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Conditional mean functions of non-linear models of US output

Author

Listed:
  • Ana B. C. Galvão

    (Department of Economics, European University Institute, Italy.)

  • Michael P. Clements

    (Department of Economics, University of Warwick, Coventry, CV4 7AL, UK)

Abstract

We compare a number of models of post War US output growth in terms of the degree and pattern of non-linearity they impart to the conditional mean, where we condition on either the previous period's growth rate, or the previous two periods' growth rates. The conditional means are estimated non-parametrically using a nearest-neighbour technique on data simulated from the models. In this way, we condense the complex, dynamic, responses that may be present in to graphical displays of the implied conditional mean.

Suggested Citation

  • Ana B. C. Galvão & Michael P. Clements, 2002. "Conditional mean functions of non-linear models of US output," Empirical Economics, Springer, vol. 27(4), pages 569-586.
    • Handle: RePEc:spr:empeco:v:27:y:2002:i:4:p:569-586
    Note: received: Feb. 1999/Final version received: June 2001
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    Citations

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    Cited by:

    1. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.

    More about this item

    Keywords

    non-linearity · business cycles · non-parametric conditional mean estimates.;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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