries with interaction code 16 and 17 that have a ‘violence against civilians’ event type are used. For all violent ‘rebel events’, entries with interaction codes 12, 22, 23, 24, 27, and 28 are used. 20
To those data, information is joined for population counts (The World Bank 2015);17 regime type dummy variables measuring whether a state is a democracy (i.e. has an annual Polity score above or equal to 6) or an autocracy (i.e. has an annual Polity score below or equal to -6) (Marshall and
Jaggers 2002);18 natural resource rents (The World Bank 2015);19 political institutions and quality, as measured by “the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media"
(Kaufmann, Kraay, and Mastruzzi 2013).20 Population counts are logged to account for extreme values. See Table 1 for further information on variables.
An initial test for whether Chinese official finance disproportionately goes to specific states – such as those with high rate of natural resource rents or specific indicators of governance – is conducted.
A dummy variable was also created to account for states with a higher than average natural resource dependence (over 17%)21 (The World Bank 2015).22 Information on political institutions and quality using the ‘voice’ indicator are from the Worldwide Governance Indicators (Kaufmann et al. 2013).
These data are altered to range from 0-5 from its original state of -2.5 to +2.5. See Table 1 for further information on variables.
17 GDP data are highly correlated with population data (0.7), so both variables were not included in models. Population was included over GDP given that it did not result in the omission of Somalia, which is missing GDP data, resulting in a more complete African dataset. The World Bank Development Indicators (2015) only offer population data up to 2013; missing values for 2014 were filled in with country averages for analysis here. 18 Polity scores are only available up to 2013; missing values for 2014 were filled in with country averages for analysis here. Democracy and autocracy dummy variables were then created using this new filled Polity variable. 19 The World Bank Development Indicators (2015) only offer natural resource export data up to 2012, and are missing data for 1997 and 2002; missing values for 1997, 2002, 2013, and 2014 were filled in with country averages for analysis here. 20 The range of this variable was altered to 0-5, changed from its original state of -2.5 to +2.5. The World Governance Indicators (Kaufmann et al. 2013) only offer governance data up to 2012, and are missing data for 1997, 1999 and 2001; missing values for 1997, 1999, 2001, 2013, and 2014 were filled in with country averages for analysis here. 21 17% is the average level of resource dependence in Africa as categorized by the World Bank. 22 Another dummy variable was also created to measure natural resource dependence using what Collier and Hoeffler (2002) regard as excessively high levels of resource dependence (over 30% of a state’s GDP being comprised of natural resource exports) as a robustness check; results hold constant for both variables. Table 1. List of Variables and Details.
Variable Description Coverage Mean (SD) Range Source Total amount of Chinese official finance received by a AidData; Chinese Official 2000- $142,000,000 $0- state in a given year; includes ODA-like, OOF-like, and Strange et al. Finance 2013 ($501,000,000) $8,140,000,000 'vague' official finance forthcoming Chinese Official Total amount of Chinese official finance received by a AidData; 2000- Finance state in a given year (logged); includes ODA-like, OOF- 13.97 (4.59) 8.66-22.82 Strange et al. 2013 (normalized) like, and 'vague' official finance forthcoming AidData; Traditional Total amount of non-Chinese official finance received by 1960- $615,000,000 $3,980,000- Tierney et al. Official Finance a state in a given year 2012 ($809,000,000) $11,400,000,000 2011 Traditional AidData; Total amount of non-Chinese official finance received by 1960- Official Finance 19.58 (1.27) 15.20-23.16 Tierney et al. a state in a given year (logged) 2012 (normalized) 2011 No Democracy: 613 Polity Project; Dummy variable capturing states with a Polity score of 6 1997- Democracy Democracy: 255 0-1 Marshall and or higher 2013 (29%) Jagger 2002 Polity Project; Dummy variable capturing states with a Polity score of -6 1997- No Autocracy: 767 Autocracy 0-1 Marshall and or lower 2013 Autocracy: 101 (12%) Jagger 2002 1960- World Bank Population Total population of a state in a given year (logged) 16.04 (1.27) 13.06-18.97 2013 Indicators 1998- Natural resource rents (i.e., sum of oil, natural gas, coal World Bank Natural Resource 2001, [hard and soft], mineral, and forest rents) of a state in a 16.78% (18.06%) 0-100% Development Exports 2003- given year as a proportion of GDP Indicators 2012 1998- Not Resource Dummy variable capturing states with high levels of World Bank Natural Resource 2001, Dependent: 593 resource dependence (over 17% of a state's GDP being 0-1 Development Dependence 2003- Resource Dependent: comprised of natural resource rents) Indicators 2012 257 (30%) World "Captures perceptions of the extent to which a country's 1998, Political Governance citizens are able to participate in selecting their 2000, Institutions & 1.92 (0.66) 0.47-3.57 Indicators; government, as well as freedom of expression, freedom of 2002- Quality Kaufmann et association, and a free media" 2012 al. 2013 ACLED; Prior Armed Number of organized, armed conflict events that occurred 1997- 72 (184) 0-2791 Raleigh et al. Conflict in a given state in the previous year 2015 2010 Spatial lag variable capturing number of organized, armed ACLED; Prior