IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v9y2005i2n1.html
   My bibliography  Save this article

Economic Growth and Revealed Social Preference

Author

Listed:
  • Day Richard H.

    (USC)

  • Yang Chengyu

    (USC)

Abstract

The Representative Agent Growth Model is estimated econometrically using the Generalized Method of Moments for the U.S. economy for three separate Growth Eras and the results compared to those obtained using the Kydland--Prescott calibration approach. The estimated parameters differ substantially in the three cases, which imply changing social preferences for present versus future income and work--leisure tradeoffs. These in turn imply switching among alternative balanced growth paths and differences in the contributions of capital, labor, and labor augmenting productivity among the three Eras. Using the GMM method yields very high productivity and capital elasticity parameters and a very low time preference parameter for Eras I compared to Eras III and IV. While both GMM and the calibration method yield much smaller leisure parameters for Era IV than for Eras I and III.

Suggested Citation

  • Day Richard H. & Yang Chengyu, 2005. "Economic Growth and Revealed Social Preference," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-18, June.
    • Handle: RePEc:bpj:sndecm:v:9:y:2005:i:2:n:1
    DOI: 10.2202/1558-3708.1277
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1558-3708.1277
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1558-3708.1277?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    2. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, vol. 98(2), pages 203-223, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Day, Richard H. & Yang, Chengyu, 2009. "From Keynes to Solow to optimal growth: An encompassing model of monetary and fiscal policy," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 780-795, November.
    2. Yang, Chengyu & Wang, Xupeng, 2023. "Income and cultural consumption in China: A theoretical analysis and a regional empirical evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 216(C), pages 102-123.
    3. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    4. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.

    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. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    2. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    3. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    4. Jim Malley & Ulrich Woitek, 2009. "Productivity shocks and aggregate cycles in an estimated endogenous growth model," IEW - Working Papers 416, Institute for Empirical Research in Economics - University of Zurich.
    5. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412.
    6. Marco Del Negro & Frank Schorfheide & Frank Smets & Raf Wouters, 2004. "On the fit and forecasting performance of New Keynesian models," FRB Atlanta Working Paper 2004-37, Federal Reserve Bank of Atlanta.
    7. Pablo A. Guerrón-Quintana & James M. Nason, 2013. "Bayesian estimation of DSGE models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 21, pages 486-512, Edward Elgar Publishing.
    8. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    9. Fritz Breuss, 2018. "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 105-126, April.
    10. Jim Malley & Ulrich Woitek, 2011. "Productivity Shocks and Aggregate Fluctuations in an Estimated Endogenous Growth Model with Human Capital," CESifo Working Paper Series 3567, CESifo.
    11. Özer Karagedikli & Troy Matheson & Christie Smith & Shaun P. Vahey, 2010. "RBCs AND DSGEs: THE COMPUTATIONAL APPROACH TO BUSINESS CYCLE THEORY AND EVIDENCE," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 113-136, February.
    12. Paccagnini, Alessia, 2010. "DSGE Model Validation in a Bayesian Framework: an Assessment," MPRA Paper 24509, University Library of Munich, Germany.
    13. Alvaro Hurtado Rendón & Humberto Franco González & Jesús Alonso Botero Garcia, 2011. "Los modelos dsge: una respuesta de la discusión macroeconómica," Estudios Economicos, Universidad Nacional del Sur, Departamento de Economia, vol. 28(57), pages 59-77, july-dece.
    14. Corradi, Valentina & Swanson, Norman R., 2007. "Evaluation of dynamic stochastic general equilibrium models based on distributional comparison of simulated and historical data," Journal of Econometrics, Elsevier, vol. 136(2), pages 699-723, February.
    15. Otrok, Christopher, 2001. "On measuring the welfare cost of business cycles," Journal of Monetary Economics, Elsevier, vol. 47(1), pages 61-92, February.
    16. Alessia Paccagnini, 2012. "Comparing Hybrid DSGE Models," Working Papers 228, University of Milano-Bicocca, Department of Economics, revised Dec 2012.
    17. Marco Del Negro & Frank Schorfheide, 2006. "How good is what you've got? DSGE-VAR as a toolkit for evaluating DSGE models," Economic Review, Federal Reserve Bank of Atlanta, vol. 91(Q 2), pages 21-37.
    18. Kawther Alimi & Mohamed Chakroun, 2022. "Wage Rigidity Impacts on Unemployment and Inflation Persistence in Tunisia: Evidence from an Estimated DSGE Model," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 474-500, March.
    19. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412, April.
    20. Carlo A. Favero, 2009. "The Econometrics of Monetary Policy: An Overview," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 16, pages 821-850, Palgrave Macmillan.

    More about this item

    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:bpj:sndecm:v:9:y:2005:i:2:n:1. See general information about how to correct material in RePEc.

    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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.