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The Energy-Bias of North–South Technology Spillovers: A Global, Bilateral, Bisectoral Trade Analysis

Abstract

We examine variations in the South–North ratios (emerging vs. industrialized countries) of energy and labor intensities driven by imports. We use the novel World input-output database that provides bilateral and bisectoral data for 40 countries and 35 sectors for 1995–2009. We find South–North convergence of energy and labor intensities, an energy bias of import-driven convergence and no robust difference between imports of intermediate and investment goods. Accordingly, trade helps emerging economies follow a ‘green growth’ path, and trade-related policies can enhance this path. However, the effects are economically small and require a long time horizon to become effective. Trade-related policies can become much more effective in selected countries and sectors: China attenuates labor intensity via imports of intermediate goods above average. Brazil reduces energy intensity via imports of intermediate and investment goods above average. Production of machinery as an importing sector in emerging countries can immoderately benefit from trade-related reductions in factor intensities. Electrical equipment as a traded good particularly decreases energy intensity. Machinery particularly dilutes labor intensity. Our main results are statistically highly significant and robust across specifications.

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Fig. 1
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Notes

  1. 1.

    http://stats.oecd.org/Index.aspx?QueryId=18063.

  2. 2.

    In the Melitz (2003) model, trade liberalization induces exit of low-productivity firms and and an expansion of the market share and the profits of high-productivity firms engaged in exporting. This raises overall productivity and welfare.

  3. 3.

    http://www.wiod.org/database/.

  4. 4.

    1. Australia, 2. Austria, 3. Belgium, 4. Canada, 5. Cyprus, 6. Czech Republic, 7. Denmark, 8. Estonia, 9. Finland, 10. France, 11. Germany, 12. Greece, 13. Hungary, 14. Ireland, 15. Italy, 16. Japan, 17. Korea, 18. Latvia, 19. Lithuania, 20. Luxembourg, 21. Malta, 22. Netherlands, 23. Poland, 24. Portugal, 25. Slovak Republic, 26. Slovenia, 27. Spain, 28. Sweden, 29. Turkey, 30. United Kingdom, 31. United States of America.

  5. 5.

    1. Brazil, 2. Bulgaria, 3. China, 4. India, 5. Indonesia, 6. Mexico, 7. Romania, 8. Russia, 9. Taiwan.

  6. 6.

    1. Agriculture, Hunting, Forestry and Fishing, 2. Mining and Quarrying, 3. Food, Beverages and Tobacco, 4. Textiles and Textile Products, 5. Leather, Leather and Footwear, 6. Wood and Products of Wood and Cork, 7. Pulp, Paper, Printing and Publishing, 8. Coke, Refined Petroleum and Nuclear Fuel, 9. Chemicals and Chemical Products, 10. Rubber and Plastics, 11. Other Non-Metallic Minerals, 12. Basic Metals and Fabricated Metal, 13. Machinery, NEC, 14. Electrical and Optical Equipment, 15. Transport Equipment, 16. Manufacturing, NEC, Recycling, 17. Electricity, Gas and Water Supply, 18. Construction, 19. Sale, Maintenance and Repair of Motor Vehicles and Motorcycles, Retail Sale of Fuel, 20. Wholesale Trade and Commission Trade, Except of Motor Vehicles and Motorcycles, 21. Retail Trade, Except of Motor Vehicles and Motorcycles, Repair of Household Goods, 22. Hotels and Restaurants, 23. Inland Transport, 24. Water Transport, 25. Air Transport, 26. Other Supporting and Auxiliary Transport Activities, Activities of Travel Agencies, 27. Post and Telecommunications, 28. Financial Intermediation, 29. Real Estate Activities, 30. Renting of M&E and Other Business Activities, 31. Public Admin and Defense, Compulsory Social Security, 32. Education, 33. Health and Social Work, 34. Other Community, Social and Personal Services, 35. Private Households with Employed Persons.

  7. 7.

    1. Food, Beverages and Tobacco, 2. Textiles and Textile Products, 3. Leather, Leather and Footwear, 4. Wood and Products of Wood and Cork, 5. Pulp, Paper, Paper, Printing and Publishing, 6. Coke, Refined Petroleum and Nuclear Fuel, 7. Chemicals and Chemical Products, 8. Rubber and Plastics, 9. Other Non-Metallic Minerals, 10. Basic Metals and Fabricated Metal, 11. Machinery, NEC, 12. Electrical and Optical Equipment, 13. Transport Equipment, 14. Manufacturing, NEC, Recycling.

