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BIASED TECHNICAL CHANGE, INTERMEDIATE GOODS, AND TOTAL FACTOR PRODUCTIVITY

Published online by Cambridge University Press:  04 February 2011

Alessio Moro
Alessio Moro*
Affiliation:
University of Cagliari
*
Address correspondence to: Alessio Moro, Department of Economics, University of Cagliari, Viale Sant'Ignazio 17, 09123 Cagliari, Italy; e-mail: [email protected].
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Abstract

In this paper I show that the intensity at which intermediate goods are used in the production process affects aggregate total factor productivity (TFP). To do this, I construct an input–output model economy in which firms produce gross output by means of a production function in capital, labor, and intermediate goods. This production function is subject, together with the standard neutral technical change, to intermediates-biased technical change. Positive (negative) intermediates-biased technical change implies a decline (increase) in the elasticity of gross output with respect to intermediate goods. In equilibrium, this elasticity appears as an explicit part of TFP in the value added aggregate production function. In particular, when the elasticity of gross output with respect to intermediates increases, aggregate TFP declines. I use the model to quantify the impact of intermediates-biased technical change for measured TFP growth in Italy. The exercise shows that intermediates-biased technical change can account for the productivity slowdown observed in Italy from 1994 to 2004.

Keywords

Total Factor ProductivityGrowthBiased Technical ChangeIntermediate Goods
Type
Articles
Information
Macroeconomic Dynamics , Volume 16 , Issue 2 , April 2012 , pp. 184 - 203
Copyright
Copyright © Cambridge University Press 2011

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References

REFERENCES

Acemoglu, D. (1998) Why do new technologies complement skills? Directed technical change and wage inequality. Quarterly Journal of Economics 113, 1055–1089.CrossRefGoogle Scholar
Acemoglu, D. (2002) Technical change, inequality, and the labor market. Journal of Economic Literature 40, 7–72.CrossRefGoogle Scholar
Baldwin, R. and Robert-Nicoud, F. (2006) Offshoring and Globalisation: What Is New about the New Paradigm? Mimeo, Graduate Institute of International Studies, Geneva/London School of Economics, London.Google Scholar
Boldrin, M. and Levine, D.K. (2001) Growth cycles and market crashes. Journal of Economic Theory 96, 13–39.Google Scholar
Boldrin, M. and Levine, D.K. (2007) Quality Ladders, Competition and Endogenous Growth. Mimeo, Levine's Working Paper Archive.Google Scholar
Bruno, M. (1984) Raw materials, profits and the productivity slowdown. Quarterly Journal of Economics 99, 1–30.CrossRefGoogle Scholar
Bureau of Economic Analysis (2006) A Guide to the National Income and Product Accounts of the United States. http://www.bea.gov/bea/an/nipaguid.pdf.Google Scholar
Castro, R., Clementi, G.L., and MacDonald, G. (2006) Legal institutions, sectoral heterogeneity, and economic development. Review of Economic Studies 76, 529–561.CrossRefGoogle Scholar
Ciccone, A. (2002) Input chains and industrialization. Review of Economic Studies 69, 565–587.CrossRefGoogle Scholar
Gabaix, X. (2008) The Granular Origins of Aggregate Fluctuations. NBER Working Paper w15286.Google Scholar
Greenwood, J., Hercowitz, Z., and Krusell, P. (1997) Long-run implications of investment-specific technological change. American Economic Review 87, 342–362.Google Scholar
Greenwood, J. and Yorukoglu, M. (1997) 1974. Carnegie–Rochester Conference Series on Public Policy 46, 49–95.CrossRefGoogle Scholar
Grossman, G.M. and Rossi-Hansberg, E. (2008) Trading tasks: A simple theory of offshoring. American Economic Review 98, 1978–1997.CrossRefGoogle Scholar
Guner, N., Ventura, G., and Xu, Y. (2008) Macroeconomic implications of size dependent policies. Review of Economic Dynamics 11, 721–744.CrossRefGoogle Scholar
Herrendorf, B. and Teixeira, A. (2005) How barriers to international trade affect TFP. Review of Economic Dynamics 8, 866–876.CrossRefGoogle Scholar
Hornstein, A. and Krusell, P. (1996) Can technology improvements cause productivity slowdowns? NBER Macroeconomics Annual 11, 209–259.Google Scholar
Horvath, M. (2000) Sectoral shocks and aggregate fluctuations. Journal of Monetary Economics 45, 69–106.CrossRefGoogle Scholar
Hulten, C.R. (1978) Growth accounting with intermediate goods. Review of Economic Studies 45, 511–518.CrossRefGoogle Scholar
Jones, C.I. (2008) Intermediate Goods, Weak Links, and Superstars: A Theory of Economic Development. NBER Working Paper W13834.CrossRefGoogle Scholar
Jorgenson, D.W., Gollop, F.M., and Fraumeni, B.M. (1987) Productivity and U.S. Economic Growth. Cambridge, MA: Harvard University Press.Google Scholar
Lagos, R. (2006) A model of TFP. Review of Economic Studies 73, 983–1007.CrossRefGoogle Scholar
Long, J. and Plosser, C. (1983) Real business cycles. Journal of Political Economy 91, 39–69.Google Scholar
O'Mahony, M. and Timmer, M.P. (2009) Output, input and productivity measures at the industry level: The EU KLEMS database. Economic Journal 119, F374–F403.Google Scholar
Parente, S. and Prescott, E.C. (1999) Monopoly rights: A barrier to riches. American Economic Review 89, 1216–1233.Google Scholar
Restuccia, D. and Rogerson, R. (2008) Policy distortions and aggregate productivity with heterogeneous plants. Review of Economic Dynamics 11, 707–720.CrossRefGoogle Scholar
Young, A.T. (2004) Labor's share fluctuations, biased technical change, and the business cycle. Review of Economic Dynamics 7, 916–931.Google Scholar