IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/0537.html
   My bibliography  Save this paper

Unexploited Connections Between Intra- and Inter-temporal Allocation

Author

Listed:
  • Crossley, T.F.
  • Low, H.W.

Abstract

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class. This class generates (at most) rank two demand systems and we can test the validity of power utility on cross-section data. Further, if we maintain the assumption of power utility, and within period preferences are not homothetic, then the intertemporal preference parameter is identified by the curvature of Engel curves. Under the power utility assumption, neither Euler equation estimation nor structural consumption function estimation is necessary to identify the power parameter. In our empirical work, we use demand data to estimate the power utility parameter and to test the assumption of the power utility representation. We .nd estimates of the power parameter larger than obtained from Euler equation estimation, but we reject the power specification of within period utility.

Suggested Citation

  • Crossley, T.F. & Low, H.W., 2005. "Unexploited Connections Between Intra- and Inter-temporal Allocation," Cambridge Working Papers in Economics 0537, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0537
    Note: PE
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe0537.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lwebel Arthur & Perraudin William, 1995. "A Theorem on Portfolio Separation with General Preferences," Journal of Economic Theory, Elsevier, vol. 65(2), pages 624-626, April.
    2. Arthur Lewbel, 2003. "A rational rank four demand system," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 127-135.
    3. Pollak, Robert A & Wales, Terence J, 1979. "Welfare Comparisons and Equivalence Scales," American Economic Review, American Economic Association, vol. 69(2), pages 216-221, May.
    4. Attanasio, Orazio P & Browning, Martin, 1995. "Consumption over the Life Cycle and over the Business Cycle," American Economic Review, American Economic Association, vol. 85(5), pages 1118-1137, December.
    5. Orazio P. Attanasio & Hamish Low, 2004. "Estimating Euler Equations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 7(2), pages 405-435, April.
    6. Atkeson, Andrew & Ogaki, Masao, 1996. "Wealth-varying intertemporal elasticities of substitution: Evidence from panel and aggregate data," Journal of Monetary Economics, Elsevier, vol. 38(3), pages 507-534, December.
    7. Richard Blundell & Martin Browning & Costas Meghir, 1994. "Consumer Demand and the Life-Cycle Allocation of Household Expenditures," Review of Economic Studies, Oxford University Press, vol. 61(1), pages 57-80.
    8. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    9. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    10. MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-146, March.
    11. Attanasio, Orazio P & Weber, Guglielmo, 1995. "Is Consumption Growth Consistent with Intertemporal Optimization? Evidence from the Consumer Expenditure Survey," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1121-1157, December.
    12. Sydney Ludvigson & Christina H. Paxson, 2001. "Approximation Bias In Linearized Euler Equations," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 242-256, May.
    13. Sule Alan & Martin Browning, 2003. "Estimating Intertemporal Allocation Parameters using Simulated Residual Estimation," CAM Working Papers 2003-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    14. Stephen G. Donald, 1997. "Inference Concerning the Number of Factors in a Multivariate Nonparametric Relationship," Econometrica, Econometric Society, vol. 65(1), pages 103-132, January.
    15. Robert A. Pollak, 1971. "Additive Utility Functions and Linear Engel Curves," Review of Economic Studies, Oxford University Press, vol. 38(4), pages 401-414.
    16. Lewbel, Arthur, 1991. "The Rank of Demand Systems: Theory and Nonparametric Estimation," Econometrica, Econometric Society, vol. 59(3), pages 711-730, May.
    17. Lewbel, Arthur, 1996. "Demand Estimation with Expenditure Measurement Errors on the Left and Right Hand Side," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 718-725, November.
    18. L. Eeckhoudt & C. Gollier & H. Schlesinger, 2005. "Economic and financial decisions under risk," Post-Print hal-00325882, HAL.
    19. Muellbauer, John, 1976. "Community Preferences and the Representative Consumer," Econometrica, Econometric Society, vol. 44(5), pages 979-999, September.
    20. Martin Browning & Thomas F. Crossley, 2000. "Luxuries Are Easier to Postpone: A Proof," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 1022-1026, October.
    21. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas F. Crossley & Hamish W. Low, 2011. "Is The Elasticity Of Intertemporal Substitution Constant?," Journal of the European Economic Association, European Economic Association, vol. 9(1), pages 87-105, February.
    2. Jesus Fernández-Villaverde & Dirk Krueger, 2007. "Consumption over the Life Cycle: Facts from Consumer Expenditure Survey Data," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 552-565, August.
    3. Arthur Lewbel, 2003. "A rational rank four demand system," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 127-135.
    4. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    5. Matteo Barigozzi & Alessio Moneta, 2016. "Identifying the Independent Sources of Consumption Variation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 420-449, March.
    6. Engelhardt, Gary V. & Kumar, Anil, 2009. "The elasticity of intertemporal substitution: New evidence from 401(k) participation," Economics Letters, Elsevier, vol. 103(1), pages 15-17, April.
    7. LaFrance, Jeffrey T., 2008. "The structure of US food demand," Journal of Econometrics, Elsevier, vol. 147(2), pages 336-349, December.
    8. Daria Pignalosa, 2019. "On the role of the utility function in the estimation of preference parameters," Metroeconomica, Wiley Blackwell, vol. 70(4), pages 793-820, November.
    9. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    10. Simon Alder & Andreas Mueller & Timo Boppart, 2018. "A theory of structural change that can fit the data," 2018 Meeting Papers 988, Society for Economic Dynamics.
    11. K. K. Gary Wong & Hoanjae Park, 2018. "Consumption dynamics in inverse demand systems: an application to meat and fish demand in Korea," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 777-786, November.
    12. Nicholas Oulton, 2012. "How To Measure Living Standards And Productivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 58(3), pages 424-456, September.
    13. Cash, Sean B. & Goddard, Ellen W., 2006. "New Directions in Consumer Behaviour Research," CAFRI: Current Agriculture, Food and Resource Issues, Canadian Agricultural Economics Society, issue 7, pages 1-10, August.
    14. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, National Bureau of Economic Research, Inc.
    15. Donald, Stephen G. & Fortuna, Natércia & Pipiras, Vladas, 2011. "Local and Global Rank Tests for Multivariate Varying-Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 295-306.
    16. Julian Thimme, 2017. "Intertemporal Substitution In Consumption: A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 31(1), pages 226-257, February.
    17. Orazio P. Attanasio & Guglielmo Weber, 2010. "Consumption and Saving: Models of Intertemporal Allocation and Their Implications for Public Policy," Journal of Economic Literature, American Economic Association, vol. 48(3), pages 693-751, September.
    18. Thomas H. Jørgensen, 2017. "Life-Cycle Consumption and Children: Evidence from a Structural Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 717-746, October.
    19. Lyssiotou, Panayiota & Pashardes, Panos & Stengos, Thanasis, 2002. "Nesting quadratic logarithmic demand systems," Economics Letters, Elsevier, vol. 76(3), pages 369-374, August.
    20. Laura Blow, 2003. "Demographics in demand systems," IFS Working Papers W03/18, Institute for Fiscal Studies.

    More about this item

    Keywords

    elasticity of intertemporal substitution; Euler equation estimation; demand systems;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cam:camdae:0537. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.econ.cam.ac.uk/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jake Dyer (email available below). General contact details of provider: https://www.econ.cam.ac.uk/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.