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Efficient Estimation of a Dynamic Error-Shock Model

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  • Cheng Hsiao
  • P. M. Robinson

Abstract

This paper is concerned with the estimation of the parameters in a dynamic simultaneous equation model with stationary disturbances under the assumption that the variables are subject to random measurement errors. The conditions under which the parameters are identified are stated. An asymptotically efficient frequency-domain class of instrumental variables estimators is suggested. The procedure consists of two basic steps. The first step transforms the model in such a way that the observed exogenous variables are asymptotically orthogonal to the residual terms. The second step involves an iterative procedure like that of Robinson [13].

Suggested Citation

  • Cheng Hsiao & P. M. Robinson, 1976. "Efficient Estimation of a Dynamic Error-Shock Model," NBER Working Papers 0157, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0157
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    References listed on IDEAS

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    1. Robinson, P M, 1976. "Instrumental Variables Estimation of Differential Equations," Econometrica, Econometric Society, vol. 44(4), pages 765-776, July.
    2. Hannan, E J, 1971. "The Identification Problem for Multiple Equation Systems with Moving Average Errors," Econometrica, Econometric Society, vol. 39(5), pages 751-765, September.
    3. Espasa, Antoni & Sargan, J Denis, 1977. "The Spectral Estimation of Simultaneous Equation Systems with Lagged Endogenous Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(3), pages 583-605, October.
    4. Hsiao, Cheng, 1976. "Identification and Estimation of Simultaneous Equation Models with Measurement Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(2), pages 319-339, June.
    5. Hannan, E J & Nicholls, D F, 1972. "The Estimation of Mixed Regression, Autoregression, Moving Average, and Distributed Lag Models," Econometrica, Econometric Society, vol. 40(3), pages 529-547, May.
    6. Robinson, P M, 1974. "Identification, Estimation and Large-Sample Theory for Regressions Containing Unobservable Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(3), pages 680-692, October.
    7. Hannan, E J & Terrell, R D, 1973. "Multiple Equation Systems with Stationary Errors," Econometrica, Econometric Society, vol. 41(2), pages 299-320, March.
    8. Goldberger, Arthur S, 1972. "Structural Equation Methods in the Social Sciences," Econometrica, Econometric Society, vol. 40(6), pages 979-1001, November.
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