Multiplicative panel data models without the strict exogeneity assumption
نویسندگان
چکیده
This paper studies estimation of multiplicative, unobserved components panel data models without imposing the strict exogeneity assumption on the explanatory variables. The method of moments estimators proposed have significant robustness properties; they require only a conditional mean assumption, and apply to models with lagged dependent variables, finite distributed lag models that allow arbitrary feedback from the explained to the explanatory variables, and models with contemporaneous endogeneity. The model can be applied to any nonnegative explained variable, including count variables, binary variables, and continuously distributed nonnegative variables. An extension of the basic model applies to certain Euler equation applications with individual data.
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