This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988) that can be used to estimate binary choice models. This method only asumes that the median of the disturbances of the econometric model takes the value zero. We compare Maximum Score with the...

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on...

A simple example is provided that shows that one test can strictly dominate another test in both local power and its robustness to asymptotic size distortion under local model misspecification, with both tests having asymptotic size equal to nominal size under correct model specification....

In this paper, several tests are suggested for the existence of individual and time effects in panel data models with interactive effects. Their asymptotic properties are obtained under some mild conditions. Monte Carlo simulation is carried out for illustration.

We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter under the null hypothesis. The resulting test is adaptive rate-optimal and consistent against Pitman local...

Conventional time series analysis, focusing exclusively on a time series at a given scale, lacks the ability to explain the nature of the data generating process. A process equation that successfully explains daily price changes, for example, is unable to characterize the nature of hourly price...

While there is growing evidence that stock prices do not follow pure random walks, the degree of existence of temporary components in stock prices is not well known. Modelling stock prices as the sum of a random walk and a general stationary (predictable) component, we propose an estimable lower...