Infrastructure Investments in Portugal

Volume II: Essays on the Economic Effects of Infrastructure Investments in Portugal

Alfredo Marvão Pereira Rui Marvão Pereira

May, 2015

Alfredo Marvão Pereira Project Coordinator Thomas Arthur Vaughn Memorial Professor of Economics The College of William and Mary Williamsburg, Virginia, USA Tel.: 001 804 741 8196 Email: [email protected]

Rui Marvão Pereira Lecturer in Economics The College of William and Mary Williamsburg, Virginia, USA Tel.: 001 757 221 2390 Email: [email protected]

Index

CHAPTER 1 Introduction: Preliminary Conceptual Remarks ______9

1.1 General Presentation of this Volume ______9

1.2 The Literature ______9

The Industry Dimension ______10

The Regional Dimension ______10

1.3 The Economic Effects of Infrastructure Investments ______12

1.4 Why and How These Essays are Different ______14

CHAPTER 2 Data Sources and Description ______17

2.1 The Industry Data Set ______17

General Scope ______17

Industry Coverage ______17

The Traded Goods versus Non-traded Goods Divide ______17

On the Evolution of the Industry Variables ______18

On the Evolution of Labor Productivity by Sector ______18

2.2 The Regional Data Set ______19

General Scope ______19

On the Regional Evolution of the Macro Variables ______20

2.3 The Infrastructure Investment Data Set ______21

General Scope ______21

On the Evolution of Investments on the Different Infrastructure Assets ______21

Overall Evolution of Infrastructure Investments ______22

The Regional Dimension of Infrastructure Investments ______23

CHAPTER 3 Methodological Considerations ______35

3.1 General Methodological Remarks ______35

General Approach ______35

The Underlying Economic Model ______35

Link to the Fiscal Multiplier Literature ______36

3.2 Preliminary Data Analysis ______36

Unit Roots Cointegration ______36

Cointegration ______37

VAR specifications ______39

3.3 Identifying Exogenous Innovations in Infrastructure Investment ______40

The Problem and Our Approach ______40

The Policy Functions ______40

The Orthogonalization Assumptions ______41

The Regional Dimension ______42

The Estimated Policy Functions ______42

3.4 Measuring the Effects of Innovations in Infrastructure Investment ______43

The Exogenous Shock ______43

The Accumulated Impulse Response Functions ______44

Error Bands and Significance ______44

The Measurement of the Total Effects ______44

The Long Term Elasticities ______45

Long Term Marginal Products ______45

Annual Rates of Return ______46

CHAPTER 4 Identifying Priorities in Infrastructure Investment ______47

4.1 Introduction ______47

4.2 On the Empirical Evidence ______49

On the Elasticities with Respect to Infrastructure Investments ______49

On the Effects of Infrastructure Investments on Labor Productivity ______50

Marginal Products with Respect to Infrastructure Investment ______50

On the Potential Budgetary Effects ______52

Rates of Return of Infrastructure Investments ______52

Long-term Marginal Products versus Effects on Impact ______53

Long-Term Marginal Products and the Relative Scarcity of Infrastructure Capital ______55

4.3 Summary and Concluding Remarks ______57

Summary ______57

Policy Implications ______58

CHAPTER 5 Is All Infrastructure Investment Created Equal? ______69

5.1 Introduction ______69

5.2 The Empirical Results ______71

Long-Term Elasticities ______71

Long-term effects on labor productivity ______72

Long-Term Marginal Products and Rates of Return ______73

Long-term Marginal Products versus Effects on Impact ______75

Long-Term Marginal Products and the Relative Scarcity of Infrastructure Capital ______78

5.3 International Comparisons ______81

5.4 Summary and Concluding Remarks ______85

Summary ______85

Policy Implications ______86

CHAPTER 6 Infrastructure Investment and the Composition of Economic Activity ______107

6.1 Introduction ______107

6.2 The Empirical Results ______108

The Effects at the Industry Level: A First Look______108

The Effects at the Industry Level: A Closer look ______109

On the Effects on the Composition of Economic Activity ______112

On the Relationship between the Aggregate and Sectorial Effects ______115

6.3 Summary and Concluding Remarks ______117

Summary ______117

Policy Implications ______118

CHAPTER 7 Infrastructure Investment, Labor Productivity, and International Competitiveness

137

7.1 Introduction ______137

7.2 The Empirical Results ______139

The Effects of Investments in Road Transportation Infrastructures ______139

The Effects of Investments in Other Transportation Infrastructures ______141

The Effects of Investments in Social Infrastructures ______142

The Effects of Investments in Public Utilities and Telecommunications ______143

The Effects on Labor Productivity from an Industry Perspective ______145

7.3 Summary and Concluding Remarks ______147

Summary ______147

Policy Implications ______148

CHAPTER 8 On the Choice of the Regional Location of Infrastructure Investments ______154

8.1 Introduction ______154

8.2 The Empirical Results ______156

Where to invest for each infrastructure asset______156

What to invest for each region ______158

The best overall infrastructure investment options ______159

How Far are the Actual Effects from the Potential Effects of Infrastructure Investments? ______160

8.3 Summary and Concluding Remarks ______162

Summary ______162

Policy Implications ______163

CHAPTER 9 On the Effects of Infrastructure Investments on the Regional Economic Mix ___ 172

9.1 Introduction ______172

9.2 Empirical Results ______173

Framing the Empirical Effects of Infrastructure Investments ______173

On The Regional Effects of Infrastructure Investments by Asset ______174

On the Effects of Infrastructure Investments by Region ______175

On the Effects Infrastructure Investments on the Regional Mix of Economic Activity ______176

9.3 Summary and Concluding Remarks ______178

Summary ______178

Policy Implications ______180

CHAPTER 10 Concluding Remarks and Directions for Future Work ______192

10.1 What These Results Are and What They Are Not ______192

10.2 Directions for Future Work ______194

10.3 The General Relevance of This Work. ______194

REFERENCES ______196

Keywords: Infrastructure Investment, Multipliers, Economic Performance, Budgetary Effects, Industry Mix, Traded and non-traded sectors, Regional Location, Regional Composition of Economic Activity, VAR, Portugal.

JEL Classification: C32, E22, E62, H54, H60, L90, L98, O47, O52, R15, R42, R53

CHAPTER 1 Introduction: Preliminary Conceptual Remarks

In this chapter, we introduce the present report. We start with a brief literature review on the empirical evidence on the aggregate sectorial and regional effects of infrastructure investments. Then, and in order to help frame the analysis of the effects of infrastructure investments we discuss the different mechanisms through which these investments and the related assets affect economic performance. We conclude this chapter with a discussion on the unique contributions that are brought forth in this work.

1.1 General Presentation of this Volume

This volume is based on six essays dealing with the analysis of economic effects of infrastructure investments in Portugal using the new data set presented in Volume I. They approach the issue from different perspectives: two at the aggregate level considering different infrastructure assets; two with a sectorial focus; and two with a regional focus. While these six essays have their own existence as separate working papers for the benefit of the more technical reader and to avoid the repetitions inevitable when writing different working papers on more or less closely related topics, we have merged the information they contain into this comprehensive volume.

This volume is organized as follows. The first three chapters present an introduction, a description of the data set, and some methodological considerations. The next six chapters mirror the individual research papers: two deal with aggregate results, two with sectorial results, and two with regional results. This volume concludes with a final chapter which provides important qualifications to the results presented here as well as avenues for future research.

1.2 The Literature

The analysis of the economic effects of infrastructure investments was brought to the limelight by the seminal work of Aschauer (1989a, 1989b). The body of empirical literature that developed in its

aftermath is extensive and focuses on a large variety of issues, both at the aggregate and at the regional levels, both for the US and for other countries [see, for example, Munnell (1992), Gramlich

(1994), Kamps (2005), Romp and de Haan (2007) and Pereira and Andraz (2013), for literature surveys]. Studies of these effects at the industry level are less common.

The Industry Dimension

Although several studies for the US make reference to specific industries, they have essentially a regional focus [see, for example, Evans and Karras (1994), and Moomaw and Williams

(1991)]. The sector-specific dimension is more directly relevant in the studies of Fernald (1993),

Gokirmak (1995), Nadiri and Mamuneas (1994, 1996), Greenstein and Spillar (1995), Holleyman

(1996), Pinnoi (1992) and Pereira and Andraz (2003). The international evidence at the industry level is even less abundant. It includes contributions such as Berndt and Hansson (1991) for Sweden,

Seitz (1994), Seitz and Licht (1995) for Germany, Lynde and Richmond (1993) for the U.K., Shah

(1992) for Mexico, and Pereira and Roca-Sagales (2001) for Spain and Pereira and Andraz (2007) for

Portugal and multi-country studies, such as Evans and Karras (1993).

The Regional Dimension

The empirical evidence of positive effects of infrastructure investments at the regional level has traditionally been unable to replicate the large effects often identified at the aggregate level.

Some of the early contributions provide evidence of a positive effects although clearly lower than the aggregate estimates [Costa et al. (1987), Duffy-Deno and Eberts (1991), Eberts (1990), Garcia-

Mila and McGuire (1992), Merriman (1990), Moomaw and Williams (1991), Munnell with Cook

(1990), and Munnell (1993)]. Later studies, however, find that after controlling for region and state specific unobserved characteristics, public capital effects are not significant [Andrews and Swanson

(1995), Eisner (1991), Evans and Karras (1994), Garcia-Milà et al. (1996), Holtz-Eakin (1993, 1994), and Moomaw et al. (1995)].

Evidence on the effects of public capital at the regional level for other countries is in many respects similar to that for the US. In general, output elasticities are positive and relatively large in

Japan [Merriman (1990)], Spain [Cutanda and Paricio (1992) and Mas et al. (1996)], Belgium

[Everaert and Heylen (2004)] and Germany [Stephan (2003)] and substantially lower for France

[Cadot et al. (1999)]. Furthermore, the adoption of cost and profit equation approaches appears to have led to smaller estimates for the effects of public capital on economic performance [Boscá et al.,

(2000), Everaert (2003), and Moreno et al. (2003)].

One possible explanation for the discrepancy between large aggregate effects and small regional effects is that spillover effects captured by aggregate level studies are not captured at the regional level [Boarnet (1998) and Mikelbank and Jackson (2000)]. As such, it could be argued that spillover effects should be an integral part of the analysis of the regional impact of public capital formation [Haugwout (1998, 2002)] as the effects of public capital formation in a region can be induced by public infrastructures installed in the region itself as well as public infrastructure outside the region. Paradoxically, possibly due to the inconclusive nature of the results on the impact of public capital on output at the regional level, the issue of the possible existence of regional spillovers from public capital formation has received little attention. Munnell (1990) deals marginally with this issue. Holtz-Eakin (1993, 1995) concludes that regional level estimates are essentially identical to those from national data, suggesting no quantitatively important spillover effects across regions. On the other hand, several other studies report evidence of spillovers [Boarnet (1998), Cohen and Paul

(2004), and Pereira and Andraz (2004)]. The empirical results reported in Pereira and Andraz (2004), for example, suggest that only about one-fifth of the aggregate effects of public investment in highways in the US are captured by the direct effect of public investment in the state itself, the

remaining corresponding to the spillover effects from public investment in highways in other states.

In addition, the significance of spillover effects is observed in some countries such as Portugal

[Pereira and Andraz (2006)] and Spain [Pereira and Roca (2003, 2007)], and help explain some of the divergences found between regional and aggregate results.

1.3 The Economic Effects of Infrastructure Investments

To help frame the analysis of the effects of infrastructure investments it is useful to understand the different mechanisms through which these investments and the related assets affect economic performance. In general terms, infrastructures fall in the category public goods or of externalities - they provide services that although being necessary for private sector activity, would not be available or would be in short supply if totally left to private sector mechanisms. As such their provision is either public or done through close public tutelage. For some assets such as public utilities and telecommunications technological advances and the evolution of the domestic and international markets has led to full private provision.

In this context, we can see infrastructure investments and the assets they generate affecting economic activity through different channels each with rather different impact on what one would expect in terms of the industry-specific incidence of the effects. First, there is what we could call a functional channel. Infrastructures fulfill a role as production inputs directly relevant for the activity in question. Transportation services for example, need a good road and other transportation network, while sectors that are either more labor intensive or rely more on skilled labor, such as finance or telecommunications, professional services, will have their productivity affected directly by the network of social infrastructures. This is, therefore, essentially a supply side channel. The ultimate effects the industry mix are going to depend on the direct relevance of the infrastructure as

an additional input to production as well as on the nature of the relationship between infrastructure and private inputs – labor and private capital.

While the functional channel is the most recognized and often the only recognized channel it is neither the only channel nor necessarily the most important. A second channel is what we could call the construction channel. These investment projects inevitably use vast pools of resources, engage the rest of the economy in the process itself of constructing these assets. Making available a road, or a port, a hospital or a waste management facility, directly engages the construction industry and through it the rest of the economy - construction materials, etc. These are demand side effects on output and employment that although reverberating throughout the economy are expected to be short-lived.

A third channel through which infrastructures affect economic performance is the operation and maintenance channel. Operating and maintaining existing infrastructures creates needs for use of resources - goods and services and labor. While the effects of the economic effort involved in operation and maintenance of road infrastructures, for example, could easily be neglected, the same cannot be said about operating and maintaining a port, an airport, a hospital or a school. This is also a demand side effect but unlike the previous one it is more long lasting.

Finally, there is what we could call a site location channel. The existence of certain infrastructures such as some types of transportation infrastructures, schools, and hospitals serve as an attractor for population and business. There should follow important effects, for example, for trade and real estate. Naturally, the opposite is true for airports, waste and wastewater facilities or power plants and refineries which have a negative effect on the desirability of where they are located.

Considering these different channels is important to understand the economic effects of infrastructure investments. The reverse is also true. The timing of the effects as well as the sectors of

economic activity that are affected the most, both offer a glimpse into what channels seem to be the most important for each infrastructure asset.

1.4 Why and How These Essays are Different

Finally, and since this is clearly not the first set of papers dealing with infrastructure investments in Portugal it is important to highlight the novelties in this work.

First, we use a new and comprehensive data set for infrastructure investment in Portugal covering the period between 1978 and 2012 [see Pereira and Pereira (2015)]. In doing so, we enlarge the scope of the analysis of the effects of infrastructure investments by considering non- transportation infrastructures. Specifically, we consider also social infrastructures – education and health facilities – and utilities – water, electricity and gas, refineries, and telecommunications. At the same time this is also the first treatment of the transportation infrastructure using data after the late

1990s as previous work used data ending in 1998.

Second, and from a more conceptual perspective, this is the first contribution that decomposes the marginal products between the short-term demand effects on impact and the long term supply side effects and that maps the evolution of the marginal products over time to identify patterns of decreasing marginal returns. Furthermore, we present standard deviation bands around the accumulated impulse response functions thereby allowing for a discussion of the significance of the long-term effects.

Finally, from a policy perspective, and in response to the economic conditions developing over the last decade, this is the first time a new taxonomy is introduced and applied and the policy implications of the results are framed in terms of the economic and budgetary dilemma. Indeed, from a taxonomic perspective, we can expect infrastructure investments to conceivably fall into three categories. First, the case of negative or low positive marginal products. In this case,

infrastructure investments are not important for the economy and have a detrimental effect on the budget and as such can be eliminated without significant economic or budgetary concerns. Second, the case of positive but not sufficiently large marginal products. These infrastructure investments are important for the economy but still have a detrimental effect on the public budget. Eliminating these investments although useful from a budgetary perspective is hurtful in economic terms. Third, the case of sufficiently large marginal products. In this case these infrastructure investments have positive economic and budgetary effects. Eliminating these investments hurts both the economy and the public budget. In this context, our quest for identifying priorities in infrastructure investments, represents searching for areas of investment that fall in this third category, i.e., infrastructure investments with virtuous economic and budgetary effects.

CHAPTER 2 Data Sources and Description

In this chapter we present the data set that is used to produce the economic analysis in the later chapters. We first present and provide some brief summary descriptive information about the aggregate, the industry and the regional data sets for the macro variables – output, employment, and private investment. More importantly we present and briefly discuss the new data set for infrastructure investments. We presents and discuss this data set from a typological perspective as well as from a regional perspective.

2.1 The Industry Data Set

General Scope

The economic data – output, employment, and private investment, are obtained from different annual issues of the National Accounts published by National Institute of Statistics and available on-line at http://www.ine.pt. Output and private investment are measured in millions of constant 2005 Euros while employment is measured in thousands of employees.

Industry Coverage

We consider twenty two industries divided in four main groups. The different sectors are grouped into two primary sectors (agriculture and mining), seven manufacturing sectors (food, textiles, paper, chemical and pharmaceutical, non-metallic minerals, metallic, and machinery), ten private services sectors (electricity, water, construction, trade, transportation, hospitality, telecommunications, finance, real estate, and professional services) and three public services sectors

(administration, health and education). In Table 2.1 we include details on the definition of the different sectors.

The Traded Goods versus Non-traded Goods Divide

We use the share of exports in the sector output over the last decade to identify the sectors producing internationally traded good and those which do not. We define the two primary sectors,

the seven manufacturing sectors, and the sector of transportation as being traded goods sectors. The remaining nine private service sectors as well as the three public service sectors are defined as non- traded. Here, however, we will find it useful to identify some private service sectors such as water, hospitality, telecommunications, finance and professional services as emerging traded goods sectors.

In these sectors international trade plays a small but possibly increasing role.

On the Evolution of the Industry Variables

Summary statistics on the industry mix during the sample period are provided in Table 2.2.

The output share of the primary and the manufacturing sectors declined sharply over the sample period. The primary sector was 7.1% of output in the 1980s and declined to 3% in the last decade.

The manufacturing sector, declined from 15.7% to 10.7%. Transportation declined in the 1990s but has somewhat rebound over the last decade. The sectors producing traded goods overall declined from 27.9% of output in the 1980s to 21.6% in the last decade, a decline that would be more pronounced if it were not for the increase in the relative role of transportation and storage services.

Private services, net of transportation, increased slightly from 61.1% of output in the 1980s to

62.3% in the last decade, led by a large increase in the role of professional services. The large increase over the sample period was in public services, which rose from 11% in the 1980s to 16.1% in the last decade, a change led directly by public administration services.

On the Evolution of Labor Productivity by Sector

We consider some basic statistical information about the evolution of labor productivity, simple measures such as output per worker. The relevant figures are presented in Table 2.3. Overall, and for the economy as a whole, despite a rather sluggish evolution over the 1990s and 2000s, we see a clear 37.4% improvement when we compare labor productivity in the 1980s and in the 2000s.

For the primary sector we see, however, a sharp decline, while the improvements in manufacturing are in line with the aggregate effects. Labor productivity in the private services sectors overall

improved by about 20% in the 2000s compared to the 1980s while the largest improvement occurred in public services – 72.4% over the same reference frame.

Let us consider more specifically, the evolution for the industries on the two sides of the traded non-traded divide. We observe that among the ten traded goods sectors, agriculture (S1), mining (S2), basic metals (S8), and machinery and equipment (S9) were the only four not showing progress over the sample period, the same being true for professional services (S19) among the five emerging traded goods sectors. In turn, among the seven non-traded goods sectors only trade (S13) and real estate (S18) did not show progress. It should be noted as well that the greatest gains in labor productivity seem to have occurred in non-traded sectors such as electricity and gas (S10), water

(S11), telecommunications (S16), finance (s17), education (S21) and health (S22).

2.2 The Regional Data Set

General Scope

We consider annual data on output, employment, gross private investment for the five contiguous administrative regions defined under the NUTS II. These regions are North (Norte),

Centre (Centro), Lisbon (Lisboa e Vale do Tejo), Alentejo, and Algarve, and their exact definition in terms of NUTS III is provided in Table 2.4. We can visualized mainland Portugal as a long rectangle with the vertical sides about three times as long as the horizontal ones. Broadly speaking, these regions run from north to south as five consecutive segments of this rectangle, with the middle region of Lisbon and the southernmost region of Algarve being geographically smaller than the other three.

The data covers the period from 1980 to 2011. This is because regional output, private investment and employment data are only available in a consistent manner after 1980. Output and

private investment are in millions of 2005 Euros, while private employment is in fulltime equivalent employees.

The macro data at the regional level were obtained from the different annual issues of the

Regional Accounts published by the National Institute of Statistics/Instituto Nacional de Estatística, which for the period after 1995 are available on-line at http://www.ine.pt. The regional disaggregation of private investment poses a particular challenge since such data does not exist until

1995. To obviate this problem, we constructed a data series for private investment by region from

1980 to 1994, using regional data for private output and data for aggregate private investment.

Specifically, private investment figures by region were obtained as the product of the aggregate private investment by the fraction of the private output in that region.

On the Regional Evolution of the Macro Variables

Summary statistics for the regional macro data are provided in Table 2.5. North and Lisbon are the two most important regions in terms of their share on the country’s economy. Over the sample period North accounted for 30.58% of the country’s output, 37.84% of investment and

35.68% of employment while Lisbon accounted for 27.21%, 40.22% and 29.02%, respectively.

Centre is a middle sized region with 20.06% of output, 21.16% of investment, and 25.27% of employment. The two remaining regions Alentejo and Algarve are substantially smaller and together account for around 11% of the economic activity in the country.

Of the five regions, North, Centre and Alentejo experience a decreasing trend in terms of their shares of output while the opposite is true for Lisbon and to a lesser extent for Algarve. The same occurs in terms of employment although there has been a rebound in Alentejo in the last decade. Finally, in terms of investment North and Alentejo have seen their shares increase, while

Centre and Algarve have seen a rebound in the last decade. On the flip side investment in Lisbon declined significantly in relative terms in the last decade.

Overall, the predominance of North and Lisbon remained high and relatively stable during the sample period. This is particularly the case for output and employment for which a slight decline in North was matched by a slight increase in the Lisbon. In turn, there is a pattern of slight decline in the concentration of private investment mostly through a great reduction in the share of Lisbon.

2.3 The Infrastructure Investment Data Set

General Scope

The data for infrastructure investment are from a new data set developed by Pereira and

Pereira (2015) and covers the period between 1978 and 2011. Infrastructure investment is measured in constant 2005 Euros. It considers twelve individual types of infrastructure investments grouped in five main groups: road transportation infrastructure, other transportation infrastructure, social infrastructures, public utilities, and telecommunication infrastructures.

On the Evolution of Investments on the Different Infrastructure Assets

Table 2.6 presents summary information for the infrastructure investment efforts, investments as a percent of GDP, as well as a percent of total infrastructure investment.

Road transportation infrastructures include national roads, municipal roads and highways and account for 28.2 percent of total infrastructure for the sample period. Investment efforts and the extension of motorways in Portugal grew tremendously during the 1990s with the last ten years marked by a substantial increase in highway investment made possible due to public private partnerships. This corresponds in absolute terms to an increase from 0.75% of the GDP in the

1980s to 1.56% in the last decade.

Other transportation infrastructures include railroads, airports and ports, and account for

9.0 percent of total infrastructure investment between 1978 and 2011. These investment reached their greatest levels, as a percent of total infrastructure investment, with the modernization of the

railroad network and port expansion projects while the last ten years has also brought with it substantial growth in investment in airports. In absolute terms, this reflects an increase from 0.22% of the GDP in the 1980s to 0.48% in the last decade.

Social infrastructures include health facilities and educational buildings. Social infrastructures account for 23.8 percent of infrastructure investment and show a slowly declining pattern over time in terms of their relative importance in total infrastructure investment. In absolute terms, however, these investments remained stable over the last two decades representing just over

1.0% of the GDP in average.

Public utilities include electric power generation, transmission and distribution, water supply and treatment, petroleum refining and telecommunications infrastructures. Together these account for 39.1 percent of total infrastructure investment in the sample period. In terms of their relative importance, investment in utilities reached a relatively high relevance in terms of total infrastructure investment in the 1980s, driven by the expansion of the telephone network, substantial investment in the major coal powered electricity production units and in two refineries.

More recently, the expansion of mobile communications networks as well as investments in renewable energies have contributed to sustained growth in investment in utilities since 2000. In absolute terms, we witnessed a constant increase in importance from 1.13% of the GDP in the

1980s to 2.09% in the last decade.

Overall Evolution of Infrastructure Investments

Overall, investment levels have grown substantially over the past thirty years, averaging

2.92% of the GDP in the 1980s, 4.45% in the 1990s and 5.17% over the last decade. The increase is particularly pronounced after 1986, the year in which Portugal joined the EU, and in the 1990s when

EU transfers within the context of the Structural and Cohesion Funds - Community Support

Framework I (1989-1993) and Community Support Framework II (1994-1999) - stimulated a

substantial increase in investment levels. The investment effort decelerated substantially during the last decade during the Community Support Framework III (2000-2006) and the QREN (2007-2013).

These landmark dates for joining the European Union as well as the start of the different community support frameworks are all considered as potential candidates for structural breaks in every single step of the empirical analysis that follows.

The Regional Dimension of Infrastructure Investments

The regional decomposition of infrastructure investments as a percentage of the GDP is summarized on Table 2.7, while the regional decomposition of investments in road infrastructures, other infrastructures, and social infrastructures is presented in Table 2.8.

Over the sample period, the North region concentrates the higher proportion of infrastructure investment, 30.81%, followed by Centre, with 26,24%, Lisbon with 24.48%, Alentejo with 12.49% and Algarve with 5.64%. Over the sample period North, Alentejo and Algarve show an increasing trend in terms of the relative importance of infrastructure investments in the region to reach 31.76%, 13.25%, and 6.67%, respectively. As to the Centre it reached a low point in the nineties and has recovered in the last decade, the opposite being the case of Lisbon, where infrastructure investments peaked in the nineties and declined substantially in the last decade to reach just 20.41%.

In terms of the regional composition of investments in road infrastructures North captures the largest share, 33.33%, followed by Centre with 29.76% but with a low in the nineties with

24.40%, Lisbon with 16.12% but with a great decline in the 2000s with 8.64%. Alentejo and Algarve capture 14.13% and 6.65% and show a clearly increasing trend. In turn for investments in both other transportation infrastructures and social infrastructures, Lisbon is in the lead with 35.37% with an increasing trend over time for other transportation and 31.96% with a decreasing trend for social infrastructures. For these two types of infrastructure investment North captures the second largest

share with an increasing tendency followed by Centre with relative stable shares. Alentejo shows a collapse in other transportation investments in the last decade while Algarve has a small but increasing share of social infrastructure investments.

Table 2.1 Industry Classification

Industry Sector

Primary Sector – Agriculture Agriculture (S1) Agriculture, forestry and fishing Mining (S2) Mining and quarrying

Secondary Sector - Manufacturing Food (S3) Manufacture of food products, beverages and tobacco products Textiles (S4) Manufacture of textiles, wearing apparel and leather products Paper (S5) Manufacture of wood and paper products, and printing Chemical and Pharmaceutical (S6) Manufacture of chemicals and chemical products. Manufacturing of basic pharmaceutical products and pharmaceutical preparations. Non-metallic minerals (S7) Manufacture of rubber and plastics products, and other non-metallic mineral products Basic metals (S8) Manufacture of basic metals and fabricated metal products, except machinery and equipment Machinery and equipment (S9) Manufacture of computer, electronic and optical products; Manufacture of electrical equipment; Manufacture of machinery and equipment; Manufacture of transport equipment; Manufacture of furniture; other manufacturing; repair and installation of machinery and equipment

Tertiary Sector - Private Services Electricity and gas (S10) Electricity, gas, steam and air-conditioning supply Water (S11) Water, sewerage, waste management and remediation activities Construction (S12) Construction Wholesale and retail trade (S13) Wholesale and retail trade, repair of motor vehicles and motorcycles Transportation and storage (S14) Transportation and storage Hospitality (S15) Accommodation and food service activities Telecommunications (S17) Telecommunications Finance (S17) Financial and insurance activities Real estate (S18) Real estate activities Professional services (S19) Publishing, audiovisual and broadcasting activities; Computer programming, consultancy and related activities; information service activities; Legal and accounting activities; activities of head offices; management consultancy activities; architecture and engineering activities; technical testing and analysis; Scientific research and development; Advertising and market research; other professional, scientific and technical activities; veterinary activities; Administrative and support service activities; Arts, entertainment and recreation; Other services activities

Tertiary Sector - Public Services Public administration (S20) Public administration and defense; compulsory social security Education (S21) Education Health (S22) Human health services; Social work activities

Table 2.2 Industry Composition

Private Investment Employment Output

1978- 1980- 1990- 2000- 1978- 1980- 1990- 2000- 1978- 1980- 1990- 2000- 2009 89 99 09 2009 89 99 09 2009 89 99 09

Agriculture 4.7 7.1 3.9 3.0 15.5 20.8 13.7 10.1 8.6 14.1 6.6 3.4 Agriculture (S1) 3.8 5.1 3.5 2.6 14.5 19.1 13.0 9.7 6.7 10.2 5.6 2.9 Mining (S2) 1.0 2.0 0.4 0.4 1.0 1.7 0.7 0.3 1.9 3.9 1.0 0.5 Manufacturing 13.1 15.7 12.3 10.7 21.8 25.0 21.7 18.0 18.1 20.5 18.5 15.1 Food (S3) 1.4 1.3 1.3 1.6 2.7 3.1 2.6 2.4 2.1 2.0 2.2 2.1 Textiles (S4) 1.3 1.9 1.3 0.7 7.4 8.9 7.6 5.5 3.7 4.2 4.2 2.7 Paper (S5) 1.4 1.6 1.2 1.5 2.3 2.5 2.3 1.8 2.2 2.4 2.2 1.8 Chemical and pharmaceutical (S6) 2.0 2.2 1.5 1.3 0.8 1.1 0.7 0.5 1.7 2.3 1.5 1.2 Non-metallic minerals (S7) 2.0 2.6 1.7 1.6 2.0 2.2 2.0 1.8 2.7 3.4 2.6 2.0 Basic metals (S8) 1.1 1.2 1.0 1.0 2.3 2.6 2.2 2.1 2.5 3.5 2.1 1.8 Machinery and equipment (S9) 4.0 4.9 4.2 2.9 4.0 4.9 4.2 2.9 3.3 2.7 3.7 3.7 Private Services 67.8 66.2 66.8 70.2 45.2 39.2 46.3 51.7 56.3 52.7 56.7 60.3 Electricity and gas (S10) 4.9 8.0 1.7 3.9 4.3 4.6 4.2 3.9 2.1 1.8 2.4 2.2 Water (S11) 3.4 5.6 1.5 2.3 0.4 0.5 0.4 0.2 0.6 0.5 0.6 0.9 Construction (S12) 5.3 5.5 6.4 4.1 0.9 1.1 0.8 0.7 7.1 6.8 7.0 7.7 Wholesale and retail trade (S13) 5.6 4.7 6.2 6.3 10.7 10.5 10.1 11.4 15.4 16.8 15.1 14.1 Transportation and storage (S14) 5.8 5.1 4.4 7.9 13.9 12.0 14.5 15.8 4.6 5.2 4.3 4.6 Hospitality (S15) 1.9 1.6 2.1 2.2 3.5 3.8 3.3 3.4 3.7 2.7 3.9 4.7 Telecommunications (S16) 2.7 2.0 3.0 3.1 4.4 3.6 4.5 5.4 1.9 1.4 2.0 2.3 Finance (S17) 4.8 5.1 6.0 3.7 0.4 0.5 0.4 0.3 6.3 6.3 6.1 6.6 Real estate (S18) 26.6 24.8 28.2 27.0 2.3 2.5 2.5 2.1 7.5 6.0 7.4 8.0 Professional services (S19) 6.7 3.9 7.3 9.7 0.5 0.2 0.6 0.7 7.2 5.2 7.8 9.1 Public Services 14.4 11.0 17.0 16.1 17.5 15.0 18.4 20.2 17.0 12.8 18.2 21.2 Public administration (S20) 10.8 8.4 13.1 11.8 8.0 7.1 8.2 9.1 8.5 7.2 8.9 9.9 Education (S21) 1.7 1.5 2.0 1.8 5.7 4.7 6.2 6.6 5.3 3.6 6.0 6.8 Health (S22) 1.9 1.1 2.0 2.6 3.8 3.2 4.0 4.6 3.2 2.0 3.3 4.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Table 2.3 Output per Worker by Industry 1978-2009 1980-89 1990-99 2000-09

Total Economy 23.0 19.5 26.1 26.8 Agriculture 11.1 13.1 11.3 9.0 Agriculture (S1) 9.5 10.3 10.2 8.0 Mining (S2) 38.0 42.9 35.4 37.6 Manufacturing 19.1 16.0 20.5 22.4 Food (S3) 18.2 12.6 19.9 24.0 Textiles (S4) 11.4 9.2 13.2 13.0 Paper (S5) 22.1 19.0 23.8 25.6 Chemical and pharmaceutical (S6) 44.7 39.1 50.1 49.1 Non-metallic minerals (S7) 29.2 29.8 30.5 28.3 Basic metals (S8) 23.9 25.7 23.4 22.4 Machinery and equipment (S9) 18.4 11.3 21.0 24.9 Private Services 28.7 26.1 29.3 31.2 Electricity and gas (S10) 152.0 67.2 146.6 250.7 Water (S11) 18.9 8.5 19.1 31.3 Construction (S12) 15.4 12.6 16.7 18.0 Wholesale and retail trade (S13) 25.2 27.2 24.9 24.0 Transportation and storage (S14) 29.9 26.6 30.9 35.5 Hospitality (S15) 19.1 14.4 21.1 23.6 Telecommunications (S16) 116.2 54.9 123.1 189.9 Finance (S17) 63.4 49.2 59.2 85.1 Real estate (S18) 460.5 529.6 305.5 300.2 Professional services (S19) 21.3 23.3 20.3 21.2 Public Services 23.6 17.4 24.9 30.0 Public administration (S20) 28.7 22.4 30.0 34.8 Education (S21) 21.3 14.8 23.1 27.8 Health (S22) 18.9 12.4 19.8 26.1

