Skip to main content

Advertisement

SpringerLink
Log in

The role of R&D and input trade in productivity growth: innovation and technology spillovers

  • Published:
The Journal of Technology Transfer Aims and scope Submit manuscript

Abstract

Productivity improvements generally are driven by technology innovation and its spillovers. This study explores the role of R&D investment and intermediate input trade in productivity growth using country-industry-level data for 25 advanced and emerging economies. This paper confirms that R&D investment and intermediate input import/export (both intra- and inter-industry) with technologically advanced economies play important roles in productivity growth in non-frontier countries. We further find that the productivity gains of technology spillovers via input trade channels are likely larger for countries/industries where technology converges to the frontier. These findings imply that the recent slowdown in R&D investment and intermediate input trade in some advanced economies may contribute to declining productivity growth. The potential productivity improvements from R&D investment and free trade as well as the importance of domestic capacity in facilitating technology spillovers should be recognized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. For instance, Korea and China face their own challenges with the rebalancing of the economy from manufacturing to services.

  2. See, for example, Aghion and Jaravel (2015) for the literature review on the issues of recent research on the role of technology (knowledge) spillovers.

  3. Bloom et al. (2013), using panel data on U.S. firms, find that the social returns from R&D are at least twice as high as the private returns by separately identifying two countervailing spillovers from R&D: positive effects from technology spillovers and negative business stealing effects from product market rivals.

  4. In this regard, the recent slowdown in trade openness likely leads to the weakening of trade-related productivity growth (Constantinescu et al. 2016).

  5. As shown in many studies, vertical specialization across countries is an important, growing feature of the world economy (Hummels et al. 2001; Hanson et al. 2005), and intermediate inputs account for roughly 60 percent of international trade (Johnson 2014).

  6. Including fixed effects for country, industry, and year, as in many studies, can partially (not fully) address bias from omitted variables by capturing the role of the other factor in productivity growth—which likely to be country, industry, and year-specific.

  7. The earlier literature mostly analyzes R&D spillovers through import in intermediate inputs. There is an exception such as Poetzsch (2017) who considers R&D spillovers through both intermediate input usage and supply.

  8. Labor productivity can also be measured in per persons engaged. The estimation results on labor productivity per persons (Table 4) are qualitatively similar to the baseline results on labor productivity per hours worked (Table 1).

  9. 22 advanced and 3 emerging economies, based on the IMF country classification, are included in our sample countries. We also analyze broader set of industries including 4 non-manufacturing indusries [i.e., Agriculture, hunting, forestry and fishing (AtB); Mining and quarrying (C); Electricity, gas and water supply (E); and Construction (F)] in our econometric analysis for a robustness check. However, industries in the service sector are not included as these industries usually do not involve much R&D activities and intermediate input trade which are our main focus of this paper. Moreover, productivity in services is extremely difficult to compare across countries due to measurement issues and many other country-specific considerations.

  10. PPP exchange rates for traded sectors from Inklaar and Diewert (2016) are used for the industries in Manufacturing; Agriculture, hunting, forestry and fishing (AtB); and Mining and quarrying (C) while those for non-traded sectors are used for the industries in Electricity, gas and water supply (E); and Construction (F) (see Table 7 for detailed industry classifications).

  11. There is also substantial divergence in productivity levels across industries within manufacturing.

  12. See Table 9 in "Appendix" for the productivity levels of the whole sample countries.

  13. We chose the U.S. as the frontier country in the econometric analysis, although the U.S. may not be the technology frontier in all industries, as the country has been the most important player in the global trade (especially in intermediate input trade) which is the main focus of this paper.

  14. Imported inputs are scaled by the total inputs used in that sector including both imported from foreign markets and supplied by domestic firms, while exported inputs are divided by the total inputs produced in that sector including both exported to foreign markets and provided to domestic firms.

  15. Introducing different industry and year-specific fixed effects for each country is expected to capture other potentially important domestic factors to determine productivity growth (e.g., human capital, institutions).

  16. By this normalization, within the variation encountered in the sample, the relationship between labor productivity growth and these variables is broadly proportional.

  17. The terminology of ‘advantages of backwardness’ was first used in Gerschenkron (1962) and adopted in many growth literature afterwards to describe the convergence of economic growth.

  18. As noted by Abramovitz (1986); Benhabib and Spiegel (1994), domestic factors including both technology gap (relative backwardness) and absorptive capacity (e.g., human capital, institutions) can be important factors for technology spillovers but proxies for human capital such as education and skill levels are not included in our specification because the reliable industry-level data are not available.

