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Location factors for multinationals: Which role for the skill distribution of employment?

Location factors for multinationals: Which role for the skill distribution of employment?. Elif KÖKSAL-OUDOT. Université Paris 1 Panthéon-Sorbonne CES-MATISSE ekoksal@wanadoo.fr. OECD – Directorate for Science, Technology and Industry elif.koksal-oudot@oecd.org.

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Location factors for multinationals: Which role for the skill distribution of employment?

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  1. Location factors for multinationals: Which role for the skill distribution of employment? Elif KÖKSAL-OUDOT Université Paris 1 Panthéon-Sorbonne CES-MATISSE ekoksal@wanadoo.fr OECD – Directorate for Science, Technology and Industry elif.koksal-oudot@oecd.org

  2. 1. Introduction1.1. Topics and purposes • Importance of human capital for innovation and economic growth since Becker (1964). • Many endogenous growth contributions (Lucas 1988, Romer 1990, Aghion-Howitt (1992) => education as a key determinant

  3. 1.1. Topics and purposes • However assessing skills goes beyond education => challenge • Lack of internationally comparable data on labour quality • => 1st objective: Assessing the labour force composition by skills and by industry in OECD countries

  4. 1.1. Topics and purposes • Globalisation : FDI flows into and from OECD countries • Especially, FDI in the high technology sectors and internationalisation of R&D • Determinants of location decisions of multinationals: what role for the skill composition of employment of the host country? => 2st objective

  5. 1.2. Implications • Creating a new database: Skills by industry • Adding a “skill” dimension to the currently available data at industry level (extending the STructural ANalysis (STAN) Database) • Comparing the two skill proxies • Occupation and education • Analysing impact of skills on FDI location decisions

  6. 1.3. Outline 2. Data and descriptive results 3. Empirical estimations 4. Conclusion and further research agenda

  7. 2. Data & Descriptive Statistics • OECD Skills by Industry (ANSKILL) database • OECD Activities of Foreign Affiliates (AFA) Database • OECD Foreign Affiliates’ Trade in Services (FATS) Database • OECD STAN Database for Structural Analysis

  8. 2.1. ANSKILL • Two proxies for skills:

  9. 2.2. AFA and FATS • AFA : Manufacturing sectors - Highly aggregated level of detail for industries • 16 variables (on production, employment, employee compensation, investment, R&D…) • FATS : Service sectors • More recent (since 1995), OECD – Eurostat joint questionnaire • Very detailed breakdown • Less variables (mainly on turnover, value added, employment, exports and imports)

  10. 2.3. STAN • Main OECD database for industry-level time-series data • Important country (32 member countries) and time coverage (since 1970’s). • Many variables on production, value added employment, labour costs, exports, imports…)

  11. 2.2. Descriptive statisticsHigh skilled workers, occupation definition ,1998 and 2008 As a percentage of all employees Source: OECD, ANSKILL Database, September 2011.

  12. High skilled workers, education definition, 1998 and 2008As a percentage of all employees Source: OECD, ANSKILL Database, September 2011.

  13. Comparative importance of occupation and educational attainment in skill assessment across countries

  14. Employees in high-skill occupations as a percentage of those with at least a university degree, 2009 Source: OECD (2010), Measuring Innovation: A New Perspective.

  15. Growth of high skilled workers, EU, 1998-2008 Source: OECD, ANSKILL Database, April 2010.

  16. Growth of high skilled workers, United States, 1997-2007 Source: OECD, ANSKILL Database, April 2010.

  17. Growth of high skilled workers, Canada, 1997-2007 Source: OECD, ANSKILL Database, April 2010.

  18. Growth of high skilled workers, Japan, 2003-2008 Source: OECD, ANSKILL Database, April 2010.

  19. Growth of high skilled workers, EU, 1998-2008 Source: OECD, ANSKILL Database, April 2010.

  20. Growth of high skilled workers, United States, 1997-2007 Source: OECD, ANSKILL Database, April 2010.

  21. Growth of high skilled workers, Canada, 1997-2007 Source: OECD, ANSKILL Database, April 2010.

  22. Growth of high skilled workers, Japan, 2003-2008 Source: OECD, ANSKILL Database, April 2010.

  23. FDI inflows to OECD countries, as a % of GDP (2005-2008 average) Source: OECD Economic Globalisation Indicators 2010 based onOECD, International Direct Investment and Annual National Accounts databases, June 2009.

  24. Share of foreign-controlled affiliates in manuf. turnover and employment, 2007 Source: OECD Economic Globalisation Indicators 2010 based onOECD, International Direct Investment and Annual National Accounts databases, June 2009.

  25. Growth of foreign-controlled affiliates and national firms’ share of manufacturing VA (1999 and 2006) Source: OECD, AFA database, December 2009.

  26. Share of foreign-controlled affiliates in high-technology manufacturing turnover, 2007 Source: OECD, AFA database, September 2011.

  27. Share of foreign affiliates in the employment of the services and manufacturing sectors, 2006 Source: OECD, AFA and FATS databases, December 2009.

  28. Labour productivity of foreign affiliates in manufacturing and services, 2006 Source: OECD, AFA and FATS databases, December 2009.

  29. 3. Empirical estimation

  30. 3.1. Specification • log NOEi,c,t = α0 + α1.logHSi,c,t + α2.logMSi,c,t + α3log(X+I) / GDP)c,t + α4.log(FDI /GDP)c,t + α5.log(VAf / VA)i,c,t + α6.log(WAGEf / WAGE)i,c,t + α7.log(Coop / POP)c,t + i,c,t

  31. 3.1. Specification • (2) logVAf / EMPi,c,t = α0 + α1.logHSi,c,t + α2.logMSi,c,t + α3log(NOE)i,c,t + α4.log(FDI / GDP)c,t + α5.log(WAGEf / WAGE)i,c,t + α6.log(RD)i,c,t + α7.log(Coop / POP)c,t + i,c,t

  32. Log (NOE) estimation results with the occupation proxy 3.2. Results

  33. Log (NOE) estimation results with the education proxy 3.2. Results

  34. Log (Vaf/EMP) estimation results with the occupation proxy 3.2. Results

  35. Log (Vaf/EMP) estimation results with the education proxy 3.2. Results

  36. 4. Conclusion and further research agenda4.1. Conclusion • Strong relationship between the high skilled share of employment in the host country and the presence of multinational firms • Both of the proxies => positive and significant while explaining labour productivity of foreign affiliates • Occupations should be taken into account, together with the educational attainment for skill assessment

  37. 4.2. For further research agenda • Completing data collection on industry x education matrices and extending the analysis to other OECD countries • Robustness checks through logistic panel estimations • Focus on the high technology industries and knowledge intensive business services in the econometrical analysis

  38. Thank you for your attention! For comments and suggestions: elif.koksal-oudot@oecd.org ekoksal@wanadoo.fr

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