Artigo Acesso aberto Revisado por pares

Using Asset Prices to Measure the Persistence of the Marginal Utility of Wealth

2005; Wiley; Volume: 73; Issue: 6 Linguagem: Inglês

10.1111/j.1468-0262.2005.00643.x

ISSN

1468-0262

Autores

Fernando Álvarez, Urban J. Jermann,

Tópico(s)

Economic theories and models

Resumo

EconometricaVolume 73, Issue 6 p. 1977-2016 Using Asset Prices to Measure the Persistence of the Marginal Utility of Wealth Fernando Alvarez, Fernando Alvarez Dept. of Economics, University of Chicago, Chicago, IL 60637, U.S.A.; and NBER; [email protected]and Dept. of Finance, The Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104-6367, U.S.A.; and NBER; jerma[email protected]; http://finance.wharton.upenn.edu/~jermann.Search for more papers by this authorUrban J. Jermann, Urban J. Jermann We thank Andy Atkeson, Erzo Luttmer, Lars Hansen, Pat Kehoe, Bob King, Narayana Kocherlakota, Stephen Leroy, Lee Ohanian, and the participants in workshops and conferences at UCLA, the University of Chicago, the Federal Reserve Banks of Minneapolis, Chicago, and Cleveland, and Duke, Boston, Ohio State, Georgetown, and Yale Universities, NYU, Wharton, the SED meeting in Stockholm, SITE, the Minnesota workshop in macroeconomic theory, and ESSFM for their comments and suggestions. We thank Robert Bliss for providing the data for U.S. zero-coupon bonds. Alvarez thanks the NSF and the Sloan Foundation for support. Earlier versions of this paper were circulated under the title “The Size of the Permanent Component of Asset Pricing Kernels.”Search for more papers by this author Fernando Alvarez, Fernando Alvarez Dept. of Economics, University of Chicago, Chicago, IL 60637, U.S.A.; and NBER; [email protected]and Dept. of Finance, The Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104-6367, U.S.A.; and NBER; jerma[email protected]; http://finance.wharton.upenn.edu/~jermann.Search for more papers by this authorUrban J. Jermann, Urban J. Jermann We thank Andy Atkeson, Erzo Luttmer, Lars Hansen, Pat Kehoe, Bob King, Narayana Kocherlakota, Stephen Leroy, Lee Ohanian, and the participants in workshops and conferences at UCLA, the University of Chicago, the Federal Reserve Banks of Minneapolis, Chicago, and Cleveland, and Duke, Boston, Ohio State, Georgetown, and Yale Universities, NYU, Wharton, the SED meeting in Stockholm, SITE, the Minnesota workshop in macroeconomic theory, and ESSFM for their comments and suggestions. We thank Robert Bliss for providing the data for U.S. zero-coupon bonds. Alvarez thanks the NSF and the Sloan Foundation for support. Earlier versions of this paper were circulated under the title “The Size of the Permanent Component of Asset Pricing Kernels.”Search for more papers by this author First published: 11 October 2005 https://doi.org/10.1111/j.1468-0262.2005.00643.xCitations: 223 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract We derive a lower bound for the volatility of the permanent component of investors' marginal utility of wealth or, more generally, asset pricing kernels. The bound is based on return properties of long-term zero-coupon bonds, risk-free bonds, and other risky securities. We find the permanent component of the pricing kernel to be very volatile; its volatility is about at least as large as the volatility of the stochastic discount factor. A related measure for the transitory component suggest it to be considerably less important. We also show that, for many cases where the pricing kernel is a function of consumption, innovations to consumption need to have permanent effects. REFERENCES Abel, A. (1999): “Risk Premia and Term Premia in General Equilibrium,”Journal of Monetary Economics, 43, 3–33. Ait-Sahalia, Y. (1996): “Nonparametric Pricing of Interest Rate Derivative Securities,”Econometrica, 64, 527–560. Aiyagari, R. S. (1994): “Uninsured Idiosyncratic Risk and Aggregate Saving,”Quarterly Journal of Economics, 109, 659–684. Alvarez, F., and U. J. Jermann (2000): “Efficiency, Equilibrium, and Asset Pricing with Risk of Default,”Econometrica 68 775–797. Alvarez, F., and U. J. Jermann (2005): “Supplement to ‘Using Asset Prices to Measure the Persistence of the Marginal Utility of Wealth’,”Econometrica, available at http://www.econometricsociety.org/ecta/supmat.3841exam.pdf. Anderson, N., and J. Sleath (1999): “ New Estimates of the UK Real and Nominal Yield Curves,”Quarterly Bulletin, Bank of England, November. Bansal, R., and B. N. Lehmann (1997): “Growth-Optimal Portfolio Restrictions on Asset Pricing Models,”Macroeconomic Dynamics, 1, 333–354. Bansal, R., and A. Yaron (2004): “Risks for the Long Run: A Potential Solution of Asset Pricing Puzzles,”Journal of Finance, 59, 1481–1509. Baxter, M., and M. Crucini (1995): “Business Cycles and the Asset