Bordering 1997- conflict events that occurred in bordering states in the 331 (428) 0-4334 Raleigh et al. Conflict 2015 previous year 2010 ACLED; Armed Conflict Number of organized, armed conflict events that occurred 1997- 80 (212) 0-2791 Raleigh et al. Events in a given state in a given year 2015 2010 ACLED; State Conflict Number of organized, armed conflict events involving 1997- 37 (105) 0-1286 Raleigh et al. Events state forces that occurred in a given state in a given year 2015 2010 State Violence Number of instances of violence against civilians ACLED; 1997- Against perpetrated by state forces that occurred in a given state in 6 (15) 0-201 Raleigh et al. 2015 Civilians a given year 2010 Number of distinct conflict locations ACLED; State Conflict 1997- (cities/towns/villages) involving state forces that occurred 13 (27) 0-223 Raleigh et al. Locations 2015 in a given state in a given year 2010 Number of conflict battles involving rebel groups (i.e., ACLED; Rebel Conflict 1997- groups wanting to overthrow the state/regime) that 34 (101) 0-1285 Raleigh et al. Events 2015 occurred in a given state in a given year 2010 Number of Number of groups (rebel groups, political and communal ACLED; 1997- Armed Actors militias) involved in organized, armed conflict against state 2 (4) 0-30 Raleigh et al. 2015 Against the State forces that occurred in a given state in a given year 2010
22
All violence hypotheses are tested with negative binomial models with fixed effects, as advised by a
Hausmann test. Initial tests of whether Chinese official finance is disproportionately distributed to
‘pariah’ or resource dependent economies (i.e. whether these states receive a higher rate of Chinese official finance) use a Poisson model with the Huber/White/Sandwich linearized estimator of variance with fixed effects.23
Results ‘Pariah’ state characteristics do not drive Chinese or traditional allocation. Institutional quality has no bearing on Chinese finance allocation (see Table 2, Model 1), while a ‘good governance’ correlation exists between strong political institutions and the amount of official finance received from traditional donors (Model 2). There is no support for the presumption that either Chinese or traditional donors specifically target democracies or autocracies.
Counter to popular expectations, natural resource rents do not drive Chinese donors. A positive relationship exists between the level of natural resource exports and official finance received from traditional donors (Model 2), but not Chinese official finance (Model 1). For resource dependent states (i.e. states with higher than average natural resource rents), there is no support that either type of donor – Chinese (Model 3) or traditional (Model 4) – targets these states specifically.
The results of conflict frequency models confirm that there are clear differences in the correlations between traditional and Chinese official finance (i.e. finance with and without conditions) and conflict rates, specifically in increasing the rate of violent behavior by the state relative to rent
23 Rather than fitting an OLS regression on a logged official finance dependent variable, a Poisson model is fit here instead with the Huber/White/Sandwich linearized estimator of variance using the original finance variables – a preferred alternative to a log linear regression. See Gould (2011) for further clarification. 23 capture violence. Table 3 presents the negative binomial – count frequency – model results for the various measures of conflict and violence as shaped by official finance from various donors.
Table 2. Determinants of Whom Receives Official Finance.
(1) (2) (3) (4) Chinese Official Traditional Official Chinese Official Traditional Official VARIABLES Finance Finance Finance Finance
Natural Resource Exports 0.0327 0.0154** (as proportion of GDP) (0.0202) (0.00602) Natural Resource -0.141 0.0644 Dependence (0.227) (0.115) Political Institutions & 2.304 0.495*** 2.348 0.475** Quality (1.863) (0.189) (1.869) (0.188) -0.375 0.0134 -0.232 0.0207 Democracy (0.315) (0.162) (0.393) (0.152) 0.117 -0.00367 -0.201 -0.0461 Autocracy (0.478) (0.323) (0.481) (0.318) 5.648*** 2.852*** 5.346*** 3.041*** Population (1.211) (0.331) (1.403) (0.320)
Number of Observations 619 754 633 770 Number of Groups 45 48 46 49 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
In support of Hypothesis 1, official finance from Chinese donors leads to an increase in all levels of organized, armed violence. Model 1 in Table 3 reports a statistically significant and positive relationship between an increase in Chinese official finance and the number of organized, armed conflict events the following year. Model 2 does not find a similar effect when considering the effect of official finance from traditional donors. Models 3 through 8 explore Hypotheses 2A, 2B, and
2C, and confirm the conflict inducing relationship between levels of Chinese finance and increased conflict by the state. Chinese official finance does not influence the likelihood of non-state (rent- capture) events (Model 9), and official finance from traditional donors does not influence the 24 likelihood of state events (Models 4, 6, and 8). Model 3 confirms Hypothesis 2A: state leaders can use official finance without conditions to bolster the capacity of the central regime, and the number of armed conflict events involving the state rises in tandem with increased Chinese official finance.
Model 4 reports that state conflict events are not affected by official finance from traditional donors, suggesting that using official finance to strengthen the central regime is more difficult to do with conditional official finance.
