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Ridge Estimators for Distributed Lag Models


  • G.S. Maddala


The paper explains how the Almon polynominal lag specification can be made stochastic in two different ways - one suggested by Shiller and another following the lines of Lindley and Smith. It is shown that both the estimators can be considered as modified ridge estimators. The paper then compares these modified ridge estimators with the ridge estimator suggested by Hoerl and Kennard. It is shown that for the estimation of distributed lag models the ridge estimator suggested by Hoerl and Kennard is not useful but that the modified ridge estimators corresponding to the stochastic versions of the Almon lag are promising. The paper has two empirical illustrations.

Suggested Citation

  • G.S. Maddala, 1974. "Ridge Estimators for Distributed Lag Models," NBER Working Papers 0069, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:0069

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    References listed on IDEAS

    1. Zellner, Arnold & Geisel, Martin S, 1970. "Analysis of Distributed Lag Models with Application to Consumption Function Estimation," Econometrica, Econometric Society, vol. 38(6), pages 865-888, November.
    2. Paul W. Holland, 1973. "Weighted Ridge Regression: Combining Ridge and Robust Regression Methods," NBER Working Papers 0011, National Bureau of Economic Research, Inc.
    3. Leamer, Edward E, 1972. "A Class of Informative Priors and Distributed Lag Analysis," Econometrica, Econometric Society, vol. 40(6), pages 1059-1081, November.
    4. 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:

    1. John F. Wilson, 1976. "Have geometric lag hypotheses outlived their time? some evidence in a Monte Carlo framework," International Finance Discussion Papers 82, Board of Governors of the Federal Reserve System (U.S.).
    2. Robert J. Shiller, 1975. "Alternative Prior Representations of Smoothness for Distributed Lag Estimation," NBER Working Papers 0089, National Bureau of Economic Research, Inc.

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