Table 2.4 Definition of Regions by NUTS II NUTS II NUTS III ALFÂNDEGA DA FÉ, ALIJÓ, AMARANTE, AMARES, ARCOS DE VALDEVEZ, ARMAMAR, AROUCA, BAIÃO, BARCELOS, BOTICAS, BRAGA, BRAGANÇA, CABECEIRAS DE BASTO, CAMINHA, CARRAZEDA DE ANSIÃES, CASTELO DE PAIVA, CELORICO DE BASTO, CHAVES, CINFÃES, ESPINHO, ESPOSENDE, FAFE, FELGUEIRAS, FREIXO DE ESPADA À CINTA, GONDOMAR, GUIMARÃES, LAMEGO, LOUSADA, MACEDO DE CAVALEIROS, MAIA, MARCO DE CANAVESES, MATOSINHOS, MELGAÇO, MESÃO FRIO, MIRANDA DO DOURO, MIRANDELA, MOGADOURO, MOIMENTA DA BEIRA, MONÇÃO, MONDIM DE BASTO, MONTALEGRE, MURÇA, OLIVEIRA DE AZEMÉIS, PAÇOS DE FERREIRA, North PAREDES, PAREDES DE COURA, PENAFIEL, PENEDONO, PESO DA RÉGUA, PONTE DA BARCA, PONTE DE LIMA, PORTO, PÓVOA DE LANHOSO, PÓVOA DE VARZIM, RESENDE, RIBEIRA DE PENA, SABROSA, SANTA MARIA DA FEIRA, SANTA MARTA DE PENAGUIÃO, SANTO TIRSO, SÃO JOÃO DA MADEIRA, SÃO JOÃO DA PESQUEIRA, SERNANCELHE, TABUAÇO, TAROUCA, TERRAS DE BOURO, TORRE DE MONCORVO, TROFA, VALE DE CAMBRA, VALENÇA, VALONGO, VALPAÇOS, VIANA DO CASTELO, VIEIRA DO MINHO, VILA DO CONDE, VILA FLOR, VILA NOVA DE CERVEIRA, VILA NOVA DE FAMALICÃO, VILA NOVA DE FOZ CÔA, VILA NOVA DE GAIA, VILA POUCA DE AGUIAR, VILA REAL, VILA VERDE, VIMIOSO, VINHAIS, VIZELA ABRANTES, ÁGUEDA, AGUIAR DA BEIRA, ALBERGARIA-A-VELHA, ALCANENA, ALCOBAÇA, ALENQUER, ALMEIDA, ALVAIÁZERE, ANADIA, ANSIÃO, ARGANIL, ARRUDA DOS VINHOS, AVEIRO, BATALHA, BELMONTE, BOMBARRAL, CADAVAL, CALDAS DA RAINHA, CANTANHEDE, CARREGAL DO SAL, CASTANHEIRA DE PÊRA, CASTELO BRANCO, CASTRO DAIRE, CELORICO DA BEIRA, COIMBRA, CONDEIXA-A- NOVA, CONSTÂNCIA, COVILHÃ, ENTRONCAMENTO, ESTARREJA, FERREIRA DO ZÊZERE, FIGUEIRA DA FOZ, FIGUEIRA DE CASTELO RODRIGO, FIGUEIRÓ DOS VINHOS, FORNOS DE ALGODRES, FUNDÃO, GÓIS, GOUVEIA, GUARDA, IDANHA-A- NOVA, ÍLHAVO, LEIRIA, LOURINHÃ, LOUSÃ, MAÇÃO, MANGUALDE, MANTEIGAS, Centre MARINHA GRANDE, MEALHADA, MEDA, MIRA, MIRANDA DO CORVO, MONTEMOR- O-VELHO, MORTÁGUA, MURTOSA, NAZARÉ, NELAS, ÓBIDOS, OLEIROS, OLIVEIRA DE FRADES, OLIVEIRA DO BAIRRO, OLIVEIRA DO HOSPITAL, OURÉM, OVAR, PAMPILHOSA DA SERRA, PEDRÓGÃO GRANDE, PENACOVA, PENALVA DO CASTELO, PENAMACOR, PENELA, PENICHE, PINHEL, POMBAL, PORTO DE MÓS, PROENÇA-A- NOVA, SABUGAL, SANTA COMBA DÃO, SÃO PEDRO DO SUL, SARDOAL, SÁTÃO, SEIA, SERTÃ, SEVER DO VOUGA, SOBRAL DE MONTE AGRAÇO, SOURE, TÁBUA, TOMAR, TONDELA, TORRES NOVAS, TORRES VEDRAS, TRANCOSO, VAGOS, VILA DE REI, VILA NOVA DA BARQUINHA, VILA NOVA DE PAIVA, VILA NOVA DE POIARES, VILA VELHA DE RÓDÃO, VISEU, VOUZELA, ALCOCHETE, ALMADA, AMADORA, BARREIRO, CASCAIS, LISBOA, LOURES, MAFRA, Lisbon MOITA, MONTIJO, ODIVELAS, OEIRAS, PALMELA, SEIXAL, SESIMBRA, SETÚBAL, SINTRA, VILA FRANCA DE XIRA, ALANDROAL, ALCÁCER DO SAL, ALJUSTREL, ALMEIRIM, ALMODÔVAR, ALPIARÇA, ALTER DO CHÃO, ALVITO, ARRAIOLOS, ARRONCHES, AVIS, AZAMBUJA, BARRANCOS, BEJA, BENAVENTE, BORBA, CAMPO MAIOR, CARTAXO, CASTELO DE VIDE, CASTRO VERDE, CHAMUSCA, CORUCHE, CRATO, CUBA, ELVAS, ESTREMOZ, ÉVORA, FERREIRA DO ALENTEJO, FRONTEIRA, GAVIÃO, GOLEGÃ, GRÂNDOLA, MARVÃO, MÉRTOLA, Alentejo MONFORTE, MONTEMOR-O-NOVO, MORA, MOURA, MOURÃO, NISA, ODEMIRA, OURIQUE, PONTE DE SOR, PORTALEGRE, PORTEL, REDONDO, REGUENGOS DE MONSARAZ, RIO MAIOR, SALVATERRA DE MAGOS, SANTARÉM, SANTIAGO DO CACÉM, SERPA, SINES, SOUSEL, VENDAS NOVAS, VIANA DO ALENTEJO, VIDIGUEIRA, VILA VIÇOSA, ALBUFEIRA, ALCOUTIM, ALJEZUR, CASTRO MARIM, FARO, LAGOA, LAGOS, LOULÉ, Algarve MONCHIQUE, OLHÃO, PORTIMÃO, SÃO BRÁS DE ALPORTEL, SILVES, TAVIRA, VILA DO BISPO, VILA REAL DE SANTO ANTÓNIO,

Figure 2.1 Map of Portuguese NUTS II Regions

Table 2.5 Summary of Regional Composition of Economic Activity

North Centre Lisbon Alentejo Algarve

GDP

1980-2011 100.0000 30.5914 20.0550 37.8427 7.2890 4.2219

1980-89 100.0000 31.3566 20.1121 36.8297 7.6442 4.0574 1990-99 100.0000 30.9163 20.2332 37.5622 7.2579 4.0303 2000-09 100.0000 29.6333 19.9236 38.8550 7.0530 4.5351

Private Investment

1980-2011 100.0000 27.2098 21.1647 40.2233 6.7580 4.6442

1980-89 100.0000 26.5371 21.8878 41.6967 5.7321 4.1463 1990-99 100.0000 26.4555 20.6526 42.9658 5.9801 3.9460 2000-09 100.0000 27.9919 21.2783 37.0182 7.9839 5.7277

Employment

1980-2011 100.0000 35.6761 25.2699 29.0247 6.3434 3.6860

1980-89 100.0000 36.0457 26.1692 27.8952 6.7912 3.0987 1990-99 100.0000 35.9548 25.3440 29.1080 5.9198 3.6734 2000-09 100.0000 35.2519 24.4907 29.7136 6.3559 4.1879

Table 2.6 Regional Composition of Infrastructure Investment Other Road National Municipal Social Highways Transportation Railroads Ports Airports Health Education Infrastructures Roads Roads Infrastructures Infrastructures North 1980-2011 33.33 31.53 36.38 29.92 23.60 21.63 25.87 27.39 30.36 24.31 35.63 1980-89 34.69 34.14 37.76 19.96 24.33 20.46 35.23 24.72 29.17 17.09 35.78 1990-99 32.22 32.09 33.00 32.35 17.02 16.96 17.89 14.41 30.55 27.78 32.69 2000-09 32.14 28.71 37.86 31.14 30.19 28.70 19.74 46.28 31.42 28.26 36.62 Centre 1980-2011 29.76 27.81 27.27 43.91 20.44 26.30 10.62 0.00 25.20 32.17 21.61 1980-89 32.96 32.69 25.03 73.99 19.03 26.64 4.74 0.00 27.75 47.49 17.44 1990-99 24.40 25.91 24.40 20.83 21.63 27.02 3.95 0.00 24.07 26.78 22.36 2000-09 33.21 25.33 31.08 44.16 19.16 22.74 23.61 0.00 24.03 24.09 24.08 Lisbon 1980-2011 16.12 15.60 19.38 12.89 35.37 31.96 37.56 57.08 31.96 29.09 31.80 1980-89 16.55 16.70 18.60 6.06 32.84 28.52 35.82 57.90 32.31 20.62 38.33 1990-99 23.70 21.02 27.17 25.23 36.65 32.78 41.34 72.43 32.64 31.26 33.11 2000-09 8.63 10.16 14.03 4.18 37.79 36.60 38.33 38.91 31.01 33.71 26.60 Alentejo 1980-2011 14.13 17.82 9.98 10.80 15.25 15.65 24.62 0.00 8.14 10.46 6.50 1980-89 9.42 10.74 10.38 0.00 17.00 18.67 23.42 0.00 7.94 12.25 5.42 1990-99 12.82 10.57 8.81 21.49 21.27 20.06 36.34 0.00 8.54 11.18 6.69 2000-09 18.83 29.88 10.29 12.70 7.37 7.45 15.68 0.00 7.86 8.18 7.33 Algarve 1980-2011 6.65 7.25 6.99 2.49 5.35 4.47 1.33 15.52 4.34 3.97 4.46 1980-89 6.39 5.73 8.23 0.00 6.81 5.71 0.80 17.38 2.83 2.55 3.02 1990-99 6.87 10.41 6.63 0.09 3.43 3.18 0.48 13.16 4.21 3.00 5.14 2000-09 7.19 5.92 6.74 7.82 5.49 4.51 2.64 14.80 5.68 5.77 5.38

Table 2.7 Infrastructure Investment by Type of Asset

% of GDP 1978-2009 1980-89 1990-99 2000-09

Road Transportation 1.42 0.89 1.59 1.88 National Roads 0.61 0.39 0.73 0.71 Municipal Roads 0.44 0.40 0.50 0.45 Highways 0.37 0.09 0.36 0.73 Other Transportation 0.46 0.26 0.56 0.57 Railroads 0.34 0.18 0.45 0.43 Airports 0.05 0.04 0.04 0.08 Ports 0.06 0.04 0,07 0.07 Social Infrastructures 1.15 0.97 1.30 1.26 Health 0.55 0.34 0.57 0.75 Education 0.60 0.63 0.73 0.51 Public Utilities 1.99 1.33 1.85 2.53 Water and Wastewater 0.37 0.17 0.32 0.52 Electricity and Gas 0.73 0.55 0.46 1.09 Petroleum Refining 0.22 0.11 0.22 0.18 Telecommunications 0.67 0.49 0.85 0.75

% of Infrastructure Investment 1978-2009 1980-89 1990-99 2000-09

Road Transportation 28.20 25.95 30.35 30.23 National Roads 12.21 11.52 14.09 11.43 Municipal Roads 9.33 11.90 9.47 7.10 Highways 6.67 2,56 6.29 11.76 Other Transportation 8.98 7.57 10.52 9.21 Railroads 6.72 5.17 8.31 6.92 Airports 1.03 1.17 0.81 1.21 Ports 1.23 1.23 1.40 1,08 Social Infrastructures 23.76 28.41 24.52 20.13 Health 10.74 9.89 10.73 11.79 Education 13.02 18.52 13.79 8.16 Public Utilities 39.06 38.04 34.61 40.43 Water and Wastewater 6.80 4.90 5.98 8.17 Electricity and Gas 14.34 15.97 8.48 17.53 Petroleum Refining 4.58 3.22 4.06 2.83 Telecommunications 13.34 13.94 16.12 11.89

Table 2.8 Regional Infrastructure Investments as a % of GDP

Other Total Road Social Transportation Infrastructures Infrastructures Infrastructures Infrastructures

North

1980-2011 0.7796 0.3961 0.0898 0.2937

1980-89 0.5502 0.2551 0.0539 0.2412 1990-99 0.8386 0.4302 0.0785 0.3299 2000-09 0.9538 0.4892 0.1419 0.3227

Centre

1980-2011 0.6639 0.3505 0.0769 0.2365

1980-89 0.5050 0.2468 0.0417 0.2165 1990-99 0.6681 0.3135 0.0986 0.2560 2000-09 0.8380 0.5053 0.0878 0.2449

Lisbon

1980-2011 0.6283 0.1868 0.1348 0.3067

1980-89 0.4535 0.1218 0.0704 0.2613 1990-99 0.8433 0.3169 0.1709 0.3555 2000-09 0.6127 0.1267 0.1712 0.3148

Alentejo

1980-2011 0.3159 0.1798 0.0587 0.0774

1980-89 0.1718 0.0700 0.0367 0.0651 1990-99 0.3682 0.1737 0.1047 0.0898 2000-09 0.3979 0.2817 0.0369 0.0793

Algarve

1980-2011 0.1426 0.0808 0.0196 0.0422

1980-89 0.0854 0.0472 0.0156 0.0226 1990-99 0.1464 0.0855 0.0155 0.0454 2000-09 0.2002 0.1155 0.0272 0.0575

Table 2.9 Summary of Regional Composition of Economic Activity

North Centre Lisbon Alentejo Algarve

GDP

1980-2011 100.0000 30.5914 20.0550 37.8427 7.2890 4.2219

1980-89 100.0000 31.3566 20.1121 36.8297 7.6442 4.0574 1990-99 100.0000 30.9163 20.2332 37.5622 7.2579 4.0303 2000-09 100.0000 29.6333 19.9236 38.8550 7.0530 4.5351

Private Investment

1980-2011 100.0000 27.2098 21.1647 40.2233 6.7580 4.6442

1980-89 100.0000 26.5371 21.8878 41.6967 5.7321 4.1463 1990-99 100.0000 26.4555 20.6526 42.9658 5.9801 3.9460 2000-09 100.0000 27.9919 21.2783 37.0182 7.9839 5.7277

Employment

1980-2011 100.0000 35.6761 25.2699 29.0247 6.3434 3.6860

1980-89 100.0000 36.0457 26.1692 27.8952 6.7912 3.0987 1990-99 100.0000 35.9548 25.3440 29.1080 5.9198 3.6734 2000-09 100.0000 35.2519 24.4907 29.7136 6.3559 4.1879

CHAPTER 3 Methodological Considerations

This chapter is dedicated to methodological considerations and is, therefore, more technical in nature. We start by justifying a dynamic multivariate approach to the issue of estimating the effects of infrastructure investment. We then proceed with preliminary data analysis – unit roots and cointegration tests, with the discussion of the VAR specification. We conclude with two critical point: the discussion of how to identify innovations in infrastructure investment and how to measure their economic impact.

3.1 General Methodological Remarks

General Approach

We use a multivariate dynamic time series methodological approach, based on the use of vector autoregressive (VAR) models, developed in Pereira and Flores (1999) and Pereira (2000,

2001) and subsequently applied to the U.S. in Pereira and Andraz (2003, 2004), to Portugal in

Pereira and Andraz (2005, 2006), and to Spain in Pereira and Roca-Sagales (2003), among others.

This econometric approach highlights the dynamic nature of the relationship between infrastructure investment and the economy. It does so at three distinct levels: i) it explicitly addresses the contemporaneous relationships in the innovations in each variable; ii) it incorporates the dynamic intertemporal feedbacks among the variables; and, iii), it accommodates the existence of long-run equilibrium co-integrating relationships among the variables. Built into the approach is the identification of a causal relationship among the variables rather than simple correlations.

The Underlying Economic Model

In addition, it should be pointed out that although our approach is eminently empirical, it is not a-theoretical. Indeed, our analysis is grounded in a dynamic model of the economy. In this model, the economy uses a production technology based on the use of capital and labor, as well as public infrastructure, to generate output. Given market conditions and the availability of public

infrastructure, private economic agents decide on the level of input demand and the supply of output. In turn, the public sector engages in infrastructure investment based on a policy rule that relates public infrastructure to the evolution of the remaining economic variables. The estimated

VAR system can be seen as a dynamic reduced form system for a production function and three input demand functions – for employment and private investment as well as infrastructure investment [a policy function]. This framework captures the role of public infrastructure investment as a direct input to production and as an externality in production. Infrastructures further affect output indirectly through their effect on the demand for labor and private capital.

Link to the Fiscal Multiplier Literature

In this context, our work is also related to the literature on fiscal multipliers, i.e., on the macroeconomic effects of taxes and government purchases [see, for example, Baunsgaard et al.

(2014) and Ramey (2011), for recent surveys of this literature, and Leduc and Wilson (2012) for a related analysis]. It is in fact very much in the spirit of the approach pioneered by Blanchard and

Perotti (2002), which is based on a VAR approach and uses the Choleski decomposition to identify government spending shocks. We focus, however, on a specific type of public spending – infrastructure investment and the channels through which it affects the economy, as opposed to aggregate spending as it is traditional in this literature. In this sense, this approach is closer in focus to Leduc and Wilson (2012).

3.2 Preliminary Data Analysis

Unit Roots Cointegration

We start by using the Augmented Dickey-Fuller t-tests to test the null hypothesis of a unit root in the different variables. Following Ivanov and Kilian (2005) we use the Bayesian Information

Criterion (BIC) to determine the number of lagged differences, the deterministic components, as

well as the dummies for the potential structural breaks to be included. For the variables in log-levels, the t-statistics are lower, in absolute levels, than the 5% critical values and, therefore, the tests cannot reject the null hypothesis of a unit root. In turn, for the tests applied to the first differences of the log-levels, i.e., the growth rates of the original variables, all critical values are greater, in absolute value, than the 5% critical value. Therefore, we can reject the null hypothesis of unit roots in the growth rates of the variables. We take this evidence as an indication that stationarity in first differences is a good approximation for all the time series under consideration.

It should be pointed out that this empirical evidence is consistent with the conventional wisdom in the macroeconomics literature that private investment, output, employment, and infrastructure investment are stationary in first differences. Although our infrastructure investment series are more disaggregated, the same pattern is not surprising.

Cointegration

We now test for cointegration among output, employment, private investment, and infrastructure investment as well as each one of the four infrastructure investment variables. We use the standard Engle-Granger approach to test for cointegration and the corresponding Gregory-

Hansen test with an unknown breakpoint. We have chosen this procedure over the often used

Johansen approach for two reasons. First, since we do not have any priors that suggest the possible existence of more than one cointegration relationship, the Johansen approach is not strictly necessary. More importantly, however, for smaller samples based on annual data, Johansen's tests are known to induce strong bias in favor of finding co-integration when it does not exist (although, arguably, the Engle Granger approach suffers from the opposite problem).

Following the standard approach, we perform four tests in each case. This is because it is possible that one of the variables will enter the cointegrating relationship with a statistically insignificant coefficient. We do not know, a priori, whether or not this will happen. If it does

happen, however, a test that uses such a variable as the endogenous variable will not pick up the cointegration. Therefore, a different variable is endogenous in each of the four tests. We apply the test to the residuals from the regressions of each variable on the remaining variables. In all of the tests, again following Ivanov and Kilian (2005), the optimal lag structure is chosen using the BIC, and deterministic components and structural breaks are included if they are statistically significant.

This amounts to forty tests, four for each of the five infrastructure investment variable for each of the two tests.

The value of the t-statistics is lower, in absolute value, than the 5% critical values in all but five of the forty cases considered and never in more than one of the four cases considered for each infrastructure type. Moreover, all the test statistics without exception are lower, in absolute value, than the 1% critical values. Thus, our tests cannot reject the null hypothesis of no cointegration.

The absence of cointegration is neither surprising nor problematic and is, in fact, consistent with results in the relevant literature [see, for example, Pereira (2000) and Pereira and Andraz (2003) for the US case, Pereira and Roca (1999) for the Spanish case, and Pereira and Andraz (2005) and

Pereira and Andraz (2006) for the Portuguese case]. On one hand, it is not surprising to find lack of evidence for long-term equilibrium relationships for an economy that has a long way to go in its process of converging to the level of its peers in the European Union. This is so at a more aggregated level and even more so when we consider the data at the regional level and its interaction with aggregate infrastructure investment variables. On the other hand, the absence of cointegration is not problematic as it only implies that a less simultaneous and dynamic approach based exclusively on OLS univariate estimates using these variables’ would lead to spurious results. Specifically, the existence of cointegration means that two variables tend to a fixed ratio that is that in the long-term they grow at the same rate. Absence of cointegration suggests that they do not grow at the same

rate, that is, there are differentiated effects of infrastructure investments on the levels of each of the other variables.

VAR specifications

We have now determined that all of the variables are stationary of first order and that they do not seem to be cointegrated, either at the aggregate level or at the more disaggregated level.

Accordingly, we follow the standard procedure in the literature and estimate the models using the growth rates of the original variables, i.e., growth rates of output, employment, private investment and the relevant infrastructure investment, which is equivalent to using the first differences of the variables in log-levels.

We estimate five VAR models. Each VAR model includes output, employment, and private investment. In addition, it includes a different infrastructure investment variable – one model for aggregate infrastructure investment and one for each of the four different types of infrastructure investment. This means that, consistent with our conceptual arguments, the infrastructure investment variables are endogenous variables throughout the estimation procedure. We use the BIC to determine whether exogenous structural breaks and deterministic components, the constant and trend, should be included in the VAR system.

Our test results suggest that a first order VAR specification with a constant and a trend as well as structural breaks in 1989, 1994, and 2000 is the preferred choice for the models with aggregate infrastructure investment, other transportation, social infrastructure, and utilities. The case of road infrastructure requires a second order VAR with the same deterministic components and structural breaks. The identification of the structural breaks is very meaningful as it shows the relevance of the inception of the first three community support frameworks but the lesser importance of the most recent one, the QREN.

Finally, it should be pointed out that the estimated matrices of variance and covariance of the residuals display in general a statistically significant block-diagonal pattern in which the innovations in the private economic variables show correlations with the infrastructure investment variables that are not statistically different from zero. The exception is utilities, in which case the block diagonal pattern does not exist. This is consistent with the significant privatization efforts of the late 1990s and early 2000s which implies that the bulk of investment in utilities is now private.

The existence of this block diagonal pattern is relevant in that it suggest that innovations in the infrastructure investment variables have contemporaneous correlation with innovations in the other variables that are not statistically different from zero, a matter to be further discussed below.

3.3 Identifying Exogenous Innovations in Infrastructure Investment

The Problem and Our Approach

While the infrastructure investment variables are endogenous in the context of the VAR models, the central issue in determining the economic impact of infrastructure investment is the identification of exogenous shocks to the infrastructure investment variables. This means that we need to identify the shocks to infrastructure investment variables that are not contemporaneously correlated with – that are orthogonal to – shocks in the other variables. These exogenous shocks allow us to identify the effects of innovations in infrastructure investment that are not contaminated by other contemporaneous innovations as they go beyond contemporaneous causality.

In dealing with this issue we draw from the approach typically followed in the literature on the effects of monetary policy [see, for example, Christiano, Eichenbaum and Evans (1996, 1999), and Rudebusch (1998)] and adopted by Pereira (2000) in the context of the analysis of the effects of infrastructure investment.

The Policy Functions

Ideally, the identification of shocks to infrastructure investment which are uncorrelated with shocks in other variables would result from knowing what fraction of the infrastructure investment in each period is due to purely non-economic reasons. The econometric counterpart to this idea is to imagine a policy function which relates the rate of growth of infrastructure investment to the relevant information set; in our case, the past and current observations of the growth rates of the economic variables. The residuals from this policy functions reflect the unexpected component of the evolution of infrastructure investment and are uncorrelated with innovations in other variables.

The Orthogonalization Assumptions

In the central case, we assume that the relevant information set for the policy function includes past but not current values of the economic variables. This is equivalent in the context of the standard Choleski decomposition to assuming that innovations in infrastructure investment lead innovations in economic variables. This means that while innovations in infrastructure investment affect the economic variables contemporaneously, the reverse is not true.

We have two reasons for making this our central case. First, it seems reasonable to believe that the economy reacts within a year to innovations in infrastructure investment decisions. Second, it also seems reasonable to assume that the public sector is unable to adjust infrastructure investment decisions to innovations in the economic variables within a year. This is due to the time lags involved in information gathering and public decision making.

The central results we report in this report are the ones obtained under our preferred orthogonalization strategy, assuming that investment in infrastructures affects all other variables contemporaneously. These are the results to focus upon. These tables also include ranges of variation over all possible statistical orthogonalization strategies under the Choleski decomposition approach. These ranges should not be understood as confidence intervals in that they just literally report the range of variation for all conceivable strategies including therefore all alternatives

statistically possible even if not meaningful from an economic perspective. They just measure the level of ambiguity that could conceivably be introduced by the well-known problem of the dependency of impulse response function in a VAR framework to the contemporaneous correlations among the estimated residuals.

Finally, it should be mentioned that given the orthogonalization strategy discussed above and given the fact that we are only interested in the effects of innovations in infrastructure investments, the ordering of the remaining variables is totally irrelevant as the effects on these variables of innovations in infrastructure investments are invariant to such ordering.

The Regional Dimension

The identification of exogenous innovations in infrastructure investment has an additional dimension at the regional level as we consider both infrastructure investment in the region and infrastructure investment elsewhere. Indeed, we need to consider the contemporaneous relationship between innovations in infrastructure investment in the region and innovations in infrastructure investment outside the region. Here our assumption is that innovations in infrastructure investment outside any given region lead innovations in infrastructure investment in the region. This means that innovations in infrastructure investment outside the region affect contemporaneously innovations of infrastructure investment in the region but the reverse is not true.

This assumption is justified by the fact that, despite the small number of regions, the fraction of infrastructure investment undertaken in any given region is always substantially smaller than the infrastructure investments undertaken in the rest of the country. Besides, the alternative assumption of having investments in a given the region leading would not only be clearly inaccurate as a general matter but would also lead to contradictions across regions, as naturally not all regions could be leading simultaneously.

The Estimated Policy Functions

The policy functions for aggregate infrastructure investment as well as the different types of infrastructure investment relate the evolution of infrastructure investment to the evolution of the economic variables with a one-year lag. The specification of these policy functions was tested. In no case were variables lagged more than one period statistically significant. More importantly, in no case were the contemporaneous values of the economic variables statistically significant. This confirms our assertion that our central case scenario is the most plausible also from an econometric perspective.

For aggregate infrastructure investment, as well as for each of the individual infrastructure types, the policy functions suggest that there is no feedback from the other variables to the infrastructure investment variable. This also means that these variables do not Granger-cause infrastructure investment, and infrastructure investment is truly an exogenous variable. The exogeneity of infrastructure investment decisions in Portugal is easily explained by the fact that, for most of the sample period, these decisions were closely related to EU structural and cohesion policies.

3.4 Measuring the Effects of Innovations in Infrastructure Investment

The Exogenous Shock

We consider the effects of one-percentage point, one-time shocks in the rates of growth of the different types of infrastructure investments on output, employment, and private investment.

We expect these temporary shocks to have temporary effects on the growth rates of the other variables and, therefore, to have permanent effects on the levels of these variables. Since the temporary effects are different for different variables, the level effects will also be different. This implies changes in the long-term observed ratios between the different variables, which is consistent with the absence of evidence of co-integration.

The Accumulated Impulse Response Functions

We compute the accumulated impulse-response functions as well as the corresponding 90% bands that characterize the likelihood shape of the effects. These figures show the cumulative effects of shocks on infrastructure investments based on the historical record of thirty two years of data as filtered through the VAR and the reaction function estimates described above. We observe that without exception the accumulated impulse response functions converge within a relatively short time period suggesting that most of the growth rate effects occur within the first ten years after the shocks occur. Naturally the level effects are permanent and continue after this convergence.

Accordingly, we present the accumulated impulse response results for a twenty-year horizon, a period reflecting the approximate life expectancy of many infrastructure assets.

Error Bands and Significance

The error bands surrounding the point estimates for the accumulated impulse responses convey uncertainty around estimation and are computed via bootstrapping methods. We consider

90% intervals although bands that correspond to a 68% posterior probability are the standard in the literature (Sims and Zha, 1999). Employing one standard deviation bands narrows the range of values that characterize the likelihood shape and only serves to reinforce and strengthen our results.

Further evidence exists that nominal coverage distances may under represent the true coverage in a variety of situations (Kilian, 1998). Similarly, placing too great a weight on the intervals presented in evaluating significance is unwarranted in all but the most extreme cases. Thus, the bands presented are wider than the true coverage would suggest. From a practical perspective, when the 90% error bands for the accumulated impulse response functions include zero in a way that is not marginal (to allow for the difference between the 90% and 68% posterior probability) we consider that the effects are not significantly different from zero.

The Measurement of the Total Effects

To measure the effects of infrastructure investment we calculate the long-term elasticities and the long-term marginal products of the different economic variables with respect to each type of infrastructure investment. However, these concepts are used in a way that departs from conventional definitions because they are not based on ceteris paribus assumptions, but include all the dynamic feedback effects among the different variables. That is, they measure both the direct and dynamic effects of infrastructure investment on the economic variables and the indirect dynamic effects of infrastructure investment through changes in the evolution of these variables. This while considering the dynamic feedbacks from these variables to the evolution of infrastructure investment. Naturally, these are the relevant concepts from the standpoint of policy making.

The Long Term Elasticities

These long-term accumulated elasticities are to be interpreted as the total accumulated percentage point long-term change in the other variables for a one-percentage point accumulated long-term change in infrastructure investment.

Long Term Marginal Products

The long-term accumulated marginal products of infrastructure investment measure the

Euro change in private investment and output, and the number of permanent jobs created, for each additional Euro of investment in infrastructures. The marginal product figures are obtained by multiplying the average ratio of each variable to infrastructure investment by the corresponding elasticity. Accordingly, the marginal product figures are the most interesting from a policy perspective as they capture the effects of scarcity in addition to the effects of the coupling of infrastructure investment and the economy as reflected in the elasticities figures.

In computing the marginal products, we use the average ratio of the economic variable to the level of infrastructure investment over the last ten years of the sample. This allows the marginal product figures to reflect the relative scarcity of the different types of infrastructures at the margin

of the sample period without letting these ratios be overly affected by business cycle factors. In addition, to measure the effects on the marginal products of evolution of the relative scarcity, we also calculate the marginal product figures using rolling ten year averages starting for the beginning of the sample period.

The marginal product figures at the regional level are weighted figures. This means that the raw marginal products for each region are multiplied by the average share of regional infrastructure investment in aggregate infrastructure investment for the last ten years. This allows us to interpret the sum on the regional marginal products as the combined effect of one Euro in aggregate infrastructure investment given the regional decomposition of infrastructure investment. Therefore, the sum of the disaggregated figures obtained from the regional-specific models is directly comparable to the marginal product figure for the whole country.

Annual Rates of Return

The rate of return is calculated from the marginal product figures by assuming a useful life schedule for railroad capital assets consistent with its observed implicit depreciation rate. The rate of return is the annual rate at which an investment of one Euro would grow over the lifetime of the asset to yield its accumulated marginal product.

CHAPTER 4 Identifying Priorities in Infrastructure Investment

Our goal is to identify priorities in infrastructure investments, i.e., areas of infrastructures investments with virtuous economic and budgetary effects. We find that investments in other transportation infrastructures – railroads, ports and airports – and social infrastructures – health and education infrastructures – have the largest effects with long-term multipliers of 15.00 and 8.45, respectively. Investments in road transportation – roads and freeways - and on utilities – electricity, gas, water, refineries, and telecommunications – induce much smaller effects with multipliers of 2.75 and 3.52, respectively. We also show that for other transportation and social infrastructure investments, the short term effects are small relative to the accumulated effects and yet, in absolute terms, they exceed the long-term effects for road transportation and utilities. Finally, we show that investments in other infrastructures and in social infrastructures will pay for themselves in the form of long term enhanced tax revenues under rather reasonable effective tax rates. Overall, we have clearly identified other transportation infrastructures and social infrastructures as the key target areas for policy intervention in this context.

4.1 Introduction

Since 1986, with the accession of Portugal to the European Union, economic policies to promote growth have focused on investments in infrastructures, primarily on road infrastructure.

Over the last decade, however, things have changed. With fewer EU funds available for infrastructure investment and the problematic and very unpopular utilization of public-private partnerships, financing for infrastructure investment must increasingly come from the public budget.

This could not have come at a worse time. The recent sovereign debt crisis and quest for austerity and budgetary consolidation have resulted in an ongoing economic recession coupled with persistently high public debt levels. Infrastructure investments are often perceived of as the most politically expedient areas for budgetary cuts due to the distribution of potential benefits and costs through time and the diffusion of these benefits over the population. Indeed, as the current crisis reached its peak, infrastructure investment has been the expenditure category with the largest decline in the public budget. Not surprisingly, it reached in recent years their lowest levels in decades.

And yet, the dual needs for public policies to promote economic performance and for debt consolidation remain. As the country seems to start coming out of the dark in terms of the economic woes and with a persistent need to improve long term employment and productivity conditions, the question again arises on how to define priorities for achieving these goals.

From our perspective, the central issue is the role that infrastructure could or should play in achieving these goals. The criticisms of and suspicion about infrastructure investment is widespread.

Long gone are the days when infrastructure investment was seen as a panacea. But critical questions remain. Is it still worth investing in infrastructures? And if so which types of assets? What are the effects of infrastructure investment on labor productivity, employment, private investment, and output? What is the relative importance of more short term demand effects versus the long term supply side effects of these investments? What are the ramifications of these investments for the long term prospects of fiscal consolidation?

In this chapter we analyze the impact of public infrastructure investment on economic performance in Portugal and address the questions above, first at the aggregate level and then considering four main types of infrastructure investments – road transportation infrastructures, other transportation infrastructures, social infrastructures, and utilities. In doing so we intend to bring a level of clarity to the debate on defining strategic priorities as far as infrastructures investments are concerned. A clarity based on empirical evidence that will allow the debate to be based on facts not preconceived notions.

Conceptually, the ultimate objective of this chapter is to estimate the long term multipliers of the different types of infrastructure investment in a way that incorporates information about their relative scarcity. The magnitude of the respective marginal products will be a good indicator of the relative economic relevance of the investments. Equally important, their magnitude will also determine if the investments will be self-financing or not over the long-term in the form of

additional tax revenues. While a positive marginal product by itself suggests a meaningful investment from an economic perspective, a sufficiently large marginal product suggests also a meaningful investment from a budgetary perspective.

4.2 On the Empirical Evidence

On the Elasticities with Respect to Infrastructure Investments

The elasticities are reported in Table 4.1 and are obtained from the accumulated impulse response functions as in Figure 4.1 and Figure 4.2. The results at the aggregate level suggest that investment in infrastructure crowds in both private investment and employment. Indeed, we estimate that the elasticity of private investment with respect to aggregate infrastructure investment is 0.6205, and the elasticity of employment with respect to aggregate infrastructure investment is

0.0881. Given the positive effects on private investment and on employment, it follows naturally a positive impact on output. Indeed, we find that aggregate infrastructure investment has a positive effect on output, with an elasticity of 0.1712.

At a more disaggregated level, considering the elasticities with respect to the four types of infrastructure, we observe that they are all positive and within relatively narrow ranges. The elasticities of private investment range from 0.2292 for road transportation to 0.3911 for social infrastructure; the elasticities of employment range from 0.0169 for road transportation to 0.0547 for public utilities; and, the elasticities of output from 0.0496 for road transportation to 0.0962 for public utilities. It should be noted that in general the elasticities are lower for road transportation and other transportation on one hand than for social infrastructures and public utilities on the other, reflecting a stronger structural connection to the rest of the economy on the part of the latter.

It should be noted that with one exception, the results above are all statistically different from zero, and strongly so, as suggested by the standard deviation bands around the accumulated impulse response functions. The exception is road infrastructures in which case the results for employment and output are not statistically different from zero with our more stringent confidence bands but would be significant be with more conventional levels and less stringent confidence intervals.

On the Effects of Infrastructure Investments on Labor Productivity

The effects of infrastructure investment on labor productivity can be determined from the relative magnitudes of the output and employment elasticities with respect to infrastructure investment. To the extent that changes in infrastructure investment have a larger effect on output than on employment, this implies that these investment activities increase output per worker and therefore the productivity of the workforce. The effects of infrastructure investments on labor productivity are depicted in Figure 4.3.

The elasticity of output with respect to aggregate infrastructure investment is significantly larger than the elasticity of labor which implies that investment in infrastructures has led to a significant increase in labor productivity in Portugal. At a more disaggregated level we see important albeit more tenuous effects and differences. Investments in social infrastructures and public utilities have the largest effects on labor productivity, 0.0435 and 0.0415, respectively. In turn, road transportation and other transportation have lower but still very significant effects, 0.0327 and

0.0393, respectively.

Marginal Products with Respect to Infrastructure Investment

While the elasticity figures are interesting in and of themselves, the marginal product figures are a better measure of the relative effects of different types of infrastructure investments and the relevant measure from a policy perspective. This is because they reflect the relative scarcity of the

different types of infrastructure investment at the margin of the sample period. They give therefore a direct measure of the long-term accumulated impact to be expected from new investments. The marginal products of the different infrastructure investments are reported in Table 4.2 and depicted in Figure 4.4.

At the aggregate level, for total infrastructure, we find a marginal product of private investment of €2.52. This means that at the aggregate level, infrastructure investment crowds in private investment and that one Euro of additional infrastructure investment will induce, in the long term, an accumulated total of €2.52 of private investment. In turn, our results suggest that at the aggregate level, 52.3 additional permanent jobs are created in the long term for each additional one million Euros in infrastructure investment.

In terms of output we estimate an aggregated marginal product of €2.77. This implies that the increase of one Euro in infrastructure investment leads to a total accumulated increase of €2.77 in output over the long term. This marginal product implies a rate of return of 5.2% assuming an average lifespan of the infrastructure assets of twenty years. In addition, it suggests that one Euro in aggregate infrastructure investment would pay for itself in the long term in the form of increased tax revenues for an effective tax rate in the economy in excess of 36.1%.

At this aggregate level, we would conclude that while there are positive economic effects from additional infrastructure investments they are relatively small and with a rate of return below what would likely be required by the private sector. More importantly the positive economic effects are certainly not strong enough to unambiguously guarantee that these investments would pay for themselves in the form of future additional tax revenues.