State violence allows a central regime to reinforce its authority by repressing opposition, competitors, and civilians who may support competitors. Model 5 finds support for Hypothesis 2B
– an increase in Chinese official finance will lead to an increase in instances of violence against civilians by the state. Model 6 suggests that civilian targeting by the state does not increase with higher levels of traditional official finance.24 In support of Hypothesis 2C, Model 7 suggests that the state extends its violence to more places with an increase in Chinese official finance; a similar result is not seen in Model 8 regarding the effect of traditional official finance. The results point to a significant increase in the expansiveness of state violence when Chinese official finance is significantly large. These findings again suggest that the lack of conditions with Chinese official finance allows states to strengthen their regime through repressing opposition support.
The findings of Chinese official finance and state violence are more significant in light of the lack of influence Chinese official finance exerts on rebel violence. There is no statistically significant effect of Chinese official finance on the number of conflict events involving rebel groups (Model 9). There is, however, a statistically significant and positive effect of official finance from traditional donors on conflict involving rebel groups (Model 10). This latter finding is in line with rent capture arguments,
24 Botswana drops out of these models given the lack of any reported instances of state violence against civilians during the time period examined here. Table 3. Effect of Official Finance on Organized, Armed Conflict.
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) VARIABLES State Violence Against Armed Conflict Events State Conflict Events State Conflict Locations Rebel Conflict Events Civilians
0.0184** 0.0269*** 0.0203* 0.0248*** 0.00979 Chinese Official Finance (0.00882) (0.00988) (0.0115) (0.00938) (0.00848) Traditional Official 0.0710 0.0370 0.0466 0.0570 0.102** Finance (0.0461) (0.0503) (0.0592) (0.0483) (0.0454) 0.00241*** 0.00189*** 0.00241*** 0.00192*** 0.00172*** 0.00142*** 0.00202*** 0.00180*** 0.00128*** 0.00141*** Prior Armed Conflict (0.000203) (0.000174) (0.000230) (0.000195) (0.000295) (0.000245) (0.000219) (0.000182) (0.000258) (0.000215) 7.90e-05 0.000141 1.16e-05 0.000117 7.85e-05 0.000176 4.09e-05 0.000125 -0.000295*** -0.000326** Prior Bordering Conflict (7.58e-05) (0.000107) (8.41e-05) (0.000117) (8.96e-05) (0.000134) (7.76e-05) (0.000112) (0.000113) (0.000128) Political Institutions & 0.0872 -0.000625 -0.130 -0.116 -0.342** -0.242 -0.0640 -0.0783 -0.187 -0.268** Quality (0.122) (0.110) (0.135) (0.123) (0.165) (0.151) (0.140) (0.128) (0.126) (0.113) Natural Resource Exports -0.00596* -0.00765*** -0.00867** -0.00941*** -0.00343 0.00210 -0.00737* -0.00835*** -0.0103*** -0.0117*** (as proportion of GDP) (0.00318) (0.00270) (0.00353) (0.00300) (0.00452) (0.00401) (0.00395) (0.00313) (0.00339) (0.00291) -0.284** -0.353*** -0.203 -0.351** -0.124 -0.225 -0.328** -0.418*** -0.249* -0.231* Democracy (0.137) (0.126) (0.157) (0.147) (0.210) (0.191) (0.156) (0.147) (0.133) (0.124) -0.721*** -0.549*** -0.674*** -0.607*** -0.567*** -0.511*** -0.743*** -0.491*** -0.102 0.112 Autocracy (0.175) (0.143) (0.190) (0.157) (0.209) (0.175) (0.197) (0.159) (0.177) (0.142) 0.0308 0.109* 0.0720 0.140** 0.126* 0.120 0.00170 0.0609 0.170*** 0.142** Population (0.0577) (0.0634) (0.0615) (0.0668) (0.0728) (0.0832) (0.0727) (0.0747) (0.0599) (0.0628) -0.792 -3.137*** -1.434 -2.993*** -2.069* -2.887** 0.168 -1.653 -2.036** -3.429*** Constant (0.927) (0.893) (1.016) (0.998) (1.173) (1.186) (1.206) (1.128) (0.966) (0.942)
Number of Observations 661 754 661 754 647 738 661 754 661 754 Number of Groups 48 48 48 48 47 47 48 48 48 48 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
26 suggesting that increased conditional assistance in the hands of the state makes the state a more attractive prize for rebels (see: Grossman 1992; Arcand and Chauvet 2001).
In short, Chinese official finance increases the ability of the state to repress domestic competition, opposition and civilians. Compared to traditional official finance, the effect is limited to state forces and goals. Official finance from traditional donors can also impact conflict; this is seen specifically through rent capture channels – as the state becomes more attractive to rebels – rather than through an impact on state violence patterns.
Discussion
Chinese official finance impacts conflict in Africa, specifically by increasing the ability of the state to engage in violence. Statistically significant and positive effects of Chinese official finance on state conflict events translate into increased and more expansive state violence, including violence against civilians. This relationship is not evident when a state receives traditional official finance. Given the win-win relationship between the Chinese and African leaders, the Sino-African relationship is likely to endure.
