Gortz, Christoph and John, Tsoukalas (2011): Learning, capital-embodied technology and aggregate fluctuations.
Download (390kB) | Preview
Business cycles in the U.S. and G-7 economies are asymmetric: recoveries and expansions tend to be long and gradual and busts tend to be short and sharp. Moreover, this type of asymmetry appears more pronounced in the last two cyclical episodes in the G-7. A large body of work views the last two cyclical U.S. episodes, namely, the``new economy" boom in the late 1990s, and the 2000s housing boom-bust as episodes where over-optimistic beliefs have played a significant role. These episodes have revived interest in expectations driven business cycles models. However, previous work in this area has not addressed the important asymmetry feature of business cycles. This paper takes a step towards addressing this limitation of expectations driven business cycle models. We propose a generalization of the Greenwood et al. (1988) model with vintage capital and learning about capital embodied productivity and show it can deliver fluctuations that are asymmetric as in the U.S. data. Learning, calibrated to match the procyclical forecast precision from the Survey of Professional Forecasters, is crucial for the model's ability to generate asymmetries. Forecast errors generated by the model are shown to: (a) amplify fluctuations, and (b) trigger recessions that mimic in magnitude, duration and depth the typical post WW II U.S. recession.
|Item Type:||MPRA Paper|
|Original Title:||Learning, capital-embodied technology and aggregate fluctuations|
|Keywords:||News shocks, expectations, growth asymmetry, Bayesian learning, business cycles|
|Subjects:||E - Macroeconomics and Monetary Economics > E2 - Macroeconomics: Consumption, Saving, Production, Employment, and Investment
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search; Learning; Information and Knowledge; Communication; Belief
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles
|Depositing User:||Christoph Görtz|
|Date Deposited:||16. Dec 2011 23:34|
|Last Modified:||12. Feb 2013 16:24|
Arrow, K. (1962). The economic imlications of learning by doing. Review of Economic Studies, 29(3):155–173.
Bahk, B.-H. and Gort, M. (1993). Decomposing learning by doing in new plants. Journal of Political Economy, 101(4):561–83.
Barro, R. and King, R. (1994). Time-separable preferences and intertemporal-substitution models of business cycles. Quarterly Journal of Economics, 99(4):817–839.
Basu, S., Fernald, J., Oulton, N., and Srinivasan, S. (2003). The case of the missing productivity growth: Or, does information technology explain why productivity accelarated in the United States but not the United Kingdom? NBER Macroeconomics Annual.
Beaudry, P. and Portier, F. (2004). An exploration into pigou’s theory of cycles. Journal of Monetary Economics, 51:1183–1216.
Beaudry, P. and Portier, F. (2007). When can changes in expectations cause business cycle fluctuations in neo-classical settings? Journal of Economic Theory, 135:458–477.
Beveridge, W. H. (1909). Unemployment: A Problem of Industry. Longmans Green, London.
Caplin, A. and Leahy, J. (1994). Business as usual, market crashes and wisdom after the crash. The American economic review, 84:548–565.
Christiano, L., Ilut, C., Motto, R., and Rostagno, M. (2008). Monetary policy and stock market boom-bust cycles. Working Paper Series 955, European Central Bank.
Clark, J. M. (1935). Strategic Factors in Business Cycles. National Bureau for Economic Research, New York.
Comin, D. (2009). On the integration of growth and business cycles. Empirica, 36(2):165–176.
Comin, D., Gertler, M., and Santacreu, A.-M. (2009). Technology innovation and diffusion as sources of output and asset price fluctuations. Working Paper Series 09-134, Harvard Business School.
Comin, D. and Mulani, S. (2009). A theory of growth and volatility at the aggregate and firm level. Journal of Monetary Economics, 56(8):1023 – 1042.
Croushore, D. (1993). Introducing: the survey of professional forecasters. Business Review, (Nov):3–15.
Den Haan, W. J. and Kaltenbrunner, G. (2009). Anticipated growth and business cycles in matching models. Journal of Monetary Economics, 56(3):309–327.