Naturally the more aggregate results are just indicative. Let’s consider now the magnitude of the effects at a more disaggregated level to identify more nuanced patterns. Here we see that the largest positive effects of infrastructure investment on private investment come from other

transportation and social infrastructure, €12.62 and €8.66, while the largest effects on employment come from other transportation, with 271 long-term jobs per million Euros, and from social infrastructure with 169 permanent jobs per million Euros.

The same pattern can be observed in terms of the impact of the different types of infrastructure on output. The largest effects come from investment in other transportation infrastructures, with a marginal product of €15.00 and social infrastructure with a marginal product of €8.45. These values imply rates of return over thirty years of 14.5% and 11.3%, for other transportation and social infrastructures, respectively, rates which are very competitive by market standards. The multipliers and rates of return for road transportation and of public utilities are significantly smaller.

On the Potential Budgetary Effects

From a policy perspective these more disaggregate effects are very informative. All marginal products are positive so that in our taxonomy all infrastructure investment types fall clearly in either case two or three, i.e., they induce relevant economic effects. The only question is what to expect in terms of budgetary effects. Here there is a significant difference. While investments in other transportation and in social infrastructures would be self-financing even for very low effective tax rates, investments in road transportation and in public utilities would only come close to paying for themselves under effective tax rates in excess of 36.3% and 28.5% respective. These two cases are too marginal to be confident about their positive budgetary effects in the long term.

Rates of Return of Infrastructure Investments

An alternative but informative way of looking at these figures is to think that under a linear distribution of the long term effects over a lifetime of thirty years and under an effective tax rate on the additional output of 25%, investments in other transportation infrastructures and social infrastructures would take eight and fourteen years to pay for themselves, respectively. In turn,

investments in road transportation infrastructures and in public utilities would take forty four and thirty three years, and, therefore, a time frame longer than the reference lifetime of the asset of thirty years. The relevant figures are reported in Table 4.3.

The policy implication is critical, while reducing investment in road infrastructures and in public utilities may help the public budget, cuts in other transportation investments and in social infrastructure investments will not; they will, in fact, have a detrimental effect on the public budget.

Long-term Marginal Products versus Effects on Impact

From a methodological perspective, it is possible to decompose the long-term effects of infrastructure investments into two effects: the effect on impact and the long-term accumulated effect. This is a very important distinction from a policy perspective. In fact, infrastructure investment can be expected to have two types of effects, short-term demand side effects that are induced by implementation of the investment efforts, mainly the construction of the infrastructure and how it reverberates in the economy. In addition, there are the long-term effects that in addition to this short-term demand effects include the impact that the availability of the infrastructure has on the economic performance of the country, that is, the longer-term supply side effects.

In Table 4.4 we report the decomposition of the marginal products of infrastructure investment in a way that in addition to the total accumulated long-term effect, it shows how much of this effect is due to a demand side impact effect, the difference being naturally the longer-term supply-side effect.

For total infrastructure investment, we estimate significant effects on impact of around 40% of the total effect for private investment, employment, and output. This means that a very sizable part of the economic as well as budgetary effects would occur almost immediately.

When we consider the four main types of infrastructure investment we get a better picture.

In terms of road transportation, the bulk of the effects on private investment and output, 59%

specifically, are on impact, that is, in the year of construction. This suggests that the declining pattern of small and decreasing marginal products have pretty much eroded the long-term supply side benefits of these infrastructures and most of what is left is short-term demand side effects related to construction. An exception to this pattern is the employment effects. The short term employment effects are a very small part of what is anyway a very small long term effect.

For other transportation, the short term effects are about one-third of the total effects.

This means that aside from the short-term demand side effects related to construction there are also quite sizable long-term supply side effects to the economy. It could be noted that in terms of their magnitude, the short term effects on impact of other infrastructure are larger than the overall long terms effects of either road transportation or utilities.

In the case of social infrastructures, the other area of significant economic and budgetary potential, the short term effects are also moderate, about 45% for private investment, 26% for employment and 35% for output. This means that the long term supply-side effects also dominate but to a lesser extent than in the case of other transportation. Equally interesting is that all of the short-term effects of social infrastructure investments are larger than the total effects of both road infrastructure and utilities, in this case with the exception of the total output effects of utilities.

Finally, for public utilities, we find that the short-term demand side effects tend to be stronger than for other transportation and social infrastructure but less than road transportation.

From a policy perspective these results suggest that the types of infrastructure investment with the largest accumulated effects – other transportation and social infrastructures – are also the ones where the short-term effects are in relative terms the least important. In absolute terms, however, we see that they dominate also in terms of the magnitude of the short-term effects. This means that even if the objective of infrastructure investment were simply to be employed as a demand side tool to promote employment and growth, investments in other transportation and

social infrastructures would still be the best bets for the public sector. Furthermore, and from a budgetary perspective, these investments would pay for themselves on impact for effective tax rates as low as 25% and 33%, respectively.

Long-Term Marginal Products and the Relative Scarcity of Infrastructure Capital

Economic theory suggests that a pattern of diminishing marginal return to infrastructure capital should be expected, meaning that with a more developed stock of infrastructure incremental additions through investment will have progressively smaller economic effects. In this context, it is important to recall that the marginal products with respect to infrastructure investment presented in this work are computed using infrastructure investment and the other relevant economic data for the last ten years. This recent period is chosen to reflect the most recently available data and accurately reflect the effect of infrastructure scarcity on the economic impact of infrastructure investment at the margin. A ten year period is chosen to ensure that the results are not overly affected by business cycle fluctuations.

To assess the evolution of the effects of scarcity on the measurement of the marginal products with respect to infrastructure investment throughout the sample period, we present now the marginal products using alternative time periods. Specifically, we consider 10-year moving averages beginning in 1978 thereby tracing the evolution of the marginal products as reflecting the evolution of the relative scarcity of the infrastructure asset. This information is particularly useful in depicting the specific patterns of diminishing marginal productivity of infrastructure investment in the different cases and specifically how fast it is decreasing. This is fundamental in evaluating the potential for policies to encourage the development of additional infrastructures.

The evolution of the marginal products for total infrastructure investment and the four main types of infrastructure assets are presented in Figure 4.5 and Figure 4.6. As a point of reference, the values for the marginal products we have presented and discussed above are the very last points

in the different figures, that is, are the points where each curve ends using averages for the last ten years of the sample.

The diminishing pattern is clear in all cases. In terms of the effects on private investment, with current values for the marginal products of investment, employment and output now at about

60%, 37%, and 55% respectively of the values implied by the scarcity in the earlier years of the sample.

Considering the four main types of infrastructure assets provides a very rich differentiation amongst the evolution of the marginal products of the different infrastructure investment. Indeed, for road transportation, we see a pattern of steady decline of marginal products, one that is more pronounced earlier in the sample period than over the last ten years. Indeed, the marginal products at the end of the sample are just 50%, 34%, and 47%, for investment, employment, and output, of the values observed earlier in the sample. This is consistent naturally with a pronounced effort throughout the sample in the development of road transportation infrastructures and the concomitant reduction of the relative scarcity of these infrastructures. The case of public utilities is similar both qualitatively and quantitatively to the case of road transportation we just described.

For other transportation infrastructures as well as for social infrastructures we also see an overall pattern of decreasing marginal returns although less pronounced and indeed with a small inflection point after the early 2000s. The levels of marginal productivity measured at the end of the sample period are actually remarkably close to the levels as measure at the end of the 1990s. This is consistent with the idea that these infrastructures were the focus of attention mostly in the latter part of the sample but even then they did not play center stage.

These patterns are relevant from a policy perspective. The marginal products for road infrastructure and public utilities tend to be small currently and show throughout the sample a strong declining pattern. The expectation therefore should be that future infrastructure investments

in these areas would generate small and progressively declining effects. Their economic effect is becoming smaller and their budgetary effects moving more and more into the potentially detrimental region. Therefore, we reinforce the idea presented above that these do not seem to be key areas for public policy efforts. In turn, the opposite is true for investments in other transportation and social infrastructure. These show large and relatively stable marginal products over the last decade adding to their desirability both in economic and budgetary terms.

4.3 Summary and Concluding Remarks

Summary

The goal of this chapter is to identify priorities in infrastructure investments in Portugal, i.e., areas of infrastructures investments with virtuous economic and budgetary effects. We employ a vector autoregressive approach to estimating the elasticity and marginal product of public infrastructure investment on private investment, employment and output. This approach is consistent with the argument that the analysis of the effects of infrastructure investment on economic variables requires the consideration of dynamic feedback effects among the different variables.

We start by establishing that overall infrastructure investments have a moderate positive impact on private investment, employment and output. More importantly, we proceed to show that these aggregate effects hide a wide variety of asset-specific results. We find that investments in other transportation – railroads, ports and airports – and social infrastructures – health facilities and educational structures, have the largest effects with long-term multipliers of 15.00 and 8.46, respectively. Investments in road transportation – roads and freeways – and in utilities – electricity, gas, water, refineries, and telecommunications – induce much smaller effects with multipliers of 2.75 and 3.52, respectively. We also show that for other transportation and social infrastructure

investments, the short term effects are small relative to the accumulated effects and yet in absolute terms they exceed the long-term effects for road transportation and utilities. Finally, we show that under rather reasonable effective tax rates investments in other infrastructures and in social infrastructures will pay for themselves in the form of greater tax receipts over the long term.

Policy Implications

Overall, we have identified other transportation infrastructure and social infrastructure as the key target areas for policy intervention in this area of infrastructure development. They have the advantage of generating not only positive economic effects but also favorable budgetary impact.

Moreover these positive effects on the economy and the budget are felt in the very short term although they continue in the longer term – the point is that the authorities do not have to wait long for the positive effects to be evident. The focus on these two areas of infrastructure investment therefore, fits perfectly into the policy and political economy conundrum of trying to promote long term growth in a context of rather delicate budgetary situation and even more fragile political balance.

Our recommendation for a strategic focus on other transportation infrastructure is consistent with the concern that investments in railroads and ports have been neglected and the investments in railroads have been rather insufficient. Our results give substance to the recommendations of a government appointed group to identify heuristically priorities in transportation infrastructure investment [see Ministério da Economia (2014)]. Their recommendation focused mostly on railroad and port investments.

In turn, our recommendation for a strategic focus on social infrastructures needs some elaboration. First, it needs to be clear that we are not talking about investing in education and health in general but rather on health and education infrastructures. There is a growing body of the international evidence suggesting that these infrastructures embody technological advances and lead

to high quality job creation. This is also consistent with a growing interest of the private sector in investments in health infrastructures through the mechanisms of public-private partnerships.

Finally, our recommendation to move away from road infrastructure investment fits into and substantiates – by giving ample empirical support – the common wisdom that this is an exhausted strategy. It is also consistent with the view of the European Commission in their refusal to allocate any further community financing in the context of the structural policy and cohesion programs to these types of projects. Our recommendation to move away from investments in utilities is also consistent with the fact that a lot of the sector has been privatized and therefore these investments are progressively out of the jurisdiction of the public sector and will be undertaken only to the extent that private profitability is guaranteed.

Table 4.1 Elasticities with respect to Infrastructure Investment - Main Types of Assets

Private Investment Employment Output

Infrastructure Investment 0.6205 0.0881 0.1712 [0.0249,0.6205] [0.0035,0.0881] [-0.0150,0.1712]

Road Transportation Infrastructure 0.2292 0.0169 0.0496 [-0.0803,0.2292] [-0.0238,0.0169] [-0.0381,0.0496]

Other Transportation Infrastructure 0.2596 0.0379 0.0772 [0.0881,0.2596] [0.0130,0.0379] [0.0275,0.0772]

Social Infrastructures 0.3911 0.0521 0.0956 [0.0117,0.3911] [0.0127,0.0521] [-0.0189,0.0956]

Utilities 0.3156 0.0547 0.0962 [0.020,0.3156] [0.0024,0.0547] [0.0006,0.0962]

Note: In parentheses we present the range of variation under the different Choleski orthogonalization strategies. These ranges do not represent and should not be understood as confidence intervals. They consider the range of variation for all statistically possible strategies, which we ruled out on economic grounds.

Table 4.2 Marginal Product of Infrastructure Investment - Main Types of Assets Private Investment Employment Output

Infrastructure Investment 2.5115 0.0523 2.7692 [0.1007,2.5115] [0.0021,0.0523] [-0.2419,2.7692]

Road Transportation Infrastructure 3.1801 0.0343 2.7492 [-1.1145,3.1801] [-0.0484,0.0343] [-2.1138,2.7492]

Other Transportation Infrastructure 12.6197 0.2706 14.9993 [4.2817,12.6197] [0.0925,0.2706] [5.3426,14.9993]

Social Infrastructures 8.6569 0.1692 8.4546 [0.2594,8.6569] [0.0413,0.1692] [-1.6690,8.4546]

Utilities 2.8891 0.0735 3.5198 [0.1828,2.8891] [0.0033,0.0735] [0.0212,3.5198]

Table 4.3 Rate of Return on Infrastructure Investment - Main Types of Assets Lifespan of 20 years 30 years 40 years 50 years

Infrastructure Investment 5.22 3.45 2.58 2.06 Road Transportation 5.19 3.43 2.56 2.04 Other Transportation 14.50 9.45 7.00 5.57 Social Infrastructures 11.26 7.37 5.48 4.36 Utilities 6.49 4.28 3.20 2.55

Table 4.4 Long-term Marginal Products versus Effects on Impact - Main Types of Assets GFCF EMP GDP

Infrastructure Investment Long Term 2.51 0.05 2.77 Short Term 1.05 0.02 1.12

(in % of total) (42%) (44%) (40%)

Road Transportation Infrastructure Long Term 3.18 0.03 2.75 Short Term 1.88 0.01 1.63

(in % of total) (59%) (19%) (59%)

Other Transportation Infrastructure Long Term 12.62 0.27 15.00 Short Term 3.75 0.09 4.07

(in % of total) (30%) (33%) (27%)

Social Infrastructures Long Term 8.66 0.17 8.45 Short Term 3.87 0.04 3.00

(in % of total) (45%) (26%) (35%)

Utilities Long Term 2.89 0.07 3.52 Short Term 1.03 0.04 1.35

(in % of total) (36%) (55%) (38%)

Figure 4.1 Accumulated Impulse Response Functions with respect to Infrastructure Investment Accumulated Response of Private Investment 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 -0.4 -0.6 -0.8 -1.0 0 2 4 6 8 10 12 14 16 18 20

Accumulated Response of Employment 0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15 0 2 4 6 8 10 12 14 16 18 20

Accumulated Response of GDP 0.25 0.20 0.15 0.10 0.05 0.00 -0.05 -0.10 -0.15 -0.20 -0.25 0 2 4 6 8 10 12 14 16 18 20

Figure 4.2 Accumulated Impulse Response Functions with respect to Infrastructure Investment Private Investment Employment GDP

1.0 0.15 0.25

0.10 0.15 0.5 0.05 0.05 0.0 0.00 -0.05 -0.05 -0.5 -0.10 -0.15

Road Infrastructures Road -1.0 -0.15 -0.25 0 10 20 0 10 20 0 10 20

1.0 0.15 0.25 0.10

0.15 0.5 0.05 0.05 0.0 0.00 -0.05 -0.05 -0.5 -0.15

Infrastructures -0.10

Other Transportation Transportation Other -1.0 -0.15 -0.25 0 10 20 0 10 20 0 10 20

1.0 0.15 0.25

0.10 0.15 0.5 0.05 0.05 0.0 0.00 -0.05 -0.05 -0.5 -0.10 -0.15

Social Infrastructures Social -1.0 -0.15 -0.25 0 10 20 0 10 20 0 10 20

1.0 0.15 0.25

0.10 0.15 0.5 0.05 0.05 0.0 0.00 -0.05 -0.05 Utilities -0.5 -0.10 -0.15

-1.0 -0.15 -0.25 0 10 20 0 10 20 0 10 20

Figure 4.3 Effects of Infrastructure Investment on Labor Productivity

Figure 4.4 Effects of Infrastructure Investment - Main Types of Assets Private Investment 12.62 8.66

2.51 3.18 2.89

Aggregate Road Other Social Public Works Infrastructure Transportation Transportation Infrastructures Infrastructure Infrastructure

Employment 0.27

0.17

0.07 0.05 0.03

Aggregate Road Transportation Other Social Public Works Infrastructure Infrastructure Transportation Infrastructures Infrastructure

Gross Domestic Product 15.00

8.45

2.77 2.75 3.52

Aggregate Road Other Social Public Works Infrastructure Transportation Transportation Infrastructures Infrastructure Infrastructure

Figure 4.5 Marginal Productivity using Alternative Sample Periods Private Investment 5 4 3 2 1 0

Employment 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00

GDP 6 5 4 3 2 1 0

Figure 4.6 Marginal Productivity using Alternative Sample Periods – by Asset Type Private Investment Employment GDP 7 0.12 6

6 0.10 5 5 0.08 4 4 0.06 3 3 2 0.04 2 1 0.02 1 0 0.00 0

Road Infrastructures Road

1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 25 0.80 35 0.70 30 20 0.60 25 15 0.50 20 0.40 10 0.30 15 10 5 0.20 0.10 5

0 0.00 0

Infrastructures Other Transportation Other

Other Transportation Transportation Other

1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 12 0.30 12 10 0.25 10 8 0.20 8 6 0.15 6 4 0.10 4 2 0.05 2 0 0.00 0

Social Infrastructures Social

1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 7 0.25 8 7 6 0.20 5 6 4 0.15 5 4 3 0.10 3 2 0.05 2 1 1

Utilities 0 0.00 0

CHAPTER 5 Is All Infrastructure Investment Created Equal?

In this chapter we analyze the effects of infrastructure investment on economic performance in Portugal using a newly developed data set. We employ a vector autoregressive approach to estimate the effects on private investment, employment and output. We find that the largest long-term accumulated effects come from investments in railroads, ports, airports, health, education, and telecommunications. For all of these infrastructures, the output multipliers are sizable enough to suggest that these investments would pay for themselves in the form of additional tax revenues. We find also that for investments in airports and health infrastructures the bulk of the effects are short-term demand side effects while for railroads and health the bulk of the effects come from long-term supply side effects. Finally, investments in health and airports show a clear pattern of decreasing marginal returns with railroads, ports, and telecommunications showing a relative stable pattern. In terms of the other infrastructure assets, we find that the economic effects of investments in municipal roads, highways, and electricity and gas are not significant or relevant. Investments in national roads, waste and wastewater, and refinery infrastructures have positive economic effects but not large enough to also have a positive budgetary effects. Clearly, not all infrastructure investments are created equal along several and rather relevant dimensions from a policy perspective.

5.1 Introduction

Any mention of infrastructure investment in Portugal nowadays is met with scorn and criticism both from large areas of the political spectrum and maybe even more so from the general public. Infrastructure investment has entered the Portuguese lexicon as evoking excess, wastefulness and special interests. And yet it was not always like this. Quite the opposite.

In fact, since 1986, with the accession of Portugal to the EU, economic policies to promote growth have focused, in no small measure, on investment in infrastructures, with a heavy focus on road infrastructure. EU structural funds were a major source of financing through the late 1990s and the burden on the domestic public budget was therefore limited. These were the glorious days of infrastructure investment. These investments were viewed as the cure to all economic problems. In practice, these efforts literally changed the landscape of the country.

After the late 1990s, however, things started to change. With fewer EU funds available for infrastructure investment the government resorted to the widespread use of public-private partnerships as a mechanism to transform investments that would otherwise be an immediate burden on the public budget into commitments to annuities to be paid from the public budget over time. These partnerships turned out to be poorly understood, their implementation problematic and they soon became very unpopular among the general public.

The recent sovereign debt crisis and austerity in the quest for budgetary consolidation resulted in an ongoing economic recession coupled with persistently high public debt levels. In the public mind, infrastructure investments were a major factor triggering these events – something that can arguably be showed to be totally off the mark. Furthermore, due to the distribution of potential benefits and costs through time and the diffusion of these benefits over the population, infrastructure investments are often perceived of as the most politically expedient areas for budgetary cuts. Indeed, as the current crisis reached its peak, infrastructure investment led the pack as the category with the largest decline in the public budget. Not surprisingly, infrastructure investment reached in recent years their lowest levels in decades.

And so here we are. Criticisms of and suspicions about infrastructure investment are widespread. Certainly, there are ample reasons to be cautious. Many white elephant infrastructure investment projects are easy to name and mismanagement and corruption in public-private partnerships are a matter of great concern. Long gone are the days when infrastructure investment was seem as a panacea and certainly the idea that the country does not need more roads and highways has its appeal.

And yet, the dual needs for public policies to promote economic performance and debt consolidation remain. As the country seems to start emerging from very significant economic woes, with a persistent need to improve employment conditions and labor productivity, the question again

arises as to how to define priorities to achieve these goals. From our perspective, the central issue is the role that infrastructure investment could or should play in achieving these goals.

So the critical questions remain: Is it still worth to invest in infrastructures? And if so which types? What are the effects of infrastructure investment on labor productivity, employment, private investment, and output? What is the relative importance of more short term demand effects versus the long term supply side effects of these investments? What are the ramifications for the long term prospects of fiscal consolidation? Ultimately, we want to answer the question: when it comes to their economic and budgetary impact are all types of infrastructure investment created equal? Which ones should be sidestepped in agreement with the popular conventional wisdom and which ones should be encouraged despite negative popular views?

In this chapter we analyze the impact of infrastructure investment on economic performance in Portugal and address the questions above, first at the aggregate level and then considering twelve types of infrastructure investments – three types of road transportation infrastructures (national roads, municipal roads, and highways), three types of other transportation infrastructures (railroads, ports, and airports), two types of social infrastructures (education and health infrastructures), and four types of utilities (water and wastewater, electricity and gas, petroleum refineries, and telecommunications). In doing so we intend to bring a level of clarity to the debate on defining specific strategic priorities as far as infrastructures investments are concerned. A clarity based on empirical evidence that will allow the debate to be based on facts not preconceived notions.

5.2 The Empirical Results

Long-Term Elasticities

The long term elasticities are reported in Table 5.1 and are obtained from the accumulated impulse functions depicted in Figure 5.1 to Figure 5.4. Each type of infrastructure investment has

a positive effect on private investment except for investments in ports. The positive elasticities are within a relatively narrow range – from 0.4321 for health infrastructures and 0.3000 for national roads to 0.0177 for refineries. The same is true in terms of the effects on employment, in which case the only negative effect comes from investment in national roads. All positive employment elasticities range again from 0.0587 for health infrastructures, 0.0268 for education and 0.0295 for telecommunications to 0.0031 to refineries and electricity and gas infrastructures. Accordingly, our estimates suggest that in the overwhelming majority of the cases infrastructure investments crowd in, albeit with different intensity, both private investment and employment.

Naturally, the effects of infrastructure investments of the different types on output are all positive. The strongest coupling effects come from investments in health infrastructures and telecommunications infrastructures with elasticities of 0.1166 and 0.0707, respectively. The lowest elasticities are for municipal roads, ports, petroleum refineries, and electricity and gas all with elasticities around 0.0050.

To put things in a statistical context, the overwhelming majority of the accumulated long- term elasticities are statistically different from zero as implied by the standard deviation bands around the accumulated impulse response function estimates. The exceptions are the elasticity of private investment with respect to investments in national roads as well as the elasticities of private investment, employment, and output with respect to investments in municipal roads. All of the remaining elasticities, even when very small, are statistically different from zero.

Long-term effects on labor productivity

The effects of infrastructure investment on labor productivity can be obtained from the values of the elasticities, as the sign of the change in the output to labor ratio is the same as that of the difference between the elasticities of output and employment. We start by observing that for all of the four main types of infrastructure, investments lead to improvements in labor productivity.

The effects for road infrastructures being somewhat more subdued than the effects from other transportation infrastructures, social infrastructures and public utilities. The impact of different types of infrastructure investment on labor productivity, however, is the first instance where getting to really disaggregated effects proves to be very informative from a policy perspective.

The disaggregated results, presented in Figure 5.5 confirm several of these ideas and fine tune others. First, the moderate effect of road infrastructure investment actually hides a very large effect from national road investment and reflects a negative effect from municipal roads and a medium size effect from highway investment. Second, the important effect of other transportation infrastructure investment on labor productivity is mostly due to railroad infrastructure investment, the effects of infrastructure investment in airports being medium size and the effects from port investments actually being essentially null. Third, the strong effects of social infrastructure investment come mostly from health infrastructure investment as the effect of education is moderate. Finally, impact of investment in public utilities on labor productivity comes primarily from investments in telecommunications as the effects from water and wastewater are moderate and the effects from refineries and electricity and gas are negligible.

Long-Term Marginal Products and Rates of Return

We now turn our attention to the marginal product of private investment, employment and output with respect to each type of public infrastructure category. The marginal product figures are a better measure of the relative effects of different types of public infrastructure investments and the relevant measure from a policy perspective. This is because they reflect the relative scarcity of the different types of public investment at the margin of the sample period. The values for the marginal products are presented in Table 5.2 and depicted in Figure 5.6 while the rates of return are presented in Table 5.3.

Starting with the marginal products of road infrastructure investment we estimate at the aggregate level small effects across the board, on investment €3.18, on labor 34 full-time long term jobs, and an output multiplier of €2.75. These low aggregate effects are consistent with generally low effects for national roads, municipal roads and highways when considered individually. The only sizable effects are the impact of national roads on private investment, €9.69, the impact of municipal roads on employment, 148 full time jobs, as well as the output multiplier of national roads, €5.70.

The remaining effects namely all the effects of highway infrastructure investment are very small. The corresponding thirty year rates of return are all low even for national roads, 5.97%, and investments in national roads are the only ones that could come close to paying for themselves in the form of future tax revenues.

The economic impacts of other transportation infrastructure investments, however, are much more significant. At the aggregate level, these investments crowd in private investment with a marginal product of €12.62, employment with a marginal product of 271 jobs, and an output multiplier of €15.00. When more disaggregated types of investments are considered these large effects are also almost universally observed although naturally to different degrees. The only exception is that investment in ports seems to have no statistically significant effect on employment in the long term. On the flip side, investments in ports have a very large effect on labor in the long term with 482 jobs, actually the largest effect among the twelve infrastructure types. In turn, airports have also large private investment and employment effects with marginal products of €17.92 and

400 jobs. The output multipliers are very large, €11.36, €9.75, and €26.52 for railroads, ports, and airports, respectively. The thirty-year rates of return are very competitive, the lowest being 7.89% for ports which is still greater than the highest rate of return for road infrastructure investments.

Furthermore, given the magnitude of the output multipliers, investments in all of the three types of

other transportation infrastructures could be expected to pay for themselves in terms of increased future tax revenues they induce.

The economic impact of social infrastructure investments is also very significant. These large effects can be identified at the aggregate level as well as for both health and education although the results tend to be larger for health infrastructure investments than for education. The effects on investment and employment are €15.34 and €14.02, and 306 and 231 jobs, for health infrastructure and education infrastructure investments, respectively. The output multipliers are €16.54 for health care infrastructure investments and €10.04 for education infrastructure investment, which imply thirty year rates of return of 9.8% and 8.0%, respectively. In both cases, the magnitude of the output multiplier suggests that from a budgetary perspective these investments would pay for themselves over the long term.

Finally, the aggregate effects of public utilities investments are relatively low and in fact of the same order of magnitude as the effects of aggregate road infrastructure investments. Here, however, the aggregate results hide some very important distinctions. In fact, while the effects of investments in water and wastewater, petroleum infrastructures and in particular electricity and gas are small, the effects of investments in telecommunication infrastructures are very sizable. The marginal products of these investments on private investment and employment are €8.60 and 164 jobs. In turn, the output multiplier is €10.70 which translates into a thirty-year annual rate of return of 8.22%. Of all of the investments in public utilities only the ones in telecommunication infrastructure could be expected to pay for themselves from a public budgetary perspective.

Long-term Marginal Products versus Effects on Impact

The analysis of the short-term effects of infrastructure investments by main type of asset reveals that in absolute terms only other transportation and telecommunications, having large accumulated long-term effects also have significant short-term effects. The short-term effects of

social infrastructure investment are either much smaller or even significantly negative in terms of employment – social infrastructure investments crowd out employment in the short-term. At the most disaggregated level, that is, considering the twelve individual types of assets, we get, naturally, the most informative results from a policy perspective in terms also of the decomposition of the long-term accumulated effects between their short-term and long-term components.

In Table 5.4 we report the decomposition of the marginal products of infrastructure investment in a way that in addition to the total accumulated long-term effect, it shows how much of this effect is due to a demand side impact effect, the difference being naturally the longer-term supply-side effect.

In terms of road transportation, the bulk of the effects on private investment and output,

59% specifically, are on impact, that is, in the year of construction. This suggests that the declining pattern of small and decreasing marginal products have pretty much eroded the long-term supply side benefits of these infrastructures and most of what is left is short-term demand side effects related to construction. An exception to this pattern is the employment effects. The short term employment effects are a very small part of what is anyway a very small accumulated long term effect.

These patterns can be better understood when we consider the three individual components of the road infrastructure assets. For national roads we observe that most of the effects on private investment and all of the effects on output are short-term effects. Actually, the short term effects on output exceed the long term accumulated effects which suggests a small negative long-term effect.

For municipal roads, whose effect are generally small they are also mostly on impact for investment and employment while the small long term positive effect on output hides a negative effect on impact. Finally for highways we observe that most of the effects, actually all of the employment effects, are long-term effects. The most important bit of information from a policy perspective is

that the moderately large long-term output multiplier for national roads is deceiving since the effects are exclusively short term effects.

For other transportation, the short term effects are about one-third of the total effects.

This means that aside from the short-term demand side effects related to construction there are also quite sizable long-term supply side effects to the economy.

Again, looking at the three different other transportation types is particularly informative.

For investments in railroad infrastructures the short-term versus longer term decomposition follows pretty much the aggregate, with about one-third of the effects being short-term effects. For port infrastructure investment the positive employment effects are short-term and about half of the long- term output multiplier effects is also short term. This is even more so for airport infrastructure investment in which case consistently about two-thirds of the long term effects are on impact. The most important bit of information from a policy perspective is that infrastructure investments in railroads is more desirable than the numbers may suggest as its effects derive less from demand side factors and mostly from long term supply side effects.

In the case of social infrastructures, the other area of significant economic and budgetary potential, the short term effects are also moderate, about 45% for private investment, 26% for employment and 35% for output. This means that the long term supply-side effects dominate. This is particularly so in the case of health infrastructures as the short term effects are well below one- third of the total long-term accumulated effects. For education, on the other hand around two-thirds of the effects on private investment and output are observed in the short-term. The most important bit of information from a policy perspective is that the effects of investments in health infrastructure are not only large but mostly long-term supply side effects.

Finally, for utilities, we find that the short-term demand side effects tend to be stronger than for other transportation and social infrastructure but less than road transportation. Again, this

hides a wide variety of patterns when we consider the individual assets. Investments in electricity and gas infrastructure are in one extreme as the very low effects observed are mainly short-term effects. On the other extreme, the effects of investments in petroleum refining are mostly long-term supply side effects, with very little effects on impact. The effects of investments in water and wastewater and in telecommunications are more evenly distributed and in the case of investment and output with more of a long-term relevance. Furthermore, employment effects for telecommunications are mainly long-term as well. The most important bit of information from a policy perspective is that the effects of investments in telecommunication infrastructure are not only large but mostly long-term supply side effects.

Long-Term Marginal Products and the Relative Scarcity of Infrastructure Capital

depicting the specific patterns of diminishing marginal productivity of infrastructure investment in the different cases and specifically how fast it is decreasing. This is fundamental in evaluating the potential for policies to encourage the development of additional infrastructures.

The evolution of the marginal products for the four main types of infrastructure assets as well as the twelve individual assets are presented in Figure 5.7 through Figure 5.10. As a point of reference, the values for the marginal products we have presented and discussed above are the very last points in the different figures, that is, are the points where each curve ends using averages for the last ten years of the sample.

For road transportation, we see a pattern of steady decline of marginal products, one that is more pronounced earlier in the sample period than over the last ten years. Indeed, the marginal products at the end of the sample are just 50%, 34%, and 47%, for investment, employment, and output, of the values observed earlier in the sample.

Further disaggregation of the road infrastructure assets - national roads, municipal roads and highways – shows that this pattern hides a meaningful variety of situations. In the case of national roads we see a pattern of decline similar to the aggregate road infrastructure, while for municipal roads we do not see significant changes throughout the period. For highways, however, the decline in marginal products is extremely steep. To illustrate the long term output multiplier which is now

€3.55 would be at about €25 if measured by the scarcity standards of the late 1980s. The same steep change can be observed in terms of the effects of investment and employment. This is consistent with an enormous effort in highway infrastructure in the last few decades.

consistent with the idea that these infrastructures were the focus of attention mostly in the latter part of the sample but even then they did not play center stage. Looking at the different assets we see a similar picture in the sense that the marginal products we estimate are between one-third and one- half of what the estimates would have been by the later 1980s. In addition, the relative stability after the early 2000s is also similar for railroads and ports, with the case of airports showing a somewhat decreasing pattern.

In the case of social infrastructures we observed that the marginal products have been consistently relatively high somewhat declining early in the sample years but remarkably stable after the early 2000s. This pattern is similar to what we observe in the case of health infrastructures. The case of education, however, is sharply different in that the marginal products have actually increased in the last decade reflecting an increasing relative scarcity of these infrastructures.

In the case of public utilities the evolution at the aggregate level is similar both qualitatively and quantitatively to the case of road transportation we just described above. At a more disaggregated level however, we see a rather stable evolution of marginal products around rather low values for refineries and around high values for telecommunications. In turn, for water and wastewater infrastructure we see an extremely sharp decline in marginal products with very low effects at the end of the sample. Finally, for electricity and gas we see a pattern of extreme decline of marginal products after the late 1990s.

We have showed that investments in railroads, ports, and airports, health and education, and telecommunications have the largest output multipliers. We have also showed that the effects of investment in railroads, health, are telecommunications are mostly long-term supply side effects while those of investments in ports, airports, and education are more short-term demand side impact effects. We now can add to this mix the idea that the long-term output multipliers of railroads, ports, airports, and health show clear decreasing patterns of marginal returns while there

seems to be an increasing scarcity of educational infrastructures and there are no clear patterns of decreasing marginal returns for investments in telecommunications.

5.3 International Comparisons

There is a wide body of literature dealing empirically with the economic effects of infrastructure investment [see, for example, Munnell (1992), Gramlich (1994), Romp and de Haan

(2007) and Pereira and Andraz (2013), for literature surveys as well as the literature review in Kamps

(2005)]. Accordingly, making general and merely qualitative comparisons is easy although not particularly interesting. More relevant quantitative comparisons are, however, surprisingly difficult.

This is because of wide differences in the temporal and typological scope and definition of the data sets used, the great different in econometric approaches, and their implications in terms of the interpretation of such trivial terms as elasticities and marginal products.

Although difficult, meaningful international comparisons are not impossible. We focus here on comparisons with the evidence on the output multipliers of infrastructure investment in Portugal

[see, Pereira and Andraz (2005, 20011)] and Spain [Pereira and Roca (2003, 2007)] on one hand and

Ontario, Canada [see Pereira and Pereira (2014)] and the U.S. [see Pereira (2000)] on the other hand.

These comparisons are presented in Table 5.5. In all cases the results are based on the same methodological approach and therefore more directly comparable to the ones developed in this chapter. Canada and the U.S. provide for a comparison with an economy at a greater level of development and with arguably a lower level of infrastructure scarcity. In contrast, Spain provides for a comparison at a similar level of development and scarcity in the infrastructure stock. Naturally, the most interesting comparisons will be with previous evidence for Portugal itself.

In most cases the data sets end in the middle to late 1990s. The exception is for the case of

Ontario, Canada where data covers 1976 to 2011 and is therefore close to the time frame used in

this chapter. The studies for the US use data from 1956 to 1997 while the Portuguese case uses info from 1978 to 1998 and the Spanish case from to 1970-1995. Finally, comparisons with the results for Portugal and Spain are more limited in that the Portuguese and Spanish cases only consider transportation infrastructure – roads, highways, ports, airports, rail – and in the Spanish case communications. The studies for Ontario, Canada and the U.S. are more generally comparable in terms of scope of the data base used, which is more comprehensive, considering infrastructure types beyond transportation. For Ontario, Canada, the study considers government, administrative and other infrastructures, health infrastructures, education infrastructures, road infrastructures, and water and wastewater infrastructures. For the U.S., the study considers road infrastructure, electric and gas facilities, water and sewage, education, hospital and other buildings, and a residual category.