Crucially, Chinese official finance should not and does not support violence generally: there is no statistically significant support for an effect of Chinese official finance on rebel behavior; civil war rates across Africa have declined during the same period when Chinese official finance has increased. New challenger forms are now far more common. Official finance from traditional donors, however, has had a statistically significant and positive effect on rebel violence in previous research. ‘Traditional’ official finance may have fuelled rebellion by making the ‘prize’ of state rents more attractive to insurgents. However, the effect of Chinese official finance is not through ‘state 27 capture’, but is rather through state use: Chinese official finance impacts state violence as a function of its unconditionality, which makes this finance highly fungible and results in minimal accountability to both donors and constituents. It is typically directed towards bolstering the central state, and regimes can use these resources to repress competition. This is arguably more difficult to do with ‘traditional’ and conditional official finance.
States that receive high and increasing levels of Chinese official finance may falter on a democratizing and human rights agenda. Developing and transitioning regimes often use violence, especially against civilians, to secure their authority. These increased actions throughout the state do not constitute large conflict operations, but widespread, persistent attacks, force and abuse on populations by the state. Regimes attack challengers, including members and leaders of opposing political parties; regimes engage in election fraud and voter repression, post-election violence, and suppressing protests and public gatherings. As many African states are dependent on external assistance and financing, that which is unaccountable is a ready source of ‘repression funds’.
Consider the case of Ethiopia: this state has been criticized for human rights abuses and the forced migration of people living in the Eastern area where it intends on developing large infrastructure for solar, wind and water energy projects which will position it as a major power producer (Human
Rights Watch 2012). Official finance from traditional donors often involves specific conditions on the movement of communities and environmental/social assessments before assistance is forthcoming. Chinese official finance does not require that the state report or engage in these activities. As a result, a higher rate of violence against civilians may be reported in areas where the
Ethiopian state has directed its Chinese official finance over traditional official finance, even if the official finance was not earmarked for this purpose originally. 28
Another example is Zimbabwe, which has long upset traditional donors. President Mugabe and his support base in the ZANU-PF political party have long been accused of human rights abuses against opposition supporters (Amnesty International USA 2015), and have engaged in a corrupt land transfer program (Smith 2013). In response, Mugabe lambasts Western governments, while he seeks support from alternative donors like the Chinese to build its surveillance capacity (Gagliardone and
Geall 2014).
Finally, consider Uganda: when faced with a revolt of traditional donors over scandals relating to the use of official finance and legalization outlawing homosexuality (Plaut 2014; Al Jazeera 2014),
Uganda began to focus more on encouraging Chinese official finance (Richards 2014).25
These cases illustrate two critical components of our argument: China supports many forms of
African regimes, and their direct and indirect effects on political violence vary depending on country specific circumstances. Only rarely do we observe an increase in more organized forms of conflict – such as rebel events – in line with Chinese support. Far more often, it is smaller and dispersed events that underscore the need to the state to assert authority and control. States have fewer constraints in engaging in these acts when Chinese (unconditional) official finance is forthcoming, over traditional (conditional) official finance.
These effects are not a function of specific characteristics of recipient states that may make them more prone to violence: both the political institutions and economic characteristics of states are considered as possible alternative explanations or biased cases. China’s agenda of non-interference
25 Many traditional donors have suggested that bilateral aid will be diverted to NGOs in the wake of the anti-gay legislation (see Richards 2014). 29 and unconditionality is confirmed given that Chinese official finance targets are not preconditioned by the recipient state. This agenda is much more amenable to African leaders who seek to remain in power, especially through repressing competition. The increased appeal of China over ‘traditional’ donors by African leaders is symbolic of this growing trend and influence of China in the region.
Though China isn’t specifically giving official finance to ‘pariah states’, it is making states into pariahs through providing resources to state leaders who are not afraid to use repression as a means to quell competition.
While current accountability mechanisms still leave much to be done in terms of preventing harm from ‘development activities’ in affected communities in the first place, the complete lack of accountability mechanisms associated with China’s current official finance has left local communities at an increased risk. The lack of oversight and accountability is dangerous to the larger public when confronted with regime power retention priorities. China itself is increasingly concerned with its official finance; in response to a call by Chinese observers and scholars to reform its foreign aid policies and systems, the Ministry of Commerce (MOFCOM) has initiated a campaign to reassess the intent of its official finance, structure, and oversight (Sun 2015). Wanting to avoid negative publicity, China is considering weakening its non-interference policy. If it undertakes such a change, it would start far more monitoring and evaluation. In line with its own financial concerns, China and its citizens may believe that the best bet for future relationships is to help foster stable regimes that have fewer incentives and reasons to use excessive patronage and repression as a tactic to stay in power.
30
Appendix
Multiple robustness tests are performed to reinforce the strength of the reported results; references to these tests can be found in footnotes throughout the paper.
Alternative Conflict Data
Robustness tests using UCDP-GED data (Sundberg and Mellander 2013) for African states from
2000-2011 are aggregated and tested to determine if alternatively coded conflict information displays similar patterns. ACLED and UCDP-GED differ in significant ways, including what types of conflict are covered, the coverage period, the event unit, and the definition of what constitutes an event. This information for ACLED is reviewed here: www.acleddata.com/methodology. When considering events perpetrated by armed and organized groups, the values still differ (see Appendix
Figure 1 for a comparison using a subset of years). Additional details regarding the differences between the two datasets are available at: http://www.acleddata.com/wp- content/uploads/2012/08/Dataset-Typology-Overview.pdf.