  8. 8.

    The investment good adds to the recipient economy-wide capital stock used for production in any sector of the recipient country.

  9. 9.

    High-skilled labor means first and second stage of tertiary education (1997 ISCED levels 5 and 6).

  10. 10.

    The sum of OECD energy use divided by the sum of OECD GDP (gross domestic product)). The same for non-OECD.

  11. 11.

    The value of trade from OECD to non-OECD divided by non-OECD GDP.

  12. 12.

    The high maximum of manufacturing energy intensities on a sectoral level comes from ‘Inland Transport’ in Russia. While Russia’s energy intensity is in general about 2.5–3 times higher than that of China or India, the energy intensity in this particular sector is even higher.

  13. 13.

    http://stats.oecd.org/Index.aspx?DataSetCode=ANBERD2011_REV3.

  14. 14.

    1. Agriculture, Hunting, Forestry and Fishing, 2. Mining and Quarrying, 3. Food, Beverages and Tobacco, 4. Textiles and Textile Products, 5. Leather, Leather and Footwear, 6. Wood and Products of Wood and Cork, 7. Pulp, Paper, Printing and Publishing, 8. Coke, Refined Petroleum and Nuclear Fuel, 9. Chemicals and Chemical Products, 10. Rubber and Plastics, 11. Other Non-Metallic Minerals, 12. Basic Metals and Fabricated Metal, 13. Machinery, NEC, 14. Electrical and Optical Equipment, 15. Transport Equipment, 16. Manufacturing, NEC, Recycling, 17. Electricity, Gas and Water Supply, 18. Construction, 19. Hotels and Restaurants, 20. Financial Intermediation, 21. Other Community, Social and Personal Services.

  15. 15.

    1. Australia, 2. Austria, 3. Belgium, 4. Canada, 5. Czech Republic, 6. Germany, 7. Spain, 8. Estonia, 9. Finland, 10. France, 11. Great Britain, 12. Greece, 13. Hungary, 14. Ireland, 15. Italy, 16. Japan, 17. Korea, 18. Netherlands, 19. Poland, 20. Portugal, 21. Slovak Republic, 22. Slovenia, 23. Turkey, 24. United States.

  16. 16.

    Due to missing data, Romania is left out in the energy price sample and in the robustness check regression based on that.

  17. 17.

    As we will see in the dynamic estimations in the robustness check, the estimated value of \(\beta _0\) is only slightly below one.

  18. 18.

    We do not apply the dynamic model because of the caveats sketched above.

  19. 19.

    We also check the twofold interaction of the R&D intensity with the investment good trade flow, yet without finding a significant impact.

  20. 20.

    We show this by running the reduced sample R&D regression without R&D expenditures as a regressor for comparison.

  21. 21.

    The average annual growth rate of energy intensity in OECD between 1995 and 2009 is \(-\)2 %, in non-OECD it is \(-\)3 %. The average annual growth rate of labor intensity in OECD is also \(-\)2 %, in non-OECD it is \(-\)5 %.

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Acknowledgments

We thank two anonymous reviewers for their very helpful comments. We also thank Simon Koesler, Michael Schymura, Francois Laisney, Andreas Löschel, Peter Nunnenkamp and Holger Görg for valuable support and comments. Funding from the German Federal Ministry of Education and Research (BMBF) within the Call ‘Ökonomie des Klimawandels’ (funding code 01LA1105B: Climate Policy and the Growth Pattern of Nations—CliPoN) is gratefully acknowledged.

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Correspondence to Michael Hübler.

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Hübler, M., Glas, A. The Energy-Bias of North–South Technology Spillovers: A Global, Bilateral, Bisectoral Trade Analysis. Environ Resource Econ 58, 59–89 (2014). https://doi.org/10.1007/s10640-013-9690-7

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Keywords

  • Energy intensity
  • Labor intensity
  • Trade
  • Technology diffusion
  • Convergence
  • Emerging countries

JEL Classifications

  • C23
  • F18
  • F21
  • O13
  • O33
  • O47
  • Q43