The estimate of the output multipliers of road infrastructure investments for the US is

1.97, the smallest of all multipliers for the U.S., while for Ontario, Canada the multiplier is actually negative. Our estimate of the output multiplier for aggregate road infrastructure is 2.75, while for each of the individual assets they are 1.02 for municipal roads, 3.55 for highways and 5.70 for national roads. They are accordingly in the same range but more importantly are also among the smallest effects we estimate.

In terms of the multipliers for other transportation infrastructure investments, the closer category for the U.S. core infrastructure which includes transit and airfields – but also electricity and gas, is 19.79 and is the largest multiplier. For Ontario, Canada, the largest multiplier is also for transit with 29.19. Our estimate for Portugal including airports, ports and railroad infrastructure is also the largest at 14.99. Each one of the individual assets has equally important effects albeit to different degrees: 11.36 for railroads, 9.75 for ports and 26.52 for airports.

The evidence for Spain contemplating total transportation infrastructure – road and other transportation - is 5.50. This figure compares directly to the evidence for Portugal for a comparable

time horizon, a multiplier of 9.54. The natural conclusion is that the marginal benefits of further investments in transportation infrastructure were greater at the time for Portugal than Spain, reflecting a pattern of greater scarcity in Portugal. In turn, the figure for just road transportation for

Portugal for the same period is 18.06, suggesting therefore an even greater marginal product and an even greater scarcity at the time when only road infrastructure is considered.

In turn, for the U.S. the multiplier for the infrastructure type that most resembles social infrastructure – but also includes administrative buildings, is 5.53, and is in the middle of the range of results, while for Ontario, Canada the estimate of the multiplier for education infrastructure is

14.17 and health infrastructure is 23.46 and are among the largest for that regions. Our estimates for social infrastructure of 16.54 for health and 10.04 for education are of the same order of magnitude and also among our largest estimates.

Finally, for public utilities, the estimates for the U.S. for water and water systems are 6.35 while for Ontario, Canada the same multiplier is 8.29. Our corresponding multiplier is 4.80, which although smaller is of the same order of magnitude.

We now turn our attention to the comparisons with previous estimates of the output multipliers for Portugal using data until the late 1990s. This is the most direct comparison we can make and the differences will be important not only to frame our new results but even more so from a policy perspective.

Again, our results now for road transportation and for other transportation are 2.75 and

14.99, respectively, while for the combination of both that is total transportation– a result not previously introduced in the chapter – it is 3.18. These figures are to be contrasted with multipliers for the period ending in the late 1990s of 18.06 for road infrastructures, around 19.0 for other transportation, and 9.54 for total transportation.

The multiplier for road transportation is now 6.5 times smaller than by the late 1990s. This not only reflects a rapid decline in the marginal productivity of these investments as could be seem from the discussion in the precious section, but even more so from a decoupling of road infrastructure investments and economic performance as reflected by the decline in the elasticity itself from 0.29 to 0.05. Overall the multiplier for total transportation infrastructure investment is now about one third of what was estimated for the late 1990s. Clearly, in terms of the output effects there is a degree of diminishing returns and even more so of increasing decoupling which is particularly large for road infrastructures investments.

When we consider the six transportation infrastructures we also see some of the same types of patterns but there are exceptions and added nuances. The decoupling of the infrastructure investment from the economy, as suggested by lower estimates of the elasticities, is particularly profound in the case of municipal roads and ports and very important although less so for national roads and railroads. In turn, the elasticities for highway investment did not change significantly while the elasticity for airports is now substantially larger. It would seem that the evolution of infrastructure investment and of the overall economy has brought the country to a place where the responsiveness of the economy to investments in municipal roads and ports has greatly declined while the responsiveness to airports has increased.

When we consider the multipliers we observe that only in the case of airport investment has the estimate increased – from 19.18 in the late 1990s to 26.52 now. This is completely due to increase in the responsiveness of the economy to these investments as the reduction in scarcity in itself would imply a decrease in the long term multiplier. On the other hand, we see a very sharp decline in the multiplier for municipal roads – from 22.32 to 1.02 – and for ports – from 107.00 to

9.75 - which are in both cases totally due to the decoupling effects that is a lower elasticity. In turn for national roads and railroads we find more of a mixed role of decoupling and decrease scarcity in

explaining the decline in the output multipliers from 31.41 to 5.70 and from 18.47 to 11.36. Finally for highway investment the decline in the multiplier from 8.24 to 3.55 is completely due to diminished scarcity.

5.4 Summary and Concluding Remarks

Summary

This chapter analyzes the effects of infrastructure investment on economic performance in

Portugal using a newly developed data set. We consider twelve types of infrastructure investments – three types of road transportation infrastructures (national roads, municipal roads, and highways), three types of other transportation infrastructures (railroads, ports, and airports), two types of social infrastructures (education and health infrastructures), and four types of public utilities (electricity and gas, water and wastewater, refineries, and telecommunications). We employ a vector autoregressive approach to estimating the elasticity and marginal product of public infrastructure investment on private investment, employment and output. This approach is consistent with the argument that the analysis of the effects of public infrastructure investment on economic variables requires the consideration of dynamic feedback effects among the different variables.

We frame our empirical results in terms of the economic policy environment, i.e., considering both the economic impacts of infrastructure investments and their budgetary implications. We find that, clearly, not all infrastructure investments are created equal along several and rather relevant dimensions from a policy perspective.

We find that the largest long-term accumulated output effects come from investments in railroads, ports, airports, health, education, and telecommunications. For all of these infrastructures, the output multipliers are sizable enough to suggest that these investments would pay for themselves in the form of additional tax revenues. If we were to assume a linear distribution of the long term

effects of these investments over a lifetime of thirty years and under an effective tax rate of 25% on the additional output they generate, investments in railroads, airports, and health infrastructures would take, respectively, about ten, five, and seven years to pay for themselves, while investments in ports, education and telecommunications would take about twelve years.

We find also that for investments in airports and health infrastructures the bulk of the effects are short-term demand side effects while for railroads and health the bulk of the effects come from long-term supply side effects. Finally, investments in health and airports show a clear pattern of decreasing marginal returns with railroads, ports, and telecommunications showing a relative stable pattern.

In terms of the other infrastructure assets, we find that the economic effects of investments in municipal roads, highways, and electricity and gas are not significant or relevant. Investments in national roads, waste and wastewater, and refinery infrastructures have positive economic effects but not large enough to also have positive budgetary effects.

Policy Implications

The wealth of information presented above suggests that a targeted approach to the design of infrastructure investment policy is absolutely necessary. Specifically, different types of infrastructure may be better suited to address different policy objectives, such as increasing labor productivity, encouraging private investment, creating job, or generating output. In addition, different investments regardless of their long-term accumulated effects may have rather different short-term effects on impact. Finally, in some cases we observe sharply decreasing marginal returns in the last decade of the sample, that is, the 2000s, while in other cases the evolution of the marginal products seem to be much more stable. When choosing where to invest all of these are aspects to be considered.

In Table 5.6 we present a scoreboard of the results by type of infrastructure asset that is, we distill the impacts of the different types of infrastructure investments in a way that makes their policy implications apparent.

The main public policy implication that follows from our results is the recommendation that the government should invest or in some way promote investments in railroads, ports, and airports, health and education, and telecommunications, as these investments have the largest output multipliers. These are not only the infrastructure assets with the highest effects on output but also the ones with high enough returns to imply that they would very likely pay for themselves in the form of future tax revenues generated by improved economic conditions. Cutting back in these types of investments would, therefore, have detrimental effects on economic performance as well as on the public budget. This also means that these investments may be good vehicles to promote not only economic growth but also budgetary consolidation. Investments in these infrastructure assets are – in general terms - a good idea.

In addition, we have showed that the effects of investment in railroads, health, and telecommunications are mostly long-term supply side effects while those of investments in ports, airports, and education are more short-term demand side impact effects. From a public policy perspective, this makes ceteris paribus, the investments on the former more desirable than on the later, as the main motivation for infrastructure investments should generally be to create conditions for long-term growth. This also means that the later are actually likely to be more desirable if the policy objective is to generate immediate short-term economic benefits.

We also found that the long-term output multipliers of railroads, ports, airports, and health, show clear decreasing patterns of marginal returns. Accordingly, a strategy of promoting investments in these assets can only go so far as additional investment reduces the scarcity factor and will bring marginal products to clearly lower levels. In turn, there are no clear patterns of

decreasing marginal returns for investments in telecommunications which may be due to the relatively recent nature of the technologies involved. For investments in education infrastructures there is a pattern of increasing marginal effects likely due to a clear disinvestment and decommissioning of educational facilities over the last decade.

On the other hand and as we consider the remaining infrastructure assets, in terms of their output effects, investments in municipal roads, highways, and electricity and gas infrastructures do not have meaningful or significant effects. Accordingly, cutting back on these investments would not particularly hurt the economy and would certainly have favorable effects on the public budget.

In the middle of our taxonomic distribution are investments in national roads, water and wastewater, and telecommunication infrastructures. In this case, although the long-term output multipliers are big enough to suggest some relevant economic effects, they are not large enough to be advantageous from a budgetary perspective. They would likely not pay for themselves in the form of future additional tax revenues.

Table 5.1 Elasticities with respect to Infrastructure Investment Private Investment Employment Output

Road Transportation Infrastructure 0.2292 0.0169 0.0496 [-0.0803, 0.2292] [-0.0238, 0.0169] [-0.0381, 0.0496]

National Roads 0.3000 -0.0042 0.0442 [-0.1680, 0.3691] [-0.0752, 0.0115] [-0.0996, 0.0684]

Municipal Roads 0.0618 0.0159 0.0040 [-0.0258, 0.1160] [0.0012, 0.0285] [-0.0249, 0.0270]

Highways 0.0839 0.0088 0.0226 [0.0367, 0.0849] [0.0027, 0.0091] [0.0101, 0.0229]

Other Transportation Infrastructure 0.2596 0.0379 0.0772 [0.0881, 0.2596] [0.0130, 0.0379] [0.0275, 0.0772]

Railroads 0.1725 0.0162 0.0433 [0.0572, 0.1725] [0.0024, 0.0162] [0.0121, 0.0433]

Ports -0.0009 0.0077 0.0057 [-0.0804, 0.0] [-0.0058, 0.0078] [-0.0193, 0.0060]

Airports 0.0533 0.0081 0.0197 [-0.0742, 0.0533] [-0.0106, 0.0081] [-0.0204, 0.0197]

Social Infrastructures 0.3911 0.0521 0.0956 [0.0117, 0.3911] [0.0127, 0.0521] [-0.0189, 0.0956]

Health Facilities 0.4321 0.0587 0.1166 [0.1829, 0.4321] [0.0290, 0.0587] [0.0441, 0.1166]

Educational Buildings 0.2385 0.0268 0.0427 [-0.2115, 0.2385] [-0.0276, 0.0268] [-0.0999, 0.0427]

Utilities 0.3156 0.0547 0.0962 [0.020, 0.3156] [0.0024, 0.0547] [0.0006, 0.0962]

Water Infrastructure 0.1103 0.0181 0.0296 [0.0034, 0.1103] [-0.0025, 0.0181] [-0.0061, 0.0296]

Petroleum Refining Infrastructure 0.0177 0.0032 0.0066 [0.0117, 0.0177] [0.0021, 0.0032] [0.0045, 0.0066]

Electricity and Gas 0.0254 0.0031 0.0050 [-0.0259, 0.0254] [-0.0054, 0.0031] [-0.0107, 0.0050]

Telecommunications 0.2270 0.0295 0.0707 [-0.0080, 0.2270] [-0.0039, 0.0295] [-0.0001, 0.0707]

Table 5.2 Marginal Product of Infrastructure Investment Private Investment Employment Output

Road Transportation Infrastructure 3.1801 0.0343 2.7492 [-1.1145, 3.1801] [-0.0484, 0.0343] [-2.1138, 2.7492]

National Roads 9.6919 -0.0201 5.6996 [-5.4282, 11.9241] [-0.3562, 0.0543] [-12.8566, 8.8247]

Municipal Roads 3.9316 0.1481 1.0177 [-1.640, 7.3875] [0.0111, 0.2666] [-6.3343, 6.8731]

Highways 3.3039 0.0511 3.5490 [1.4450, 3.3423] [0.0156, 0.0526] [1.5839, 3.6069]

Other Transportation Infrastructure 12.6197 0.2706 14.9993 [4.2817, 12.6197] [0.0925, 0.2706] [5.3426, 14.9993]

Railroads 11.3172 0.1563 11.3596 [3.7538, 11.3172] [0.0226, 0.1563] [3.1668, 11.3596]

Ports -0.3845 0.4820 9.7478 [-34.1297, 0.0125] [-0.3595, 0.4877] [-32.6855, 10.1533]

Airports 17.9219 0.4002 26.5152 [-24.9690, 17.9219] [-0.5252, 0.4002] [-27.4347, 26.5152]

Social Infrastructures 8.6569 0.1692 8.4546 [0.2594, 8.6569] [0.0413, 0.1692] [-1.6690, 8.4546]

Health Facilities 15.3392 0.3057 16.5441 [6.4938, 15.3392] [0.1511, 0.3057] [6.2541, 16.5441]

Educational Buildings 14.0215 0.2310 10.0373 [-12.4288, 14.0215] [-0.2381, 0.2310] [-23.4497, 10.0373]

Utilities 2.8891 0.0735 3.5198 [0.1828, 2.8891] [0.0033, 0.0735] [0.0212, 3.5198]

Water Infrastructure 4.4793 0.1077 4.7967 [0.1393, 4.4793] [-0.0148, 0.1077] [-0.9934, 4.7967]

Petroleum Refining 2.0365 0.0536 3.0468 [1.3418, 2.0365] [0.0357, 0.0536] [2.0486, 3.0468]

Electricity and Gas 0.5133 0.0092 0.4010 [-0.5232, 0.5133] [-0.0161, 0.0092] [-0.8668, 0.4010]

Telecommunications 8.5996 0.1642 10.7004 [-0.3023, 8.5996] [-0.0218, 0.1642] [-0.0213, 10.7004]

Table 5.3 Rate of Return on Infrastructure Investment Lifespan of 20 years 30 years 40 years 50 years

Road Transportation Infrastructure 5.19 3.43 2.56 2.04

National Roads 9.09 5.97 4.45 3.54 Municipal Roads 0.09 0.06 0.04 0.04 Highways 6.54 4.31 3.22 2.57

Other Transportation Infrastructure 14.50 9.45 7.00 5.57

Railroads 12.92 8.44 6.26 4.98 Ports 12.06 7.89 5.86 4.66 Airports 17.81 11.54 8.54 6.78

Social Infrastructures 11.26 7.37 5.48 4.36

Health Facilities 15.06 9.80 7.27 5.77 Educational Buildings 12.22 7.99 5.94 4.72

Utilities 6.49 4.28 3.20 2.55

Water Infrastructure 8.16 5.37 4.00 3.19 Petroleum Refining 5.73 3.78 2.82 2.25 Electricity and Gas

Telecommunications 12.58 8.22 6.10 4.85

Table 5.4 Long-term Marginal Products versus Effects on Impact Private Employment GDP Investment

Road Transportation Infrastructure Long Term 3.18 0.03 2.75 Short Term 1.88 0.01 1.63

(in % of total) (59%) (19%) (59%)

National Roads Long Term 9.69 -0.02 5.70 Short Term 6.52 -0.05 6.72

(in % of total) (67%) (250%) (118%)

Municipal Roads Long Term 3.93 0.15 1.02 Short Term 1.93 0.07 -1.81

(in % of total) (49%) (48%) (-178%)

Highways Long Term 3.30 0.05 3.55 Short Term 1.16 -0.00 1.00

(in % of total) (35%) (-2%) (28%)

Other Transportation Infrastructure Long Term 12.62 0.27 15.00 Short Term 3.75 0.09 4.07

(in % of total) (30%) (33%) (27%)

Railroads Long Term 11.32 0.16 11.36 Short Term 3.61 0.03 2.62

(in % of total) (32%) (16%) (23%)

Ports Long Term -0.38 0.48 9.75 Short Term -0.22 0.48 4.66

(in % of total) (57%) (100%) (48%)

Airports Long Term 17.92 0.40 26.52 Short Term 11.45 0.27 18.43

(in % of total) (64%) (68%) (69%)

Social Infrastructures Long Term 8.66 0.17 8.45 Short Term 3.87 0.04 3.00

(in % of total) (45%) (26%) (35%)

Health Facilities Long Term 15.34 0.31 16.54 Short Term 4.75 0.07 3.91

(in % of total) (31%) (23%) (24%)

Educational Buildings Long Term 14.02 0.23 10.04 Short Term 9.49 0.09 6.01

(in % of total) (68%) (39%) (60%)

Utilities Long Term 2.89 0.07 3.52 Short Term 1.03 0.04 1.35

(in % of total) (36%) (55%) (38%)

Water Infrastructure Long Term 4.48 0.11 4.80 Short Term 1.52 0.07 2.11

(in % of total) (34%) (68%) (44%)

Petroleum Refining Long Term 2.04 0.05 3.05 Short Term 0.03 0.01 0.39

(in % of total) (2%) (15%) (13%)

Electricity and Gas Long Term 0.51 0.01 0.40 Short Term 0.40 0.01 0.35

(in % of total) (78%) (143%) (88%)

Telecommunications Long Term 8.60 0.16 10.70 Short Term 3.46 0.02 4.44

(in % of total) (40%) (12%) (41%)

Table 5.5 International Comparisons for the Estimated Output Multipliers Present United Ontario, Portugal Spain Study States Canada

Time Period 1980-2011 1978-1998 1970-1995 1956-1997 1976-2011

Transportation 3.18 9.54 5.50

Road Transportation Infrastructures 2.75 18.06 1.97 National Roads 5.70 Municipal Roads 1.02 Highways 3.55 Other Transportation Infrastructures 15.00 19.00 19.79 29.19 Railroads 11.36 Airports 9.75 Ports 26.52 Social Infrastructures 8.45 5.53 Education 16.54 14.17 Health Facilities 10.04 23.46 Utilities 3.52 Water and Water Systems 4.80 6.35 8.29

Table 5.6 Infrastructure Investments: Scoreboard of Effects National Roads Private Investment Large and stable: €9.69 [67% on impact] Employment Small and stable: negative [negative on impact] GDP Medium and stable: €5.70 [100% on impact] Impact on the Public Budget Negative/Neutral Labor Productivity Large: 0.0484 Municipal Roads Private Investment Medium and stable: €3.93 [49% on impact] Employment Medium and stable: 148 jobs [48% on impact] GDP Small and stable: €1.01 [negative on impact] Impact on the Public Budget Negative Labor Productivity Small: negative Highways Private Investment Small and decreasing: €3.30 [35% on impact] Employment Small and decreasing: 51 jobs [0% on impact] GDP Small and decreasing: €3.55 [28% on impact] Impact on the Public Budget Neutral/Negative Labor Productivity Medium: 0.0178 Railroad Private Investment Medium and stable: €11.31 [32% on impact] Employment Medium and stable: 156 jobs [16% on impact] GDP Medium and stable: €11.36 [23% on impact] Impact on the Public Budget Positive Labor Productivity Medium: 0.0271 Airport Private Investment Large and decreasing: €17.92 [64% on impact] Employment Large and decreasing: 482 jobs [69% on impact] GDP Large and decreasing: €26.51 [69% on impact] Impact on the Public Budget Positive Labor Productivity Medium: 0.0116 Port Private Investment Small and stable: negative [negative on impact] Employment Large and stable: 400 jobs [100% on impact] GDP Large and stable: €9.75 [48% on impact] Impact on the Public Budget Positive Labor Productivity Small: negative Health Facilities Private investment Large and decreasing: €15.34 [31% on impact] Employment Large and decreasing: 306 jobs [23% on impact] GDP Large and decreasing: €16.54 [24% on impact] Impact on the Public Budget Positive Labor Productivity Large: 0.0579 Educational Buildings Private investment Large and increasing: €14.02 [68% on impact] Employment Large and increasing: 231 jobs [39% on impact] GDP Large and increasing: €10.04 [60% on impact] Impact on the Public Budget Positive Labor Productivity Medium: 0.0159 Water Infrastructures Private investment Small and decreasing: €4.47 [34% on impact] Employment Medium and decreasing: 108 [68% on impact] GDP Small and decreasing: €4.80 [44% on impact] Impact on the Public Budget Neutral Labor Productivity Medium: 0.0115

Electricity and Gas Private investment Small and decreasing: €0.51 [78% on impact] Employment Small and decreasing: 9 jobs [100% on impact] GDP Small and decreasing: €0.40 [88% on impact] Impact on the Public Budget Negative Labor Productivity Small: 0.002 Petroleum Refining Private investment Small and stable: €2.04 [2% on impact] Employment Small and stable: 54 jobs [12% on impact] GDP Small and stable: €3.05 [13% on impact] Impact on the Public Budget Neutral Labor Productivity Small: 0.0034 Telecommunications Private investment Medium and stable: €8.60 [40% on impact] Employment Medium and stable: 164 jobs [12% on impact] GDP Large and stable: €10.70 [41% on impact] Impact on the Public Budget Positive Labor Productivity Large: 0.0412

Figure 5.1 Accumulated Impulse Response Functions – Road Transportation

Private Investment Employment GDP

1.0 0.15 0.20 0.10 0.15

0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 -0.5 -0.10 NationalRoads -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15

0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 -0.5 -0.10 Municipal Municipal Roads -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15 0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 Highways -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

Figure 5.2 Accumulated Impulse Response Functions – Other Transportation

Private Investment Employment GDP

1.0 0.15 0.20 0.10 0.15 0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 Railroads -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15 0.5 0.10 0.05 0.05 0.0 0.00 0.00

Ports -0.05 -0.05 -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15 0.5 0.10 0.05

0.05 0.0 0.00 0.00 -0.05

Airports -0.05 -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

Figure 5.3 Accumulated Impulse Response Functions – Social Infrastructures

Private Investment Employment GDP

1.0 0.15 0.20 0.10 0.15 0.5 0.10

0.05 0.05

0.0 0.00 0.00 -0.05 Health -0.05 -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15 0.5 0.10

0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 Education -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

Figure 5.4 Accumulated Impulse Response Functions – Public Utilities Private Investment Employment GDP

1.0 0.15 0.20 0.10 0.15 0.5 0.10

0.05 0.05

0.0 0.00 0.00

Water -0.05 -0.05 -0.5 -0.10 -0.10 -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.15

0.10 0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 -0.5 -0.10 -0.10

Petroleum Refining -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.10 0.15 0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 -0.5 -0.10 -0.10 Electricity and Gas -0.15 -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

1.0 0.15 0.20 0.15 0.10 0.5 0.10 0.05 0.05 0.0 0.00 0.00 -0.05 -0.05 -0.5 -0.10

-0.10 -0.15 Telecommunications -1.0 -0.15 -0.20 0 10 20 0 10 20 0 10 20

Figure 5.5 Effect of Infrastructure Investment on Labor Productivity

100

Figure 5.6 Long-Term Marginal Products of Infrastructure Investment Private Investment

17.92 15.34 14.02 12.62 11.32 9.69 8.66 8.60 3.18 3.93 3.30 2.89 4.48 2.04 0.51

-0.38

Ports

Water

Health

Utilities

Airports

Railroads

Highways

Road

Social

Education

Other

Infrastructures

Transportation Transportation

National RoadsNational

MunicipalRoads

Telecommunicatio Electricity ang Electricity Gas Petroelum Refining Employment

482 400 306 271 231 156 169 164 148 108 73 54 34 51 9

Ports

Water

Health

Utilities

Airports

Railroads

Highways

Road

Social

Education

Other

Infrastructures

Transportation Transportation

NationalRoads

MunicipalRoads

Electricity ang Gas Petroelum Refining Telecommunication Output

26.52

15.00 16.54 11.36 10.70 9.75 8.45 10.04 5.70 4.80 2.75 3.55 3.52 3.05

1.02 0.40

Ports

Water

Health

Utilities

Airports

Railroads

Highways

Education

Other

Transportation

NationalRoads

MunicipalRoads

Electricity ang Gas

Petroelum Refining

Telecommunications Road Transportation SocialInfrastructures

101

Figure 5.7 Evolution of the Marginal Products – Road Transportation

Private Investment Employment GDP

20 0.00 14 -0.01 12 15 -0.02 10 -0.03 8 10 -0.04 6 5 -0.05 4 -0.06 2

0 -0.07 0 NationalRoads

1979-1988 1988-1997 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1982-1991

5 0.25 1.2 4 0.20 1.0

0.8 3 0.15 0.6 2 0.10 0.4 1 0.05 0.2

0 0.00 0.0 Municipal Municipal Roads

1982-1991 1985-1994 1991-2000 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1988-1997 1994-2003 1997-2006 2000-2009 1979-1988

25 0.60 30 20 0.50 25 0.40 20 15

0.30 15 10 0.20 10 5 0.10 5

Highways 0 0.00 0

1979-1988 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1982-1991

102

Figure 5.8 Evolution of the Marginal Products – Other Transportation

Private Investment Employment GDP

25 0.50 30 20 0.40 25 20 15 0.30

15 10 0.20 10 5 0.10 5

Railroads 0 0.00 0

0.0 1.2 16 -0.1 1.0 14 12 -0.2 0.8 10 -0.3 0.6 8 -0.4 0.4 6 4

Ports -0.5 0.2 2 -0.6 0.0 0

50 1.4 60 40 1.2 50 1.0 40 30 0.8

30 20 0.6 0.4 20 10 0.2 10 Airports 0 0.0 0

103

Figure 5.9 Evolution of the Marginal Products – Social Infrastructures

Private Investment Employment GDP

35 1.0 40 35 30 0.8 25 30 20 0.6 25 20 15 0.4 15 10 10 5 0.2 Health 5 0 0.0 0

16 0.3 12 14 10 12 0.2 8 10 0.2 8 6 0.1 6 4 4 0.1 2 2

Education 0 0.0 0

104

Figure 5.10 Evolution of the Marginal Products – Public Utilities

Private Investment Employment GDP 20 0.7 20 0.6 15 0.5 15 0.4 10 10

0.3 5 0.2 5

Water 0.1 0 0.0 0

0 0.0 0 Petroleum Refining

1.5 0.03 1.0 0.02 0.8 1.0 0.02 0.6 0.5 0.01 0.4 0.01 0.2

0.0 0.00 0.0 Electricity and Gas

1988-1997 1994-2003 2000-2009 1985-1994 1991-2000 1982-1991 1985-1994 1991-2000 1997-2006 1979-1988 1982-1991 1985-1994 1988-1997 1991-2000 1994-2003 1997-2006 2000-2009 1979-1988 1982-1991 1988-1997 1994-2003 1997-2006 2000-2009 1979-1988 14 0.4 20 12 0.4 10 0.3 15 8 0.3 0.2 10 6 0.2 4 0.1 5 2 0.1

0 0.0 0 Telecommunications

105

106

CHAPTER 6 Infrastructure Investment and the Composition of Economic Activity

This chapter analyzes the effects of infrastructure investment at the industry level using a newly developed data set for Portugal. We employ a vector autoregressive approach for twenty two sectors covering the whole spectrum of economic activity in the country and consider five main types of infrastructure assets to estimate industry-infrastructure specific effects. We first establish that the most important effects come from infrastructure investments in other transportation (railroads, ports, and airports), social infrastructures (education and health) and telecommunications with some less important effects from road infrastructures (roads and highways) and insignificant effects from public utilities (electricity, water, and refineries). In relative terms, with a focus on the industry divide between sectors producing traded and non-traded goods, we find that the infrastructure investments tend to shift the industry mix towards private and public services and therefore mostly towards non- traded good sectors. We find that the sectors that benefit the most in relative terms are construction, trade, and real estate among the private services and public administration, education and health among the public services, all of these non-traded goods sectors. There also some important effects in some traded goods sectors such as chemical and pharmaceutical, machinery and equipment and in particular transportation and storage, as well among emerging trading sectors, such as hospitality and professional services. In general, these results highlight the fact that infrastructure development strategies may be far from neutral for the perspective of the industry mix. Moreover, the fact that the benefits accrue mostly to sectors producing non-traded goods represents a move in the direction of a development model based on domestic demand, a model that may not be sustainable given its implications for the foreign account position of the country.

6.1 Introduction

One issue that is virtually absent in this literature on the impact of infrastructure investments at the industry level is the relationship between aggregate and industry-specific effects, specifically how the aggregate effects can be decomposed at the industry level. This is a critical issue since the relevance of the aggregate of the effects of infrastructure investments does not provide any useful information as to the industry incidence of such effects. Significant positive aggregate effects can be associated with balanced positive industry-level effects or they can mask uneven gains across industries. Also, it is conceivable that small effects at the aggregate level could hide significant effects for specific industries. Ultimately, there is the question of how the development of an infrastructure network has affected the industry mix in the country.

107

The question of how infrastructure investments affect the industry mix is a critical one when we consider small open economies depending on their ability to export to sustain improvements in their standards of living. Here, the effects of infrastructure investments as they affect the industry mix along the divide between sectors that produce traded and non-traded goods is of the utmost importance. Infrastructure investments that affect mostly sectors producing traded goods will help with this export-oriented development strategy, while those affecting mostly sectors producing non- traded goods will create added pressure on the external accounts and thereby erode the long term sustainability of the development model. The aggregate effects of infrastructure investments may, therefore, hide very different industry-specific patterns and thereby lead the economy into markedly different directions.

6.2 The Empirical Results

The Effects at the Industry Level: A First Look

The most aggregate results are reported in last rows of Table 6.1 to Table 6.5. When we consider the five main infrastructure assets a clear pattern emerges. Investments in other transportation has the largest effects closely followed by investments in social infrastructures and in telecommunications. Investments in road transportation infrastructure have positive but much smaller effects while the effects of investments in public utilities are negligible. For example, in terms of the long-term output multipliers, the effects of other transportation, social infrastructures, and telecommunications are €19.84, €18.50, and €13.98, respectively, while the multipliers for road transportation is €5.69.

When we consider the effects of the five main types of infrastructures at the more disaggregated level on four different economic activities: primary sector, manufacturing, private

108

services and public services, again a clear pattern emerges. The empirical results are reported in

Table 6.1 to Table 6.5 in the rows with the partial totals.

There are stark differences in terms of the sector-specific effects. The effect of the different types of infrastructure investments on the primary sector are either negative or very small while the effects on manufacturing are generally positive but small. The effects on private services are the largest followed at a distance by the effects on public services. For example, the effects of other transportation infrastructure investments on the output of the private services and public services are €17.16 and €3.68, respectively, the effects of social infrastructures, €13.58 and €4.58, and of telecommunications €10.88 and €1.82. For a sense of perspective the largest effect on primary sector output comes from other transportation infrastructures with -€0.08 and the largest effect on manufacturing comes from social infrastructure with €1.46.

The Effects at the Industry Level: A Closer look

We consider now the effects of the five main types of infrastructure assets across the twenty two sectors covering the whole spectrum of the domestic economic activity.

The effects of investments in road infrastructure are reported in Table 6.1 and Figure 6.1.

When we consider the four main sectors of economic activity, we observe that the relatively small effects of road infrastructure investments are concentrated mostly on private services and to a lesser extent on public services, the effect on manufacturing being much smaller and in the case of the primary sector negative. Looking at the more detailed results, we see that for the primary sectors and for manufacturing sectors, the effects are all very small – 15 of the twenty seven elasticities estimated are not statistically different from zero. In terms of the private and public services, the picture is richer. For private investment, the largest benefits accrue to S18 (real estate), S19 (professional services) and S20 (public administration), but are all very small compared to the effects observed from other types of infrastructures. For employment, the benefits accrue mostly to S13 (trade) and

109

S19 (professional services). In turn, the main benefits in terms of output accrue to S18 (real estate) with €2.47. The much smaller effects on S12 (construction), S13 (trade), S20 (public administration) and S21 (education) are also very small comparatively to the effects of other infrastructures.

In terms of other transportation infrastructure investments, the results are reported in

Table 6.2 and Figure 6.2. The effects are substantial and overwhelmingly concentrated on private services, and to a lesser extent on public services, while the only effects worth mentioning for the primary sector are for employment and for the manufacturing sector for investment. For private investment the largest benefits accrue to S12 (construction), S13 (trade), S14 (transportation), and

S19 (public administration). For employment, the largest effects are in S12 (construction), S13

(trade), and S19 (professional services) and to a lesser extent S15 (hospitality) and S20 (public administration). In terms of the effects on output, the sectors that benefit the most are S18 (real estate) with €10.45 followed by S12 (construction), S13 (trade), S19 (public administration), and S20

(education) with still rather sizable effects of €2.44, €2.54, €1.70 and €1.79, respectively.

The effects of social infrastructure investments are reported in Table 6.3 and Figure 6.3.

Across the four main sectors of economic activity the benefits are again overwhelmingly concentrated on private services and to a lesser extent on public services, being mostly negative for the primary sectors and small but most often than not positive for manufacturing. At a more disaggregated level, the positive effects on private investment are particularly significant for S18 (real estate) and S19 (professional services) and very important for S13 (trade), S17 (finance), and S20

(public administration). In terms of employment, we start by noticing sizable negative effects on employment in S1 (agriculture), S4 (textiles), and S15 (hospitality). On the other hand, we see very large effects on employment in S12 (construction), S13 (trade) and S19 (professional services). As output is concerned, there are sizable positive effects on output of S9 (machinery and equipment) and sizable negative effects for output of S10 (electricity and gas) and S11 (water). The largest

110

output effects are on S12 (construction) with €3.41 and S18 (real estate) with €5.31, with very sizable effects for S13 (trade), S14 (transportation), S17 (finance), and S19 (professional services) and the three public services sectors, S20 (administration), S21 (education) and S22 (health).

As to investments in public utilities, results are reported in Table 6.4 and Figure 6.4. The results are, with very few exceptions, very small. Indeed, forty of the sixty six elasticities estimated are not statistically different from zero.

Finally, the effects of investments in telecommunications are reported in Table 6.5 and

Figure 6.5. These investments have the greatest impact on private services with moderate positive effects on the output in public services, employment in all the other sectors and private investment in manufacturing. The largest effects on private investment are in S14 (transportation), S18 (real estate) and S19 (professional services) and to a lesser extent in S13 (trade) while the largest effects on employment occur in sectors S12 (construction), S13 (trade) and S19 (professional services), and to a lesser extent on S15 (hospitality). In terms of output, the largest effects occur in S18 (real estate) with €4.47 followed by S12 (construction), S13 (trade), S17 (finance), S19 (professional services), and

S21 (public administration) with effects of €1.79, €1.16, €1.59, €1.19, and €1.04, respectively.

A clear picture emerges from these more disaggregated results. The fact that the benefits of the different types of infrastructure investments accrue mostly to private services and to a lesser extent to public services is now sharpened as even within these sectors there are sectors that seem to benefit the most while others seem to be mainly unaffected. Let’s consider some informative details.

We have identified one hundred and ten infrastructure-industry specific effects on each of private investment, employment, and output. For private investment, we observe fourteen effects that are significantly positive and above €1, of which twelve are in private services – three in S13

(trade), S19 (professional services), two in S18 (real estate) and S14 (transportation) and one for S12

(construction) and S17 (finance). For employment there are sixteen effects that are significantly

111

positive and larger than 15 full time jobs per one million Euros of investment. Of these, thirteen accrue to private services – four to S12 (construction) and S19 (professional services) three to S13

(retail) and two to S15 (hospitality). The remaining three go to S20 (public administration), S21

(education) and S1 (agriculture). Finally, for output there are seventeen effects that are significantly positive and greater that €1, fourteen for private services – five for S18 (real estate) three for S12

(construction) and two for S13 (trade) and S19 (professional services), with the remaining for S15

(hospitality) and S17 (finance) - and three for public services – two for S20 (public administration) and one for S21 (education).

A casual observation, therefore, suggests that within private services S12 (construction), S13

(trade), S18 (real estate) and S19 (professional services) and to a lesser extent S15 (hospitality) and

S17 (finance) were in absolute terms the great beneficiaries from infrastructure investments. In turn,

S20 (public administration) was the greatest beneficiary for public services.

On the Effects on the Composition of Economic Activity

In this section, we probe more formally into the issue of which sectors benefit the most from infrastructure investments. We want to identify the effects of infrastructure investment on the industry mix in the country, in particular as it affects the traded – non-traded divide.

To analyze the effects of infrastructure investments on the industry mix, we need to move beyond the magnitude of the effects of infrastructure investments in absolute terms and turn to the effects in relative terms. This means, first, for each sector the size of its effects relative to the total effects for all sectors and, second, these shares relative to the size of the industry. The point is that the small effects for certain sectors, maybe just a reflection of the fact that these sectors are small.

