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Stochastic Trends, Demographics and Demand Systems

  • Clifford Attfield

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    Techniques for determining the number of stochastic trends generating a set of non-stationary panel data are applied to budget shares for a number of commodity groups from the Family Expenditure Survey (FES) for the UK for the years 1973-2001. It is argued that some stochastic trends in macro data are generated by the aggregation of fixed demographic effects in the micro data. From cross section data, fixed effect coefficients are estimated which incorporate both age and income distribution effects. The estimated coefficients are combined with age proportion variables to form a set of I(1) indices for broad commodity groups which are then incorporated into a system of aggregate demand equations. The equations are estimated and tested in a non-stationary time series setting.

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    File URL: http://www.efm.bris.ac.uk/economics/working_papers/pdffiles/dp04563.pdf
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    Paper provided by Department of Economics, University of Bristol, UK in its series Bristol Economics Discussion Papers with number 04/563.

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    Length: 26 pages
    Date of creation: Apr 2004
    Date of revision:
    Handle: RePEc:bri:uobdis:04/563
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    1. Ng, S., 1995. "Testing for Homogeneity in Demand Systems when the Regressors Are Non-Stationary," Cahiers de recherche 9516, Universite de Montreal, Departement de sciences economiques.
    2. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
    3. Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
    4. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, 07.
    5. 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.
    6. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    7. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    8. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    9. 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, vol. 54(3), pages 461-72, August.
    10. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
    11. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-97, June.
    12. Lewbel, Arthur, 1996. "Aggregation without Separability: A Generalized Composite Commodity Theorem," American Economic Review, American Economic Association, vol. 86(3), pages 524-43, June.
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