A significant difference between the datasets is the coding of political violence outside of defined
‘civil war’ periods. There are fewer records for states not in an active civil war in the UCDP-GED set. For example, there is less coverage of state violence in Kenya and Zimbabwe, or attacks in
Nigeria, Sudan and Ethiopia, under UCDP-GED coding rules.
In addition, ACLED codes events ‘atomically’ meaning that an event (ACLED has 9 types of events) occurs on a specific day in a specific location involving specific actors. If a battle extends for more than one day, each day the battle is reported to have occurred is coded separately. Hence, each event has a source that notes the day(s) of an event. UCDP-GED has a number of ‘campaign’ and Appendix Figure 1. Comparison of Organized, Armed Conflict Event Numbers and Locations Using UCDP-GED vs. ACLED.
32
‘summary’ events for which a single battle may occur for any number of days (from the beginning to the end point), but it cannot be assumed that the same battle occurred on each day. In fact, UCDP-
GED notes that for these types of events there is no exact disaggregated information available; “in other words, it is unclear how many battles took place during the time period specified” (Sundberg,
Lindgrem, and Padskocimaite 2010:6). If these campaigns (i.e. conflict events coded for months or more) are artificially disaggregated to mirror ACLED’s atomic modeling, the result is hundreds of assumed events occurring.
The initial point regarding coding in and outside of ‘civil wars’ is evident in the results table below.
Appendix Table 1 shows the differences in findings surrounding Chinese official finance when observations are distinguished by civil war. Due to poor coverage of violent incidences by UCDP-
GED outside of civil war periods, only country-years during civil war periods return positive and significant influences of Chinese official finance on state violence against civilians. UCDP-GED mainly records rebel agents, despite a significantly high number of non-state, non-rebels active within and outside of civil war periods.
Appendix Table 1. Effect of Chinese Official Finance on State Violence against Civilians: Comparison Models Using UCDP-GED Data.
(1) (2) (3) VARIABLES State Violence against Civilians State Violence against Civilians State Violence against Civilians No Civil War Civil War No Civil War Civil War No Civil War Civil War
0.0724 0.0826*** 0.0765 0.0776** 0.0668) 0.0813** Chinese Official Finance (0.0482) (0.0313) (0.0491) (0.0325) (0.0467) (0.0320) 0.7318* -0.412** 1.5776** -0.221 1.0236* -0.194 Population (0.3772) (0.181) (0.5388) (0.196) (0.5329) (0.194) Prior Armed Conflict 0.0086 0.00341*** 0.0092 0.00147 0.0084 0.00112 (UCDP) (0.0127) (0.00105) (0.0142) (0.00139) (0.0139) (0.00131) Total Number of Civil Wars -0.0034 -0.00178 in Bordering States (UCDP) (0.0033) (0.00113) Total Conflict in Bordering 0.0032 -0.000891 States (UCDP) (0.0020) (0.000861) Civil War in Bordering 1.4276** omitted States Dummy (UCDP) (0.6613) Political Institutions & -0.3051 0.400 -0.6986 0.228 -0.8178 0.326 Quality (0.7894) (0.457) (0.7634) (0.507) (0.8001) (0.500) Natural Resource Exports 0.0330* 0.0173 0.0118 0.0186* 0.0160 0.0184* (as proportion of GDP) (0.0182) (0.0116) (0.0169) (0.0103) (0.0170) (0.0104) -1.0431 -0.819 -1.4455 -1.125** -1.3026 -1.158** Democracy (1.0089) (0.503) (0.9535) (0.571) (0.9309) (0.574) -13.5713 1.289** -13.9648 0.778* -13.4839 0.856* Autocracy (1167.978) (0.518) (994.4548) (0.463) (781.0167) (0.484) -15.4014*** 3.707 -28.3748*** 1.690 -19.2707** 0.718 Constant (5.9725) (3.050) (8.5360) (3.414) (8.3280) (3.301)
Number of Observations 172 143 122 110 122 110 Number of Groups 17 16 16 16 16 16 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
34
References
Adisu, Kinfu, Thomas Sharkey, and Sam C. Okoroafo. (2010) The Impact of Chinese Investment in
Africa. International Journal of Business and Management 5(9):3-9.
Al Jazeera. (2013). Gambia Severs Diplomatic Ties with Taiwan. Al Jazeera, November 13. <
http://www.aljazeera.com/news/africa/2013/11/gambia-breaks-off-diplomatic-ties-with-
taiwan-2013111422285906417.html>.
-----. (2014). US Cuts Aid to Uganda over Anti-Gay Law. Al Jazeera, 20 June. <
http://www.aljazeera.com/news/africa/2014/06/us-cuts-aid-uganda-over-anti-gay-law-
201462052127734317.html>.
Alden, Chris. (2005) China and Africa. Survival 47(3):147-64.
Alesina, Alberto, and David Dollar. (2000) Who Gives Foreign Aid to Whom and Why? Journal of
Economic Growth 5(1):33-63.
Amnesty International USA. (2015). Zimbabwe Human Rights. < http://www.amnestyusa.org/our-
work/countries/africa/zimbabwe>.
