Often, economic policies are directed toward outcomes that are measured as counts. Examples of economic variables that use a basic counting scale are number of children as an indicator of fertility, number of doctor visits as an indicator of health care demand, and number of days absent from...

This paper proposes a procedure for testing alternative specifications of the short term interest rate's dynamics which takes into account that according to some restrictions the interest rate is nonstationary, i.e. the traditional test statistic has a non-standard distribution. Moreover, we do...

The paper proposes two estimation approaches for duration models that are subject to right censored observations and selection effects. Main focus is on accelerated duration models and the estimators that are of the limited information type, i.e. they are not based on a fully specified selection...

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest which follow...

Hausman (1978) developed a widely-used model specification test that has passed the test of time. The test is based on two estimators, one being consistent under the null hypothesis but inconsistent under the alternative, and the other being consistent under both the null and alternative...

This paper studies the identification of coefficients in generalized linear predictors where the outcome variable suffers from non-classical measurement errors. Combining a mixture model of data errors with the bounding procedure proposed by Stoye (2007), I derive bounds on the coefficient...

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

This paper investigates the effects of ordinal regressors in linear regression models. Each ordered categorical variable is interpreted as a rough measurement of an underlying continuous variable as it is often done in microeconometrics for the dependent variable. It is shown that using ordinal...

This papers describes an estimator for a standard state-space model with coefficients generated by a random walk that is statistically superior to the Kalman filter as applied to this particular class of models. Two closely related estimators for the variances are introduced: A maximum...