Structure of Foreign Trade,”International Economic Review, 36, 821–854. Beveridge, S., and C. R. Nelson (1981): “A New Approach to Decomposition of Economic Time Series into Permanent and Transitory Components with Particular Attention to Measurement of the Business Cycle,”Journal of Monetary Economics, 7, 151–174. Blanchard, O., and D. Quah (1989): “The Dynamic Effects of Aggregate Demand and Supply Disturbances,”American Economic Review, 79, 655–673. Bliss, R. (1997): “ Testing Term Structure Estimation Methods,”in Advances in Futures and Options Research, Vol. 9, ed. by P. Boyle, G. Pennachi, and P. Ritchken. Greenwich , CT : JAI Press, 197–231. Campbell, J. Y. (1996): “Understanding Risk and Return,”Journal of Political Economy, 104, 298–345. Campbell, J. Y., and J. H. Cochrane (1999): “By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior,”Journal of Political Economy, 107, 205–251. Christiano, L., M. Eichenbaum, and R. Vigfusson (2002): “ What Happens after a Technology Shock?”Unpublished Manuscript, Northwestern University. Cochrane, J. H. (1988): “How Big Is the Random Walk in GNP Journal of Political Economy, 96, 893–920. Cochrane, J. H. (2005): Asset Pricing. Princeton , NJ : Princeton University Press. Cochrane, J.H., and L. P. Hansen (1992): “ Asset Pricing Exploration for Macroeconomics,”in NBER Macroeconomics Annual, ed. by O. J. Blanchard and S. Fischer. Cambridge , MA : MIT Press, 152–165. Daniel, K. D., and D. A. Marshall (2001): “ Consumption and Asset Returns at Short- and Long-Horizons,”Unpublished Manuscript, Northwestern University. Dolmas, J. (1998): “Risk Preferences and the Welfare Cost of Business Cycles,”Review of Economic Dynamics, 1, 646–676. Duffie, D. (1996): Dynamic Asset Pricing Theory. Princeton , NJ : Princeton University Press. Epstein, L. G., and S. E. Zin (1989): “Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: A Theoretical Framework,”Econometrica, 57, 937–969. Ferson, W. E., and G. M. Constantinides (1991): “Habit Persistence and Durability in Aggregate Consumption: Empirical Tests,”Journal of Financial Economics, 29, 199–240. Fisher, J. D. M. (2002): “ Technology Shocks Matter,”Working Paper 2002-14, Federal Reserve Bank of Chicago. Gali, J. (1999): “Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations American Economic Review, 89, 249–271. Hall, A. D., H. M. Anderson, and C. W. J. Granger (1992): “A Cointegration Analysis of Treasury Bill Yields,”Review of Economics and Statistics, 74, 116–126. Hansen, G. D. (1997): “Technical Progress and Aggregate Fluctuations,”Journal of Economic Dynamics and Control, 21, 1005–1023. Hansen, L. P., J. C. Heaton, and N. LI (2004): “ Consumption Strikes Back,”Unpublished Manuscript, University of Chicago. Hansen, L. P., and R. Jagannathan (1991): “Implications of Security Market Data for Models of Dynamic Economies,”Journal of Political Economy, 99, 225–262. Hansen, L. P., and J. Scheinkman (2003): “ Semi Group Pricing,”Unpublished Manuscript, University of Chicago and Princeton University. Ibbotson Associates (2000): Stocks, Bonds, Bills, and Inflation–1998 Yearbook. Chicago : Ibbotson Associates. Kazemi, H. B. (1992): “An Intertemporal Model of Asset Prices in a Markov Economy with Limiting Stationary Distribution,”Review of Financial Studies, 5, 85–104. Lettau, M., and S. Ludvigson (2004): “Understanding Trend and Cycle in Asset Values: Reevaluating the Wealth Effect on Consumption,”American Economic Review, 94, 276–299. Luttmer, E. G. J. (1996): “Asset Pricing in Economies with Frictions,”Econometrica, 64, 1439–1467. Luttmer, E. G. J. (2003): “ Two Decompositions of the Local Variance of State Prices,”Unpublished Manuscript, University of Minnesota. Mcculloch, J. H., and H.-C. Kwon (1993): “ U.S. Term Structure Data, 1947–1991,”Working Paper 93-6, Ohio State University. Nelson, C. R., and C. I. Plosser (1982): “Trend and Random Walks in Macroeconomic Time-Series: Some Evidence and Implications,”Journal of Monetary Economics, 10, 139–162. Newey, W. K., and K.D. West (1987): “A Simple, Positive Semidefinite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix,”Econometrica, 55, 703–708. Shapiro M., and M. Watson (1988): “Sources of Business Cycle Fluctuations,”NBER Macroeconomics Annual, 3, 111–148. Shiller, R. (1998): “ Annual Data on US Stock Market Prices, Dividends, Earnings, 1871–Present with Associated Interest Rate, Price Level and Consumption Data,”available at http://www.econ.yale.edu/~shiller/data/chapt26.html. Theil, H. (1967): Economics and Information Theory. Amsterdam : North-Holland. Weil, P. (1990): “Non-Expected Utility in Macroeconomics,”Quarterly Journal of Economics, CV, 29–42. Citing Literature Volume73, Issue6November 2005Pages 1977-2016 ReferencesRelatedInformation

Referência(s)