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A General Algorithm for Simultaneous Estimation of Constant and Randomly-Varying Parameters in Lineal Relations

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  • Alexander H. Sarris

Abstract

A recursive algorithm for estimating linear models with both constant and time-varying parameters is derived by maximization of a likelihood function. Recursive formulas are also derived for derivatives of the likelihood function; the derivatives are needed for numerical evaluation of some parameters. Smoothing formulas are also derived. The estimation algorithm is compared with others for similar classes of models.

Suggested Citation

  • Alexander H. Sarris, 1974. "A General Algorithm for Simultaneous Estimation of Constant and Randomly-Varying Parameters in Lineal Relations," NBER Working Papers 0038, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0038
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    1. Cooley, Thomas F & Prescott, Edward C, 1973. "An Adaptive Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 364-371, June.
    2. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
    3. Barr Rosenberg, 1973. "A Survey of Stochastic Parameter Regression," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 381-397, National Bureau of Economic Research, Inc.
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    1. Various, 1975. "Staff Reports on Research Under Way," NBER Chapters, in: Understanding Economic Change, pages 9-120, National Bureau of Economic Research, Inc.

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