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Simple estimators for dynamic panel data models with errors in variables

  • Mathematics


Q,--~`~R Discussion for ~ F.conomic Research 51 er b~lpll~llllllllllllll~lllllu~lllllll~~ll No. 8951 SIMPLE ESTIMATORS FOR DYNAMIC PANEL DATA MODELS WITH ERRORS IN VARIABLES ~'f~ by Tom Wansbeek and Arie Kapteyn October, 1989 SIMPLE ESTIMATORS FOR DYNAMIC PANEL DATA MODELS WITH ERRORS IN VARIABLES Tom Wansbeek, Groningen University Arie Kapteyn, Tilburg University Abstract. Simple dynamic models with individual effects are considered in which lagged endogenous or exogenous variabels are observed with error. The inconsistencies of estimators based on the elimination of individual effects are established. The results can be used to construct tractable consistent, and sometimes asymptotically efficient estimators. The em- phasis is on simplicity of derivations and tractability of the resulting estimators, rather than on generality or newness of results. Forthcoming in: Ronald IIewley and Tran Van Hoa (eds.), In Honour of Henri Theil, 1989. We thank Marno Verbeek for coinments. 1 1. INTRODUCTION The model considered in this paper is a rather simple dynamic error components model. Models of this type have been studied by a number of authors, including Nerlove (1967, 1971), Trognon (1978), Anderson and Hsiao (1981), and Sevestre and Trognon (1985). Our assumptions will be fairly conventional, except for the fact that lagged endogenous or exogenous variables are allowed to suffer from measurement error. A variant of this model, not including error components, has been studied extensively in the literature, cf. Aigner et al. (1984). A full treatment of ML estimation in this so-called dynamic shock-error model has been given by Ghosh (1989). Griliches and Hausman (1986) study another variant, namely a static panel data model with measurement error in the exogenous variables. The analysis oF parameter estimation in models of this type tends to lead to rather complicated, if not messy, algebra. Our emphasis is on the use of inethods that s

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