on an empirical likelihood ratio. The computations necessary for obtaining a test statistic also provide estimates of the … be used to perform bootstrap tests that can turn out to provide much improved reliability of inference compared with the …

We propose a specification test for a wide range of parametric models for the conditional distribution function of an … outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted … an empirical application, we use our test to study the validity of various models for the conditional distribution of …

Average Treatment Effects. The tests allow researchers not only to test for selection on either or both of the treated and …

real effects; and (iii) feasible GLS estimation combined with robust inference can increase power considerably whilst …A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic … maintaining correct test size – again, even with few groups …

trivial due to the incidental parameters problem that arises, and its implications for estimation and inference. We approach … that are robust to cross-sectional heteroskedasticity of unknown form. By means of Monte Carlo simulation, we investigate … proposed in the literature. Simulation results reveal that, in terms of median absolute errors and accuracy of inference, the …

and may lead to an invalid statistical inference even when the test value is positive. With a correct specification of the … with a Hausman-McFadden test. As is confirmed by many findings in the literature, this test sometimes produces negative …

statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression … representation methods on visual inference using randomized experiments. We find that bin widths and fit lines have the largest … compare visual inference with widely used econometric inference procedures. We find that visual inference achieves similar or …

uniformly valid inference on function-valued objects. This avoids coefficient re-estimation and is shown to be consistent for a …