Eusepi, S. and Preston, B. (2011). Expectations, learning and business cycle fluctuations. American Economic Review, forthcoming.
Fisher, J. D. M. (2006). The dynamic effects of neutral and investment-specific technology shocks. Journal of Political Economy, 114(3):413–451.
Flodén, M. (2007). Vintage capital and expectations driven business cycles. Centre for Economic Policy Research discussion paper, (6113).
Greenwood, J., Hercowitz, Z., and Huffman, G. (1988). Investment, capacity utilization, and the real business cycle. The American Economic Review, 78:402–217.
Greenwood, J., Hercowitz, Z., and Krusell, P. (2000). The role of investment specific technological change in the business cycle. European Economic Review, 44:91–115.
Greenwood, J. and Yorukoglu, M. (1997). 1974. Carnegie-Rochester Conference Series on Public Policy, 46:49–95.
Gunn, C. and Johri, A. (2011). News and knowledge capital. Review of Economic Dynamics, 14(1):92–101.
Guo, S. (2008). News shocks, expectation driven business cycles and financial market frictions. Manuscript, Concordia University.
Hansen, G. D. (1985). Indivisible labor and the business cycle. Journal of Monetary Economics, 16:309–327.
Helpman, E. and Trajtenberg, M. (1994). A time to sow and a time to reap: Growth based on general purpose technologies. NBER Working Paper, (4854).
Jaimovich, N. and Rebelo, S. (2009). Can news about the future drive the business cycle? American Economic Review, 99(4):1097–1118.
Justiniano, A. and Primiceri, G. E. (2008). The time-varying volatility of macroeconomic fluctuations. The American Economic Review, 98(3):604 – 641.
Justiniano, A., Primiceri, G. E., and Tambalotti, A. (2010). Investment shocks and business cycles. Journal of Monetary Economics, 57(2):132 – 145.
Justiniano, A., Primiceri, G. E., and Tambalotti, A. (2011). Investment shocks and the relative price of investment. Review of Economic Dynamics, 14(1):101 – 121.
Karnizova, L. (2010). The spirit of capitalism and expectation-driven business cycles. Journal of Monetary Economics, 57(6):739 – 752.
Keiichiro, K., Tomoyuki, N., and Masaru, I. (2007). Collateral constraint and news-driven cycles. Discussion papers 07013, Research Institute of Economy, Trade and Industry (RIETI).
King, R. G., Plosser, C., and Rebelo, S. T. (1988). Production, growth, and business cycles: I the basic neoclassical model. Journal of Monetary Economics, 21:195–232.
Kobayashi, K. and Nutahara, K. (2010). Nominal rigidities, news-driven business cycles, and monetary policy. The B.E. Journal of Macroeconomics, 10(1).
Lorenzoni, G. (2009). A theory of demand shocks. The American Economic Review, 99(5):2050–2084.
Mian, A. R. and Sufi, A. (2010). Household leverage and the recession of 2007 to 2009. NBER Working Papers 15896, National Bureau of Economic Research, Inc.
Morley, J. and Piger, J. (2011). The asymmetric business cycle. Review of Economics and Statistics, forthcoming. Pigou, A. C. (1926). Industrial Fluctuations. Macmillan. London.
Sakellaris, P. and Wilson, D. (2004). Quantifying embodied technological change. Review of Economic Dynamics, 7:1–26.
Schmitt-Grohe, S. and Uribe, M. (2008). What’s news in business cycles. NBER Working Papers 14215, National Bureau of Economic Research, Inc. Shiller, R. J. (2007). Understanding recent trends in house prices and home ownership.Working Paper 13553, National Bureau of Economic Research.
Sichel, D. E. (1993). Business cycle asymmetry: A deeper look. Economic Inquiry, 31:224– 236.
Van Nieuwerburgh, S. and Veldkamp, L. (2006). Learning asymmetries in real business cycles. Journal of Monetary Economics, 53:753–772.