Furthermore, even small effects are significant if the share of the total effects they represent exceeds the share of the sector in the total economy. In this case, the marginal effects induced by the

112

infrastructure investments exceed the average size of the sector and as such infrastructure investments tend to make such sector relatively more important in the industry mix.

We can conceptualize the results in four categories – for sectors with negative effects or effects that are not statistically different from zero, infrastructure investments have decisively changed the industry mix away from them, while for sectors with positive effects in particularly when the share of the total effects they represent exceeds the share of the sector in the total economy, infrastructure investments have biased the industry mix in their favor. The results of infrastructure investments in the industry mix are reported in Table 6.6 to Table 6.10.

Road infrastructure investments at the more aggregated level leads to a shift of private investment to private and public services, employment to private services, and output to both private and public services. At a more disaggregated level, in terms of private investment the largest gains go to S19 (professional services) followed by S15 (hospitality) and S21 (education) while for employment, the largest relative gains go also to S19 (professional services), followed by S13 (trade),

S15 (hospitality), and S20 (public administration). Finally, in terms of the output mix, the largest gains in relative terms come to S18 (real estate), and to a lesser extent, to S12 (construction), S15

(hospitality), S21 (education), and S22 (health).

Other transportation infrastructure investments, at a more aggregated level induce a shift in the industry mix towards greater employment and private investment shares in private services and a clear shift in output towards private and public services. In terms of private investment the largest relative gains go to S3 (food), S5 (paper) S14 (transportation), S15 (hospitality), S19 (professional services) while for employment the largest relative gains go to S2 (mining), as well as S12

(construction), S15 (hospitality) and S19 (professional services). For output, S18 (real estate) is the largest beneficiary in relative terms, followed by S10 (electricity and gas), S11 (water), S12

(construction), S15 (hospitality), and S21 (education).

113

In terms of social infrastructure investments, the industry mix is shifted toward manufacturing and public services for private investment, private services for employment and private and public services for output. At a more detailed level, for private investment, the large relative gains accrue to S5 (paper) and S8 (basic metals) as well as S13 (trade), S17 (finance), S19

(professional services), S21 (education) and S22 (health). For employment, we see high relative gains for S12 (construction), S18 (real estate), and S19 (professional services) and to a lesser extent S7

(non-metallic) and S8 (basic metal). For output the largest relative gains accrue to S12 (construction),

S18 (real estate) followed by S9 (machinery and equipment) S14 (transportation and storage), S17

(finance), S19 (professional services), S21 (education), and S22 (health).

The case of investments in public utilities is not particularly interesting or informative as its effects tend to be rather small and make very little difference in terms of the industry mix. Finally, for investments in telecommunication infrastructures, the effects suggest an industry shift towards manufacturing for private investment and towards private services for private investment, employment, and output. For private investment the largest relative gains accrue to S3 (food) S5

(paper) S7 (non-metallic) as well as S14 (transportation), S15 (hospitality), S16 (telecommunications),

S21 (education) and S22 (health). The largest relative employment effects go for S7 (non-metallic) and S9 (machinery and equipment) as well as S15 (hospitality), S18 (real estate), S19 (professional services), and S21 (education). Finally, the largest relative output effects go to S7 (non-metallic), S12

(construction), S18 (real estate), and S19 (professional services).

In final analysis, overall the ten sectors producing traded goods lost ground in their relative importance due to the impact of infrastructure investments. This is despite some relative gains across the board for S7 (non-metallic minerals), S8 (basic metals), S9 (machinery and equipment) and S14 (transportation and storage), some employment gains for S2 (mining) and S8 (basic metals), and some private investment gains for S3 (food) and S5 (paper). Among the five emerging traded

114

sectors only S15 (hospitality) and S19 (professional services), seemed to have benefitted in a very clear, consistent and significate manner. Finally, the largest gains in relative terms across the board go unquestionably to S12 (construction), S18 (real estate), S21 (education) and S22 (health), with important gains for S13 (trade) in terms of employment and private investment and for S20 (public administration) in terms of employment.

On the Relationship between the Aggregate and Sectorial Effects

The relationship between the aggregate effects and the sum of the industry-specific results deserves some considerations. This is because we want to make sure that the results discussed here which were obtained from the twenty two individual industries for each one of the five main infrastructure assets, are consistent with the results obtained at a more aggregate level, say when we consider the aggregate economy as a whole.

Given their public good nature, when infrastructure investments occur, the new assets become available, simultaneously, to all industries. From this standpoint, one could think that the sum of the marginal products of infrastructure investments across industries should be equal to the marginal products estimated with more aggregate models.

It is more likely, however, for the sum of the industry-specific effects to somewhat differ from the aggregate effects. This is due to the likely existence of general equilibrium effects that are not captured at the individual industry level. Consider, for example, the effects of infrastructure investments on private input decisions. When an infrastructure is made available, more inputs are desired, simultaneously, by all industries. This simultaneous increase in demand, however, is limited by resource constraints in the economy. Therefore, part of the increased demand induces higher input prices and a downward adjustment of the industry-specific input demands. Thus, it is likely that the sum of the sectorial marginal products will somewhat exceed the aggregate effects.

In the same vein, the increase in output observed for each industry individually would not

115

affect substantially the output prices at the aggregate level. This is to say that it is as if each sector has a horizontal output supply schedule. At the aggregate level, however, we would expect the simultaneous increase in output in most industries to lead to a reduction in the equilibrium output price and to smaller aggregate output effects.

To check on this issue, we first obtain the sum (weighted by the share of each infrastructure asset in total infrastructure investment) across the different industries of all of the statistically significant marginal products of infrastructure investment (among the one hundred and ten estimates). We then obtain the sum (again weighted by the share of each infrastructure asset) of the marginal products obtained with the five aggregate models for the whole economy, one for each of the infrastructure assets. The weights allow us to interpret both sums as the total marginal product for the economy of a one Euro invested in infrastructures in the country. We find that the sum of the marginal products from the one hundred and ten industry-infrastructure specific models represent for private investment, employment, and output, 134.7%, 125.5% and 167.4%, respectively, of the sum of the marginal products for the five aggregate models. In light of the previous discussion, these figures have several corollaries. First, the results from the industry- infrastructure specific models are very much in line with the results from the more aggregate models.

Second, the general equilibrium effects seem to be relevant in all cases, in particular output. Finally, the magnitude of these general equilibrium effects are in line with our estimates for Portugal, Spain and the United States [see, Pereira and Andraz (2001), Pereira and Roca (2001), Pereira and Andraz

(2007)], although they tend to be slightly larger general equilibrium effects in our case.

From a practical perspective what this means is that the estimates presented here at the individual industry-infrastructure specific level are likely to over-estimate the actual effects of the infrastructure investments. There is no reason, however, to think that this would in any way affect

116

the disaggregated patterns we have identified in terms of the effects both in absolute terms and in relative terms.

6.3 Summary and Concluding Remarks

Summary

This chapter analyzes the effects of infrastructure investment at the industry level in

Portugal. We employ a vector autoregressive approach for twenty two sectors covering the whole spectrum of economic activity and considering five different infrastructure assets to estimate industry-infrastructure specific effects and ultimately identify the effects of infrastructure investments on the industry mix.

At a more aggregate level, we first establish that the most important effects from infrastructure investments come from other transportation, social infrastructures and telecommunications with some less important effects from road infrastructures and insignificant effects from public utilities. We also find that the benefits from infrastructure investment tend to accrue mostly to private services and to a lesser extent to public services with typically detrimental effects on the primary sector and more mixed effects on the manufacturing sector.

With this background information, we analyze the industry effects in detail. In absolute terms, we find that within the private service sectors, construction, trade, real estate, and professional services, and to a lesser extent hospitality and finance, were the greatest beneficiaries from infrastructure investments while public administration was the greatest beneficiary among the public service sectors.

In relative terms, with a focus on the industry divide between traded and non-traded goods, we find that the infrastructure investments tended to shift the industry mix towards private and public services and therefore mostly towards sectors producing non-traded goods. We find that the

117

sectors that tended to benefit the most in relative terms are construction, trade, and real estate among the private services and public administration, education and health among the public services. All of these are sectors producing non-traded goods. There also some important effects in some sectors producing traded sectors such as chemical and pharmaceutical, machinery and equipment and, in particular, transportation and storage, as well as among emerging trading sectors such as hospitality and professional services.

Policy Implications

There are several important policy implications from these results. They stem from the key finding that the positive aggregate effects of the different types of infrastructure investments mask rather diverse effects at the industry level. Accordingly, a first policy implication is the recognition that infrastructure development strategies are far from neutral in that they effectively represent picking winners and losers as different industries are concerned. Moreover, the fact that the lopsided benefits accrue mostly to non-traded sectors represents a push in the direction of a development model based on domestic demand that may not be sustainable given its implications for the foreign account position of the country.

Second, and from a prospective standpoint, there is the issue of what can be expected from the infrastructure investments that are currently being considered in the country. It would seem that the great focus for the next few decades will be on non-road transportation and social infrastructure.

Indeed, the time has passed for any focus on road infrastructure, which is perceived as having already achieved a high level of maturity if not outright overinvestment. In addition, investments in public utilities and telecommunications are now mostly in the hands of the private sector and therefore less directly affected by public policy.

As per our results, infrastructure investments in the areas of other transportation and social infrastructures will have very important aggregate effects but may also deepen the bias in the

118

industry mix towards non-traded goods. Investments in other transportation in relative terms mostly favors employment in professional services and to a lesser extent construction, hospitality, and real estate, and mostly favors output in real estate and to a lesser extent in utilities, construction, and education. In turn, investments in social infrastructures tend to increase the share of employment in real estate, professional services, and construction as well as the traded sectors of non-metallic minerals and basic metals, and the share of output in real estate, construction, finance, education, and health as well as the traded sector of machinery and equipment.

119

120

Table 6.1 Effects of Road Transportation Investment by Sector of Economic Activity Elasticity Marginal Product

Private Private Employment Output Employment Output Investment Investment

Agriculture and Mining -0.03 0.9 -0.19 Agriculture (S1) 0.1641* 0.0024* -0.1180 0.06* 0.5* -0.18 Mining (S2) -1.4527 0.0545* -0.0566* -0.09 0.4* -0.01* Manufacturing 0.60 2.0 0.41 Food (S3) 0.0882* -0.0359 0.1138 0.02* -1.7 0.13 Textiles (S4) 0.3323* -0.0031* 0.0629* 0.03* -0.3* 0.09* Paper (S5) 0.1283* 0.0396 -0.0505* 0.03* 1.4 -0.05* Chemical and Pharmaceutical (S6) 1.1317 0.0092* -0.1251 0.11 0.1* -0.06 Non-metallic minerals (S7) 0.4417 0.0435 0.1530 0.10 1.6 0.16 Basic metals (S8) 0.3712 0.0162* -0.0557* 0.05 0.7* -0.05* Machinery and equipment (S9) 0.6143 0.0031* 0.0965* 0.26 0.2* 0.19* Private Services 3.62 55.1 4.16 Electricity and gas (S10) 0.2866* -0.1848 -0.0824* 0.16* -0.9 -0.10* Water (S11) 0.8385* -0.1461 -0.0949* 0.28* -2.2 -0.04* Construction (S12) 0.2550* 0.0125* 0.1429 0.15* 2.8* 0.58 Wholesale and retail trade (S13) 0.4155 0.0628 0.0965 0.37 19.7 0.72 Transportation and storage (S14) 0.4518* 0.0031* 0.0017* 0.51* 0.2* 0.00* Hospitality (S15) 0.5122 0.0796 0.1558 0.16 8.5 0.39 Telecommunications (S16) 0.3827 0.0007* -0.0027* 0.17 0.0* 0.00* Finance (S17) 0.5326 -0.0328* 0.0613* 0.28 -1.4* 0.22* Real estate (S18) 0.2431 0.0055* 0.5827 0.94 0.1* 2.47 Professional services (S19 0.4446 0.1233 -0.0163* 0.61 28.3 -0.08* Public Services 0.93 10.9 1.31 Public administration (S20) 0.4184 0.0611 0.1094 0.62 8.1 0.51 Education (S21) 0.4842 0.0128* 0.1407 0.12 1.7* 0.51 Health (S22) 0.3256* 0.0082* 0.0936 0.19* 1.1* 0.29 TOTAL 5.13 68.9 5.69

(*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

121

Figure 6.1 Effects of Road Transportation Investment by Sector of Economic Activity 7 Marginal Product for Private Investment (Euros) 5 3 0.37 0.51 0.94 0.61 0.62 1 0.06 0.02 0.03 0.03 0.11 0.10 0.05 0.26 0.16 0.28 0.15 0.16 0.17 0.28 0.12 0.19 -1 -0.06 -3 -5 -7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

28.3 Marginal Product for Employment (Jobs) 25 19.7

15 8.5 8.1 2.8 5 0.5 0.1 1.4 0.1 1.6 0.7 0.2 0.2 0.0 0.1 1.7 1.1

-5 -1.7 -0.3 -0.9 -2.2 -1.4 -15 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Output (Euros) 15

5 2.47 0.13 0.09 0.16 0.19 0.58 0.72 0.00 0.39 0.22 0.51 0.51 0.29 0 -0.18-0.02 -0.05-0.06 -0.05 -0.10-0.04 0.00 -0.08 -5 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

122

Table 6.2 Effects of Other Transportation Investment by Sector of Economic Activity Elasticity Marginal Product

Private Private Employment Output Employment Output Investment Investment Agriculture and Mining 0.21 38.9 -0.08

Agriculture (S1) 0.4602 0.0507 -0.0159* 0.56 32.3 -0.08* Mining (S2) -1.7191 0.2900 0.0008* -0.35 6.6 0.00* Manufacturing 1.93 -18.9 -0.92

Food (S3) 0.5144 -0.0291 0.0718 0.38 -4.5 0.27 Textiles (S4) 0.4315 0.0143* 0.0315* 0.15 5.1* 0.15* Paper (S5) 0.6064 0.0173* -0.0536* 0.42 2.1* -0.17* Chemical and Pharmaceutical (S6) 0.8075 0.0009* -0.0690 0.27 0.0* -0.10 Non-metallic minerals (S7) 0.0981* -0.0101* 0.0151* 0.07* -1.2* 0.05* Basic metals (S8) 0.1424* -0.0210* -0.0136* 0.07* -2.9* -0.04* Machinery and equipment (S9) 0.6038 -0.0679 -0.1832 0.84 -17.5 -1.17 Private Services 13.68 245.6 17.16

Electricity and gas (S10) 0.6703* -0.0950 0.1714 1.21* -1.5 0.67 Water (S11) -0.3523* -0.0378* 0.1440 -0.38* -1.8* 0.22 Construction (S12) 0.6136 0.0975 0.1814 1.19 72.8 2.44 Wholesale and retail trade (S13) 0.4940 0.0507 0.1026 1.46 52.3 2.54 Transportation and storage (S14) 1.1246 0.0175* -0.0560* 4.15 4.0* -0.45* Hospitality (S15) 0.9224 0.0834 0.1330 0.96 29.3 1.10 Telecommunications (S16) 0.3642 -0.0215* -0.0376 0.54 -0.5* -0.15 Finance (S17) -0.4479 -0.1193 -0.0009* -0.77 -16.4 -0.01* Real estate (S18) 0.1878* 0.1007* 0.7476 2.40* 4.7* 10.45 Professional services (S19 0.6419 0.1358 0.0229* 2.92 102.7 0.37* Public Services 1.33 8.3 3.68

Public administration (S20) 0.1967* 0.0352 0.1116 0.96* 15.4 1.70 Education (S21) 0.2413* 0.0150* 0.1492 0.20* 6.4* 1.79 Health (S22) 0.0878* -0.0295* 0.0192 0.17* -13.5* 0.19 TOTAL 17.15 273.9 19.84

(*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

123

Figure 6.2 Effects of Other Transportation Investment by Sector of Economic Activity 7 Marginal Product for Private Investment (Euros) 5 4.15 2.40 2.92 3 1.21 1.19 1.46 0.56 0.38 0.42 0.84 0.96 0.54 0.96 1 0.15 0.27 0.07 0.07 0.20 0.17 -1 -0.28 -0.38 -0.77 -3 -5 -7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

120 Marginal Product for Employment (Jobs) 102.7 72.8 70 52.3 32.3 29.3 15.4 20 4.7 5.1 2.1 0.0 4.0 4.7 6.4

-4.5 -1.2 -2.9 -1.5 -1.8 -0.5 -30 -17.5 -16.4 -13.5 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Output (Euros) 15 10.45 10

5 2.44 2.54 1.70 1.79 0.27 0.15 0.05 0.67 0.22 1.10 0.37 0.19 0 -0.08-0.02 -0.17-0.10 -0.04 -0.45 -0.15-0.01 -5 -1.17 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

124

Table 6.3 Effects of Social Infrastructure Investment by Sector of Economic Activity Elasticity Marginal Product

Private Private Employment Output Employment Output Investment Investment Agriculture and Mining -0.12 -59.1 -1.12

Agriculture (S1) 0.1627* -0.1364 -0.2930 0.14* -60.1 -1.03 Mining (S2) -1.8931* 0.0602* -0.1525 -0.26* 1.0* -0.09 Manufacturing 2.91 16.2 1.46

Food (S3) 0.1629* 0.0143* 0.0562* 0.08* 1.5* 0.14* Textiles (S4) 0.1150* -0.0545 -0.1206 0.03* -13.5 -0.39 Paper (S5) 0.7114 0.0001* 0.1377 0.34 0.0* 0.29 Chemical and Pharmaceutical (S6) 1.2704 0.0432 -0.2060 0.29 0.9 -0.21 Non-metallic minerals (S7) 0.8187 0.0913 0.2366 0.43 7.6 0.56 Basic metals (S8) 1.2334 0.1049 0.0347* 0.41 10.0 0.07* Machinery and equipment (S9) 0.7296 0.0543* 0.2804 0.70 9.7* 1.24 Private Services 12.40 191.2 13.58

Electricity and gas (S10) 1.1682* -0.0738 -0.4602 1.46* -0.8 -1.24 Water (S11) 0.6854* -0.1370 -0.4291 0.51* -4.6 -0.45 Construction (S12) 0.7300 0.1629 0.3659 0.98 84.2 3.41 Wholesale and retail trade (S13) 0.8651 0.0611 0.0707 1.77 43.7 1.21 Transportation and storage (S14) 0.1068* 0.0742 0.2468 0.27* 11.6 1.37 Hospitality (S15) -0.0124* -0.0727 -0.0362* -0.01* -17.7 -0.21* Telecommunications (S16) 0.0164* -0.0287* -0.0297* 0.02* -0.4* -0.08* Finance (S17) 1.0855 0.0204* 0.2547 1.30 1.9* 2.06 Real estate (S18) 0.3488 0.1755 0.5494 3.08 5.7 5.31 Professional services (S19 0.9586 0.1482 0.1985 3.02 77.6 2.20 Public Services 3.21 31.1 4.58

Public administration (S20) 0.4642 0.0086* 0.1505 1.57 2.6* 1.59 Education (S21) 1.1187 0.0575 0.2369 0.65 17.1 1.96 Health (S22) 0.7540 0.0359 0.1481 0.99 11.4 1.03 TOTAL 18.40 179.4 18.50

(*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

125

Figure 6.3 Effects of Social Infrastructure Investment by Sector of Economic Activity 7 Marginal Product for Private Investment (Euros) 5 3.08 3.02 3 1.46 1.77 1.30 1.57 0.34 0.43 0.41 0.70 0.51 0.98 0.65 0.99 1 0.14 0.08 0.03 0.29 0.27 0.02 -1 -0.04 -0.01 -3 -5 -7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

110 Marginal Product for Employment (Jobs) 84.2 77.6

60 43.7

11.6 17.1 11.4 7.6 10.0 9.7 5.7 2.6 10 0.9 1.5 0.0 0.9 1.9 -0.8 -4.6 -0.4 -13.5 -40 -17.7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Output (Euros) 15

10 5.31 3.41 5 1.37 2.06 2.20 1.59 1.96 0.14 0.29 0.56 0.07 1.24 1.21 1.03 0 -1.03-0.12 -0.39 -0.21 -0.45 -0.21-0.08 -5 -1.24 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

126

Table 6.4 Effects of Public Utility Investment by Sector of Economic Activity Elasticity Marginal Product

Private Private Employment Output Employment Output Investment Investment Agriculture and Mining -0.06 -3.5 -0.12

Agriculture (S1) -0.1680 -0.0205 -0.0891 -0.07 -4.2 -0.15 Mining (S2) 0.0955* 0.0953 0.1095 0.01* 0.7 0.03 Manufacturing -0.04 2.3 -0.02

Food (S3) -0.1905 0.0107* -0.0053* -0.05 0.5* -0.01* Textiles (S4) -0.0166* 0.0122 0.0002* 0.00* 1.4 0.00* Paper (S5) -0.2232 -0.0051* -0.0028* -0.05 -0.2* 0.00* Chemical and Pharmaceutical (S6) -0.0319* 0.0177 -0.0579 0.00* 0.2 -0.03 Non-metallic minerals (S7) -0.1272 -0.0066* -0.0113* -0.03 -0.3* -0.01* Basic metals (S8) 0.2288* 0.0413 0.1307 0.04* 1.8 0.13 Machinery and equipment (S9) -0.0607* -0.0108* -0.0663 -0.03* -0.9* -0.14 Private Services 0.21 -17.7 -1.29

Electricity and gas (S10) 1.3999 0.0156* -0.0695 0.82 0.1* -0.09 Water (S11) 1.0323 0.0108* -0.0381* 0.36 0.2* -0.02* Construction (S12) -0.0887* 0.0424 0.0227* -0.06* 10.3* 0.10* Wholesale and retail trade (S13) -0.0715* 0.0046* 0.0156 -0.07* 1.5* 0.13 Transportation and storage (S14) -0.2044* 0.0040* -0.0202* -0.25* 0.3* -0.05* Hospitality (S15) -0.2324 -0.0056* -0.0023* -0.08 -0.6* -0.01* Telecommunications (S16) -0.2096 0.0080* -0.0027* -0.10 0.1* 0.00* Finance (S17) -0.2227* -0.0250 -0.0420* -0.13* -1.1 -0.16* Real estate (S18) -0.0539* -0.0829 -0.2726 -0.22* -1.3 -1.24 Professional services (S19 -0.0433* -0.1063 0.0103* -0.06* -26.2 0.05* Public Services -0.06 2.6 0.07

Public administration (S20) -0.0308* 0.0198 0.0312 -0.05* 2.8 0.16 Education (S21) -0.0285* 0.0036* -0.0298* -0.01* 0.5* -0.12* Health (S22) -0.0011* -0.0046* 0.0088* 0.00* -0.7* 0.03* TOTAL 0.05 -16.3 -2.36

(*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

127

Figure 6.4 Effects of Public Utility Investment by Sector of Economic Activity 7 Marginal Product for Private Investment (Euros) 5 3 0.82 0.36 1 0.01 0.04 -1 -0.07 -0.05 0.00 -0.05 0.00 -0.03 -0.03 -0.06-0.07-0.25-0.08-0.10-0.13-0.22-0.06-0.05-0.01 0.00 -3 -5 -7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Employment (Jobs) 15 10.3 10 1.8 2.8 5 0.7 0.5 1.4 0.2 0.1 0.2 1.5 0.3 0.1 0.5 0 -5 -0.2 -0.3 -0.9 -0.6 -1.1 -1.3 -0.7 -4.2 -10 -15 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Output (Euros) 15

5 0.03 0.00 0.13 0.10 0.13 0.05 0.16 0.03 0 -0.15 -0.01 0.00 -0.03-0.01 -0.14-0.09-0.02 -0.05-0.01 0.00 -0.16 -0.12 -5 -1.24 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

128

Table 6.5 Effects of Telecommunications Infrastructure Investment by Industry Elasticity Marginal Product

Private Private Employment Output Employment Output Investment Investment Agriculture and Mining 0.32 9.4 0.12

Agriculture (S1) 0.4452 0.0134* 0.0126* 0.36 5.7* 0.04* Mining (S2) -0.3155* 0.2457 0.1336* -0.04* 3.7 0.08* Manufacturing 2.39 24.4 1.16

Food (S3) 0.7388 0.0073* 0.0194* 0.37 0.8* 0.05* Textiles (S4) 0.7068 0.0276 -0.0146* 0.16 6.6 -0.05* Paper (S5) 0.7540 0.0405 0.0955 0.35 3.2 0.20 Chemical and Pharmaceutical (S6) 0.6313 0.0355 -0.0117* 0.14 0.7 -0.01* Non-metallic minerals (S7) 0.5976 0.0384 0.0746 0.30 3.1 0.17 Basic metals (S8) 0.6244 0.0584 0.1609 0.20 5.3 0.33 Machinery and equipment (S9) 0.7399 0.0280 0.0276* 0.69 4.8 0.12* Private Services 8.91 183.6 10.88

Electricity and gas (S10) -0.6879 -0.0317 0.0283* -0.83 -0.3 0.07* Water (S11) -1.3333 -0.0643 0.0294* -0.96 -2.1 0.03* Construction (S12) 0.7664 0.1114 0.1994 0.99 55.6 1.79 Wholesale and retail trade (S13) 0.5943 0.0515 0.0701 1.17 35.5 1.16 Transportation and storage (S14) 0.8416 0.0463 0.0327* 2.07 7.0 0.17* Hospitality (S15) 1.1400 0.0699 0.0946 0.79 16.4 0.52 Telecommunications (S16) 0.6483 0.0003* -0.0397 0.64 0.0* -0.11 Finance (S17) 0.3142 -0.0282 0.2044 0.36 -2.6 1.59 Real estate (S18) 0.2806 0.0939 0.4793 2.39 2.9 4.47 Professional services (S19 0.7542 0.1509 0.1112 2.29 76.2 1.19 Public Services 0.98 20.5 1.82

Public administration (S20) 0.1216* 0.0253* 0.1024 0.40* 7.4* 1.04 Education (S21) 0.3463 0.0176 0.0671* 0.19 5.0 0.54* Health (S22) 0.3045 0.0264* 0.0355* 0.39 8.1* 0.24* TOTAL 12.60 237.9 13.98

(*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

129

Figure 6.5 Effects of Telecommunications Investment by Sector of Economic Activity 7 Marginal Product for Private Investment (Euros) 5 2.07 2.39 2.29 3 1.17 0.36 0.37 0.35 0.30 0.69 0.99 0.79 0.64 0.36 0.40 0.39 1 0.16 0.14 0.20 0.19 -1 -0.01 -0.83 -3 -0.96 -5 -7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

Marginal Product for Employment (Jobs) 105 85 76.2 65 55.6 45 35.5 16.4 25 7.0 7.4 8.1 5.7 2.7 0.8 6.6 3.2 0.7 3.1 5.3 4.8 0.0 2.9 5.0 5 -15 -0.3 -2.1 -2.6 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

20 Marginal Product for Output (Euros) 15

10 4.47 5 1.79 1.59 0.04 0.04 0.05 0.20 0.17 0.33 0.12 0.07 0.03 1.16 0.17 0.52 1.19 1.04 0.54 0.24 0 -0.05 -0.01 -0.11 -5 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22

130

Table 6.6 Effects of Road Infrastructure Investment on the Industry Mix Private Investment Employment Output

Share Share of Marginal Share of Marginal Share of Share Marginal Share of of Ratio Ratio Private Ratio Product Benefits Product Benefits of Emp Product Benefits GFCF Output Agriculture and Mining - - 4.8 - 0.9 0.1 15.5 0.0 - - 8.6 - Agriculture (S1) 0.1* 1.2* 3.8 0.3* 0.5* 0.6* 14.5 0.0* - - 6.7 - Mining (S2) - - 1.0 - 0.4* 0.5* 1.0 0.5* -* -* 1.9 -* Manufacturing 0.60 11.6 13.1 0.9 2.0 2.9 21.8 0.1 0.41 6.9 18.1 0.4 Food (S3) 0.0* 0.4* 1.4 0.3* - - 2.7 - 0.1 2.0 2.1 1.0 Textiles (S4) 0.0* 0.7* 1.3 0.5* -* -* 7.4 -* 0.1* 1.4* 3.7 0.4* Paper (S5) 0.0* 0.5* 1.4 0.4* 1.4 1.9 2.3 0.8 -* -* 2.2 -* Chemical and Pharm.(S6) 0.1 2.2 2.0 1.0 0.1* 0.1* 0.8 0.2* - - 1.7 - Non-metallic minerals (S7) 0.1 1.9 2.0 1.0 1.6 2.1 2.0 1.0 0.2 2.5 2.7 0.9 Basic metals (S8) 0.1 1.0 1.1 1.0 0.7* 0.9* 2.3 0.4* -* -* 2.5 -* Machinery and equipment (S9) 0.3 5.0 4.0 1.2 0.2* 0.3* 4.3 0.1* 0.2* 3.0* 3.3 0.9* Private Services 3.62 70.2 67.8 1.1 55.1 79.9 45.2 1.8 4.16 70.7 56.3 1.3 Electricity and gas (S10) 0.2* 3.0* 4.9 0.6* - - 0.4 - -* -* 2.1 -* Water (S11) 0.3* 5.3* 3.4 1.5* - - 0.9 - -* -* 0.6 -* Construction (S12) 0.2* 2.9* 5.3 0.5* 2.8* 3.7* 10.7 0.4* 0.6 9.2 7.1 1.3 Wholesale & retail trade (S13) 0.4 7.1 5.6 1.3 19.7 26.1 13.9 1.9 0.7 11.4 15.4 0.7 Transportation & storage (S14) 0.5* 9.7* 5.8 1.7* 0.2* 0.3* 3.5 0.1* 0.0* 0.1* 4.6 0.0* Hospitality (S15) 0.2 3.1 1.9 1.6 8.5 11.3 4.4 2.6 0.4 6.2 3.7 1.7 Telecommunications (S16) 0.2 3.3 2.7 1.2 0.0* 0.0* 0.4 0.0* -* -* 1.9 -* Finance (S17) 0.3 5.3 4.8 1.1 -* -* 2.3 -* 0.2* 3.4* 6.3 0.5* Real estate (S18) 0.9 18.0 26.6 0.7 0.1* 0.1* 0.5 0.2* 2.5 38.9 7.5 5.2 Professional services (S19) 0.6 11.7 6.7 1.8 28.3 37.5 8.1 4.6 -* -* 7.2 -* Public Services 0.93 18.0 14.4 1.3 10.9 15.8 17.5 0.9 1.31 22.3 17.0 1.3 Public administration (S20) 0.6 11.9 10.8 1.1 8.1 10.8 8.0 1.3 0.5 8.0 8.5 0.9 Education (S21) 0.1 2.4 1.7 1.4 1.7* 2.2* 5.7 0.4* 0.5 8.0 5.3 1.5 Health (S22) 0.2* 3.6* 1.9 1.9* 1.1* 1.5* 3.8 0.4* 0.3 4.5 3.2 1.4 100.0 100.0 100.0 100.0 - 100.0 100.0

(*) The effects marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

131

Table 6.7 Effects of Other Infrastructure Investment on the Industry Mix Private Investment Employment Output Share Share of Marginal Share of Marginal Share of Share Marginal Share of of Ratio Ratio Private Ratio Product Benefits Product Benefits of Emp Product Benefits GFCF Output Agriculture and Mining 0.21 1.2 4.8 0.3 38.9 13.3 15.5 0.9 - - 8.6 - Agriculture (S1) 0.6 2.9 3.8 0.8 32.3 9.7 14.5 0.7 -* -* 6.7 -* Mining (S2) - - 1.0 - 6.6 2.0 1.0 2.0 0.0* 0.0* 1.9 0.0* Manufacturing 1.93 11.3 13.1 0.9 - - 21.8 - 18.1 Food (S3) 0.4 2.0 1.4 1.5 - - 2.7 - 0.3 1.2 2.1 0.6 Textiles (S4) 0.1 0.8 1.3 0.6 5.1* 1.5* 7.4 0.2* 0.1* 0.7* 3.7 0.2* Paper (S5) 0.4 2.2 1.4 1.6 2.1* 0.6* 2.3 0.3* -* - 2.2 - Chemical and Pharm.(S6) 0.3 1.4 2.0 1.3 0.0* 0.0* 0.8 0.0* - - 1.7 - Non-metallic minerals (S7) 0.3* 1.4* 2.0 0.7* 0.0* 0.0* 2.0 0.0* -* - 2.7 - Basic metals (S8) 0.1* 0.4* 1.1 0.3* -* -* 2.3 -* -* - 2.5 - Machinery and equipment (S9) 0.8 4.4 4.0 1.1 - - 4.3 - - - 3.3 - Private Services 13.68 79.8 67.8 1.2 245.6 83.9 45.2 1.9 17.16 82.3 56.3 1.5 Electricity and gas (S10) 1.2* 6.4* 4.9 1.3* - - 0.4 - 0.7 3.0 2.1 1.4 Water (S11) -* -* 3.4 -* -* -* 0.9 -* 0.2 1.0 0.6 1.5 Construction (S12) 1.2 6.3 5.3 1.2 72.8 21.8 10.7 2.0 2.4 10.9 7.1 1.5 Wholesale & retail trade (S13) 1.5 7.7 5.6 1.4 52.3 15.7 13.9 1.1 2.5 11.3 15.4 0.7 Transportation & storage (S14) 4.1 21.9 5.8 3.8 4.0* 1.2* 3.5 0.3* -* -* 4.6 -* Hospitality (S15) 1.0 5.1 1.9 2.7 29.3 8.8 4.4 2.0 1.1 4.9 3.7 1.3 Telecommunications (S16) 0.5 2.8 2.7 1.1 -* -* 0.4 -* - - 1.9 - Finance (S17) - - 4.8 - - - 2.3 - -* -* 6.3 -* Real estate (S18) 2.4* 12.7* 26.6 0.5* 4.7* 1.4* 0.5 2.9* 10.4 46.6 7.5 6.3 Professional services (S19) 2.9 15.5 6.7 2.3 102.7 30.8 8.1 3.8 0.4* 1.6* 7.2 0.2* Public Services 1.33 7.7 14.4 0.5 8.3 2.8 17.5 0.2 3.68 17.7 17.0 1.1 Public administration (S20) 1.0* 5.1* 10.8 0.5* 15.4 4.6 8.0 0.6 1.7 7.6 8.5 0.9 Education (S21) 0.2* 1.1* 1.7 0.6* 6.4 1.9 5.7 0.3 1.8 8.0 5.3 1.5 Health (S22) 0.2* 0.9* 1.9 0.5* - - 3.8 - 0.2 0.9 3.2 0.3 100.0 100.0 100.0 100.0 - 100.0 100.0

