This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten...

This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten...

Fixed effects estimators of panel models can be severely biased because of the well-known incidental parameters problem. We show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large T. We give bias corrections for averages over the fixed...

The central concern of the paper is with the formulation of tests of neglected parameter heterogeneity appropriate for model environments specified by a number of unconditional or conditional moment conditions. We initially consider the unconditional moment restrictions framework. Optimal...

Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias correction method has no effect on the higherorder variance of semiparametrically efficient parametric estimators, so long as the estimate of the bias is asymptotically linear. It is...

Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these...

Treatment effects are often estimated by the least squares estimator controlling for some covariates. This paper investigates its properties. When the propensity score is constant, it is a consistent estimator of the average treatment effects if it is viewed as a semiparametric partially linear...

In this note, we characterize the semiparametric efficiency bound for a class of semi- parametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional...

Many social experiments are run in multiple waves, or are replications of earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for...

Many structural economics models are semiparametric ones in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly nonnested or overlapping conditioning sets, and the finite dimensional parameters of interest are over-identified via...