Arcand, Jean-Louis and Lisa Chauvet. (2001) Foreign Aid, Rent-Seeking Behavior, and Civil War.
Unpublished manuscript.
Askouri, Ali. (2007) China’s Investment in Sudan: Displacing Villages and Destroying Communities.
In African Perspectives of China in Africa, ed. Firoze Manji and Stephen Marks, 71-86. Nairobi
and Oxford: Fahamu.
Balaton-Chrimes, Samantha and Fiona Haines. (2015) ‘The depoliticisation of accountability
processes for land-based grievances, and the IFC CAO’, Global Policy, 6(4), pp. 446–454.
Berthelemy, Jean-Claude and Ariane Tichit. (2004) Bilateral Donors Aid Allocation Decisions: A
Three Dimensional Panel Analysis. International Review of Economics and Finance 13(3):253–74. 35
Branch, Adam and Zachariah Mampilly. (2015). Africa Uprising: Popular Protests and Political Change.
London: Zed Books.
Brautigam, Deborah. (2009) The Dragon’s Gift: The Real Story of China in Africa. Oxford: Oxford
University Press.
-----. (2011) Aid ‘With Chinese Characteristics’: Chinese Foreign Aid and Development Finance
Meet the OECD-DAC Aid Regime. Journal of International Development 23(5):752-64.
Broadman, Harry G. (2007) Africa’s Silk Road: China and India’s new economics frontier. Washington, DC:
World Bank.
Brookes, Peter, and Ji Hye Shin. (2006) China’s Influence in Africa: Implications for the United
States. Heritage Foundation Backgrounder (1916).
Brown, Stephen. (2005). Foreign Aid and Democracy Promotion: Lessons from Africa. The European
Journal of Development Research 17(2):179-98.
-----. (2011). ‘Well, What Can You Expect?’: Donor Officials’ Apologetics for Hybrid Regimes in
Africa. Democratization 18(2):512-34.
Clapham, Christopher. (1996) Africa and the International System. Cambridge, UK: Cambridge
University Press.
Collier, Paul, and Anke Hoeffler. (2002) Aid, Policy, and Peace: Reducing the Risks of Civil Conflict.
Defence and Peace Economics 13(6):435-50.
-----. (2005). Resource Rents, Governance, and Conflict. Journal of Conflict Resolution 49(4):625-33.
Crawford, Gordon. (1997) Foreign Aid and Political Conditionality: Issues of Effectiveness and
Consistency. Democratization 4(3):69–108.
Davenport, Christian. (2007a). State Repression and the Tyrannical Peace. Journal of Conflict Resolution,
44(4): 485-504. 36
-----. (2007b). State Repression and the Domestic Democratic Peace. New York: Cambridge University Press.
Davies, Martyn, Hannah Edinger, Nastasya Tay, and Sanushy Naidu. (2008) How China Delivers
Development Assistance to Africa. Stellenbosch: Centre for Chinese Studies, University of
Stellenbosch.
De Lorenzo, Mauro. (2007) African Perspective on China. Presentation at the American Enterprise
Institute for Public Policy Research, Washington, DC, October 3.
De Maria, William. (2008) Cross Cultural Trespass Assessing African Anti-Corruption Capacity.
International Journal of Cross Cultural Management 8(3):317–41.
De Ree, Joppe, and Eleonora Nillesen. (2009) Aiding Violence or Peace? The Impact of Foreign Aid
on the Risk of Civil Conflict in sub-Saharan Africa. Journal of Development Economics 88(2):301–
13.
De Waal, Alex. (2015). The ‘Political Marketplace’ & the Roots of Persistent Conflict. Fletcher Security
Review.
Dellios, Hugh. (1997). Victims Describe Mobutu’s Long Reign of Torture: As His Power Ebbs,
Some Zairians Fear Last Gasp of Cruelty. Chicago Tribune, 29 April 1997.
Dörrie, Peter. (2015) China Is Stealthily Arming Troops in South Sudan. The Week, March 11.
Dreher, Axel and Andreas Fuchs. (2011) Rogue Aid? The Determinants of China’s Aid Allocation.
Courant Research Centre: Poverty, Equity and Growth – Working Paper Series (93).
Dreher, Axel, Andreas Fuchs, Roland Hodler, Bradley C. Parks, Paul A. Raschky, and Michael J.
Tierney. (2014) Aid on Demand: African Leaders and the Geography of China’s Foreign
Assistance. AidData – Working Paper Series (3).
Dreher, Axel, Peter Nunnenkamp, and Rainer Thiele. (2011) ‘Are “New” Donors Different?
Comparing the Allocation of Bilateral Aid Between non-DAC and DAC Donor Countries’,
World Development, 39 (11), pp. 1950–1968. 37
Dunne, Paul, and Sam Perlo-Freeman. (2003). The Demand for Military Spending in Developing
Countries. International Review of Applied Economics 17(1):23-48.
Dunning, Thad. (2004) Conditioning the Effects of Aid: Cold War Politics, Donor Credibility, and
Democracy in Africa. International Organization 58(2):409–23.
Economy, Elizabeth, and Karen Monaghan. (2006) The Perils of Beijing’s Africa Strategy – Opinion
– The International Herald Tribune. New York Times, November 1.
