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Quantiles for Counts

Author

Listed:
  • J.A.F. Machado

    (Faculdade de Economia, Universidade Nova de Lisboa)

  • J. M. C. Santos Silva

    (ISEG, Universidade Técnica de Lisboa)

Abstract

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.

Suggested Citation

  • J.A.F. Machado & J. M. C. Santos Silva, 2003. "Quantiles for Counts," Econometrics 0303001, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0303001 Note: Type of Document - Acrobat PDF; prepared on IBM PC ; pages: 39
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    References listed on IDEAS

    as
    1. Galindo, Luis Miguel, 1997. "El modelo P* como indicador de la política monetaria en una economía con alta inflación," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(254), pages 221-239, abril-jun.
    2. Hallman, Jeffrey J & Porter, Richard D & Small, David H, 1991. "Is the Price Level Tied to the M2 Monetary Aggregate in the Long Run?," American Economic Review, American Economic Association, vol. 81(4), pages 841-858, September.
    3. Arnold, Ivo J. M., 1996. "Stochastic trends in the long-run behavior of velocity: A new test of the institutional hypothesis," Journal of Policy Modeling, Elsevier, vol. 18(6), pages 623-641, December.
    4. Hall, Stephen G & Milne, Alistair, 1994. "The Relevance of P-Star Analysis to UK Monetary Policy," Economic Journal, Royal Economic Society, vol. 104(424), pages 597-604, May.
    5. Kenneth N. Kuttner, 1989. "Monetary and non-monetary sources of inflation: an error correction analysis," Working Paper Series, Macroeconomic Issues 89-15, Federal Reserve Bank of Chicago.
    6. Charles L. Evans & Kenneth N. Kuttner, 1998. "Can VAR's describe monetary policy?," Working Paper Series WP-98-19, Federal Reserve Bank of Chicago.
    7. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    8. Jeffrey J. Hallman & Richard G. Anderson, 1993. "Has the long-run velocity of M2 shifted? Evidence from the P* model," Economic Review, Federal Reserve Bank of Cleveland, issue Q I, pages 14-26.
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    More about this item

    Keywords

    Asymmetric maximum likelihood; Jittering; Maximum score estimator; Quantile regression; Smoothing.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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