  19. R&D decisions can be also endogenous as more R&D can be invested in more productive industries. However, we focus on the issue of endogeneity between input trade variables and productivity as it is not easy to address the endogeneity in R&D decisions econometrically at the industry level. Note that Bloom et al. (2013) address this issue using the firm-level data.

  20. We use a bilateral trade with the U.S. instead of overall trade with all other countries to reduce causality concerns and to identify the potential technology spillover channels from the technology frontier to non-frontier countries.

  21. This method is widely adopted in the recent literature to address the endogeneity issues between trade and economic growth.

  22. Estimation results are not presented in the paper but they can be provided upon request.

  23. However, it is notable that the measurement of intra- and inter-industry input trade openness can critically depend on industry classification.

References

  • Abramovitz, M. (1986). Catching up, forging ahead, and falling behind. Journal of Economic History, 46(2), 385–406.

    Article  Google Scholar 

  • Acemoglu, D., Aghion, P., & Zilibotti, F. (2006). Distance to frontier, selection, and economic growth. Journal of the European Economic Association, 4(1), 37–74.

    Article  Google Scholar 

  • Aghion, P., Harris, C., Howitt, P., & Vickers, J. (2001). Competition, imitation and growth with step-by-step innovation. The Review of Economic Studies, 68(3), 467–492.

    Article  Google Scholar 

  • Aghion, P., Bloom, N., Blundell, R., Griffith, R., & Howitt, P. (2005a). Competition and innovation: An inverted-U relationship. The Quarterly Journal of Economics, 120(2), 701–728.

    Google Scholar 

  • Aghion, P., Howitt, P., & Mayer-Foulkes, D. (2005b). The effect of financial development on convergence: Theory and evidence. The Quarterly Journal of Economics, 120(1), 173–222.

    Google Scholar 

  • Aghion, P., & Jaravel, X. (2015). Knowledge spillovers, innovation and growth. The Economic Journal, 125(583), 533–573.

    Article  Google Scholar 

  • Autor, D. H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. The American Economic Review, 103(6), 2121–2168.

    Article  Google Scholar 

  • Badinger, H., & Egger, P. (2016). Productivity spillovers across countries and industries: New evidence from OECD countries. Oxford Bulletin of Economics and Statistics, 78(4), 501–521.

    Article  Google Scholar 

  • Balassa, B. (1978). Exports and economic growth: Further evidence. Journal of Development Economics, 5(2), 181–189.

    Article  Google Scholar 

  • Barro, R., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223–251.

    Article  Google Scholar 

  • Benhabib, J., Perla, J., & Tonetti, C. (2013). Catch-up and fall-back through innovation and imitation. Journal of Economic Growth, 19(1), 1–35.

    Article  Google Scholar 

  • Benhabib, J., & Spiegel, M. M. (1994). The role of human capital in economic development evidence from aggregate cross-country data. Journal of Monetary Economics, 34(2), 143–173.

    Article  Google Scholar 

  • Bernard, A., & Jones, C. (1996). Productivity across industries and countries: Time series theory and evidence. The Review of Economics and Statistics, 78(1), 135–146.

    Article  Google Scholar 

  • Bloom, N., Schankerman, M., & Van Reenen, J. (2013). Identifying technology spillovers and product market rivalry. Econometrica, 81(4), 1347–1393.

    Article  Google Scholar 

  • Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European Economic Review, 39(5), 859–887.

    Article  Google Scholar 

  • Constantinescu, C., Mattoo, A., & Ruta, M. (2016). Does the global trade slowdown matter? Journal of Policy Modeling, 38, 711–722.

    Article  Google Scholar 

  • De Loecker, J. (2013). Detecting learning by exporting. The American Economic Journal: Microeconomics, 5(3), 1–21.

    Google Scholar 

  • Duarte, M., & Restuccia, D. (2010). The role of the structural transformation in aggregate productivity. The Quarterly Journal of Economics, 125(1), 129–173.

    Article  Google Scholar 

  • Gerschenkron, A. (1962). Economic backwardness in historical perspective: A book of essays. Cambridge, MA: Belknap Press of Harvard University Press.

    Google Scholar 

  • Griffith, R., Redding, S., & Van Reenen, J. (2004). Mapping the two faces of R&D: Productivity growth in a panel of OECD industries. The Review of Economics and Statistics, 86(4), 883–895.

