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From the help desk: Polynomial distributed lag models

Author

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  • Allen McDowell

    (StataCorp)

Abstract

Polynomial distributed lag models (PDLs) are finite-order distributed lag models with the impulse-response function constrained to lie on a polynomial of known degree. You can estimate the parameters of a PDL directly via constrained ordinary least squares, or you can derive a reduced form of the model via a linear transformation of the structural model, estimate the reduced-form parameters, and recover estimates of the structural parameters via an inverse linear transformation of the reduced-form parameter estimates. This article demonstrates both methods using Stata. Copyright 2004 by StataCorp LP.

Suggested Citation

  • Allen McDowell, 2004. "From the help desk: Polynomial distributed lag models," Stata Journal, StataCorp LP, vol. 4(2), pages 180-189, June.
    • Handle: RePEc:tsj:stataj:v:4:y:2004:i:2:p:180-189
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    References listed on IDEAS

    as
    1. Shiller, Robert J, 1973. "A Distributed Lag Estimator Derived from Smoothness Priors," Econometrica, Econometric Society, vol. 41(4), pages 775-788, July.
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    Cited by:

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    3. Robert Kunst & Philip Franses, 2015. "Asymmetric time aggregation and its potential benefits for forecasting annual data," Empirical Economics, Springer, vol. 49(1), pages 363-387, August.
    4. Bernd Brandl & Christian Lyhne Ibsen, 2017. "Instability and Change in Collective Bargaining: An Analysis of the Effects of Changing Institutional Structures," British Journal of Industrial Relations, London School of Economics, vol. 55(3), pages 527-550, September.
    5. Maestas, Nicole & Mullen, Kathleen J. & Strand, Alexander, 2021. "The effect of economic conditions on the disability insurance program: Evidence from the great recession," Journal of Public Economics, Elsevier, vol. 199(C).

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