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Empirical Proxies for the Consumption-Wealth Ratio

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  • Jeremy Rudd

    (Board of Governors of the Federal Reserve System)

  • Karl Whelan

    (Central Bank and Financial Services Authority of Ireland)

Abstract

Using a log-linearized approximation to an aggregate budget constraint, it is possible to show that the ratio of consumption to total (human and non-human) wealth summarizes agents' expectations concerning both future labor income and future asset returns. In a series of recent papers, Lettau and Ludvigson construct an empirical analogue to the consumption-wealth ratio by approximating total wealth with a linear combination of labor income and observable non-human wealth. If valid, this framework suggests that consumption, assets, and labor income will be cointegrated. We demonstrate, however, that standard tests fail to reject the hypothesis of no cointegration once one employs measures of consumption, assets, and labor income that are jointly consistent with an underlying budget constraint. We also show that deviations of consumption, assets, and income from an estimated common trend are unable to predict future excess returns on stocks out of sample once theoretically consistent measures are used. (Copyright: Elsevier)

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Bibliographic Info

Article provided by Elsevier for the Society for Economic Dynamics in its journal Review of Economic Dynamics.

Volume (Year): 9 (2006)
Issue (Month): 1 (January)
Pages: 34-51

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Handle: RePEc:red:issued:v:9:y:2006:i:1:p:34-51

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Related research

Keywords: Budget constraint; Return forecastability; Cointegration; cay;

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References

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  1. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198774501, October.
  2. John Y. Campbell, 1993. "Understanding Risk and Return," NBER Working Papers 4554, National Bureau of Economic Research, Inc.
  3. Lettau, Martin & Ludvigson, Sydney C., 2005. "tay's as good as cay: Reply," Finance Research Letters, Elsevier, Elsevier, vol. 2(1), pages 15-22, March.
  4. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, Econometric Society, vol. 59(6), pages 1551-80, November.
  5. repec:cbi:wpaper:4/rt/02 is not listed on IDEAS
  6. Lettau, Martin & Ludvigson, Sydney, 2001. "Time-Varying Risk Premia and the Cost of Capital: An Alternative Implication of the Q Theory of Investment," CEPR Discussion Papers, C.E.P.R. Discussion Papers 3103, C.E.P.R. Discussion Papers.
  7. Campbell, J.Y. & Perron, P., 1991. "Pitfalls and Opportunities: What Macroeconomics should know about unit roots," Papers, Princeton, Department of Economics - Econometric Research Program 360, Princeton, Department of Economics - Econometric Research Program.
  8. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  9. Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2002. "Spurious Regressions in Financial Economics?," NBER Working Papers 9143, National Bureau of Economic Research, Inc.
  10. Dale W. Jorgenson & Kevin J. Stiroh, 2000. "Raising the Speed Limit: US Economic Growth in the Information Age," OECD Economics Department Working Papers 261, OECD Publishing.
  11. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 12(2-3), pages 231-254.
  12. Amit Goval & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," NBER Working Papers 10483, National Bureau of Economic Research, Inc.
  13. Martin Lettau & Sydney Ludvigson, 2001. "Resurrecting the (C)CAPM: A Cross-Sectional Test When Risk Premia Are Time-Varying," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 109(6), pages 1238-1287, December.
  14. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(5), pages 563-77, Sept.-Oct.
  15. Brennan, Michael J. & Xia, Yihong, 2005. "tay's as good as cay," Finance Research Letters, Elsevier, Elsevier, vol. 2(1), pages 1-14, March.
  16. Campbell, John, 1993. "Intertemporal Asset Pricing Without Consumption Data," Scholarly Articles 3221491, Harvard University Department of Economics.
  17. Martin Lettau & Sydney Ludvigson, 2003. "Understanding Trend and Cycle in Asset Values: Reevaluating the Wealth Effect on Consumption," NBER Working Papers 9848, National Bureau of Economic Research, Inc.
  18. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Department of Economics, University of Oxford, vol. 54(3), pages 461-72, August.
  19. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," Harvard Institute of Economic Research Working Papers, Harvard - Institute of Economic Research 2084, Harvard - Institute of Economic Research.
  20. Michael Palumbo & Jeremy Rudd & Karl Whelan, 2002. "On the relationships between real consumption, income and wealth," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2002-38, Board of Governors of the Federal Reserve System (U.S.).
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