Often, a treatment and the outcome of interest are characterized by the moment they occur, and these moments are realizations of stochastic processes with dependent unobserved determinants. We develop a simple and intuitive method for inference on the treatment effect. The method can be...

Often, a treatment and the outcome of interest are characterized by the moment they occur, and these moments are realizations of stochastic processes with dependent unobserved determinants. We develop a simple and intuitive method for inference on the treatment effect. The method can be...

This paper introduces an alternative testing procedure to test the distribution of the error term in the Autoregressive Conditional Duration (ACD) class of models. In these models, the error term is normally interpreted as the standardized duration by which its probability distribution may have...

For a time-continuous discrete-state Markov process as model for rating transitions, we study the time-stationarity by means of a likelihood ratio test. For multiple Markov process data from a multiplicative intensity model, maximum likelihood parameter estimates can be represented as martingale...

This paper considers inference for conditional moment inequality models using a multiscale statistic. We derive the asymptotic distribution of this test statistic and use the result to propose feasible critical values that have a simple analytic formula. We also propose critical values based on...

This paper considers inference for conditional moment inequality models using a multiscale statistic. We derive the asymptotic distribution of this test statistic and use the result to propose feasible critical values that have a simple analytic formula, and to prove the asymptotic validity of a...

A common practice in modeling intertrade durations is to use various hazard functions for data fitting. This paper calls into question this practice and suggests mixing the hazard function as exponential. An underlying hypothesis of the suggestion is that duration data have a mixture of...

I expose the risk of false discoveries in the context of multiple treatment effects. A false discovery is a nonexistent effect that is falsely labeled as statistically significant by its individual t-value. Labeling nonexistent effects as statistically significant has wide-ranging academic and...

This paper shows how to increase the power of Hausman's (1978) specification test as well as the difference test in a large class of models. The idea is to impose the restrictions of the null and the alternative hypotheses when estimating the covariance matrix. If the null hypothesis is true...