Showing 1 - 10 of 134
robustness properties of PAE for estimation and prediction. As illustrations, we report PAE estimates of distributions of …
Persistent link: https://www.econbiz.de/10012295267
Economists are often interested in estimating averages with respect to distributions of unobservables, such as moments of individual fixed-effects, or average partial effects in discrete choice models. For such quantities, we propose and study posterior average effects (PAE), where the average...
Persistent link: https://www.econbiz.de/10012617686
establish two robustness properties of posterior average effects under misspecification of the assumed distribution of …-case bias within a large class of estimators. We establish related robustness results for posterior predictors. In addition, we …
Persistent link: https://www.econbiz.de/10012063813
We propose a framework for estimation and inference about the parameters of an economic model and predictions based on it, when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We derive formulas to...
Persistent link: https://www.econbiz.de/10011912653
We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model,...
Persistent link: https://www.econbiz.de/10012241904
A popular approach to perform inference on a target parameter in the presence of nuisance parameters is to construct estimating equations that are orthogonal to the nuisance parameters, in the sense that their expected first derivative is zero. Such first-order orthogonalization may, however,...
Persistent link: https://www.econbiz.de/10015191457
In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that there are corresponding sufficient conditions for nonparametric models. A nonparametric rank...
Persistent link: https://www.econbiz.de/10009127271
Fixed effects estimators of nonlinear panel data models can be severely biased because of the well-known incidental parameter problem. We develop analytical and jackknife bias corrections for nonlinear models with both individual and time effects. Under asymptotic sequences where the...
Persistent link: https://www.econbiz.de/10010209259
In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities...
Persistent link: https://www.econbiz.de/10009667984
Fixed effects estimators of nonlinear panel data models can be severely biased because of the well-known incidental parameter problem. We develop analytical and jackknife bias corrections for nonlinear models with both individual and time effects. Under asymptotic sequences where the...
Persistent link: https://www.econbiz.de/10010382120