(*) The effects marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

132

Table 6.8 Effects of Social Infrastructure Investment on the Industry Mix Private Investment Employment Output Share of Marginal Share of Share of Marginal Share of Share of Marginal Share of Ratio Ratio Private Ratio Product Benefits GFCF Product Benefits Emp Product Benefits Output Agriculture and Mining - - 4.8 - - - 15.5 - - - 8.6 - Agriculture (S1) 0.1* 0.7* 3.8 0.2* - - 14.5 - - - 6.7 - Mining (S2) -* -* 1.0 -* 1.0* 0.3* 1.0 0.3* - - 1.9 - Manufacturing 2.91 15.7 13.1 1.2 16.2 6.8 21.8 0.3 1.46 7.4 18.1 0.4 Food (S3) 0.1* 0.5* 1.4 0.3* 1.5* 0.5* 2.7 0.2* 0.1* 0.6* 2.1 0.3* Textiles (S4) 0.0* 0.1* 1.3 0.1* - - 7.4 - - - 3.7 - Paper (S5) 0.3 1.8 1.4 1.3 0.0* 0.0* 2.3 0.0* 0.3 1.3 2.2 0.6 Chemical and Pharm.(S6) 0.3 1.6 2.0 1.4 0.9 0.3 0.8 0.5 - - 1.7 - Non-metallic minerals (S7) 0.4 2.3 2.0 1.1 7.6 2.7 2.0 1.3 0.6 2.5 2.7 0.9 Basic metals (S8) 0.4 2.2 1.1 2.1 10.0 3.5 2.3 1.5 0.1* 0.3* 2.5 0.1* Machinery and equipment (S9) 0.7 3.8 4.0 0.9 9.7* 3.4* 4.3 0.8* 1.2 5.5 3.3 1.7 Private Services 12.4 66.9 67.8 1.0 191.2 80.2 45.2 1.8 13.58 69.2 56.3 1.2 Electricity and gas (S10) 1.5* 7.8* 4.9 1.6* - - 0.4 - - - 2.1 - Water (S11) 0.5* 2.8* 3.4 0.8* - - 0.9 - - - 0.6 - Construction (S12) 1.0 5.3 5.3 1.0 84.2 29.4 10.7 2.8 3.4 15.2 7.1 2.1 Wholesale & retail trade (S13) 1.8 9.5 5.6 1.7 43.7 15.3 13.9 1.1 1.2 5.4 15.4 0.4 Transportation & storage (S14) 0.3* 1.5* 5.8 0.3* 11.6 4.0 3.5 1.1 1.4 6.1 4.6 1.3 Hospitality (S15) -* -* 1.9 - - - 4.4 - -* -* 3.7 -* Telecommunications (S16) 0.0* 0.1* 2.7 0.0* -* -* 0.4 -* -* -* 1.9 -* Finance (S17) 1.3 7.0 4.8 1.4 1.9* 0.7* 2.3 0.3* 2.1 9.2 6.3 1.5 Real estate (S18) 3.1 16.5 26.6 0.6 5.7 2.0 0.5 4.1 5.3 23.7 7.5 3.2 Professional services (S19) 3.0 16.2 6.7 2.4 77.6 27.1 8.1 3.3 2.2 9.8 7.2 1.4 Public Services 3.21 17.4 14.4 1.2 31.1 13.0 17.5 0.7 4.58 23.4 17.0 1.4 Public administration (S20) 1.6 8.4 10.8 0.8 2.6* 0.9* 8.0 0.1* 1.6 7.1 8.5 0.8 Education (S21) 0.6 3.5 1.7 2.0 17.1 6.0 5.7 1.1 2.0 8.7 5.3 1.7 Health (S22) 1.0 5.3 1.9 2.9 11.4 4.0 3.8 1.0 1.0 4.6 3.2 1.5 100.0 100.0 100.0 100.0 - 100.0 100.0

(*) The effects marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

133

Table 6.9 Effects of Public Utilities Investment on the Industry Mix Private Investment Employment Output Margin Share of Share of Share of Marginal Share of Share of Marginal Share of al Ratio Ratio Private Ratio Benefits GFCF Product Benefits Emp Product Benefits Product Output Agriculture and Mining - - 4.8 - - - 15.5 - - - 8.6 - Agriculture (S1) 0.4 2.5 3.8 0.7 5.7 2.3 14.5 0.2 0.0 0.3 6.7 0.0 Mining (S2) -* -* 1.0 -* 3.7 1.5 1.0 1.5 0.1 0.5 1.9 0.3 Manufacturing - - 13.1 - 2.3 + 21.8 + - - 18.1 - Food (S3) 0.4 2.5 1.4 1.8 0.8* 0.3* 2.7 0.1* 0.0* 0.3* 2.1 0.2* Textiles (S4) 0.2* 1.1* 1.3 0.8* 6.6 2.7 7.4 0.4 -* -* 3.7 -* Paper (S5) 0.3 2.4 1.4 1.7 3.2* 1.3* 2.3 0.6* 0.2* 1.4* 2.2 0.6* Chemical and Pharm.(S6) 0.1* 1.0* 2.0 0.9* 0.7 0.3 0.8 0.4 - - 1.7 - Non-metallic minerals (S7) 0.3 2.1 2.0 1.0 3.1* 1.2* 2.0 0.6* 0.2* 1.2* 2.7 0.4* Basic metals (S8) 0.2* 1.4* 1.1 1.3* 5.3 2.2 2.3 0.9 0.3 2.3 2.5 0.9 Machinery and equipment (S9) 0.7* 4.8* 4.0 1.2* 4.8* 1.9* 4.3 0.5* 0.1 0.8 3.3 0.3 Private Services 0.21 + 67.8 + - - 45.2 - - - 56.3 - Electricity and gas (S10) - - 4.9 - -* -* 0.4 - 0.1 0.5 2.1 0.3 Water (S11) - - 3.4 - -* -* 0.9 - 0.0* 0.2* 0.6 0.3* Construction (S12) 1.0* 6.9* 5.3 1.3* 55.6* 22.4* 10.7 2.1* 1.8* 12.7* 7.1 1.8* Wholesale & retail trade (S13) 1.2* 8.1* 5.6 1.4* 35.5* 14.3* 13.9 1.0* 1.2 8.2 15.4 0.5 Transportation & storage (S14) 2.1* 14.3* 5.8 2.5* 7.0* 2.8* 3.5 0.8* 0.2* 1.2* 4.6 0.3* Hospitality (S15) 0.8 5.5 1.9 2.9 16.4* 6.6* 4.4 1.5* 0.5* 3.7* 3.7 1.0 Telecommunications (S16) 0.6 4.4 2.7 1.7 0.0* 0.0* 0.4 0.0* -* -* 1.9 -* Finance (S17) 0.4* 2.5* 4.8 0.5* - - 2.3 - 1.6* 11.3* 6.3 1.8* Real estate (S18) 2.4* 16.5* 26.6 0.6* 2.9 1.2 0.5 2.4 4.5 31.6 7.5 4.2 Professional services (S19) 2.3* 15.8* 6.7 2.4* 76.2 30.7 8.1 3.8 1.2* 8.4* 7.2 1.2* Public Services - - 14.4 - 2.6 53.1 17.5 + 0.07 + 17.0 + Public administration (S20) 0.4* 2.7* 10.8 0.3* 7.4 3.0 8.0 0.4 1.0 7.4 8.5 0.9 Education (S21) 0.2* 1.3* 1.7 0.8* 5.0* 2.0* 5.7 0.4* 0.5* 3.8* 5.3 0.7* Health (S22) 0.4* 2.7* 1.9 1.4* 8.1* 3.2* 3.8 0.8* 0.2* 1.7* 3.2 0.5* 100.0 100.0 100.0 100.0 - 100.0 100.0

(*) The effects marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

134

Table 6.10 Effects of Telecommunication Infrastructure Investment on the Industry Mix Private Investment Employment Output Margin Share of Share of Share of Marginal Share of Share of Marginal Share of al Ratio Ratio Private Ratio Benefits GFCF Product Benefits Emp Product Benefits Product Output Agriculture and Mining 0.32 2.5 4.8 0.5 9.4 4.0 15.5 0.3 0.12 0.1 8.6 0.0 Agriculture (S1) 0.7 2.6 3.8 0.7 -* - 14.5 - 0.5* 1.9* 6.7 0.3* Mining (S2) -* -* 1.0 -* - - 1.0 - -* -* 1.9 -* Manufacturing 2.39 19.0 13.1 1.4 24.4 10.3 21.8 0.5 1.16 8.3 18.1 0.5 Food (S3) 0.5 1.9 1.4 1.4 -* - 2.7 - 0.2* 0.6* 2.1 0.3* Textiles (S4) 0.3 1.0 1.3 0.8 - - 7.4 - 0.5* 2.0* 3.7 0.5* Paper (S5) 0.7 2.6 1.4 1.9 - - 2.3 - 0.3 1.0 2.2 0.5 Chemical and Pharm.(S6) 0.3 1.1 2.0 1.0 0.4 0.1 0.8 0.2 -* -* 1.7 -* Non-metallic minerals (S7) 0.6 2.4 2.0 1.2 9.4 3.3 2.0 1.6 0.9 3.4 2.7 1.3 Basic metals (S8) 0.1 0.5 1.1 0.5 5.6 2.0 2.3 0.8 - - 2.5 - Machinery and equipment (S9) 0.1 0.5 4.0 0.1 20.7 7.2 4.3 1.7 1.9* 7.7* 3.3 2.3* Private Services 8.91 70.8 67.8 1.1 183.6 77.2 45.2 1.7 10.88 77.8 56.3 1.4 Electricity and gas (S10) - - 4.9 - - - 0.4 - -* -* 2.1 -* Water (S11) 0.6 2.5 3.4 0.7 - - 0.9 - -* -* 0.6 -* Construction (S12) 1.8 7.2 5.3 1.3 - - 10.7 - 3.1 12.2 7.1 1.7 Wholesale & retail trade (S13) 1.4 5.6 5.6 1.0 37.3 13.0 13.9 0.9 1.5* 6.0* 15.4 0.4* Transportation & storage (S14) 4.5 17.9 5.8 3.1 1.8 0.6 3.5 0.2 0.4 1.5 4.6 0.3 Hospitality (S15) 0.9 3.5 1.9 1.9 20.6 7.2 4.4 1.6 0.6 2.2 3.7 0.6 Telecommunications (S16) 0.9 3.7 2.7 1.4 -* - 0.4 - - - 1.9 - Finance (S17) 0.9 3.4 4.8 0.7 - - 2.3 - - - 6.3 - Real estate (S18) 4.1 16.1 26.6 0.6 4.9 1.7 0.5 3.6 7.5 29.8 7.5 4.0 Professional services (S19) 1.8 7.2 6.7 1.1 157.6 55.0 8.1 6.8 1.9 7.5 7.2 1.1 Public Services 0.98 7.8 14.4 0.5 20.5 8.6 17.5 0.5 1.82 13.0 17.0 0.8 Public administration (S20) 3.5* 14.0* 10.8 1.3* 8.2* 2.9 8.0 0.4 1.2 4.9 8.5 0.6 Education (S21) 0.6 2.3 1.7 1.4 20.0 7.0 5.7 1.2 3.2* 12.6* 5.3 2.4* Health (S22) 1.0 3.8 1.9 2.1 -* - 3.8 - 1.0* 3.9* 3.2 1.2* 100.0 100.0 100.0 100.0 - 100.0 100.0

(*) The effects marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

135

136

CHAPTER 7 Infrastructure Investment, Labor Productivity, and International Competitiveness

This chapter analyzes the effects of infrastructure investment on labor productivity at the industry level using a newly developed data set for infrastructure investments in Portugal. We employ a vector autoregressive approach and consider twenty two sectors of activity and twelve infrastructure assets to estimate industry-infrastructure specific effects on labor productivity. This allows us to highlight the differential effects on traded and non-traded sectors. We find, first, that investments in national roads have positive effects, particularly large for public services, while the effects of investments in municipal roads are mixed and investments in highways have mostly benefited the non-traded sectors. Second, we find that railroad investments, and to a lesser extent airports have clearly biased labor productivity gains toward the non-traded sectors while the effects of port investment are more muted and mixed. Third, for social infrastructure investments the effects tend to be large and again particularly favorable to the non-traded sectors. Fourth, for public utilities the effects are in general small with the exception of investments in telecommunications which have large positive effects mainly on non-traded sectors. As a corollary of our results, we conclude that infrastructure investments in the last three decades have contributed to the growth of labor productivity in the country but have done so in a way that is rather uneven across sectors and has benefitted mostly non-traded goods sectors. This may be a matter of concern for a small open economy in a currency union and with a development model greatly depending on exports.

7.1 Introduction

The importance of labor productivity improvements in creating a favorable investment environment and in fostering competitiveness is well understood. It is also well understood that, the international competitiveness of a small open economy depends, in no small part, on differences in labor productivity growth between traded and non-traded goods sectors. This is particularly true for members of a currency union, such as the European Monetary Union, who are unable to devalue their currency to encourage export growth. It follows that no discussion of development strategies in countries such as Portugal, Ireland, Italy, Greece, and Spain, can ignore the issue of how to improve labor productivity in general and, particularly in the traded goods sector, as a way to

137

ultimately sustaining improved standards of living [see, for example, EU (2014a, 2014b), IMF (2013,

2014), OECD (2013, 2014), and WEF (2014a)].

In the last three decades, in these same countries, notably in Portugal, infrastructure investment has played a pivotal role in the structural and cohesion policies designed to encourage convergence to EU standards of living. Thus, much of the economic growth and development strategies over this period were directly linked to infrastructure investments. Infrastructures are critically important for private sector growth, its availability increasing labor productivity directly as an externality as well as indirectly through a more efficient use of private inputs.

This was, naturally, a reasonable strategy. An extensive and efficient infrastructure network is considered together with proper institutions, a good macroeconomic environment and a good health and education systems, as key basic requirement for competitiveness [see, for example, WEF

(2014a)]. It also seems to have been, at least by some measures, a successful strategy. According to the World Economic Forum Global Competitiveness Index [WEF (2014a)], Portugal ranks 36 in the world among 144 countries. Of the twelve comprehensive competitiveness pillars, including infrastructures, that are used to form this index, Portugal ranks the highest in the infrastructure pillar

– 17. If we consider the more detailed individual competitiveness indicators, Portugal ranks 12 on the overall quality of infrastructures and an impressive 2 in the quality of the road network (as a reference point Portugal only ranks in the top ten in the world in nine of these almost one hundred and twenty individual competitiveness indicators).

Uncovering the empirical evidence on the link between infrastructure investments and labor productivity is very important. Besides identifying the magnitude of the aggregate effects of infrastructure investments on labor productivity, there are important unanswered questions as to the effects of different types of infrastructure assets. More importantly, what is not known is the effect of these infrastructure investments on labor productivity in different industries, in particular as it

138

relates to the traded/non-traded goods divide. And yet, this is a critical issue for a small open economy in its quest for improved global competitiveness. Aggregate improvements in labor productivity may be driven by larger effects in sectors which trade internationally, concentrated in industries that do not, or reflect a more balanced effect across industries.

These alternative situations have very different policy implications as they impact international competitiveness in opposite ways. Are improvements in labor productivity coming mostly from traded goods sectors and thereby enhancing international competitiveness? In this case, improvements in standards of living are sustainable and maybe even self-reinforcing. Or are labor productivity improvements mostly in non-traded goods sectors in which case they mask a loss in international competitiveness? In this case gains, in standards of living are likely not sustainable in the longer term.

In this chapter, we address the issue of the industry-specific effects of infrastructure investments on labor productivity in Portugal with an eye on the differences between traded and non-traded goods sectors. From a methodological perspective, we use a multivariate dynamic time series approach, based on the use of industry-infrastructure specific vector autoregressive (VAR) models including industry output, employment, and private investment, in addition to different types of infrastructure investments. We consider investment in twelve infrastructure assets and twenty two sectors spanning the whole spectrum of economic activity.

7.2 The Empirical Results

The Effects of Investments in Road Transportation Infrastructures

The effects of investments in road transportation infrastructures on labor productivity are reported in Table 7.1. At the most aggregate level, the effects of investments in different road

139

infrastructure assets are actually quite different, as we see a large effect from national road investment, 0.0484, a negative effect from municipal roads, -0.0119, and a moderate effect from highway investment, 0.0138. When we consider the effects on the four main sectors of economic activity, we see that national roads have had meaningful positive effects across all sectors, particularly large for public services, while the effects of investments in municipal roads are mixed, particularly detrimental for the primary sector and investments in highways have mostly benefited private and public services.

When consider the effects of investments in national roads we see large effects on non- metallic minerals (S7) and machinery (S9) and moderate effects on agriculture (S1), food (S3), and textiles (S4), paper (S5). For the remaining traded sectors, the effects are large negative for mining

(S2) and not significantly different from zero for the other three. As to the non-traded goods sectors, we see large positive effects on construction (S12), real estate (S18), education (S21), and health (S22). In turn, negative effects are estimated for electricity (S10), water (S11), and professional services (S19). The remaining five effects are not statistically significant.

In terms of municipal roads, investments have moderately positive effects on labor productivity on food (S3), textiles (S4), and non-metallic minerals (S7) among the traded goods and trade (S13) and hospitality (S15) among the non-traded. In turn, they have large negative effects for agriculture (S1), paper (S5) and chemical (S6) among traded sectors and for telecommunications

(S16) among non-traded. In addition, three of the effects on the ten traded sectors and nine of the twelve traded goods sectors are not statistically different from zero.

For highway infrastructure investment most of the effects are small, with effects not statistically significant for six of the ten traded goods sectors and four of the twelve non-traded sectors. We see a moderate negative effect on labor productivity on mining (S2) and on the flip side a moderate positive effect on finance (S17) and a large positive effect on real estate (S18).

140

Overall, there are significant benefits for both traded and non-traded goods sectors from investments in road transportation, in particular national roads, with more pervasive gains for food

(S3), textiles (S4), and non-metallic minerals (S7) among the traded sectors and real estate (S18) among the non-traded sectors. On the negative side one could highlight the effects on mining (S2).

The Effects of Investments in Other Transportation Infrastructures

The effects of investments in other transportation infrastructures on labor productivity are reported in Table 7.2. At the aggregate level, the most important effects come from railroad infrastructure investment, 0.0271, the effects of infrastructure investment in airports being more moderate, 0.0118, and the effects from port investments is statistically zero. When we consider the four main industry aggregates, we see that railroad investments, and to a lesser extent airports have clearly biased labor productivity gains toward the private and public services while the effects of port investment are more muted and mixed.

In terms of investments in railroad infrastructure, and in a more disaggregated setting, we find significant effects for four of the traded goods sectors and eight of the non-traded. We see large positive effects for electricity (S10), water (S11), and real estate (S18) and moderate positive effects for construction (S12), trade (S13), public administration (S20), and education (S21). These are non- traded good sectors. In turn, we identified negative effects for agriculture (S1), paper (S5), and machinery (S9). All of these are traded goods sectors. We also find moderate negative effect for the non-traded sector of professional services (S19). Overall, railroad infrastructure investment affects labor productivity positively, in a strong or moderate manner, in 7 of 12 non-traded sectors and affects labor productivity negatively, in a strong or moderate manner, in 3 of the 10 traded sectors.

Railroad investments have decisively favored non-traded sectors.

For investments in airport infrastructures, we find that most effects are small and fifteen of the twenty two not statistically significant. There are, however, large positive effects on electricity

141

(S10) and water (S11). In turn, we find moderate negative effects for paper (S5) and transportation

(S14) which are traded sectors. Overall, in relative terms we again seem to have a pattern of investments in airport infrastructures leading mostly to labor productivity gains in non-traded goods.

Finally, for port infrastructure investments we also find that most effects on labor productivity are very small even when significant, again with fifteen of the twenty two effects not statistically different from zero. As such, investments in ports do not seem to have played a major role in the evolution of the labor productivity. We find small positive effects for food (S3), textiles

(S5), and basic metals (S8) as well as hospitality (S15) and finance (S17) and small negative effects for chemicals (S6).

Overall, we find that the bulk of the effects of investments in other transportation infrastructures go to non-traded goods sectors, but with railroad investment playing a greater role than investments in ports or airports.

The Effects of Investments in Social Infrastructures

The effects of investments in social infrastructure on labor productivity are reported in

Table 7.3. At the most aggregate level, health infrastructure investments have a large effect on labor productivity, 0.0408, while the effects of investment in education infrastructures are more moderate,

0.0159. At a more disaggregated level, for health infrastructure investments, we found a large positive aggregate effect which was particularly large for private services, and significant for primary and manufacturing. Education infrastructure investment, has a large negative effect on the primary sector, and large positive effects on services, in particular public services.

In terms of the effects of health infrastructures at a more disaggregated level, among the traded sectors, we find large positive effects on labor productivity for mining (S2), transportation

(S14) and moderate on paper (S5), non-metallic minerals (S7) and machinery (S9). In addition, we find moderately negative effects for chemicals (S6). For traded goods, only four of the ten sectors

142

show effects that are not statistically significant. In turn, for the non-traded goods sectors we find large positive effects for construction (S12) and moderately positive effects for real estate (S18) and actually a large negative effect for electricity (S10) and water (S11). The remaining eight effects are not significant. Overall, health infrastructure investments seem to have improved labor productivity for both traded and non-traded sectors, without clearly affecting the balance between the two.

At the full disaggregated level we find that education infrastructure investments affect strongly finance (S17) and education (S21), and moderately construction (S12), professional services

(S19), public administration (S20), and health (S22). Overall, six of the twelve non-traded goods sectors show a clear gain in labor productivity while the effects on the remaining six sectors are not statistically significant. In terms of the traded goods sectors, large improvements occur in non- metallic minerals (S7), machinery (S9), and more moderate on food (S3), paper (S5), and transportation (S14), while moderate negative effects ensue to textiles (S4), and basic metals (S8) and large negative effects for agriculture (S1) and mining (S2), and chemicals (S6). Given the nature of the effects and the relative size of the different sectors, it is clear that these investments, while affecting positively both traded and non-traded sectors, have benefited most labor productivity in non-traded goods sectors.

The Effects of Investments in Public Utilities and Telecommunications

The effects on labor productivity of investments in public utilities and in telecommunications are reported in Table 7.4. We estimate at the aggregate level a moderate effect from investments in water and wastewater, 0.0115, while the effects from investments in refineries and electricity and gas are negligible. The effects of investments in telecommunications however are positive and very large. Across the four main sectors of economic activity, the effects of public utilities tend also to be small, with sizable negative effects of water on the primary sector and public services and small positive effects of electricity in manufacturing and refinery in public services. For

143

telecommunications, however, we estimate very substantial effects for private and public services and a moderate negative effect on labor productivity in the primary sector.

Investments in water and wastewater infrastructure are a mixed bag when it comes to the effects on traded versus non-trade sectors. Moderate positive effects occur in mining (S2), and hospitality (S15). In turn, agriculture (S1), paper (S5), and chemicals (S6) have moderate negative effects while machinery (S9), a traded sector and real estate (S18) a non-traded have large negative effects.

Electricity and gas infrastructure investments have in general small effects on labor productivity, with only nine of the twenty two effects statistically significant. The exceptions are moderate positive effects on professional services (S19) and moderate negative effects on electricity

(S10) and finance (S17).

The effects of investments on refinery infrastructures are also overwhelmingly small at the most disaggregate level and mostly non-significant – only six of the twenty two effects are statistically different from zero The only exception is a moderate negative effect on electricity (S10).

In general however, and despite their small magnitude, most of the positive effects are on non- traded industries.

Finally, for telecommunication infrastructures, we identified very large positive effects with special incidence on the non-traded sectors. Indeed, among the non-traded sectors, we observe very large positive effects on finance (S17) and real estate (S18) and moderate positive effects on construction (S12), public administration (S20) and education (S21). The remaining seven effects are not statistically significant. In turn, for the traded sectors we observe moderate positive effects for basic metals (S8) and small for non-metallic minerals (S7), the remaining eight effects being statistically null. Overall the pattern on greater positive influence on the non-traded sectors is clear.

144

The Effects on Labor Productivity from an Industry Perspective

We can also summarize the effects of the different investments in infrastructure assets at the sector level from an industry perspective. It is just another way of looking at the info in Table 7.1 to

Table 7.4.

For the primary sectors, sectors producing traded good, there are very few positive effects on labor productivity from infrastructure investments, most noticeably national roads on agriculture

(S1) and health and water on mining (S2). The negative effects are much more prevalent and sizable the largest being from municipal roads and education on agriculture (S1) and education for mining

(S2). It can be ascertained that infrastructure investments have played a role in the decline of labor productivity in the primary sectors.

As to the manufacturing sectors, which are all producers of traded goods, we find in general positive effects from national road investments [food (S3), textiles (S4), non-metallic minerals (S7), and machinery (S9)], from municipal roads [food (S3), textiles (S4), and non-metallic minerals (S7)], from health [paper (S5), non-metallic minerals (S7), and machinery (S9)], education

[food (S3), paper (S5), non-metallic minerals (S7), and machinery (S9)], and telecommunications

[basic metals (S8)]. Interestingly only chemicals (S6) does not seem to benefit from investments in any infrastructure assets, and this despite the important gains in labor productivity present in the data. On the negative side, meaningful effects can also be observed from municipal roads [chemicals

(S6)], from railroads [paper (S5) and machinery (S9)], health [chemicals (S6)], education [textiles (S4), chemicals (S6), and basic metals (S8)], and water [paper (S5), chemicals (S6), and machinery (S9)].

Private services sectors, which except for transportation (S14) are non-traded sectors, benefit from investments in national roads [construction (S12) and real estate (S18)], municipal roads

[trade (S13), transportation (S14), and hospitality (S15)], railroads [electricity (S10), water (S11), construction (S12), trade (S13), and real estate (S18)], health [construction (S12), transportation

145

(S14), and real estate (S18)], education [construction (S12), transportation (S14), and finance (S17)], and telecommunications [construction (S12), finance (S17), and real estate (S18)].

It should be noted that trade (S13) and real estate (S18) seem to greatly benefit in terms of labor productivity improvements induced by infrastructure investments despite the fact that productivity was either stagnant over the sample period – in trade, or actually saw a sharp decline – as in real estate. The only sectors that do not seem to benefit from any type of infrastructure investments is telecommunications (S16), which actually saw a substantial increase in labor productivity over the sample period closely followed by professional services (S19), a sector where labor productivity was stagnant. In turn, electricity (S10) and water (S11) show sizable labor productivity losses induced by investments in national roads and health. This despite the fact they actually show a substantial overall improvement in labor productivity over the sample period.

Finally, public services, sectors producing non-traded goods, benefit from moderate or large effects on labor productivity from investments in national roads [education (S21), and health

(S22)], railroads [public administration (S20) and education (S21)], education [public administration

(S20), education (S21), and health (S22)], and Telecommunications [public administration (S20) and education (S21)]. As such, overall infrastructure investments in all major types of infrastructure assets, except public utilities, have a positive effect on labor productivity in the sector

As a final remark, the fact that a sector sees an evolution in labor productivity in the sample period that goes in the opposite direction of the effects we identify here from infrastructure investments poses no more a contradiction or a puzzle than the fact that the country has a top ranking infrastructure and yet the overall competitiveness is less stellar. The fact is that, besides infrastructure investments many other factors affect the productivity of each individual sector.

Therefore, the actual effects of infrastructure investments we have teased out are hidden under a myriad of other factors (to recall the World Economic Forum used one hundred and twenty four

146

individual factors affecting productivity of which only nine are related to infrastructures). Naturally, we do not claim that infrastructure investments are the only or even the main driver of labor productivity gains.

7.3 Summary and Concluding Remarks

Summary

In this chapter we aim at identifying the empirical effects of infrastructure investments on labor productivity at the industry level. We want to identify the effects as they relate to the divide between the effects on traded and non-traded sectors and as such on the evolution of international competitiveness and the long term prospects of the domestic economy to achieve improvements in standards of living.

Our main conclusions can be summarized as follows. We find, first, that investments in national roads have positive effects, particularly large for public services, while the effects of investments in municipal roads are mixed and investments in highways have mostly benefited the non-traded sectors. Second, we find that railroad investments, and to a lesser extent airports have clearly biased labor productivity gains toward the non-traded sectors while the effects of port investment are more muted and mixed. Third, for social infrastructure investments the effects tend to be large and again particularly favorable to the non-traded sectors. Fourth, for public utilities the effects are in general small with the exception of investments in telecommunications which have large positive effects mainly on non-traded sectors.

From an industry perspective, the traded goods sectors benefit in some cases but never very strongly. Infrastructure investment has led pretty much across the board to a decline in labor productivity for the primary sectors while the manufacturing sectors have somewhat benefited from investment in road infrastructure and social infrastructures, and have either negative or small effects

147

from the remaining three main types of infrastructure assets. Private services and public services sectors, which are mostly non-traded sectors, benefit from large effects from investments in road infrastructure, other infrastructure, social infrastructure, and telecommunications. Only public utilities seem to have a marginal impact on the labor productivity of these sectors.

Policy Implications

There are several important policy implications of these results. First, from a retrospective standpoint these results help understand how the patterns of infrastructure development over the last few decades have affected labor productivity overall and international competitiveness as measured by the differential effects on traded and non-traded goods sectors. The last three decades saw substantial renewal of the investment efforts in national roads, highways, railroads, health, electricity and gas, telecommunications, and to a lesser extent water and wastewater infrastructure.

We have found that national roads had widespread large positive impact on labor productivity, in particular for public services while highway, railroad, health and telecommunication investments decisively biased labor productivity gains in favor of the non-traded goods sectors. Finally, the impact of water and wastewater and electricity and gas are much more subdued and with overall effects less discernible. All in all, infrastructure investments seem to have reduced any competitive edge the traded sectors might have had in terms of differentials in labor productivity vis-à-vis the traded goods sectors. Naturally, this is not meant to imply that infrastructure investments are the only or even the most important factor behind the observed changes but rather to argue that infrastructure investments seem to have played a role in those shifts.

Second from a prospective standpoint, there is the issue of what can be expected from the infrastructure investments that are currently being considered for the future. It would seem that the great focus for the next few decades will be on non-road transportation, in particular railroad and ports, and social infrastructure, health and education facilities. Indeed, the time has passed for any

148

focus on road infrastructure which is perceived as having already achieved a high level of maturity if not outright overinvestment - the Portuguese road infrastructure network is ranked second in the world by the Global Competitive Report [WEF (2014b)]. In addition, investments in public utilities are now mostly in the hands of the private sector and therefore less directly affected by economic policy. As per our results investments in railroad, health and education facilities will all have a strong bias towards greater labor productivity gains in non-traded goods sectors. The effects of investments in ports and airports will be less significant and in the case of ports more evenly distributed.

Equally from a perspective standpoint there is the issue of the effects of these infrastructure investments on the labor productivity of sectors we could consider emerging traded-sectors, sectors which have traditionally been non-traded but which are showing signs of increased openness and participation in the international markets. These are the cases of the private services sectors of water, telecommunications, and professional services, and to a lesser extent hospitality, and finance. We want to consider for these sectors the effects of future infrastructure investments on railroads, ports, health and education, as currently being considered. Our results suggest that, the water sector is poised to see improvements in labor productivity from railroad investments but losses from the remaining three; labor productivity in the telecommunications will be essentially unaffected by these investments, while labor productivity in professional services will be negatively affected by railroad and airports but positively by education. In turn, labor productivity in hospitality services will be positively affected but only by education while in the financial services will be affect positively by all in particular education. Overall, investments in railroads and in particular education are the most likely to benefit these increasingly internationalized sectors.

149

Table 7.1 Effects on Labor Productivity by Industry: Road Transportation

Elasticity of Labor Productivity

National Municipal Highways Roads Roads

Total Economy 0.0484 -0.0119 0.0138 Agriculture and Mining 0.0410 -0.1190 -0.0161* Agriculture (S1) 0.1389 -0.1460 -0.0037* Mining (S2) -0.1728* -0.0150* -0.0662 Manufacturing 0.0685 0.0245 0.0028* Food (S3) 0.0966 0.1172 0.0027* Textiles (S4) 0.1457 0.0493 -0.0039* Paper (S5) 0.1080* -0.1645 0.0287 Chemical and pharmaceutical (S6) -0.0468* -0.1989 -0.0089* Non-metallic minerals (S7) 0.2129 0.0569 0.0188 Basic metals (S8) -0.0805* 0.0929* -0.0029* Machinery and equipment (S9) 0.2754 -0.0639* 0.0320 Private Services 0.0477 0.0129 0.0203 Electricity and gas (S10) -0.3935 0.0146* 0.0175* Water (S11) -0.5398 -0.0061* 0.0206* Construction (S12) 0.3192 -0.0151* 0.0379 Wholesale and retail trade (S13) 0.0309* 0.0712 -0.0075 Transportation and storage (S14) 0.0506* 0.0366 -0.0114* Hospitality (S15) 0.0107* 0.1443 -0.0020* Telecommunications (S16) -0.0192* -0.0683 0.0033* Finance (S17) -0.0561* 0.1056* 0.0562 Real estate (S18) 0.5367 -0.1123* 0.1825 Professional services (S19) -0.1128 -0.0499* -0.0200 Public Services 0.1853 -0.0086* 0.0260 Public administration (S20) 0.0769* -0.0103* 0.0177 Education (S21) 0.2711 -0.0267* 0.0393 Health (S22) 0.1507 0.0322* 0.0260 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the difference between the accumulated impulse response functions for output and employment.

150

Table 7.2 Effects on Labor Productivity by Industry: Other Transportation Elasticity of Labor Productivity

Railroads Airports Ports

Total Economy 0.0271 0.0118 -0.0020* Agriculture and Mining -0.0798 -0.0146* 0.0026* Agriculture (S1) -0.0635 0.0047* -0.0011* Mining (S2) -0.0976* -0.0725* -0.0296* Manufacturing -0.0328 -0.0005* 0.0103 Food (S3) 0.0355 0.0247 0.0245 Textiles (S4) -0.0275* -0.0038* 0.0134 Paper (S5) -0.1108 -0.0424 0.0252 Chemical and pharmaceutical (S6) -0.0731* 0.0079* -0.0271 Non-metallic minerals (S7) -0.0319* 0.0061* 0.0148 Basic metals (S8) -0.0223* -0.0003* 0.0205 Machinery and equipment (S9) -0.1209 0.0103* -0.0049* Private Services 0.0437 0.0131 -0.0014* Electricity and gas (S10) 0.2421 0.1652 -0.0312* Water (S11) 0.2260 0.1405 -0.0356* Construction (S12) 0.0955 0.0069* -0.0148* Wholesale and retail trade (S13) 0.0557 0.0071* -0.0045 Transportation and storage (S14) -0.0476* -0.0461 0.0124 Hospitality (S15) 0.0118* 0.0248 0.0262 Telecommunications (S16) 0.0215* -0.0184* -0.0088* Finance (S17) 0.0495* 0.0360* 0.0278 Real estate (S18) 0.7975 -0.0446* 0.0183* Professional services (S19) -0.0920 -0.0284* 0.0032* Public Services 0.0486 0.0276 0.0088* Public administration (S20) 0.0489 -0.0029* 0.0009* Education (S21) 0.0509 0.0431 0.0025* Health (S22) 0.0321* 0.0211* 0.0083* (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the difference between the accumulated impulse response functions for output and employment.

151

Table 7.3 Effects on Labor Productivity by Industry: Social Infrastructures Elasticity of Labor Productivity

Health Education

Total Economy 0.0408 0.0159 Agriculture and Mining 0.0183* -0.1339 Agriculture (S1) -0.0194* -0.1707 Mining (S2) 0.1881 -0.3516 Manufacturing 0.0202 0.0217 Food (S3) -0.0395* 0.0533 Textiles (S4) -0.0142* -0.0928 Paper (S5) 0.0693 0.0980 Chemical and pharmaceutical (S6) -0.0964 -0.1785 Non-metallic minerals (S7) 0.0884 0.1021 Basic metals (S8) -0.0078* -0.0844 Machinery and equipment (S9) 0.1319 0.1596 Private Services 0.0994 0.0593 Electricity and gas (S10) -0.2341 -0.1789* Water (S11) -0.2422 -0.0570* Construction (S12) 0.1703 0.1419 Wholesale and retail trade (S13) 0.0067* 0.0036* Transportation and storage (S14) 0.1888 0.0777 Hospitality (S15) 0.0197* 0.0725* Telecommunications (S16) 0.0140* -0.0114* Finance (S17) 0.0555* 0.2021 Real estate (S18) 0.2019 0.2523* Professional services (S19) -0.0067* 0.0785 Public Services -0.0169* 0.1413 Public administration (S20) 0.0047* 0.1278 Education (S21) -0.0145* 0.1437 Health (S22) 0.0140* 0.1351 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the difference between the accumulated impulse response functions for output and employment.

152

Table 7.4 Effects on Labor Productivity by Industry: Public Utilities Elasticity of Labor Productivity

Water Electricity Refineries Telecom.

Total Economy 0.0115 -0.0033* 0.0029* 0.0461 Agriculture and Mining -0.0162* -0.0017* -0.0034* -0.0139* Agriculture (S1) -0.0483 -0.0166 -0.0020* -0.0008* Mining (S2) 0.1056 -0.0032* -0.0156* -0.1048* Manufacturing 0.0046* 0.0114 0.0020* 0.0092* Food (S3) 0.0294 -0.0203 0.0029* 0.0121* Textiles (S4) 0.0144* -0.0080* -0.0013* -0.0423* Paper (S5) -0.0564 0.0180 0.0147 0.0549* Chemical and pharmaceutical (S6) -0.0532 -0.0294 -0.0207 -0.0472* Non-metallic minerals (S7) 0.0163* -0.0067* -0.0006* 0.0362 Basic metals (S8) 0.0115* 0.0219 0.0064* 0.1025 Machinery and equipment (S9) -0.1272 -0.0017* -0.0049* -0.0005* Private Services -0.0008* -0.0057* 0.0044* 0.0759 Electricity and gas (S10) -0.0493* -0.0338 -0.0372 0.0599* Water (S11) -0.0421* -0.0192* -0.0097* 0.0937* Construction (S12) -0.0193* -0.0120* 0.0097* 0.0880 Wholesale and retail trade (S13) 0.0297 -0.0038* 0.0032* 0.0187* Transportation and storage (S14) 0.0232 -0.0129 -0.0051* -0.0136* Hospitality (S15) 0.0626 -0.0038* 0.0011* 0.0247* Telecommunications (S16) -0.0157* -0.0029* 0.0016* -0.0400* Finance (S17) 0.0493* -0.0421 0.0117 0.2326 Real estate (S18) -0.1724 -0.0756* 0.0050* 0.3854 Professional services (S19) -0.0291* 0.0702 0.0126 -0.0397* Public Services -0.0313 -0.0047* 0.0106 0.0540 Public administration (S20) -0.0225 -0.0035* 0.0128 0.0771 Education (S21) -0.0203 -0.0130* 0.0096* 0.0495 Health (S22) -0.0099* 0.0023* 0.0078* 0.0042* (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the difference between the accumulated impulse response functions for output and employment.

