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TECHNOLOGY SHOCKS AND BUSINESS CYCLES IN INDIA

Published online by Cambridge University Press:  26 July 2017

Shesadri Banerjee
Affiliation:
Centre for Studies in Social Sciences, Calcutta
Parantap Basu*
Affiliation:
Durham University, UK
*
Address correspondence to: Parantap Basu, Durham University Business School, Durham University, Mill Hill Lane, DH1 3LB, Durham, UK; e-mail: [email protected].

Abstract

In this paper, we develop a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model to understand the relative importance of two key technology shocks, Hicks neutral total factor productivity (TFP) shock and investment specific technology (IST) shock for an emerging market economy like India. In addition to these two shocks, our model includes three demand side shocks such as fiscal spending, home interest rate, and foreign interest rate. Using a Bayesian approach, we estimate our DSGE model with Indian annual data for key macroeconomic variables over the period of 1971–2010, and for subsamples of pre-liberalization (1971–1990) and post-liberalization (1991–2010) periods. Our study reveals three main results. First, output correlates positively with TFP, but negatively with IST. Second, TFP and IST shocks are the first and the second most important contributors to aggregate fluctuations in India. In contrast, the demand side disturbances play a limited role. Third, although TFP plays a major role in determining aggregate fluctuations, its importance vis-à-vis IST has declined during the post liberalization era. We find that structural shifts of nominal friction and relative home bias for consumption to investment in the post-liberalization period can account for the rising importance of the IST shocks in India.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

This paper is an extension of an earlier working paper (WP 109) available on the website of National Council of Applied Economic Research. We are grateful to the Canadian International Development Research Centre for sponsoring this project generously. We are grateful to two referees for very insightful comments which significantly enriched this paper. Thanks are also due to the participants of the International Growth and Development Conference in the Indian Statistical Institute, New Delhi in 2015 and the AIEFS participants at the ASSA conference in Chicago in 2017 for useful comments. The first author also gratefully acknowledges the feedback from the internal workshop at the Centre for Studies in Social Sciences, Calcutta. Yongdae Lee and Ajaya Sahu are gratefully acknowledged for very competent research assistance. The usual disclaimer applies.

