Trade and Employment From Myths to Facts - International Labour ...

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Chapter 7: Trade diversification: Drivers and impacts and low production costs) but also “second-nature” ones – pure agglomeration forces. 22 Among those, Alfaro and Chen examine the role of labour-market pooling (a larger pool reduces unemployment risk for workers and, therefore, wage premia), capitalequipment linkages (larger pools of capital-intensive industries attract support services), input-output (IO) linkages, and knowledge spillovers between industries measured by cross-citations in patents. They find very strong evidence of capital-equipment linkages and knowledge spillovers in the location of subsidiaries. IO linkages are significant, although weaker. By contrast, evidence of labour-market pooling is weak. Inter-industry spillovers are also identified empirically by Shakurova (2010), who estimates how the probability of exporting a good depends on previous experience in exporting either similar goods (“horizontal” spillovers) or upstream ones (“vertical” spillovers). Cross-country regressions at the industry level show that the size of those spillovers varies across industries but is, in most cases, statistically significant. Figure 7.9 shows those spillovers in the form of marginal effects for each industry. Figure 7.9: Vertical and horizontal export spillovers Vertical spillover marginal effect 0 .1 .2 .3 Transport Source: Adapted from Shakurova (2010). Plastics Jewerly Metals Paper Textiles Machinery Glass Wood Chemicals Optics Oils Minerals Footware Vegetable Food Leather Arms Live animals .1 .2 .3 Horizontal spillover marginal effect Note: Marginal effects from a probit regression of export status in product i on export status in product j at t-1 on a cross-section of countries. Those shown were significant at 5 per cent or more. 22 Alfaro and Chen (2009) combine geocode software with Dunn and Bradstreet’s worldbase data set, which contains detailed location information on over 41 million establishments, to calculate distances between establishments belonging to different industries (as Alfaro and Chen focus on between-industry agglomeration). Distances are used to estimate actual and counterfactual densities, the difference between the two being the agglomeration index. 275
Trade and Employment: From Myths to Facts Other externalities include information spillovers leading to underinvestment in export entrepreneurship at the extensive margin (Hausmann and Rodrik, 2003). That is, export expansion at the extensive margin reflects a “self-discovery” process whereby export entrepreneurs test the viability of new products on foreign markets. Once they succeed, imitators follow, creating a public-good problem. Spillovers at the extensive margin among exporters of the same country are documented using firm-level data from four African countries by Cadot et al. (2011), who find that the probability of survival of an exporter of good k to country d past the first year rises with the number of exporters of k to d from the same country. Strikingly, the number of exporters of k to d from other countries is insignificant, suggesting that the externality is essentially within-country. Interacting this network effect with various measures of dependence on finance suggests that the information spillover may go through domestic credit markets (using competitor performance as a substitute for direct information on export risk) rather than through the direct firm-to-firm imitation effect postulated by Hausmann and Rodrik, although the implications are similar. If the case for externalities across exporters and industries seems fairly well-established both conceptually and empirically, what governments can do to leverage those externalities is less clear. Harrison and Rodriguez-Clare (2010) give a long list of studies whose gist is that industries supported by government protection in one form or another do not enjoy faster productivity growth. However, all these studies are vulnerable to the endogeneity critique of Rodrik (2007). Namely, if governments support industries to compensate for market failures, slower productivity growth in supported industries may reflect the underlying constraints rather than the effect of (endogenous) industrial policies. A few case studies identify industries successfully supported by industrial policy. For instance, Hansen, Jensen and Madsen (2003) show how Denmark’s subsidies to wind power (a guaranteed-price scheme for wind power combined with an obligation to buy for power companies that was also adopted in other EU countries, and a favourable tax treatment of investments in wind-turbine manufacturing) have helped create an industry that, by the early 2000s, supplied half the world’s demand for wind turbines. As export sales were not subsidized (although they could possibly be cross-subsidized by Denmark’s four large manufacturers), their growth was suggestive of success. Hansen, Jensen and Madsen indeed show evidence of strong learning economies. They also argue that overall benefits from the industry’s development had, by the early 2000s, outweighed the total cost of the subsidies, although the calculation is complex. Export promotion has a more uneven record. After reviewing the mixed evidence so far, Lederman, Olarreaga and Payton (2006, 2009) find, on the basis of crosscountry evidence, extremely high rates of return on public money invested in export-promotion agencies (EPAs). Some conditions, however, must be fulfilled, including private-sector involvement in agency management. They also find strongly diminishing returns; that is, a little money does a lot of good, but a lot of money does not. A recent impact evaluation of Tunisia’s export-promotion agency by Gourdon et al. (2011) sheds some light on whether export promotion promotes 276
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Trade and Employment From Myths to
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Trade and Employment From Myths to
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PREFACE Trade negotiations -bilater
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Trade and Employment: From Myths to
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EDITORS AND CONTRIBUTORS EDITORS Ma
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ACKNOWLEDGEMENTS The editors wish t
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NEW EVIDENCE ON TRADE AND EMPLOYMEN
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Chapter 2: New evidence on trade an
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Region Annualized percentage change
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Region 1980 1985 1990 1995 2000 200
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Figure 2.4.b: Long-run association
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20 See Harrison and Rodriguez-Clare
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ASSESSING THE IMPACT OF TRADE ON EM
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Chapter 3: Assessing the impact of
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p * Chapter 3: Assessing the impact
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APPPENDIX 3.A: TABLES Chapter 3: As
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TRADE AND THE INFORMAL ECONOMY 4.1
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Chapter 4: Trade and the informal e
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For more than two decades, quantita
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GENDER ASPECTS OF TRADE 5.1 INTRODU
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and income-earning opportunities ge
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Figure 5.1: Description of gender i
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Chapter 5: Gender aspects of trade
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A third view is that the type of jo
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REFERENCES Chapter 5: Gender aspect
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