153

CHAPTER 8 On the Choice of the Regional Location of Infrastructure Investments

In this chapter we deal with the issue of identifying empirically the best location for infrastructure investments. We define the best location for investment as the one that maximizes the benefits for the whole country, that is, across all regions, in terms of output, employment or private investment. To address this issue we use a new data set for infrastructure investments in Portugal at the level of the NUTS II. We use a region-specific VAR approach which considers for each region not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere. We can summarize our results as follows. When we consider the issue of the best overall alternatives in terms of infrastructure investments and locations, we find that the largest output effects come from infrastructure investments in ports (except for North) and education (except for Lisbon). Investments in education are also very important in terms of both the employment and private investment effects (except again for Lisbon). In addition, investments in all airports have important private investment effects as do investments in ports in North and Center and municipal roads in Alentejo and Algarve. On the other hand, as to the question of how far the actual effects of infrastructure investments have been from their potential, as defined by the best location, our results suggest that the infrastructure assets that have actual long term effects closer to the potential effects are airports, education, and health. On the other hand, the actual long- term effects of investments in railroad are very far from the potential effects.

8.1 Introduction

In this chapter we deal with the issue of identifying empirically the best location for infrastructure investments. We define the best location as the one that maximizes the benefits for the whole country, i.e., across all regions, in terms of output, employment or private investment. To address this issue we use a new regional data set for infrastructure investments in Portugal at the level of the NUTS II. We use a region-specific VAR approach which considers for each region not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere.

Our discussion is centered on four intertwined research questions. First, we want to determine for each infrastructure asset the best regional location for investments. This allows us to

154

determine in which region to invest to maximize the benefits for the country as a whole. Second, we want to determine the best infrastructure investment alternatives for each region. This allows us to determine for each region in what infrastructure assets to invest to maximize the benefits for the country as a whole. Third, we consider the issue of the best overall alternatives in terms of infrastructure investments and locations. This allows us in general to determine what and where to invest to maximize the benefits for the country as a whole. Finally, we compare the actual effects of infrastructure investments with their potential effects as defined by the best location decision as discussed before. This allows us to have an idea of how close or how far these investment have been from reaching their full potential in terms of their economic effects.

This chapter is in the confluence of the regional literature on the effects of infrastructure investments and the issue of economic spillovers which is central to the whole approach. In addition, it deals with issues that are virtually absent in the literature, the issue of the empirical determination of the best location for infrastructure investment.

In terms of the scope of the analysis, we consider five regions at the NUTS II level – North,

Centre, Lisbon, Alentejo, and Algarve - spanning the Portuguese continental territory. We use a newly developed data set for infrastructure investments in Portugal [see Pereira and Pereira (2015a)], including regionalized information for eight infrastructure assets: three types of road transportation infrastructures (national roads, municipal roads, and highways), three types of other transportation infrastructures (railroads, ports, and airports), and two types of social infrastructures (education and health infrastructures).

We estimate region and asset specific models. For each of the five regions we estimate eight models one for each of the eight individual infrastructure investments. In each of these models we consider in addition to regional output, employment and private investment, both infrastructure investment in the region and infrastructure investments elsewhere. This is consistent with the

155

evidence on the potential relevance of regional spillovers, that is, economic performance in each region being affected also by infrastructure investments elsewhere.

8.2 The Empirical Results

Where to invest for each infrastructure asset

In this section, we address the issue of identifying for each infrastructure asset the regional location that maximizes its benefits for the country as a whole. One can think about a decision to invest in a given infrastructure asset and the determination of where to locate such investment efforts. Empirical results are reported in

156

Table 8.1 to Table 8.3.

We consider first investments in road transportation infrastructures. For national roads the largest output effect occurs with investments in North, with a multiplier of €16.76. The output effects for investments in the other regions are much smaller and actually negligible for investments in Lisbon. In turn, investments in North and Center have also important effects on private investment and employment as do investments in Alentejo and Algarve in terms of private investments. Investments in Lisbon, Alentejo and Algarve have negative albeit small effects on employment. For municipal roads, investments in Lisbon lead to the largest output benefits with a multiplier of €45.54, with important output effects from investments in North and Alentejo with

€13.45 and €21.27. The effects on private investment are large, in particular for Centre and Alentejo as are the effects on employment, except for Centro. Finally, for highways the effects are typically small across the board for private investment, employment as well as output (again with relatively important spillover effects). The largest output effects are for investments in North with a multiplier of €4.29.

We consider now the effects of investments in other transportation infrastructures. We see that the largest output effects for railroads are for investments in North with a multiplier of

€10.75 and in Lisbon with a multiplier of €14.37. On the flip side, for investments in Centre we actually see a large negative effect. In turn, for private investment there are large effects from investments in Lisbon and the effects for employment are all very small. Investments in airports show very favorable results in the three regions with major airports the largest being in the North, followed by Lisbon, and Algarve, with output multipliers of €33.90, €24.63, and €15.33, respectively.

There are important private investment effects from investments in the three regions and important employment effects from investments in North. For port infrastructure, we observe very sizable effects particularly so in Centre with a multiplier of €62.97, followed by North, Alentejo and Algarve

157

all with very large effects. We also find, across the board quantitatively important effects on both private investment and employments.

Finally, for social infrastructures we observe large effects across the board. In terms of education infrastructures, the largest effects are from investments in Centre, Lisbon and Algarve with multipliers of €47.57, €40.63, and €41.36. Very sizable effects across the two remaining regions,

€12.35 for investments in North and €25.94 for investments in Alentejo. For private investment and employment are quantitatively very important leading to very large effects in both cases, especially, private investment effects from investments in Centre and Algarve and employment effects from investments in Centre and Alentejo. In turn, for health care infrastructures the largest effects come from investments in North and Alentejo with multipliers of €11.27 and €1.78, respectively.

Moderate size effects occur for private investment and employment from investments in all regions.

What to invest for each region

We consider now the issue of the choice of location for investments from a different perspective. The issue is to identify for each region the best investments. One could think about a political decision to invest in one given region and wanting to determine which infrastructure assets to invest in to maximize the overall benefits for the country. Empirical results are also reported in

Table 8.4 to Table 8.6.

For investments located in North, the largest output effects come from investments in airports and ports with multipliers of €33.89 and €30.10. There are still large output effects from investments in national roads, municipal roads, railroads and education. In terms of the effects on private investment and employment, we see again a great importance of investments in airports, ports, and education.

For investments in Centre, the best effects across the board for private investment, employment, and output come from ports and education. The largest output effects come from

158

investments in ports and education with multipliers of €62.97 and €47.57, respectively. On the other hand, we do not find output benefits from investments in highways while investments in railroads in the region are to be avoided.

For infrastructure investments located in Lisbon, the best output results come from investments in municipal roads, airports and education, with multipliers of €45.54, €24.63 and

€40.63, respectively, with sizable effects from investments in railroads and ports. The effects from investments in national roads, highways are negligible. In terms of the effects on private investment, there are important effects from investments in municipal roads, railroads, airports, and education while for employment the largest effects come from investments in municipal roads, ports and education.

For Alentejo, the best investments in terms of output effects are in municipal roads, ports, and education with multipliers of €21.27, €30.10 and €25.94, respectively, with important effects from investments in health infrastructures. In turn, the largest effects in terms of private investment, come from investments in municipal roads and education while for the employment effects the largest effects are from investments in municipal roads, ports, and education.

For Algarve, the best benefits come from ports and education, with multipliers of €26.42 and €41.63, with sizable effects from investments in airports. Important effects on private investment are induced by investments in airports and education and on employment by investments in municipal roads, ports, and education.

The best overall infrastructure investment options

We consider now the best investment options. The idea is to determine what are the best uses overall across all regions and all infrastructure assets. For each infrastructure asset there is the possibility of locating it in one of five regions. Accordingly, there are a total of forty outcomes. We want to identify the infrastructure-region combinations that maximize the national benefits in terms

159

on their effects on private investment, employment, and output. One can think about a political decision to invest in infrastructures and wanting to determine what to invest on and where. Once again, the empirical results are reported in Table 8.4 to Table 8.6.

For private investment, the largest effects come from airport and education investments in the North, municipal roads, ports and education in the Centre, municipal roads and airports in

Lisbon, education in Alentejo, and airports and education in Algarve. Clearly, investments in airports and educational infrastructures seem to dominate these effects. Centre concentrates three of the top ten effects and Alentejo only one.

For employment, the largest effects come from investments in airports, ports, and education in the North, ports and education in the Centre, education in Lisbon, municipal roads and education in Alentejo and in both Algarve. In this case investments in educational infrastructures seem to dominate these effects with five of the top ten effects with a significant role for municipal roads and ports. North concentrates three of the top ten effects and Lisbon only one.

For output, the largest effects come from investments in airports and ports in the North, ports and education in the Centre, municipal roads and education in Lisbon, and ports and education in Alentejo and Algarve. Investments in ports and education are the two most important types of investment. Together they account for eight of the top ten largest output effects.

How Far are the Actual Effects from the Potential Effects of Infrastructure Investments?

One last issue we want to address is to compare the potential with the actual effects of investments for each infrastructure asset. The idea is to determine how far the actual effects are from the potential effects and thereby to identify areas of relative strength and weakness in terms of the patterns of infrastructure investments followed in the past.

The potential effects for each infrastructure asset are defined and the largest regional marginal product for each asset, thereby reflecting the best location alternative for each

160

infrastructure investment. In turn, the actual effects, are taken from Pereira and Pereira (2015b) where the same data set and the same methodological approach are used to provide a regional decomposition of the aggregate effects of investments in the different types of infrastructure assets considering both the direct effect in the region as well as the spillover effects captured by each region. These actual effects are, therefore, directly comparable to the potential effects we identify in this chapter. Table 8.7 reports the actual effects from Pereira and Pereira (2015b), the best effects as identified in this chapter, and the ratio between the two which gives an indication of how far or how close the actual investments have been from their full potential.

Our results suggest that in terms of the output effects, the infrastructure assets that have actual long term effects closer to the potential are airports, education, and health all with ratios of actual to potential above 70%. The same is true for highways, airports, education and health for private investment and ports and health in terms of the employment effects. On the other hand, railroad investments across the board, municipal roads for private investment and output and national roads and highways for employment, are all far from their potential effects, with ratios under 40%.

Overall, there is a clear pattern, as the economic effects of investments in airports and health are much closer to their potential than the remaining infrastructure assets, closely followed by education and ports. Investments in railroads fare very poorly. The case of airports is paradigmatic as being on average at 80% of their potential, something that can be understood if we consider that we are talking about three main airports. Investments in railroads, known as having been somewhat neglected over the sample period, fare very poorly on average at less than 30% of their potential.

From a different perspective we can also observe that the ratios for the different infrastructure investments are on average lowest for employment and greatest for private investment. In fact, four of the eight private investment ratios exceed 70% while three of the eight

161

employment ratios are under 40%. This also goes with the perception of important rigidities in the labor markets.

8.3 Summary and Concluding Remarks

Summary

In this chapter we deal with the issue of identifying empirically the best location for infrastructure investments. We define the best location as the one that maximizes the benefits for the whole country, that is, across all regions, in terms of output, or employment or private investment. To address this issue we use a new data set for infrastructure investments in Portugal at the level of the NUTS II. We use a region-specific VAR approach which considers for each region not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere.

We can summarize our results as follows. When we consider the issue of the best overall alternatives in terms of infrastructure investments and locations, we find that the largest output effects come from infrastructure investments in ports (except for North) and education (except for

Lisbon). Investments in education are also very important in terms of both the employment and private investment effects (except again for Lisbon). In addition, investments in all airports have important private investment effects as do investments in ports in North and Center and municipal roads in Alentejo and Algarve.

On the other hand, as to the question of how far the actual effects of infrastructure investments have been from their potential, as defined by the best location, our results suggest that the infrastructure assets that have actual long term effects closer to the potential effects are airports, education, and health. On the other hand, the actual long-term effects of investments in railroads are very far from the potential effects.

162

Policy Implications

The policy implications of our results are self-evident. This being the case, however, it is critical to understand the scope of the results, what they are informative about and what they are not. These results are meant to give very clear guidance as to the infrastructure assets and regions to pay attention to in the design of infrastructure policy. They are important inputs in determining what and where to invest in general terms and in helping identify the potential effects of specific investment projects. What they cannot do, is to be used as the only factor to justify any specific infrastructure investment project in any given region. For that there is no substitute to a serious, substantive and informative benefit-cost analysis.

163

Table 8.1 Elasticities with respect to Road Transportation Investment Private Investment Employment Output Effect of Investment Effect of Investment Effect of Investment Outside the Outside the Outside the In the Region In the Region In the Region region region region

National Roads North 0.3427 0.2017 0.0901 -0.0185 0.0687 0.0186* Centre -0.0081* 0.1761 0.0372 -0.0463 -0.0282* 0.0012* Lisbon -0.0492* 0.4098 -0.0062* 0.0861 0.0028* 0.0922 Alentejo 0.1952 0.3420 -0.0425 -0.0898 0.0398 0.0680 Algarve -0.0146* -0.1619* -0.0014* -0.1327 0.0007* -0.0714 Municipal Roads North -0.1308* 0.2525 0.0043* 0.0379 -0.0531* 0.0563 Centre 0.1579 0.4182 -0.0441 0.0525 0.0051* 0.1480 Lisbon 0.1722 0.0381* 0.0060* 0.0418 0.0363 0.0175* Alentejo 0.1815 0.3757 -0.0155* 0.0252 0.0082* 0.0243* Algarve -0.1927 0.1370 -0.0265* 0.0845 -0.0860 0.0574 Highways North 0.0411 0.0703 0.0094 0.0055* 0.0125 0.0114 Centre -0.0839 0.0411 -0.0110 0.0013* -0.0288 0.0170 Lisbon 0.0083* 0.0856 -0.0001* 0.0138 0.0020* 0.0156 Alentejo -0.0028* 0.1259 -0.0014* -0.0213 -0.0014* 0.0321 Algarve 0.0099* 0.0541 0.0023* -0.0082* 0.0028* -0.0020* (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

164

Table 8.2 Elasticities with respect to Other Transportation Investment Private Investment Employment Output Effect of Investment Effect of Investment Effect of Investment Outside the Outside the Outside the In the Region In the Region In the Region region region region

Railroads North 0.0068* 0.2206 0.0206* 0.0249 0.0185 0.0186 Centre -0.0912 0.1535 -0.0178 0.0157 -0.0476 0.0525 Lisbon 0.1473 -0.1474 0.0164 0.0059* 0.0214 -0.0157* Alentejo 0.0429 0.3332 -0.0103 -0.0565 -0.0116 0.0401 Algarve 0.0031* -0.0087 0.0029* -0.0282 0.0039* 0.0088* Airports North 0.0460 0.0314 0.0103 -0.0025* 0.0151 -0.0004* Centre - 0.0562 - -0.0084* - 0.0108 Lisbon 0.0488 0.0242 0.0117 0.0105 0.0131 0.0083 Alentejo - 0.1751 - -0.0273 - 0.0236 Algarve 0.0410 -0.0200* -0.0063* 0.0104* 0.0005* 0.0257 Ports North 0.0125 0.0086* 0.0018 0.0015* 0.0025* 0.0075* Centre 0.0644 0.0825 0.0055 0.0126 0.0255 0.0192 Lisbon -0.0324* -0.0202* -0.0031* 0.0017* 0.0030* 0.0159 Alentejo -0.0233 0.0830 -0.0017* 0.0344 -0.0007* 0.0002* Algarve 0.0001* 0.0720 0.0003* 0.0310 0.0001* 0.0349 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

165

Table 8.3 Elasticities with respect to Investment in Social Infrastructures Private Investment Employment Output Effect of Investment Effect of Investment Effect of Investment Outside the Outside the Outside the In the Region In the Region In the Region region region region

Education North 0.1464 0.4116 0.0196 0.0767 0.0215* 0.1233 Centre 0.3167 0.5300 0.0644 0.0360 0.1370 0.1504 Lisbon 0.0288* 0.2688 0.0178 0.0773 0.0278 0.0119* Alentejo -0.2486* 0.4736 0.0746 0.0476 -0.0228* 0.1241 Algarve 0.1346 0.0742* -0.0076* 0.0600 0.0487 -0.0641 Health North 0.0871 0.1954 0.0159 0.0777 0.0384 0.0513 Centre 0.0866 0.3785 0.0201 0.0288 0.0350 0.1032 Lisbon 0.0140 0.1813 0.0035 0.0293 0.0044* 0.0180* Alentejo 0.1501 0.5600 -0.0229 0.0175 0.0418 0.1179 Algarve 0.0090* -0.0197* -0.0243 -0.1259 0.0044* -0.1969 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

166

Table 8.4 Marginal Product with respect to Road Transportation Investments in each Region

Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment

On the On the Total On the On the Total On the On the Total region other region other region other itself regions itself regions itself regions

National Roads

North 10.9415 8.1883 19.1298 0.5258 -0.002 0.5238 10.3284 6.4282 16.7566 Centre 9.2276 9.2276 0.1746 0.0269 0.2015 6.4282 6.4282 Lisbon 5.5446 5.5446 -0.1861 -0.1861 0.4872 0.4872 Alentejo 1.7399 9.5571 11.297 -0.0442 -0.0071 -0.0513 1.3913 5.4279 6.8192 Algarve 10.8392 10.8392 -0.0173 -0.0173 6.9413 6.9413 Municipal Roads

North 11.0721 11.0721 0.3717 0.3717 13.451 13.451 Centre 6.623 10.1946 16.8176 -0.3198 0.3951 0.0753 8.6444 8.6444 Lisbon 25.4532 18.5202 51.0941 0.4391 0.4391 24.267 21.2732 45.5402 Alentejo 8.5083 16.3211 24.8294 0.5587 0.5587 21.2732 21.2732 Algarve -10.4746 17.9728 7.4982 0.539 0.539 -16.759 20.451 3.692 Highways

North 1.1689 2.4268 3.5957 0.049 0.0173 0.0663 1.6753 2.6108 4.2861 Centre -1.7665 3.188 1.4215 -0.04 0.0173 -0.0227 -2.6012 2.6227 0.0215 Lisbon 2.4733 2.4733 -0.0087 -0.0087 2.4663 2.4663 Alentejo 3.3139 3.3139 0.026 0.026 3.1863 3.1863 Algarve 3.6232 3.6232 0.0173 0.0173 3.6287 3.6287 Note - The empty entries correspond to the estimates that are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

167

Table 8.5 Marginal Product with respect to Other Transportation Investment in each Region

Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment

On the On the Total On the On the Total On the On the Total region other region other region other itself regions itself regions itself regions

Railroads

North -0.74 -0.74 -0.0012 -0.0012 5.7619 4.9826 10.7445 Centre -5.4451 2.3165 -3.1286 -0.1841 0.0698 -0.1143 -12.1956 3.2181 -8.9775 Lisbon 9.7576 10.502 20.2596 0.1365 0.1191 0.2556 7.0762 7.2966 14.3728 Alentejo 3.4281 3.1852 6.6133 -0.0966 0.157 0.0604 -3.6568 6.3925 2.7357 Algarve 5.1351 5.1351 0.1317 0.1317 7.2966 7.2966 Airports

North 10.7334 14.3782 25.1116 0.4368 0.2147 0.6515 16.5343 17.3648 33.8991 Centre 0 0 0 0 0 0 0 0 0 Lisbon 12.4971 14.0448 26.5419 0.3751 -0.0876 0.2875 16.7409 7.8919 24.6328 Alentejo 0 0 0 0 0 0 0 0 0 Algarve 7.2339 19.5987 26.8326 0.2147 0.2147 15.3275 15.3275 Ports

North 5.9431 15.0302 20.9733 0.1593 0.5123 0.6716 30.0975 30.0975 Centre 25.0523 5.3711 30.4234 0.367 0.2575 0.6245 42.4967 20.4696 62.9663 Lisbon 15.0302 15.0302 0.5123 0.5123 12.815 12.815 Alentejo -4.3499 11.4936 7.1437 0.3414 0.3414 30.0975 30.0975 Algarve 13.1957 13.1957 0.4257 0.4257 26.9104 26.9104 Note - The empty entries correspond to the estimates that are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

168

Table 8.6 Marginal Product with respect to Social Infrastructure Investments in each Region

Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment

On the On the Total On the On the Total On the On the Total region other region other region other itself regions itself regions itself regions

Education

North 6.3753 18.7059 25.0812 0.1556 0.4261 0.5817 12.3519 12.3519 Centre 16.0476 21.3655 37.4131 0.5645 0.7122 1.2767 29.7529 17.8185 47.5714 Lisbon 22.6378 22.6378 0.1957 0.5447 0.7404 12.1581 28.4724 40.6305 Alentejo 27.6691 27.6691 0.5652 0.7864 1.3516 25.9438 25.9438 Algarve 9.299 30.1261 39.4251 0.7914 0.7914 12.0573 29.303 41.3603 Health

North 3.3675 9.083 12.4505 0.1122 0.0978 0.21 7.0011 4.2723 11.2734 Centre 2.7463 8.0682 10.8145 0.11 0.2462 0.3562 4.7512 3.2741 8.0253 Lisbon 0.5088 8.2297 8.7385 0.0159 0.2227 0.2386 7.637 7.637 Alentejo 5.1209 10.0278 15.1487 -0.091 0.2888 0.1978 5.6052 6.1699 11.7751 Algarve 11.8029 11.8029 -0.0911 0.3257 0.2346 9.1947 9.1947 Note - The empty entries correspond to the estimates that are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

169

Table 8.7 How Far are the Actual Effects from the Potential Effects of Infrastructure Investments?

Private Investment Employment Output

Effect of Investment Average Effect of Investment Average Effect of Investment Average /Marg. /Marg. /Marg. Average Marginal Average Marginal Average Marginal (%) (%) (%) Road Transportation National Roads 12.44 19.13 65.03 160 524 30.53 9.17 16.76 54.72 Municipal Roads 19.03 51.09 37.25 316 559 69.20 17.18 45.54 37.73 Highways 2.65 3.62 73.20 21 66 31.82 2.39 4.29 55.71 Other Transportation Railroads 6.87 20.26 33.91 71 256 27.73 3.72 14.37 25.89 Airports 26.00 26.83 96.91 424 652 65.03 27.21 33.90 80.27 Ports 18.92 30.42 62.20 550 672 81.84 32.75 62.97 52.20 Social Infrastructure Education 27.66 39.43 70.15 881 1352 65.16 33.63 47.57 70.70 Health 11.33 15.15 74.79 253 356 71.07 9.55 11.78 81.07

170

171

CHAPTER 9 On the Effects of Infrastructure Investments on the Regional Economic Mix

In this chapter we deal with the issue of the effects of infrastructure investments on the regional mix of economic activity in Portugal. To address this issue we use a new data set for infrastructure investments in Portugal at the level of the NUTS II. We use a region- specific VAR approach which considers, for each region, not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere. Our results can be summarized as follows. First, we find that the largest aggregate effects are for investments in municipal roads, airports, ports, and education. Second, regional spillovers are very important across the board, and are particularly relevant for municipal roads and highways. Third, we find that for road transportation infrastructures, investments in national roads shift the regional concentration of economic activity towards North, Lisbon, and Alentejo, while investments in municipal roads have the same effects for Centre and investments in highways once again in North, Lisbon and Alentejo. For other transportation infrastructures the shifts in regional economic composition occur in North and Alentejo for railroad investments, Lisbon, Alentejo, and Algarve for airport investment, and Centre and Algarve for port infrastructure investments. Finally, investments in both education and health shift the regional output mix towards North and Centre, and in the case of health Alentejo as well. Accordingly, the aggregate effects of infrastructure investments hides a wide variety of effects across regions and across different infrastructure assets. Being mindful of these differences is fundamental in designing policies that help with aggregate economic performance without increasing regional disparities.

9.1 Introduction

In this chapter we deal with the issue of empirically identifying the effects of infrastructure investments on the regional mix of economic activity in Portugal. To address this issue we use a new data set for infrastructure investments in Portugal at the level of the NUTS II regions. We use a region-specific VAR approach which considers, for each region, not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere.

Our discussion is centered on three intertwined research questions. First, we want to determine the regional decomposition of the aggregate effects of different types of infrastructure

172

investments. This helps us determine which locations benefit the most in absolute terms when we consider the patterns of infrastructure investments in the country. Second, we want to identify for each type of infrastructure asset the relevance of regional spillovers. This allows us to determine how much a region benefits from infrastructure investments elsewhere. Finally, and using the information on the two previous questions we want to determine the impact of national patterns of each type of infrastructure investment on the regional composition of economic activity. This allows us to identify which regions benefit the most relative to their economic size, that is, whether or not infrastructure investments contribute to the regional concentration or to the regional diversification of economic activity.

9.2 Empirical Results

Framing the Empirical Effects of Infrastructure Investments

We start by framing the regional effects of infrastructure investments by addressing the issue of the aggregate effects for the whole country as measured by the sum of the direct effects for each region from investments in the region and the spillover effects for each region from investments elsewhere. These results for each assets are reported in the total rows of Table 9.2 and Table 9.3 for road infrastructures, other transportation infrastructures, and social infrastructures, respectively.

We find that the largest aggregate effects for the country, in terms of either employment, private investment or output, are infrastructure investment in municipal roads, airports, ports, and education, with long term output marginal products of 15.437, 27.069, 40.787, and 35.363, respectively. More moderate effects accrue to investments in national roads and health with 9.167 and 11.111, while the effects of investments in highways and railroads are clearly smaller, with 4.505 and 2.619.

173

Of the total effects, it is informative to consider the part that reflects for each region, spillovers from investments in other regions. Our results indicate that these spillovers are very important across the board, although naturally with important nuances. For example for the output effects, spillovers correspond to 100% of the observed effects for municipal roads and highways while for railroads they correspond to 85.0%. On the lower range, for national roads, airports, ports, education, and health, the spillovers are 69.9%, 45.1%, 65.7%, 63.9%, and 58.9%, respectively. As a general statement for employment, private investment, and output, spillovers are particularly relevant for municipal roads and highways. On the other hand, investments in national roads and airports show relatively low spillover effects.

On The Regional Effects of Infrastructure Investments by Asset

Having presented the effects of investments on different infrastructure assets at the aggregate level, we now turn to the decomposition of these effects at the regional level. The idea is to identify for each infrastructure asset the regions that benefit the most, when we account for both the effects of investments in the region and spillover effects from investments elsewhere. We focus our discussion on the output effects although in most, but not all cases, the effects on private investment and employment show similar patterns. The results are reported in

174

Table 9.1 and Figure 9.1, Table 9.2 and Figure 9.2, and Table 9.3 Figure 9.3, for road infrastructure, other transportation infrastructures, and social infrastructures, respectively.

For road infrastructures, the largest effects for investments in national roads occur in North and Lisbon, with marginal products of 3.823 and 5.499. The effects for Lisbon are mostly due to spillovers from investments in other regions. For investments on municipal roads, the largest output effects occur in Centre and Lisbon, with 8.861 and 6.123 and, here, spillovers are important in both cases, but particularly relevant in Centre. Finally, for investments in highways the effects are small across the board.

With respect to other transportation infrastructures, the only region that benefits in a meaningful way from railroad investments is North with 3.235. Output spillovers effects are very important for both North and Centre. In the case of Centre they offset detrimental effects from investments in the region itself. As to investments in airports, the largest benefits occur in North and Lisbon with 6.447 and 12.941. Spillovers are relevant in Lisbon, but more importantly in Centre and Alentejo where no major airports are located. Finally, for investments in ports the largest effects occur in Centre and Lisbon with 17.546 and 14.435, with the effects in North and Algarve also very important. Spillover effects are relevant for all regions except for Alentejo and are the bulk of the overall effects for North, Lisbon, and Algarve.

Finally, for social infrastructures, investments in educational facilities benefit both the North and Centre with 13.040, and 15.177, and to a lesser extent Lisbon with 5.375. Output spillover effects are particularly important for North and Centre as well as Alentejo. In terms of infrastructures in health facilities the largest effects occur in North and Centre as well with marginal products of 4.799 and 4.459, respectively. In both cases spillovers are very significant.

On the Effects of Infrastructure Investments by Region

175

We consider now the results from a different perspective, i.e., for each region we want to identify which infrastructure assets lead to the greatest effects when we consider both the direct effects of investments in the region itself and the spillover effects captured by the region from investments in other regions. We still consider 9, 10, and 11, and again focus on the output effects – the effects on employment and private investment following similar patterns.

For North, the largest output effects come from investments in education with 13.041, and to a lesser extent investment in airports, ports and health with 6.447, 5.762, and 4.799. This region captures sizable spillover effects from port and education investments but also from municipal roads elsewhere.

In turn, for Centre, the largest output effects are due to investments in ports and education with marginal products of 17.546 and 15.177, respectively, and to a lesser extent municipal roads and health with 8.861 and 4.459, respectively. In each of these cases spillovers from investments elsewhere are very significant. Spillovers are also significant from investments in railroads and airports.

As to Lisbon, the best output effects come from investments in airports and ports with

12.941 and 14.435 and to a lesser extent national roads, municipal roads and education with 5.499,

6.123, and 5.375. Output spillovers are particularly strong for investments in national roads and ports and still very significant for investments in municipal roads and airports.

Finally, for Alentejo and Algarve, all effects are relatively small and the spillovers not very sizable. For Alentejo, the largest effects come from investments in airports and education and are due to spillover effects from investments elsewhere while for Algarve the largest effects are from investments in airports and ports and are also due mostly to spillovers.

On the Effects Infrastructure Investments on the Regional Mix of Economic Activity

176

In this section, we probe more formally into the issue of which regions benefit the most from infrastructure investments. We want to identify the effects of infrastructure investment on the regional mix of economic activity in the country.

To analyze the effects of infrastructure investments on the regional mix, we need to move beyond the magnitude of the effects of infrastructure investments in absolute terms and turn to the effects in relative terms. This means, first, for each region the size of its effects relative to the total effects for all regions and, second, these shares relative to the size of the region. The point is that the small effects for certain regions, maybe just a reflection of the fact that these regions are small.

Furthermore, even small effects are significant if the share of the total effects they represent exceeds the share of the region in the total economy. In this case, the marginal effects induced by the infrastructure investments exceed the average size of the region and as such infrastructure investments tend to make such region relatively more important in the regional mix. The results of infrastructure investments in the regional economic composition are reported in Table 9.4,

Table 9.5, and Table 9.6, for road infrastructures, other transportation infrastructures, and social infrastructures, respectively. As before, we focus our discussion on the effects on the regional output mix. The effects on the regional mix of employment and private investment are also reported in the same tables and follow in broad strokes the same patterns.

For road transportation infrastructures, investments in national roads shift the output regional mix towards North, Lisbon, and Alentejo, while investments in municipal roads have the same effects for Centre and investments in highways once again in North, Lisbon and Alentejo.

None of the investments in road infrastructure assets shifts the composition of regional output toward Algarve.

For other transportation infrastructures the shifts in regional output composition occur in

North and Alentejo for railroad investments, Lisbon, Alentejo, and Algarve for airport investment,

177

and Centre and Algarve for port infrastructure investments. This means that every region benefits in relative terms from investments in one of the other transportation infrastructure assets.

Finally, for social infrastructures, investments in both education and health shift the regional output mix towards North and Centre, for health infrastructures, towards the Alentejo as well.

Accordingly, Lisbon and Algarve do not benefit in relative terms from either education or health infrastructure investments.

If we look at this issue from the perspective of each region, the relative importance of North in the regional output mix is enhanced by investments in national roads, highways, railroads, education, and health while the relative importance of Centre is enhanced by investments in municipal roads, ports, education, and health. In turn, for Lisbon, its relative importance in the regional output mix is increased by investments in national roads, highways, and airports. For

Alentejo the relative importance increases with investments in national roads, highways, railroads, airports and health. Finally, Algarve sees its output share increased by only investments in airports and ports.

9.3 Summary and Concluding Remarks

Summary

In this chapter we deal with the issue of identifying empirically the effects of infrastructure investments on the regional mix of economic activity in Portugal. To address this issue we use a new data set for infrastructure investments in Portugal at the level of the NUTS II regions. We use a region-specific VAR approach which considers for each region not only the effects of infrastructure investments in the region itself but also the regional spillover effects for each region from infrastructure investments elsewhere.

178

Our results can be summarized as follows. First, we find that considering all of the direct and spillover effects for all regions, the infrastructure investments with the largest aggregate effects are in municipal roads, airports, ports, and education, while more moderate effects stem from investments in national roads and health and the effects of investments in highways and railroads are clearly the smallest. Regional spillovers are very important across the board, and are particularly relevant for municipal roads and highways. On the flip side, investments in national roads and airports show relatively low spillover effects.

Second, when we consider the regional effects of infrastructure investments in terms of their absolute magnitude we observe that in terms of road infrastructures, the largest effects for investments in national roads occur in North and Lisbon, the effects for Lisbon being mostly due to spillovers. For investments on municipal roads, the largest effects occur in Centre and Lisbon with spillovers particularly relevant in Centre while for investments in highways the effects are small across the board. For other transportation infrastructure the only region that benefits in a meaningful way from railroad investments is North with important spillover effects. As to investments in airports, the largest benefits occur in North and Lisbon with spillovers relevant in

Lisbon, while for investments in ports the largest effects occur in Centre and Lisbon, with spillover representing the bulk of the effects for Lisbon. Finally, for social infrastructures investments in educational and health facilities benefit mostly North and Centre, in both cases with important spillover effects.

Third, when we consider the regional effects of infrastructure investments in terms of their magnitude relative to size of the region, we find that for road transportation infrastructures, investments in national roads shift the output regional mix towards North, Lisbon, and Alentejo, while investments in municipal roads have the same effect for Centre and investments in highways once again in the North, Lisbon and Alentejo. For other transportation infrastructures the shifts in

179

regional output composition occur in North and Alentejo for railroad investments, Lisbon, Alentejo, and Algarve for airport investment, and Centre and Algarve for port infrastructure investments.

Finally, investments in both education and health shift the regional output mix towards North and

Centre, and for health infrastructures, towards the Alentejo as well.

Policy Implications

There are some important policy messages from these results. The regional disaggregation of aggregate effects of infrastructure investments shows a wide disparity of effects, the prevalence of regional spillovers, and important shifts in the regional economic mix. This suggests that emphasis on road investments in the last few decades, for example, may have shifted economic activity away from Centre and even more so Algarve. These ideas are also important to keep in mind in the design of new infrastructure investments. For example a new focus on other transportation infrastructures may have more balanced regional effects while a new focus on social infrastructures shifts the regional mix in the country for North and Centre. Naturally, this is not meant to imply that infrastructure investments are the only or even the most important factor behind the observed shifts in the regional economic mix but rather to argue that infrastructure investments seem to have played a role in those shifts.