References

REFERENCES

Abel, A. (1990) Asset prices under habit formation and catching up with the Joneses. American Economic Review 80, 3842.Google Scholar
Aguiar, M. and Gopinath, G. (2007) Emerging market business cycles: The cycle is the trend. Journal of Political Economy 115, 69102.Google Scholar
Anand, R., Peiris, S., and Saxegaard, M. (2010) An Estimated Model with Macrofinancial Linkages for India. IMF working paper series WP/10/21.Google Scholar
Araujo, E. (2012) Investment-specific shocks and real business cycles in emerging economies: Evidence from Brazil. Economic Modelling 29 (3), 671678.Google Scholar
Backus, D., Kehoe, P., and Kydland, F. (1994) Dynamics of the trade balance and the terms of trade: The J-curve. American Economic Review 84, 84103.Google Scholar
Banerjee, S. and Basu, P. (2015) A Dynamic Stochastic General Equilibrium Model for India. NCAER working paper 109, IDRC-TTI grant.Google Scholar
Banerjee, S. and Basu, P. (2016) Indian economy during the era of quantitative easing: A dynamic stochastic general equilibrium perspective. In Ghate, Chetan and Kletzer, Ken (eds.), Monetary Policy in India: A Modern Macroeconomic Perspective. New Delhi: Springer.Google Scholar
Banga, R. and Das, A. (eds.) (2012) Twenty Years of India's Liberalization. New York, NY: Centre for WTO Studies, United Nations New York and Geneva.Google Scholar
Basu, P. and McLeod, D.. (1992) Terms of trade, and economic fluctuations in developing countries. Journal of Development Economics 37, 89110.Google Scholar
Basu, P. and Thoenissen, C. (2011) International business cycles and the relative price of investment. Canadian Journal of Economics 44 (2), 586606.Google Scholar
Basu, S., Fernald, J., and Kimball, M. (1999) Are Technology Improvements Contractionary? Mimeo.Google Scholar
Benigno, P. (2009) Price stability with imperfect financial integration. Journal of Money, Credit and Banking 41 (S1), 121149.Google Scholar
Bhattacharya, R. and Pattnaik, I. (2013) Credit Constraints, Productivity Shocks and Consumption Volatility in Emerging Economies. IMF working paper WP/13/120.Google Scholar
Brooks, P. and Gelman, A. (1998) General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7 (4), 434455.Google Scholar
Calvo, G. (1983) Staggered prices in a utility maximizing framework. Journal of Monetary Economics 12 (3), 383398.Google Scholar
Christiano, L. J., Eichenbaum, M., and Evans, C. L. (2005) Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113 (1), 145.Google Scholar
Cooley, T. F. and Prescott, E. C. (1995) Economic growth and business cycles. In Cooley, T. F. (ed.), Frontier in Business Cycle Research, pp. 138. Princeton, NJ: Princeton University Press.Google Scholar
Dey, J. (2017) The role of investment specific technology shocks in driving international business cycles: A Bayesian approach. Macroeconomic Dynamics 21 (3), 555598.Google Scholar
Fisher, J. D. M. (2006) The dynamic effect of neutral and investment-specific technology shocks. Journal of Political Economy 114 (3), 413451.Google Scholar
Francis, N. (2001) Sectoral Technology Shocks Revisited. Lehigh University. Mimeo.Google Scholar
Furlanetto, F. and Seneca, M. (2013) New perspectives on depriciation shocks as a source of business cycle fluctuations. Macroeconomic Dynamics 18 (6), 12091233.Google Scholar
Gabriel, V., Levine, P., Pearlman, J., and Yang, B. (2010) An Estimated DSGE Model of the Indian Economy. Working papers 11/95, National Institute of Public Finance and Policy.Google Scholar
Gali, J. (1999) Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89 (1), 249271.Google Scholar
Garcia-Cicco, J., Pancrazi, R., and Uribe, M. (2010) Real business cycles in emerging countries? American Economic Review 100 (5), 25102531.Google Scholar
Goyal, A. (2011) A general equilibrium open economy model for emerging markets: Monetary policy with a dualistic labor market. Economic Modelling 28 (3), 13921404.Google Scholar
Greenwood, J., Hercowitz, Z., and Krusell, P. (2000) The role of investment-specific technological change in the business cycle. European Economic Review 44 (1), 91115.Google Scholar
Greenwood, J., Hercowitz, Z., and Krusell, P. (1997) Long-run implications of investment-specific technological change. American Economic Review 87 (3), 342362.Google Scholar
Heathcote, J. and Perri, F. (2002) Financial autrarky and international business cycles. Journal of Monetary Economics 49, 601627.Google Scholar
Iskrev, N. (2010a) Evaluating the Strength of Identification in DSGE Models. An A Priori Approach. Working papers w201032, Banco de Portugal, Economics and Research Department.Google Scholar
Iskrev, N. (2010b) Local identification in DSGE models. Journal of Monetary Economics 57, 189202.Google Scholar
Iskrev, N. and Ratto, M. (2010a) Computational advances in analyzing identification of DSGE models. In Proceedings of the 6th DYNARE Conference, June 3-4, Gustavelund, Tuusula, Finland: Bank of Finland, DSGE-net and Dynare Project at CEPREMAP.Google Scholar
Iskrev, N. and Ratto, M. (2010b) Identification toolbox for DYNARE. In Proceedings of the 1st MONFISPOL Conference, London, 4-5 November. The London Metropolitan University and the European Research project (FP7-SSH) MONFISPOL.Google Scholar
Justiniano, A., Primiceri, G., and Tambalotti, A. (2011) Investment shocks and the relative price of investment. Review of Economic Dynamics 14 (1), 101121.Google Scholar
King, R. G. and Rebelo, S. T. (1999) Resuscitating real business cycles. In Taylor, J. B. and Woodford, M. (eds.), Handbook of Macroeconomics, 1st. ed., vol. 1, pp. 9271007. North Holland.Google Scholar
Kiley, M. T. (1997) Labor Productivity in U.S. Manufacturing: Does Sectoral Comovement Reflect Technology Shocks? Federal Reserve Board.Google Scholar
Kletzer, K. (2012) Financial friction and monetary policy transmission in India. In Ghate, Chetan (ed.), The Oxford Handbook of the Indian Economy. Oxford/New Delhi: Oxford University Press.Google Scholar
Kollmann, R. (2002) Monetary policy rules in the open economy: Effects on welfare and business cycles. Journal of Monetary Economics 49, 9891015.Google Scholar
Kydland, F. E. and Prescott, E. C. (1982) Time to build and aggregate fluctuations. Econometrica 50 (6), 13451370.Google Scholar
Levine, P. and Pearlman, J. (2011) Monetary and Fiscal Policy in a DSGE Model of India. Working papers 11/96, National Institute of Public Finance and Policy.Google Scholar
Mendoza, R. (1995) The terms of trade, the real exchange rate and economic fluctuations. International Economic Review 36 (1), 101135.Google Scholar
Mohanty, D. (2010) Measures of inflation in India: Issues and perspectives. Speech at the Conference of Indian Association for Research in National Income and Wealth (IARNIW), http://www.esocialsciences.org.Google Scholar
Mishra, P., Montiel, P., and Sengupta, R. (2016) Monetary transmission in developing countries: Evidence from India. In Ghate, Chetan and Kletzer, Ken (eds.), Monetary Policy in India: A Modern Macroeconomic Perspective. New Delhi: Springer.Google Scholar
Prescott, E. C. (1986) Theory ahead of business cycle measurement. Quarterly Review 10, 922.Google Scholar
Ravn, M. O. and Uhlig, H. (2002) On adjusting the Hodrick-Prescott filter for the frequency of observations. Review of Economics and Statistics 84 (2), 371376.Google Scholar
RBI (Reserve Bank of India) (2013) Handbook of Statistics of Indian Economy. Mumbai: Reserve Bank of India.Google Scholar
RBI (Reserve Bank of India) (2014) Report of the expert committee to revise and strengthen the monetary policy framework. Mumbai. Available at: https://rbidocs.rbi.org.in/rdocs/PublicationReport/Pdfs/ECOMRF210114_F.pdfGoogle Scholar
Shea, J. (1998) What do technology shocks do? In NBER Macroeconomics Annual, vol. 13, pp. 275322. Cambridge, MA: National Bureau of Economic Research, Inc.Google Scholar
Smets, F. and Wouters, R. (2007) Shocks and frictions in US business cycles: A Bayesian approach. American Economic Review 97 (3), 586606.Google Scholar
Thoenissen, C. (2011) Exchange rate dynamics, asset market structure, and the role of the trade elasticity. Macroeconomic Dynamics 15 (01), 119143.Google Scholar