There exist a number of important applications in which interest centers on the sign rather than the overall shape of a mean regression. These include certain decision-making problems as well as the problems of calibration and econometric equation inversion. We show that the sign of a mean...

Nonparametric regression is often considered as unreliable in small samples when the number of regressors is large. This may be different if the dependent variable is bounded. First, the small-sample properties of nonparametric regression with 14 regressors (4 continuous, 10 binary) are...

This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the...

We consider the regression discontinuity (RD) design with categorical outcomes, and exploit the possibility of adapting well-developed microeconometric models to the RD setting. The channels through which the forcing variable affects the potential outcome distributions are constrained to be...

The most familiar fixed effects (FE) and random effects (RE) panel data treatments for count data were proposed by Hausman, Hall and Griliches (HHG) (1984). The Poisson FE model is particularly simple and is one of a small few known models in which the incidental parameters problem is, in fact,...

This study presents several extensions of the most familiar models for count data, the Poisson and negative binomial models. We develop an encompassing model for two well known variants of the negative binomial model (the NB1 and NB2 forms). We then propose some alternative approaches to the...

This paper estimates the average structural function and partial effects of endogenous regressors in binary response models using a special regressor. We present formal asymptotic theory for the proposed logistic series estimator and estimate migration probabilities within the US

The Random Utility Model (RUM) is a workhorse model for valuing new products or changes in public goods. But RUMs have been faulted along two lines. First, for including idiosyncratic errors that imply unreasonably high values for new alternatives and unrealistic substitution patterns. Second,...

This paper deals with the identification of treatment effects when the outcome variable is ordered. If outcomes are measured ordinally, previously developed methods to investigate the impact of an endogenous binary regressor on average outcomes cannot be applied as the expectation of an ordered...