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input choices. We introduce a new method that exploits (increasingly available) data on a firm’s expectations of its future … demand assumptions. In contrast to dynamic panel methods, our proposed estimator can be implemented on very short panels … our proposed estimator yields results that are either similar to or more credible than commonly-used alternatives. These …
Persistent link: https://www.econbiz.de/10014577758
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This paper extends Imbens and Manski’s (2004) analysis of confidence intervals for interval identified parameters. For their final result, Imbens and Manski implicitly assume superefficient estimation of a nuisance parameter. This appears to have gone unnoticed before, and it limits the...
Persistent link: https://www.econbiz.de/10003739665
penalized sieve minimum distance (SMD) estimator of the unknown functions that are identified via the conditional moment models … important applications: root-n asymptotic normality of the plug-in penalized SMD estimator of a weighted average derivative of a …
Persistent link: https://www.econbiz.de/10003739667
Suppose that a target function is monotonic, namely weakly increasing, and an original estimate of this target function is available, which is not weakly increasing. Many common estimation methods used in statistics produce such estimates. We show that these estimates can always be improved with...
Persistent link: https://www.econbiz.de/10003739689
-smooth indicators. The GEL class includes a number of estimators recently introduced as alternatives to the efficient GMM estimator …. In particular, a number of these tests avoid the necessity of providing an estimator for the Jacobian matrix which may be …
Persistent link: https://www.econbiz.de/10003739699
We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables. We treat models in which Y is censored from above or below or potentially from both. The basic idea...
Persistent link: https://www.econbiz.de/10003739704
We consider cross-sectional data that exhibit no spatial correlation, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entailing a form of spatial autoregression, can explain such behaviour. The...
Persistent link: https://www.econbiz.de/10003765993
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