Escriba-Folch, Abel. (2013). Repression, political threats, and survival autocracy. International Political
Science Review, 34(5): 543-60.
Fantaye, Dawit Kiros. (2004). Fighting Corruption and Embezzlement in Third World
Countries. The Journal of Criminal Law, 68(2): 170-176.
Findley, Michael, Josh Powell, Daniel Strandow, and Jeff Tanner. (2011) The Localized Geography
of Foreign Aid: A New Dataset and Application to Violent Armed Conflict. World
Development 39(11):1995-2011.
Fine, Ben, and Jomo, K. S. (2005) The New Development Economics: Post Washington Consensus Neoliberal
Thinking. London: Zed.
Foster, Vivien, William Butterfield, Chuan Chen, Nataliya Pushak. (2008). Building Bridges: China’s
Growing Role As Infrastructure Financier For Sub-Saharan Africa. The World Bank, Trends
and Policy Options, no.5.
Gagliardone, Iginio, and Sam Geall. (2014). China in Africa’s Media and Telecommunications:
Cooperation, Connectivity and Control. Norweigan Peacebuilding Resource Centre, expert analysis,
April.
Goldsmith, Arthur A. (2001) Foreign Aid and Statehood in Africa. International Organization
55(1):123–48. 38
Gould, William. (2011). Use Poisson Rather than Regress; Tell a Friend. The Stata Blog. 22 August
2011.
Grossman, Herschel I. (1992). Foreign Aid and Insurrection. Defence and Peace Economics 3(4):275-88.
Guimei, Yao. (2010). China and Africa: Mutual Benefit and Win-Win. Forum on China-Africa
Cooperation (FOCAC) Archives, 18 June 2010.
Hafner-Burton, Emilie M., Susan D. Hyde, and Ryan S. Jablonski. (2010). Terrorizing freedom:
When governments use repression to manipulate elections. Unpublished manuscript.
Halakhe, Abdullahi Boru. (2014). China’s Rise Meets America’s Decline in Africa. Al Jazeera, 27 May
2014.
Human Rights Watch. (2012). Ethiopia: Pastoralists Forced off Their Land for Sugar Plantations. 18
June. < https://www.hrw.org/news/2012/06/18/ethiopia-pastoralists-forced-their-land-
sugar-plantations>.
Huth, Paul and David Backer. (2014) (Re)assessing the Relationship between Food Aid and Armed
Conflict. USAID Technical Brief (October, DCHA/CMM)
Kaplinsky, Raphael, Dorothy McCormick, and Mike Morris. (2007) The Impact of China on Sub-
Saharan Africa. Institute of Development Studies – Working Paper Series (291).
Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi. (2013) Worldwide Governance Indicators.
Worldwide Governance Indicators Project
Kolstad, Ivar, Verena Fritz, and Tam O’Neil. (2008). Corruption, Anti-Corruption Efforts and Aid:
Do Donors Have the Right Approach? ODI: Good Governance, Aid Modalities and Poverty
Reduction Working Paper Series, working paper 3.
Kragelund, Peter. (2011) ‘Back to BASICs? The Rejuvenation of Nontraditional Donors’
Development Cooperation with Africa’, Development and Change, 42 (2), pp. 585–607. 39
Lamb, David. (1987). The Africans. New York, NY: Vintage Books.
Macdonald, Kate. (2014) ‘The Meaning and Purposes of Transnational Accountability’, Australian
Journal of Public Administration, 73 (4), pp. 426–436.
Macdonald, Kate. and May Miller-Dawkins. (2015a) ‘Accountability in Public International
Development Finance’, Global Policy, 6 (4), pp. 429–434.
-----. (2015b) 'Have those hard-won accountability reforms had any impact?' From Poverty to
Power: Oxfam Blog (8 December 2015).
Marshall, Monty G. and Keith Jaggers. (2002) Polity IV Project: Political Regime Characteristics and
Transitions, 1800-2002. Version p4v2002e. College Park, MD: Center for International
Development and Conflict Management, University of Maryland.
McGreal, Chris. (2007). Chinese aid to Africa May Do More Harm than Good, Warns Benn. The
Guardian, 7 February 2007.
Mohan, Giles, and Dinar Kale. (2007). The Invisible Hand of South-South Globalization: Chinese
Migrants in Africa. The Development Policy and Practice Department (Report for the Rockefeller
Foundation).
Moss, Todd and Sarah Rose. (2006) China’s ExIm Bank and Africa: New Lending, New Challenges.
Washington, DC: Center for Global Development.
Mwenda, Andrew M. and Roger Tangri. (2005) Patronage Politics, Donor Reforms, and Regime
Consolidation in Uganda. African Affairs 104(416):449-67.
Naim, Moises. (2009) Rogue aid, Foreign Policy, October 15.
Nanda, Ved P. (2006) The ‘Good Governance’ Concept Revisited. The ANNALS of the American
Academy of Political and Social Science 603(1):269–83. 40
Nunn, Nathan and Nancy Qian. (2014) U.S. Food Aid and Civil Conflict. American Economic Review
104(6):1630-66.
