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Why do industrial policy? Does it work?

Why do industrial policy? Does it work?. Growing out of natural resources The natural resources curse The Dutch disease Escaping excessive concentration Picking priorities Special economic zones: What do they bring? Tax incentives: How efficient Soft industrial policy: Export promotion.

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Why do industrial policy? Does it work?

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  1. Why do industrial policy? Does it work? • Growing out of natural resources • The natural resources curse • The Dutch disease • Escaping excessive concentration • Picking priorities • Special economic zones: What do they bring? • Tax incentives: How efficient • Soft industrial policy: Export promotion

  2. Why diversify? The natural resources curse Sachs-Warner 2001: Growth 1970-89 vs the share of primary-product exports in GDP Growth 1970-89 Share of natural resources in exports, 1971

  3. The «conditional curse»: controlling for other growth determinants

  4. Plotting a partial correlation Correlation between growth and share of natural resources after controlling for initial income and OPEN

  5. The curse revisited Growth and NR wealth using an exogenous measure Volatility and NR wealth Oil prices, 1980-2012

  6. The Dutch disease

  7. Why do industrial policy?

  8. Why do industrial policy? • Justifying industrial policy requires a market failure • Synergies/externalities • Imperfect information, … Good 1 Good 1 Producer-price ratio E E 1 1 World price line PPF PPF E 2 Good 2 Good 2 Zone of increasing returns / agglomeration in the Targeted by IP production of good 2

  9. Identifying sectoral priorities for diversification • Three approaches to help guide governments to think about export-diversification potential at the sectoral level: • A retrospective approach based on revealed comparative advantage, looking at products that the country has already exported as evidence of potential; • A resource-based approach based on the country’s existing endowment of factors of production (capital, labor, and education); • A prospective approach based on a business-style analysis of market potential at the product level.

  10. Recommendations in terms of export promotion (iI) bla

  11. Tunisia’s export promotion • Program covers 2005-2009 • Mixture of matching grants and technical assistance to • Develop an export activity/grow out of single-buyer relationships • Get into new markets • Export new products • 455 firms had completed Famex programs at end-2009 • Activities co-financed by FAMEX • Prospection: acquisition of information on foreign markets, purchase of data, or missions abroad to visit foreign exhibitions • Promotion: production of marketing information (design, production and publication of ads in various media), firm representation in fairs and exhibitions, and mailings • Product development: production of samples, package design • Firm development: organizational issues like setting up a marketing watch, an export cell, or an export-oriented business plan • Foreign subsidiary creation: legal, consulting, rental and salary costs for the first year of establishment.

  12. Estimating « treatment effects » (i) • Matching-DID estimator (see Heckman et al. 1998, Blundell & Costa Dias 2009): • τ is treatment year and wij are the weights used in the matching (kernel, NN). • Compares the change in outcomes for FAMEX firms relative to the change in outcomes for matched control firms before and after FAMEX • Controls for differences in pre-treatment attributes through matching • Problem: Tunisian firms received FAMEX assistance in different years, so τ = τ(i), and calendar time matters for performance

  13. Estimating « treatment effects » (ii) One possible fix: restrict matching for treatment firm treated in τ(i) to controls observed in τ(i): Alternative: revert to a regression framework using propensity score as weights (Hirano, Imbens and Ridder 2003). That is, estimate a simple DID equation with unit weights for treated firms and for controls.

  14. Exporters spreading themselves too thin? • Cumulative effects: • Disappear after 2 years for export value • Remain significant up to 5 years for # of products and destinations Note: All regs include firm controls and year effects Baseline impact effect

  15. Results vs. expectations Initial expectations… …vs. what happened

  16. Impact effect, by objective Effects on primary stated objective (along diagonal) do not appear either larger or more precisely estimated; most precisely estimated effects are always on # of destinations Dummies, add up to treatment

  17. Impact effect, by activity Effects of prospection (getting to know) and promotion (getting known) seem most significant (suggesting informational market failure?) Amounts Total (program) amounts disbursed by activity: See last slide Selection correction based on PSM, i.e. corrects only for selection into the program; not into particular activity amounts

  18. Externalities Impressive absence of results—like Bernard & Jensen 2004. Bad proxy? Or no externalities? If anything, negative (also like B&J): poaching of managers/workers using taxpayer’s money?