    Article  Google Scholar 

  • Grossman, G. M., & Helpman, E. (1991a). Quality ladders in the theory of growth. The Review of Economic Studies, 58(1), 43–61.

    Article  Google Scholar 

  • Grossman, G. M., & Helpman, E. (1991b). Innovation and growth in the global economy. Cambridge, MA: MIT Press.

    Google Scholar 

  • Halpern, L., Koren, M., & Szeidl, A. (2015). Imported inputs and productivity. The American Economic Review, 105(12), 3660–3703.

    Article  Google Scholar 

  • Hanson, G. H., Mataloni, R. J, Jr., & Slaughter, M. J. (2005). Vertical production networks in multinational firms. The Review of Economics and Statistics, 87(4), 664–678.

    Article  Google Scholar 

  • Helpman, E., & Krugman, P. R. (1985). Market structure and foreign trade: Increasing returns, imperfect competition, and the international economy. Cambridge: MIT press.

    Google Scholar 

  • Howitt, P. (2000). Endogenous growth and cross-country income differences. The American Economic Review, 90(4), 829–846.

    Article  Google Scholar 

  • Howitt, P., & Mayer-foulkes, D. (2005). R&D, implementation and stagnation: A Schumpeterian theory of convergence clubs. Journal of Money, Credit and Banking, 37(1), 147–177.

    Article  Google Scholar 

  • Hummels, D., Ishii, J., & Yi, K. M. (2001). The nature and growth of vertical specialization in world trade. Journal of International Economics, 54(1), 75–96.

    Article  Google Scholar 

  • Inklaar, R., & Diewert, W. E. (2016). Measuring industry productivity and cross-country convergence. Journal of Econometrics, 191(2), 426–433.

    Article  Google Scholar 

  • Inklaar, R., Timmer, M., & Van Ark, B. (2008). Market services productivity across Europe and the US. Economic Policy, 23(53), 139–194.

    Article  Google Scholar 

  • Johnson, R. C. (2014). Trade in intermediate inputs and business cycle comovement. The American Economic Journal: Macroeconomics, 6(4), 39–83.

    Google Scholar 

  • Kasahara, H., & Rodrigue, J. (2008). Does the use of imported intermediates increase productivity? Plant-level evidence. Journal of Development Economics, 87(1), 106–118.

    Article  Google Scholar 

  • Keller, W. (2002). Trade and the transmission of technology. Journal of Economic Growth, 7(1), 5–24.

    Article  Google Scholar 

  • Keller, W. (2010). International trade, foreign direct investment, and technology spillovers. Handbook of the Economics of Innovation, 2, 793–829.

    Article  Google Scholar 

  • Nishioka, S., & Ripoll, M. (2012). Productivity, trade and the R&D content of intermediate inputs. European Economic Review, 56(8), 1573–1592.

    Article  Google Scholar 

  • O’Mahony, M., & Timmer, M. (2009). Output, input and productivity measures at the industry level: The EU KLEMS database. The Economic Journal, 119(538), F374–F403.

    Article  Google Scholar 

  • Poetzsch, C. (2017). Technology transfer on a two-way street: R&D spillovers through intermediate input usage and supply. Review of World Economics, 153(4), 735–751.

    Article  Google Scholar 

  • Samaniego, R. M., & Sun, J. Y. (2016). Productivity growth and structural transformation. Review of Economic Dynamics, 21, 266–285.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. International Monetary Fund and Bank of Korea, 700 19th St NW, Washington, DC, 20431, USA

    Dongyeol Lee

Authors
  1. Dongyeol Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dongyeol Lee.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

I am grateful to JaeBin Ahn, Thomas Helbling, Dirk Muir, Ryota Nakatani, and seminar participants at the International Monetary Fund, and Midwest Economics Association Annual Conference for their comments and suggestions. I am also particularly thankful to two anonymous referees for their thoughtful comments and suggestions. The views expressed in this paper are those of the author and do not necessarily represent those of the International Monetary Fund or Bank of Korea.

Appendix

Appendix

See Tables 6, 7, 8 and 9.

Table 6 Data description and source
Full size table
Table 7 List of industries
Full size table
Table 8 Labor productivity: growth
Full size table
Table 9 Labor productivity: level
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, D. The role of R&D and input trade in productivity growth: innovation and technology spillovers. J Technol Transf 45, 908–928 (2020). https://doi.org/10.1007/s10961-019-09717-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10961-019-09717-0

Keywords

JEL Classification:

Search

Navigation