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Conditional Correlation Demand Systems

Author

Listed:
  • Apostolos Serletis

    (University of Calgary)

  • Libo Xu

    (University of San Francisco)

Abstract

We address the estimation of singular demand systems with heteroscedastic disturbances. As in Serletis and Isakin (Econ Rev 36:1111–1122, 2017) and Serletis and Xu (Empir Econ, 2019, forthcoming) we assume that the covariance matrix of the errors of the demand system is time-varying, and contribute to the literature by considering the constant conditional correlation and dynamic conditional correlation parameterizations of the variance model. We derive a number of important practical results and also provide an empirical application to support our methodology.

Suggested Citation

  • Apostolos Serletis & Libo Xu, 2020. "Conditional Correlation Demand Systems," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 77-86, June.
    • Handle: RePEc:kap:compec:v:56:y:2020:i:1:d:10.1007_s10614-018-9874-x
    DOI: 10.1007/s10614-018-9874-x
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    References listed on IDEAS

    as
    1. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
    2. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    3. Apostolos Serletis & Libo Xu, 2020. "Demand systems with heteroscedastic disturbances," Empirical Economics, Springer, vol. 58(4), pages 1913-1921, April.
    4. Apostolos Serletis & Maksim Isakin, 2017. "Stochastic volatility demand systems," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1111-1122, November.
    5. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    6. William Barnett & Jia Liu & Ryan Mattson & Jeff Noort, 2013. "The New CFS Divisia Monetary Aggregates: Design, Construction, and Data Sources," Open Economies Review, Springer, vol. 24(1), pages 101-124, February.
    7. BARTEN, Anton P., 1969. "Maximum likelihood estimation of a complete system of demand equations," LIDAM Reprints CORE 34, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Blundell, Richard, 1988. "Consumer Behaviour: Theory and Empirical Evidence--a Survey," Economic Journal, Royal Economic Society, vol. 98(389), pages 16-65, March.
    9. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1975. "Transcendental Logarithmic Utility Functions," American Economic Review, American Economic Association, vol. 65(3), pages 367-383, June.
    10. Barnett, William A. & Serletis, Apostolos, 2008. "Measuring Consumer Preferences and Estimating Demand Systems," MPRA Paper 12318, University Library of Munich, Germany.
    11. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    More about this item

    Keywords

    Flexible functional forms; Demand systems; Volatility;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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