The paper discusses the effect of model deviations such as data contamination on the maximum likelihood estimator (MLE) for a general class of latent trait models (citeNP{MoKn:00}). This is done with the use of the influence function (Hampel 1968, 1974) a mathematical tool to assess the...

In this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed. It is found that the MLE and the classical Rao's score test can be misleading in the presence of model...

We augment the increasingly common practice of typically ad hoc robustness tests into a research methodology that allows reliable inferences when researchers do not know the true data-generating process. We identify three principal sources of model uncertainty. First, theories simplify and aim...

We develop new tail-trimmed QML estimators for nonlinear GARCH models with possibly heavy tailed errors. Tail-trimming allows both identification of the true parameter and asymptotic normality. In heavy tailed cases the rate of convergence is below but arbitrarily close to root-n, the highest...

For predictive quantile regressions with highly persistent regressors, a conventional test statistic suffers from a serious size distortion and its limiting distribution relies on the unknown persistence degree of predictors. This paper proposes a double-weighted approach to offer a robust...

This article proposes doubly robust estimators for the average treatment effect on the treated (ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID estimators, the proposed estimators are consistent if either (but not necessarily both) a propensity score or...

This paper presents simulation results on the robustness of normal parametric inference in non-linear mixed models. A linearization approach to inference is compared with two two-stage methods (standard two-stage, STS, and global two-stage, GTS). When the assumptions of normality of the...

This paper takes a revealed preference approach for set identifying the discount factor in the exponential discounting model. My methodology allows for measurement error in prices and full heterogeneity in preferences. Using longitudinal data from checkout scanners, I obtain bounds on the...