Plaut, Martin. (2014). Uganda Donors Cut Aid after President Passes Anti-Gay Law. The Guardian,
25 February. < http://www.theguardian.com/global-development/2014/feb/25/uganda-
donors-cut-aid-anti-gay-law>.
Quadir, Fahimul. (2013) ‘Rising Donors and the New Narrative of ‘South-South’ Cooperation: what
prospects for changing the landscape of development assistance programmes?’, Third World
Quarterly, 34 (2), pp. 321–338.
Qiang, Zeng. (2007) China Africa Relations Since the Introduction of FACAC. Beijing: China Institute of
Contemporary Relations.
Raleigh, Clionadh. (2014). Pragmatic and Promiscuous Explaining the Rise of Competitive Political
Militias across Africa. Journal of Conflict Resolution.
Raleigh, Clionadh, Andrew Linke, Håvard Hegre and Joakim Karlsen. (2010). Introducing ACLED-
Armed Conflict Location and Event Data. Journal of Peace Research 47(5):1-10.
Richards, Clint. (2014) Uganda Looks to China. The Diplomat, March 4.
Samy, Yiagadeesen. (2010) China's Aid Policies in Africa: Opportunities and Challenges. The Round
Table: The Commonwealth Journal of International Affairs 99(406):75-90.
Sautman, Barry, and Yan Hairong. (2007) Friends and Interests: China’s Distinctive Links with
Africa. African Studies Review 50(3):75-114.
Savun, Burcu, and Daniel C. Tirone. (2011) Foreign Aid, Democratization, and Civil Conflict: How
Does Democracy Aid Affect Civil Conflict? American Journal of Political Science 55(2):233–46. 41
-----. (2012) Exogenous Shocks, Foreign Aid, and Civil War. International Organization 66(3):363–93.
Smith, David. (2013). Robert Mugabe’s Land Reform Comes under Fresh Scrutiny. The Guardian, 10
May. < http://www.theguardian.com/world/2013/may/10/robert-mugabe-land-reform>.
Snyder, Richard. (1992). Explaining Transitions from Neopatrimonial Dictatorships. Comparative
Politics, 24(4): 379-99.
Strange, Austin M., Axel Dreher, Andreas Fuchs, Bradley Parks, and Michael J. Tierney.
(forthcoming). Tracking Underreported Financial Flows: China’s Development Finance and
the Aid–Conflict Nexus Revisited. Journal of Conflict Resolution.
Sun, Yun. (2015). China’s Foreign Aid Reform and Implications for Africa. Brooking Blog (1 July
2015). < http://www.brookings.edu/blogs/africa-in-focus/posts/2015/07/01-china-
foreign-aid-africa-sun>.
Sundberg, Ralph, Mathilda Lindgrem, and Ausra Padskocimaite. (2010) UCDP GED Codebook,
Version 1.0-2011. Uppsala: Department of Peace and Conflict Research, Uppsala University.
Sundberg, Ralph and Erik Melander. (2013) Introducing the UCDP Georeferenced Event Dataset.
Journal of Peace Research 50(4):523-32.
Taylor, Ian. (1998) China’s Foreign Policy towards Africa in the 1990s. The Journal of Modern African
Studies 36(3):443–60.
Thornycroft, Peta. (2014). Robert Mugabe Says He Prefers Chinese Aid Because Beijing Does Not
Force Him to Accept Homosexuality. UK Telegraph, August 31.
Tierney, Michael J., Daniel L. Nielson, Darren G. Hawkins, J. Timmons Roberts, Michael G.
Findley, Ryan M. Powers, Bradley Parks, Sven E. Wilson, and Robert L. Hicks. (2011) More
Dollars than Sense: Refining Our Knowledge of Development Finance Using AidData.
World Development 39(11):1891-906. 42
Tilak, Jandhyala. (2014) ‘South-South Cooperation: India’s Programme of Development Assistance
– Nature, Size and Functioning’, Asian Education and Development Studies, 3 (1), pp. 58–
75.
Tull, Denis. M. (2006) China’s Engagement in Africa: Scope, Significance and Consequences. Journal
of Modern African Studies 44(3):459-79.
Uvin, Peter. (1998). Aiding Violence: The Development Enterprise in Rwanda. West Hartford, CT:
Kumarian Press.
Van Cranenburgh, Oda. (2011). Democracy Promotion in Africa: The Institutional
Context. Democratization 18(2):443-61.
Wenping, He. (2007) The Balancing Act of China’s African Policy. China Security 3(3):23-40.
World Bank. (2015) World Development Indicators. World Bank. catalog/world-development-indicators>. Wrong, Michela. (2010) It’s Our Turn to Ear: The Story of a Kenyan Whistleblower. UK: Fourth Estate. Zafar, Ali. (2007) The Growing Relationship Between China and Sub-Saharan Africa: Macroeconomic, Trade, Investment, and Aid Links. The World Bank Research Observer 22(1):103-30. Zimmermann, Felix and Kimberly Smith. (2011) ‘More Actors, More Money, More Ideas for International Development Cooperation’, Journal of International Development, 23 (5), pp. 722–738. Zweig, David, and Bi Jianhai. (2005) China’s Global Hunt for Energy. Foreign Affairs, September/October.