180

181

Table 9.1 Marginal Product with respect to Road Transportation Investment Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment Total Total Total In the Outside In the Outside In the Outside

Region the region Region the region Region the region

National Roads North 3.184 1.879 5.064 0.153 -0.031 0.122 3.006 0.817* 3.823 Centre -0.056* 1.205 1.149 0.044 -0.055 -0.011 -0.828* 0.035* -0.793 Lisbon -0.571* 4.759 4.188 -0.009* 0.126 0.116 0.160* 5.340 5.499 Alentejo 0.515 0.902 1.418 -0.013 -0.028 -0.041 0.412 0.704 1.116 Algarve -0.028* -0.306* -0.333 0.000* -0.027 -0.028 0.005* -0.483 -0.478 3.046 8.439 11.486 0.175 -0.016 0.159 2.755 6.413 9.167 Municipal Roads North -2.407* 4.630 2.223 0.014* 0.127 0.141 -4.603* 4.863 0.259 Centre 2.131 5.647 7.778 -0.103 0.123 0.020 0.295* 8.566 8.861 Lisbon 3.918 0.873* 4.790 0.017* 0.120 0.137 4.121 2.001* 6.123 Alentejo 0.952 1.953 2.905 -0.009* 0.015 0.006 0.168* 0.496* 0.664 Algarve -0.710 0.510 -0.200 -0.011* 0.034 0.024 -1.136 0.766 -0.370 3.883 13.613 17.497 -0.092 0.420 0.328 -1.156 16.692 15.537 Highways North 0.477 0.787 1.264 0.020 0.011* 0.031 0.684 0.603 1.286 Centre -0.667 0.354 -0.313 -0.015 0.002* -0.013 -0.982 0.626 -0.356 Lisbon 0.205* 1.160 1.365 0.000* 0.024 0.023 0.243* 1.051 1.294 Alentejo -0.008* 0.410 0.403 0.000* -0.008 -0.009 -0.015* 0.410 0.395 Algarve 0.016* 0.127 0.143 0.000* -0.002* -0.002 0.017* -0.017* -0.001 0.024 2.838 2.861 0.005 0.027 0.031 -0.054 2.673 2.619 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

182

Figure 9.1 Effects of Road Transportation Investment Private Investment

12 Road Transportation National Roads Municipal Roads Highways 10 8 6 4 2 0

Marginal Marginal Product -2

-4

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

Employment 0.4 Road Transportation National Roads Municipal Roads Highways 0.3 0.2 0.1 0.0 -0.1

-0.2 Marginal Marginal Product -0.3

-0.4

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

Output 12 Road Transportation National Roads Municipal Roads Highways 10 8 6 4 2 0

Marginal Marginal Product -2 -4

-6

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

183

Table 9.2 Marginal Product with respect to Other Transportation Investment Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment Total Total Total In the Outside In the Outside In the Outside

Region the region Region the region Region the region

Railroads North 0.1205* 4.2795 4.400 0.0667* 0.0882 0.155 1.5394 1.6958 3.235 Centre -1.3866 2.0744 0.688 -0.0469 0.0367 -0.010 -3.1057 3.0399 -0.066 Lisbon 3.4170 -3.5105 -0.093 0.0478 0.0178* 0.066 2.4780 -1.8618* 0.616 Alentejo 0.2650 1.7665 2.032 -0.0075 -0.0350 -0.042 -0.2827 0.8342 0.552 Algarve 0.0102* -0.0336 -0.023 0.0010* -0.0120 -0.011 0.0467* 0.1212* 0.168 2.426 4.576 7.003 0.061 0.096 0.157 0.676 3.829 4.505 Airports North 4.2989 3.1296 7.428 0.1749 -0.0463* 0.129 6.6222 -0.1751* 6.447 Centre - 4.0113 4.011 - -0.1035* -0.104 - 3.3040 3.304 Lisbon 5.9634 2.9037 8.867 0.1790 0.1580 0.337 7.9884 4.9526 12.941 Alentejo - 4.8130 4.813 - -0.0876 -0.088 - 2.5506 2.551 Algarve 0.8847 -0.3879* 0.497 -0.0148* 0.0222* 0.007 0.0384* 1.7881 1.827 11.147 14.470 25.617 0.339 -0.057 0.282 14.649 12.420 27.069 Ports North 1.5570 1.0461* 2.603 0.0417 0.0330* 0.075 1.4881* 4.2738* 5.762 Centre 6.0348 7.3323 13.367 0.0884 0.1934 0.282 10.2370 7.3086 17.546 Lisbon -4.9653* -3.0760* -8.041 -0.0593* 0.0331* -0.026 2.3285* 12.1067 14.435 Alentejo -0.7318 2.9416 2.210 -0.0061* 0.1421 0.136 -0.0811* 0.0220* -0.059 Algarve 0.0025 1.7806 1.783 0.0008* 0.0841 0.085 0.0095* 3.0934 3.103 1.897 10.025 11.922 0.066 0.486 0.551 13.982 26.804 40.787 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

184

Figure 9.2 Effects of Other Transportation Investment Private Investment

15 Other Transportation Railroads Airports Ports 10

-5 Marginal Marginal Product

-10

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

Employment

0.5 Other Transportation Railroads Airports Ports 0.3

0.1

-0.1

-0.3 Marginal Marginal Product

-0.5

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

Output

20 Other Transportation Railroads Airports Ports 15

0 Marginal Marginal Product

-5

Norte Norte Norte Norte

Lisboa Lisboa Lisboa Lisboa

Centro Centro Centro Centro

Algarve Algarve Algarve Algarve

Alentejo Alentejo Alentejo Alentejo

In the Region Outside the region Total

185

Table 9.3 Marginal Product with respect to Investment in Social Infrastructures Private Investment Employment Output

Effect of Investment Effect of Investment Effect of Investment Total Total Total In the Outside In the Outside In the Outside

Region the region Region the region Region the region

Education North 1.677 8.415 10.093 0.041 0.287 0.328 1.162* 11.879 13.041 Centre 3.801 6.686 10.486 0.134 0.079 0.212 7.047 8.131 15.177 Lisbon 0.895* 4.835 5.731 0.069 0.175 0.244 4.307 1.067* 5.375 Alentejo -1.373* 2.248 0.874 0.048 0.026 0.074 -0.495* 2.313 1.818 Algarve 0.564* 0.252* 0.816 -0.003* 0.022 0.019 0.732 -0.780 -0.048 5.564 22.437 28.001 0.289 0.589 0.877 12.753 22.610 35.363 Health North 1.328 1.647 2.975 0.044 0.120 0.164 2.761 2.038 4.799 Centre 0.681 2.808 3.490 0.027 0.037 0.064 1.179 3.281 4.459 Lisbon 0.120 2.730 2.850 0.004 0.055 0.059 0.187* 1.352* 1.540 Alentejo 0.375 1.645 2.020 -0.007 0.006 -0.001 0.411 1.360 1.770 Algarve 0.015* -0.041* -0.026 -0.004 -0.029 -0.033 0.026* -1.483 -1.457 2.519 8.789 11.308 0.064 0.189 0.253 4.563 6.548 11.111 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

186

Figure 9.3 Effects of Social Infrastructure Investment Private Investment

12 Social Infrastructure Education Health 10 8 6 4 2

Marginal Marginal Product 0

-2

Norte Norte Norte

Lisboa Lisboa Lisboa

Centro Centro Centro

Algarve Algarve Algarve

Alentejo Alentejo Alentejo

In the Region Outside the region Total

Employment 0.5 Social Infrastructure Education Health 0.4 0.3 0.2 0.1 0.0 -0.1 -0.2

Marginal Marginal Product -0.3 -0.4

-0.5

Norte Norte Norte

Lisboa Lisboa Lisboa

Centro Centro Centro

Algarve Algarve Algarve

Alentejo Alentejo Alentejo

In the Region Outside the region Total

Output 18 Social Infrastructure Education Health 16 14 12 10 8 6 4 2

Marginal Marginal Product 0 -2

-4

Norte Norte Norte

Lisboa Lisboa Lisboa

Centro Centro Centro

Algarve Algarve Algarve

Alentejo Alentejo Alentejo

In the Region Outside the region Total

187

Table 9.4 Effects of Road Infrastructure Investment on the Regional Composition of Economic Activity North Centre Lisbon Alentejo Algarve

National Roads Private Investment Marginal Product 5.06 1.15 4.19 1.42 -0.33 Share of Benefits 42.85 9.72 35.44 12.00 0.00 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 1.48 0.46 0.99 1.46 0.00 Employment Marginal Product 0.1216 -0.0107 0.1165 -0.0408 -0.0277 Share of Benefits 51.07 0.00 48.93 0.00 0.00 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 1.46 0.00 1.63 0.00 0.00 Output Marginal Product 3.82 -0.79* 5.50 1.12 -0.48 Share of Benefits 36.62 0.00* 52.68 10.69 0.00 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 1.24 0.00 1.35 1.53 0.00 Municipal Roads Private Investment Marginal Product 2.22 7.78 4.79 2.90 -0.20 Share of Benefits 12.56 43.95 27.07 16.42 0.00 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 0.43 2.08 0.75 2.00 0.00 Employment Marginal Product 0.1413 0.0198 0.1375 0.0058 0.0237 Share of Benefits 43.08 6.02 41.90 1.76 7.23 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 1.23 0.25 1.40 0.28 1.70 Output Marginal Product 0.26 8.86 6.12 0.66 -0.37 Share of Benefits 1.63 55.71 38.49 4.17 0.00 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 0.06 2.81 0.99 0.60 0.00 Highways Private Investment Marginal Product 1.26 -0.31 1.36 0.40 0.14 Share of Benefits 39.81 0.00 42.99 12.68 4.51 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 1.38 0.00 1.20 1.54 0.77 Employment Marginal Product 0.0313 -0.0131 0.0232 -0.0085 -0.0017 Share of Benefits 57.38 0.00 42.62 0.00 0.00 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 1.64 0.00 1.42 0.00 0.00 Output Marginal Product 1.29 -0.36 1.29 0.40 0.00 Share of Benefits 43.23 0.00 43.49 13.29 0.00 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 1.46 0.00 1.11 1.90 0.00

188

Table 9.5 Effects of Other Transportation Investment on the Regional Composition of Economic Activity North Centre Lisbon Alentejo Algarve

Railroads Private Investment Marginal Product 4.40 0.69 -0.09 2.03 -0.02 Share of Benefits 61.80 9.66 0.00 28.53 0.00 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 2.14 0.46 0.00 3.47 0.00 Employment Marginal Product 0.1548 -0.0101 0.0656 -0.0424 -0.0109 Share of Benefits 70.24 0.00 29.76 0.00 0.00 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 2.01 0.00 0.99 0.00 0.00 Output Marginal Product 3.24 -0.07 0.62 0.55 0.17 Share of Benefits 70.78 0.00 13.48 12.07 3.67 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 2.39 0.00 0.35 1.73 0.81 Airports Private Investment Marginal Product 7.43 4.01 8.87 4.81 0.50 Share of Benefits 29.00 15.66 34.61 18.79 1.94 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 1.00 0.74 0.96 2.28 0.33 Employment Marginal Product 0.1287 -0.1035 0.3370 -0.0876 0.0074 Share of Benefits 27.20 0.00 71.24 0.00 1.56 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 0.78 0.00 2.37 0.00 0.37 Output Marginal Product 6.45 3.30 12.94 2.55 1.83 Share of Benefits 23.82 12.21 47.81 9.42 6.75 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 0.80 0.62 1.22 1.35 1.48 Ports Private Investment Marginal Product 2.60 13.37 -8.04 2.21 1.78 Share of Benefits 13.04 66.96 0.00 11.07 8.93 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 0.45 3.17 0.00 1.35 1.53 Employment Marginal Product 0.0747 0.2818 -0.0261 0.1361 0.0848 Share of Benefits 12.94 48.80 0.00 23.57 14.69 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 0.37 2.00 0.00 3.72 3.45 Output Marginal Product 5.76 17.55 14.44 -0.06 3.10 Share of Benefits 14.11 42.96 35.34 0.00 7.60 Ratio 0.48 2.17 0.90 0.00 1.67 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

189

Table 9.6 Effects of Social Infrastructure Investment on the Regional Composition of Economic Activity North Centre Lisbon Alentejo Algarve

Education Infrastructures Private Investment Marginal Product 10.09 10.49 5.73 0.87 0.82 Share of Benefits 36.05 37.45 20.47 3.12 2.92 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 1.25 1.77 0.57 0.38 0.50 Employment Marginal Product 0.3277 0.2123 0.2440 0.0744 0.0189 Share of Benefits 37.35 24.20 27.81 8.49 2.15 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 1.07 0.99 0.93 1.34 0.51 Output Marginal Product 13.04 15.18 5.37 1.82 -0.05 Share of Benefits 36.83 42.86 15.18 5.13 0.00 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 1.24 2.16 0.39 0.73 0.00 Health Infrastructures Private Investment Marginal Product 2.98 3.49 2.85 2.02 -0.03 Share of Benefits 26.25 30.79 25.14 17.82 0.00 Share of GFCF 28.90 21.12 35.92 8.23 5.83 Ratio 0.91 1.46 0.70 2.17 0.00 Employment Marginal Product 0.1639 0.0642 0.0592 -0.0006 -0.0333 Share of Benefits 57.04 22.35 20.61 0.00 0.00 Share of Employment 35.01 24.37 30.03 6.34 4.25 Ratio 1.63 0.92 0.69 0.00 0.00 Output Marginal Product 4.80 4.46 1.54 1.77 -1.46 Share of Benefits 38.18 35.48 12.25 14.09 0.00 Share of Output 29.59 19.80 39.05 6.99 4.56 Ratio 1.29 1.79 0.31 2.01 0.00 (*) The estimates marked with asterisk are not significantly different from zero as implied by the standard deviation bands around the accumulated impulse response functions.

190

191

CHAPTER 10 Concluding Remarks and Directions for Future Work

In this concluding chapter we provide important remarks to help the reader frame the analysis and results presented in this work, that is, to make it clear what the results are and mean and what they have left out. This is also a natural way of introducing some areas of future research that follow directly and immediately from the present work and that are considered particularly pertinent from a policy perspective.

10.1 What These Results Are and What They Are Not

Because of their immediate relevance for policy making it is appropriate to include here several cautionary notes about these results. This being the case it is critical to understand the scope of the results, what they are informative about and what they are not informative about.

First, our results deal with general macroeconomic impacts and provide proper but general guidance. The fact that an infrastructure asset is identified as yielding important positive effects does not imply that all investment projects pertaining to the same assets are equally desirable or even desirable at all. The same reasoning applies to the assets that we have identified as less important – it does not mean that all projects in these areas would also be undesirable. To make these determinations there is no substitute for a benefit-cost analysis.

In the same vein, our results are meant to give very clear guidance as to the infrastructure assets and regions to pay attention to in the design of infrastructure policy. They are important inputs in determining what and where to invest in general terms and in helping identify the potential effects of specific investment projects. What they cannot do, is to be used as the only factor to justify any specific infrastructure investment project in any given region.

Second, the macroeconomic impacts we have identified are relevant from a policy perspective and are indicative of the benefits for the country as a whole as determined by its

192

economic fabric. These numbers are not indicative of the desirability that these projects could have for the private sector.

Third, and from a different perspective, our results establish the relevance of infrastructure investments both in absolute and in relative terms. They cannot be regarded as implying that infrastructure investments are the only factor or even the most important behind any economic change we observe in the economic fabric of the country. Clearly, we do not compare the effects of infrastructure investments with the effects of other public policies, namely fiscal policies, tax reductions, other expenditure programs, or investment subsidies. Clearly, we do not contrast the effects of infrastructure investments with any other major drivers of the economic growth in the country such as improved openness of the economy to foreign trade, financial integration, market liberalization, foreign direct investment, just to name a few.

Fourth, the issue of the mechanisms of financing of the infrastructure investments and their impacts are not considered. Naturally, it makes a difference if investments are financed through taxation, government borrowing, or public private partnerships. The side effects of the financing mechanisms may be significant and, therefore, from this perspective our results should be understood as an upper bound on the macro effects.

Finally, by dealing with infrastructure investments, by definition, we do not consider, at least directly, the issue of the quality of infrastructures being made available or the issue of the effects of changes in the actual patterns of utilization of the infrastructures. While the quality of the infrastructure can in some way be subsumed in its cost, there is no way around the issue of utilization. From this perspective our results should be understood as reflecting the impact of infrastructure investments under the historical patterns of utilization.

193

10.2 Directions for Future Work

Naturally, all the qualifications above can be understood already as directions for future work. But more directly, our results open the door to several important avenues of future research relevant for policy purposes. An important next step would be going more in the direction of the fiscal multiplier literature and to explore how non-linearities may affect the effects of infrastructure investments. In particular, it would be interesting to consider the issue of regime switching, i.e., if it makes a different if the investments occur in a boom or a bust, as well as the issue of the potential differential effects between investment increases and decreases. In addition, a closer look at the timing of the effects, that is, the issue of whether most of the effects occur in the short-term or over a longer time frame would help in understanding the nature of the mechanisms behind these effects.

Finally, exploring the panel dimension of the data could bring new insights into the results and obviate any concerns about relative small sample sizes so common in this literature.

From a more practical perspective there is much to be exploited, even with the confines of the existing empirical results presented here, in terms of the effects of different infrastructure investments at the specific industry or regional level. For example, how do investments in health and education affect labor productivity and the industry or regional economic mixes? How has the evolution of agriculture been affected by the patterns of infrastructure investments? How was the real estate affected by infrastructure investments? How much of the decline in economic activity in

Alentejo can be attributed to infrastructure investments and how could these investments be used to reverse the trend?

10.3 The General Relevance of This Work.

To conclude, it should be mentioned that although this work is an application to the

Portuguese case and is intended to be directly relevant from the perspective of policy making in

Portugal, its interest is far from parochial. The quest for policies that promote long-term growth in a

194

framework of fragile public budgets is widespread. As EU structural transfers have shifted towards new members, countries such as Ireland, Greece, and Portugal have been forced to rely on domestic public policies to promote real convergence. This poses a challenge since growing public spending, pro-cyclical policies, and more recently, falling tax revenues have contributed to rapidly increasing levels of public debt and a sharp need for budgetary consolidation. How to direct the infrastructure investment efforts in a way that is friendly to both the economy and the public budget is, therefore, a question in search of an answer in many other countries facing similar difficulties.

195

REFERENCES

1. Andrews, K. and Swanson, J. (1995), “Does public infrastructure affect regional performance?” Growth and Change, Vol. 26, No. 2, pp. 204-216.

2. Aschauer, A. (1989a), “Is Public Expenditure Productive?” Journal of Monetary Economics 23 (2), pp. 177-200.

3. Aschauer, A. (1989b), “Does Public Capital Crowd out Private Capital?” Journal of Monetary Economics 24 (2), pp. 171-188.

4. Baunsgaard, T., A. Mineshima, M. Poplawski-Ribeiro, and A. Weber (2014). “Fiscal Multipliers,” in Post-Crisis Fiscal Policy C. Cottarelli, P. Gerson, and A. Senhadji (Eds.). MIT Press.

5. Berndt, E., and B. Hansson (1991), “Measuring the Contribution of Public Infrastructure Capital in Sweden,” Scandinavian Journal of Economics 94, 151-168.

6. Blanchard, O. and R. Perotti (2002), “An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output,” Quarterly Journal of Economics 117, 1329-68.

7. Boarnet, M. G. (1998), “Spillovers and the Locational Effects of Public Infrastructure,” Journal of Regional Science, 38, 381-400.

8. Boscá, J., Escriba, J. and Murgui, M. (2000), “The effect of public infrastructure on the private productive sector of Spanish regions,” Journal of Regional Science, Vol. 42, pp. 301-326.

9. Cadot, O., Roller, L. and Stephan, A. (1999), “A political economy model of infrastructure allocation: an empirical assessment,” CEPR Discussion Paper Nº 2336, Wissenschaftszentrum, Berlin, December.

10. Christiano, L., M. Eichenbaum, C. Evans (1996), “The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds,” Review of Economics and Statistics 78(1), pp. 16-34.

11. Christiano, L., M. Eichenbaum, C. Evans (1999), “Monetary Policy Shocks: What Have we Learned and to What End?” in Handbook of Macroeconomics Vol. 1A, Eds. John B. Taylor and Michael Woodford. North-Holland.

12. Cohen, J. and Paul, C. (2004), “Public infrastructure investment, interstate spatial spillovers and manufacturing costs,” Review of Economics and Statistics, Vol. 86, No. 2, pp. 551-560.

13. Costa, J., R. Ellson and R. Martin (1987), “Public Capital, Regional Output, and Development: Some Empirical Evidence,” Journal of Regional Science, 27(3), 419-437.

14. Cutanda, A. and Parício, J., (1992), “Infrastructure and regional economic growth: the Spanish case,” Regional Studies, Vol. 28, No. 1, pp. 69-77.

196

15. Duffy-Deno, K. and R. Eberts (1991), “Public Infrastructure and Regional Economic Development: A Simultaneous Equations Approach,” Journal of Urban Economics 30, 329-43.

16. Eberts, R. (1990), “Cross sectional analysis of public infrastructure and regional productivity growth,” Working Paper No. 9004, Federal Reserve Bank of Cleveland, Cleveland, May.

17. Eisner, R. (1991), “Infrastructure and regional economic performance: comment,” New England Economic Review, September, pp. 47-58.

18. Evans, P. and G. Karras (1994), “Are Government Activities Productive? Evidence From a Panel of U.S. States,” Review of Economics and Statistics, 76(1) 1-11.

19. Everaert, G. (2003), “Balanced growth and public capital: an empirical analysis with I(2) trends in capital stock data,” Economic Modelling, Vol. 20, pp. 741-763.

20. Everaert, G. and Heylen, F. (2004), “Public capital and long term labor market performance in Belgium,” Journal of Policy Modeling, Vol. 26, pp. 95-112.

21. European Commission (2014), “The Economic Adjustment Programme for Portugal, 2011- 2014,” European Economy Occasional Papers 202.

22. European Union (2014a), Reindustrializing Europe, Member State’s Competitiveness Report 2014, A Europe 2020 Initiative, European Commission.

23. European Union (2014b), Helping Firms Grow, European Competitiveness Report 2014, , European Commission

24. Fernald, J. (1993), “How Productive is Infrastructure? Distinguishing Reality and Illusion with a Panel of US Industries,” mimeo.

25. Garcia-Milà, T. and T. McGuire (1992), “The Contribution of Publicly Provided Inputs to States’ Economies,” Regional Science and Urban Economics, 22, 229-41.

26. Garcia-Milà, T., T. McGuire and R. Porter (1996), “The Effect of Public Capital in State-Level Productions Functions Reconsidered,” Review of Economics and Statistics, 78(1), 177-80.

27. Gokirmak, H. (1995), “Infrastructure and Economic Performance,” Ph.D. Dissertation, American University.

28. Gramlich, E. (1994), “Infrastructure investment: A review essay,” Journal of Economic Literature 32, 1176-96.

29. Greenstein, S. and P. Spiller (1995), “Modern Telecommunications Infrastructure and Economic Activity: An Empirical Investigation,” Industrial and Corporate Change 4(4), 647-665.

30. Haugwout, F, (1989), “Aggregate Production Functions, Interregional Equilibrium, and the Measurement of Infrastructure Productivity,” Journal of Urban Economics, 44, 216-27.

197

31. Haugwout, F. (2002), “Public Infrastructure Investments, Productivity and Welfare in Fixed Geographical Areas,” Journal of Public Economics, 83, 402-28.

32. Holleyman, C. (1996), “Industry Studies of the Relationship between Highway Infrastructure Investment and Productivity,” Logistics and Transportation Review 32(1), 93-117.

33. Holtz-Eakin, D. (1993), “Public investment in infrastructure,” Journal of Economic Perspectives, Vol. 7, No. 4, pp. 231-234.

34. Holtz-Eakin, D. (1994), “Public Sector Capital and the Productivity Puzzle,” Review of Economics and Statistics, 76 (1), 12-21.

35. Holtz-Eakin, D. and A. Schwartz (1995), “Spatial Productivity Spillovers from Public Infrastructure: Evidence from State Highways,” International Tax and Public Finance, 2, 459-68.

36. Instituto Nacional de Estatística www.ine.pt

37. International Monetary Fund (2012), Coping with High Debt and Sluggish Growth. World Economic Outlook.

38. International Monetary Fund (2013), “Anchoring Growth: The Importance of Productivity- Enhancing Reforms in Emerging Markets and Developing Economies,” IMF Staff Discussion Note SDN/13/08.

39. International Monetary Fund (2014), “Adjustment in Euro Area Deficit Countries: Progress, Challenges and Policies,” IMF Staff Discussion Note SDN/14/07.

40. Ivanov, V. and L. Kilian (2005), “A Practitioner’s Guide to Lag Order Selection for VAR Impulse Response Analysis,” Studies in Nonlinear Dynamics and Econometrics 9 (1), article 2.

41. Kamps, C. (2005), “The dynamic effects of public capital: VAR evidence for 22 OECD countries,” International Tax and Public Finance 12, 533-558.

42. Kilian, Lutz (1998), “Small-Sample Confidence Intervals for Impulse Response Functions,”. The Review of Economics and Statistics, Vol. 80. No.2, pp. 218-230.

43. Leduc, Sylvain and Daniel Wilson (2012), “Roads to Prosperity or Bridges to Nowhere? Theory and Evidence on the Impact of Public Infrastructure Investment,” NBER Macroeconomics Annual Vol. 27 No. 1, pp. 89-142.

44. Lynde, C., and J. Richmond (1993), “Public Capital and Long-Run Costs in U.K. Manufacturing,” Economic Journal 103, 880-893.

45. Mas, M., Maudos J., Perez, F. and Uriel, E. (1996), “Infrastructures and productivity in the Spanish regions,” Regional Studies, Vol. 30, No. 7, pp. 641-650.

46. Merriman, D. (1990), “Public capital and regional output: another look at some Japanese and American data,” Regional Science and Urban Economics, Vol. 20, pp. 437-458.

198

47. Mikelbank, B. A. and R. W. Jackson (2000), “The Role of Space in Public Capital Research,” International Regional Science Review, 23 (3), 235-58.

48. Mikelbank, B. and Jackson, R. (2000), “The role of space in public capital research,” International Regional Science Review, Vol. 23, No. 3, pp. 235-258.

49. Moomaw R. and Williams, M. (1991), “Total factor productivity growth in manufacturing: further evidence from the states,” Journal of Regional Science, Vol. 31, No. 1, pp. 17-34.

50. Moomaw, R., Mullen, J. and Williams, M. (1995), “The interregional impact of infrastructure capital,” Southern Economic Journal, Vol. 61, No. 3, pp. 830-845.

51. Moreno, R., López_Bazo, E. and Artís, M. (2003), “On the effectiveness of private and public capital,” Applied Economics, Vol. 35, pp. 727-740.

52. Munnell, A. (1990), “Why Has Productivity Growth Declined? Productivity and Public Investment,” New England Economic Review, January/February, 3-22.

53. Munnell, A. (1992), “Infrastructure, Investment and Economic Growth,” Journal of Economic Perspectives, 6, 189-98.

54. Munnell, A. and L. Cook (1990), “How Does Public Infrastructure Affect Regional Economic Performance?” New England Economic Review, September/October, Federal Reserve Bank of Boston, 11-33.

55. Nadiri, M., and T. Mamuneas (1994), “The Effects of Public Infrastructure and R&D Capital on the Cost Structure and Performance of U.S. Manufacturing Industries,” Review of Economics and Statistics, 76(1), 22-37.

56. OECD (2013), OECD Compendium of Productivity Indicators, OECD Statistics Directorate and Directorate for Science, Technology and Industry.

57. OECD (2014) Portugal – Deepening Structural Reform to Support Growth and Competitiveness, Better Policy Series, OECD Secretariat.

58. Pereira, A. (2000), “Is all public capital created equal?” Review of Economics and Statistics 82, pp. 513-518.

59. Pereira, A. (2001), “Public capital formation and private investment: what crowds in what?” Public Finance Review 29, 3-25.

60. Pereira, A. and Andraz, J. (2003), “On the impact of public investment on the performance of US industries,” Public Finance Review 31, 66-90.

61. Pereira, A. and Andraz, J. (2004), “Public highway spending and state spillovers in the USA,” Applied Economics Letters 11, 785-788.

62. Pereira, A. and Andraz, J. (2005), “Public investment in transportation infrastructures and economic performance in Portugal,” Review of Development Economics 9, 177-196.

199

63. Pereira, A. and Andraz, J. (2007), “Public investment in transportation infrastructures and industry performance in Portugal,” Journal of Economic Development Economics 32, 1-20.

64. Pereira, A. and Andraz, J. (2011), "On the Economic and Fiscal Effects of Investment in Road Infrastructure in Portugal," International Economics Journal 25 (3), 465-492.

65. Pereira, A. and Andraz, J. (2013), "On the economic effects of public infrastructure investment: a survey of the international evidence," Journal of Economic Development 38 (4), 1-37.

66. Pereira, A. and Flores, R. (1999), “Public capital accumulation and private-sector performance in the U.S.,” Journal of Urban Economics 46, 300-322.

67. Pereira, A. and R. Pereira, R. (2014), “On the Effects of Infrastructure Investment on Economic Performance in Ontario,” mimeo.

68. Pereira, A. and R. Pereira (2015), Investimentos em Infraestruturas em Portugal: Dados e Factos Estilizados. Fundação Francisco Manuel dos Santos, forthcoming.

69. Pereira, A. and O. Roca-Sagales (1999). “Public Capital Formation and Regional Development in Spain,” Review of Development Economics, 3(3), 281-294.

70. Pereira, A. and O. Roca-Sagales (2001), “Public Capital and Private Sector Performance in Spain: A Sectoral Analysis,” Journal of Policy Modeling, 23, 371-384.

71. Pereira, A. and O. Roca-Sagales (2003), “Spillover effects of public capital formation: evidence from the Spanish regions,” Journal of Urban Economics 53, 238-256.

72. Pereira, A. and O. Roca-Sagales (2007), "Public Infrastructures and Regional Asymmetries in Spain," Revue d’Economie Regionale et Urbaine, 503- 520.

73. Pinnoi, N. (1992), “Public Investment and Private Production: Measuring Relative Contributions,” Journal of Economic Behavior and Organization, 23(2), 127-48.

74. Ramey, V. (2011), “Can Government Purchases Stimulate the Economy?” Journal of Economic Literature 49 (3), 673-85.

75. Romp, W. and de Haan, J. (2007), “Public capital and economic growth: a critical survey,” Perspektiven der Wirtschaftspolitik, 8, Special Issue, April, 6-52.

76. Rudebusch, G. D. (1998), “Do Measures of Monetary Policy in a VAR Make Sense?” International Economic Review, 39(4), 907-931.

77. Seitz, H. (1994), “Public Capital and the Demand for Private Inputs,” Journal of Public Economics 54, 287-307.

78. Shah, A. (1992), “Dynamics of Public Infrastructure, Industrial Productivity and Profitability,” Review of Economics and Statistics 74(1), 28-33.

200

79. Sims, Christopher A. and Tao Zha. (1999), “Error Bands for Impulse Responses,” Econometrica. Vol. 67, no. 5. pp. 1113-1155.

80. Stephan, A. (2000), “Regional infrastructure policy and its impact on productivity: a comparison of Germany and France,” Applied Economics Quarterly, Vol. 46, pp. 327– 356.

81. World Economic Forum (2014a), Europe 2020 Competitiveness Report – Building a More Competitive Europe, Insight Report.

82. World Economic Forum (2014b), Global Competitiveness Report 2014-2015, Insight Report.

201

List of Figures

Figure 2.1 Map of Portuguese NUTS II Regions ...... 29

Figure 4.1 Accumulated Impulse Response Functions with respect to Infrastructure Investment .... 63

Figure 4.2 Accumulated Impulse Response Functions with respect to Infrastructure

Investment...... 64

Figure 4.3 Effects of Infrastructure Investment on Labor Productivity...... 65

Figure 4.4 Effects of Infrastructure Investment - Main Types of Assets ...... 65

Figure 4.5 Marginal Productivity using Alternative Sample Periods ...... 66

Figure 4.6 Marginal Productivity using Alternative Sample Periods – by Asset Type ...... 67

Figure 5.1 Accumulated Impulse Response Functions – Road Transportation ...... 96

Figure 5.2 Accumulated Impulse Response Functions – Other Transportation ...... 97

Figure 5.3 Accumulated Impulse Response Functions – Social Infrastructures ...... 98

Figure 5.4 Accumulated Impulse Response Functions – Public Utilities...... 99

Figure 5.5 Effect of Infrastructure Investment on Labor Productivity ...... 100

Figure 5.6 Long-Term Marginal Products of Infrastructure Investment ...... 101

Figure 5.7 Evolution of the Marginal Products – Road Transportation ...... 102

Figure 5.8 Evolution of the Marginal Products – Other Transportation ...... 103

Figure 5.9 Evolution of the Marginal Products – Social Infrastructures ...... 104

Figure 5.10 Evolution of the Marginal Products – Public Utilities ...... 105

Figure 6.1 Effects of Road Transportation Investment by Sector of Economic Activity ...... 122

Figure 6.2 Effects of Other Transportation Investment by Sector of Economic Activity ...... 124

Figure 6.3 Effects of Social Infrastructure Investment by Sector of Economic Activity ...... 126

Figure 6.4 Effects of Public Utility Investment by Sector of Economic Activity ...... 128

202

Figure 6.5 Effects of Telecommunications Investment by Sector of Economic Activity ...... 130

Figure 9.1 Effects of Road Transportation Investment ...... 183

Figure 9.2 Effects of Other Transportation Investment ...... 185

Figure 9.3 Effects of Social Infrastructure Investment ...... 187

203

List of Tables

Table 2.1 Industry Classification...... 25

Table 2.2 Industry Composition ...... 26

Table 2.3 Output per Worker by Industry ...... 27

Table 2.4 Definition of Regions by NUTS II ...... 28

Table 2.5 Summary of Regional Composition of Economic Activity ...... 30

Table 2.6 Regional Composition of Infrastructure Investment ...... 31

Table 2.7 Infrastructure Investment by Type of Asset ...... 32

Table 2.8 Regional Infrastructure Investments as a % of GDP ...... 33

Table 2.9 Summary of Regional Composition of Economic Activity ...... 34

Table 4.1 Elasticities with respect to Infrastructure Investment - Main Types of Assets ...... 61

Table 4.2 Marginal Product of Infrastructure Investment - Main Types of Assets ...... 61

Table 4.3 Rate of Return on Infrastructure Investment - Main Types of Assets ...... 62

Table 4.4 Long-term Marginal Products versus Effects on Impact - Main Types of Assets ...... 62

Table 5.1 Elasticities with respect to Infrastructure Investment ...... 89

Table 5.2 Marginal Product of Infrastructure Investment ...... 90

Table 5.3 Rate of Return on Infrastructure Investment ...... 91

Table 5.4 Long-term Marginal Products versus Effects on Impact ...... 92

Table 6.1 Effects of Road Transportation Investment by Sector of Economic Activity ...... 121

Table 6.2 Effects of Other Transportation Investment by Sector of Economic Activity ...... 123

Table 6.3 Effects of Social Infrastructure Investment by Sector of Economic Activity ...... 125

Table 6.4 Effects of Public Utility Investment by Sector of Economic Activity ...... 127

204

Table 6.5 Effects of Telecommunications Infrastructure Investment by Industry ...... 129

Table 6.6 Effects of Road Infrastructure Investment on the Industry Mix ...... 131

Table 6.7 Effects of Other Infrastructure Investment on the Industry Mix ...... 132

Table 6.8 Effects of Social Infrastructure Investment on the Industry Mix ...... 133

Table 6.9 Effects of Public Utilities Investment on the Industry Mix ...... 134

Table 6.10 Effects of Telecommunication Infrastructure Investment on the Industry Mix ...... 135

Table 7.1 Effects on Labor Productivity by Industry: Road Transportation ...... 150

Table 7.2 Effects on Labor Productivity by Industry: Other Transportation ...... 151

Table 7.3 Effects on Labor Productivity by Industry: Social Infrastructures ...... 152

Table 7.4 Effects on Labor Productivity by Industry: Public Utilities ...... 153

Table 8.1 Elasticities with respect to Road Transportation Investment ...... 164

Table 8.2 Elasticities with respect to Other Transportation Investment ...... 165

Table 8.3 Elasticities with respect to Investment in Social Infrastructures ...... 166

Table 8.4 Marginal Product with respect to Road Transportation Investments in each Region ...... 167

Table 8.5 Marginal Product with respect to Other Transportation Investment in each Region ...... 168

Table 8.6 Marginal Product with respect to Social Infrastructure Investments in each Region ...... 169

Table 8.7 How Far are the Actual Effects from the Potential Effects of Infrastructure Investments?

...... 170

Table 9.1 Marginal Product with respect to Road Transportation Investment ...... 182

Table 9.2 Marginal Product with respect to Other Transportation Investment ...... 184

Table 9.3 Marginal Product with respect to Investment in Social Infrastructures ...... 186

Table 9.4 Effects of Road Infrastructure Investment on the Regional Composition of Economic

Activity...... 188

205

Table 9.5 Effects of Other Transportation Investment on the Regional Composition of Economic

Activity...... 189

Table 9.6 Effects of Social Infrastructure Investment on the Regional Composition of Economic

Activity...... 190

206

207