Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-27T05:10:13.127Z Has data issue: false hasContentIssue false
  • English
  • Français

CREDIT CONSTRAINTS, LEARNING, AND AGGREGATE CONSUMPTION VOLATILITY

Published online by Cambridge University Press:  07 June 2012

Daniel L. Tortorice
Daniel L. Tortorice*
Affiliation:
Brandeis University
*
Address correspondence to: Daniel L. Tortorice, Department of Economics, Brandeis University, Mailstop 021, 415 South St., Waltham, MA 02454-9110, USA; e-mail: tortoric@brandeis.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper documents three facts. First, the volatility of consumption growth relative to income growth rose from 1947 to 1960 and then fell dramatically by 50% from the 1960s to the 1990s. Second, the correlation between consumption growth and personal income growth fell by about 50% over the same time period. Finally, the absolute deviation of consumption growth from its mean exhibits one break in U.S. data, and the mean of the absolute deviations has fallen by about 30%. A standard dynamic stochastic general equilibrium model is unable to explain these facts. I examine ability of two hypotheses to account for these facts: a fall in credit constraints and changing beliefs about the permanence of income shocks. I find evidence for both explanations. The beliefs explanation is more consistent with the data.

Keywords

ConsumptionBusiness FluctuationsLearningLiquidity Constraints
Type
Articles
Information
Macroeconomic Dynamics , Volume 18 , Issue 2 , March 2014 , pp. 338 - 368
Copyright
Copyright © Cambridge University Press 2012 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Adda, Jerome and Cooper, Russell W. (2003) Dynamic Economics: Quantitative Methods and Applications. Cambridge, MA: MIT Press.Google Scholar
Aguiar, Mark and Gopinath, Gita (2007) Emerging market business cycles: The cycle is the trend. Journal of Political Economy 115, 69–102.CrossRefGoogle Scholar
Andrews, Donald W. K. 1991. Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59 (3), 817–858.CrossRefGoogle Scholar
Bai, Jushan and Perron, Pierre (1998) Estimating and testing linear models with multiple structural changes. Econometrica 66 (1), 47–78.CrossRefGoogle Scholar
Bai, Jushan and Perron, Pierre (2003) Computation and analysis of multiple structural change models. Journal of Applied Econometrics 18 (1), 1–22.CrossRefGoogle Scholar
Benito, Andrew and Mumtaz, Haroon (2009) Consumption excess sensitivity, liquidity constraints, and the collateral role of housing. Macroeconomic Dynamics 13 (3), 305–326.CrossRefGoogle Scholar
Bullard, James, Evans, George W., and Honkapohja, Seppo (2010) A model of near-rational exuberance. Macroeconomic Dynamics 14 (2), 166–188.CrossRefGoogle Scholar
Campbell, John Y. and Mankiw, N. Gregory (1990) Permanent income, current income, and consumption. Journal of Business and Economic Statistics 8 (3), 265–279.Google Scholar
Cecchetti, Stephen G., Flores-Lagunes, Alfonso, and Krause, Stefan (2005) Assessing the sources of changes in the volatility of real growth. In Kent, Christopher and Norman, David (eds.), The Changing Nature of the Business Cycle, pp. 115–138. Sydney: RBA Annual Conference Volume, Reserve Bank of Australia.Google Scholar
Cecchetti, Stephen G., Flores-Lagunes, Alfonso, and Krause, Stefan (2006) Financial Development, Consumption Smoothing, and the Reduced Volatility of Real Growth. AEA Conference Papers 2007.Google Scholar
Cochrane, John (2001) Asset Pricing. Princeton, NJ: Princeton University Press.Google Scholar
Cochrane, John H. (1988) How big is the random walk in GNP? Journal of Political Economy 96 (5), 893–920.CrossRefGoogle Scholar
Cogley, Timothy and Sargent, Thomas J. (2005) The conquest of US inflation: Learning and robustness to model uncertainty. Review of Economic Dynamics 8 (2), 528–563.CrossRefGoogle Scholar
Deaton, Angus (1992) Understanding Consumption. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Dynan, Karen E., Edelberg, Wendy, and Palumbo, Michael (2009) The effects of population againg on the relationship among aggregate consumption, saving and income. American Economic Review: Papers and Procedings 99 (2), 380–386.CrossRefGoogle Scholar
Dynan, Karen E., Elmendorf, Douglas W., and Sichel, Daniel E. (2006) Can financial innovation help to explain the reduced volatility of economic activity? Journal of Monetary Economics, 53 (1), 123–150.CrossRefGoogle Scholar
Evans, George and Honkapohja, Seppo (2001) Learning and Expectations in Macroeconomics. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Georges, Christophre and Wallace, John C. (2009) Learning dynamics and nonlinear misspecification in an artificial financial market. Macroeconomic Dynamics 13 (5), 625–655.CrossRefGoogle Scholar
Guvenen, Fatih (2007) Learning your earning: Are labor income shocks really very persistent? American Economic Review 97 (3), 687–712.CrossRefGoogle Scholar
Hamilton, James (1994) Time Series Analysis. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Kreps, David (1998) Anticipated utility and dynamic choice, a 1997 Schwartz Lecture. In Jacobs, Donald, Kalai, Ehud, and Kamien, Morton (eds.), Frontiers of Research in Economic Theory, pp. 242–274. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Ljungovist, Lars and Sargent, Thomas (2004) Recursive Macroeconomic Theory. Cambridge, MA: MIT Press.Google Scholar
Ludvigson, Sydney (1999) Consumpiton and credit: A model of time-varying liquidity constraints. Review of Economics and Statistics 81 (3), 434–447.CrossRefGoogle Scholar
Nakajima, Makoto (2007) Solving RBC Models with L–Q Approximation. Mimeo, UIUC.Google Scholar
Sargent, Thomas (2001) The Conquest of American Inflation. Princeton, NJ: Princeton University Press.Google Scholar
Stock, James H. (1991) Confidence intervals for the largest autoregressive root in U.S. macroeconomic time series. Journal of Monetary Economics 28 (3), 435–459.CrossRefGoogle Scholar
Stock, James H. and Watson, Mark (2003) Has the business cycle changed and why? In Gertler, Mark and Rogoff, Kenneth (eds.), NBER Macroeconomics Annual 2002, pp. 159–230. Cambridge, MA: National Bureau of Economic Research.Google Scholar
Tauchen, George and Hussey, Robert (1991) Quadrature-based methods for obtaining approximate solutions to nonlinear asset pricing models. Econometrica 59 (2), 371–396.CrossRefGoogle Scholar
Tillman, Peter (2011) Parameter uncertainty and non-linear monetary policy rules. Macroeconomic Dynamics 15 (2), 184–200.CrossRefGoogle Scholar
Tortorice, Daniel L. (2012) Unemployment expectations and the business cycle. B.E. Journal of Macroeconomics (Topics) 12 (1), 1–47.Google Scholar
Waters, George (2009) Learning, commitment and monetary policy. Macroeconomic Dynamics 13 (4), 421–449.CrossRefGoogle Scholar