  19. A rough cost-benefit analysis Estimated treatment benefit Average annual export growth for control firms, 2004-2008: 8.35% Estimated annual export growth for treated firms in treatment year: 8.35%*1.667= 13.9% Average exports per firm in 2004: TND 2’308K Estimated treated-firm exports in treatment year: TND 2’308K *1.139 = TND 2’629K Estimated treated-firm exports in treatment year: TND 2’308K *1.083 = TND 2’501K Difference attributable to treatment: TND 128.5K Treatment cost Average grant amount disbursed per Famex beneficiary: TND 21.7K Total cost (matching grant + firm own expense) : TND 2*21.7K = TND 43.4K Return based on impact effect On grant: TND 128.5k additional exports for 21.7k TND (6 for 1) On total investment: TND 128.5k for 43.4k TND (3 for 1) Is exports the right metric? Value added? Profits?

  20. Special economic zones • Spreading all over the world • By 2006, 130 countries had one, 3’500 around the world • Motivations • Short-cut reforms • Aggomeration economies • Visibility • Well known successes • Masan • Penang • Shenzen • Mauritius • But many other less successful—most of Africa’s

  21. Special economic zones, the silver bullet?

  22. The tangiers EPZ and automobile-sector FDI bla

  23. SEZs: backward linkages Some of the most successful ones (Vietnam, Bangladesh, Lesotho before 2005) have the weakest backward linkages

  24. SEZs: good jobs? Differential between SEZ average wage and economy-wide minimum wage, in percent

  25. SEZs: Local hiring

  26. Special economic zones: Incentives for foreign investors

  27. Fiscal incentives: The case of Antigua In 2003, Antigua extended the tax holiday for hotels from 5 years to 25 All Eastern Caribbeans share similar institutions and business climate Source: World Bank (2012), Tax burden and incentives in Gabon, p. 29

  28. Corporate taxation: Good news… Corporate income taxes / GDP, 1996-2007 Source: Abbas, Ali; A. Klemm, S. Bedi and J. Park (2012), “A Partial Race to the Bottom: Corporate tax Developments in Emerging and Developing Countries; IMF working paper WP/12/28

  29. … Masking a race to the bottom Effective average tax rates, 1996-2007 Effective marginal tax rates, 1996-2007 Source: Abbas, Ali; A. Klemm, S. Bedi and J. Park (2012), “A Partial Race to the Bottom: Corporate tax Developments in Emerging and Developing Countries; IMF working paper WP/12/28

  30. Customs duties losses to exemptions In Gabon, duty and tax exemptions are generously granted to foreign investors. The result: Reduced revenue for the Treasury Losses due to special regimes, in percent of potential tax revenue Source: World Bank (2012), Tax burden and incentives in Gabon, p. 29

  31. Pattern of tax reforms suggests race to the bottom rather than rationalisation What you want: lower tax rates, less generous tax breaks What you see: lower tax rates, more generous tax breaks Source: Abbas, Ali; A. Klemm, S. Bedi and J. Park (2012), “A Partial Race to the Bottom: Corporate tax Developments in Emerging and Developing Countries; IMF working paper WP/12/28

  32. A case study: The elimination of investment incentives in India Source: James, Sebastian, 2007, “The Effect of Tax Rates on Declared Income: An Analysis of Indian Taxpayer Response to Changes in Income Tax Rates,” Ph.D. diss., Harvard University, quoted in James (2009)

  33. Prima-facie evidence from large tax reforms Source: Abbas, Ali; A. Klemm, S. Bedi and J. Park (2012), “A Partial Race to the Bottom: Corporate tax Developments in Emerging and Developing Countries; IMF working paper WP/12/28

  34. The effect of tax incentives on FDI Regression line for bad-investment climate countries Source: James, Sebastian, 2007, “The Effect of Tax Rates on Declared Income: An Analysis of Indian Taxpayer Response to Changes in Income Tax Rates,” Ph.D. diss., Harvard University, quoted in James (2009)

  35. Econometric evidence from a panel of 47 countries (lagged) Source: Abbas, Ali; A. Klemm, S. Bedi and J. Park (2012), “A Partial Race to the Bottom: Corporate tax Developments in Emerging and Developing Countries; IMF working paper WP/12/28

  36. Supply-side constraints: Human-capital accumulation • Insufficient investment in education shows up through international comparison • Morocco has been investing • But the world has been moving faster • Worse: the provision of education is highly inefficient

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