The Kuhn-Tucker model of Wales and Woodland (1983) provides a utility theoretic framework for estimating preferences over commodities for which individuals choose not to consume one or more of the goods. Due to the complexity of the model, however, there have been few applications in the literature and little attention has been paid to the problems of welfare analysis within the Kuhn-Tucker fra...

Many important economic questions hinge on the extent to which new goods either crowd out or complement consumption of existing products. Recent methods for studying new goods rule out complementarity by assumption, so their applicability to these questions has been limited. I develop a new model that relaxes this restriction, and use it to study competition between print and online newspapers....

Multivariate Discriminant Analysis (MDA) has long been used to classify failing and non-failing firms with high accuracy rates, although a number of methodological flaws are well known. The alternative approach based on Conditional Probability Analysis (CPA) models have been applied to forecast mergers and acquisitions and extended to the prediction of corporate failure. This is used her to dis...

Fertility Assimilation of Immigrants: Evidence from Count Data Models This study applies count data estimation techniques to investigate the fertility adjustment of immigrants in the destination country. Data on completed fertility are taken from the 1996 wave of the German Socioeconomic Panel (GSOEP). While the economic literature stresses the role of prices and incomes as determinants of fert...

We derive forecasts for Markov switching models that are optimal in the MSFE sense by means of weighting observations. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the e↵ect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substan...

In regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, an average treatment effect can be nonparametrically identi ed. We show that the derivative of this treatment effect with respect to the threshold is also nonparametrically identi ed and easily estimated, in both sharp and fuzzy designs. This marginal threshold tr...

This article reports Monte Carlo results on the simulated maximum likelihood estimation of discrete panel statistical models. Among them are Markov, Generalized Poly, Renewal, and Habit Persistence Models with or without unobserved heterogeneity and serially correlated disturbances. We investigate statistical properties and computational performance of simulated maximum likelihood methods and a...

Concern over the distributional effects of policies which induce changes in peer group structure, or ‘associational redistributions’ (Durlauf, 1996c), motivates a substantial body of theoretical and empirical research in economics, sociology, psychology, and education. A growing collection of econometric methods for characterizing the effects of such policies are now available. This chapter sur...

This paper proposes a rank-based estimator for a location parameter in the binary choice model under a monotonic index and symmetry condition, given an initial Jnconsistent estimator for the slope parameter. The estimator converges at the usual parametric rate. Compared with existing estimators, no nonparametric smoothing is needed here. A small Monte Carlo study illustrates the usefulness of t...

This paper provides estimators of discrete choice models, including binary, ordered, and multinomial response (choice) models. The estimators closely resemble ordinary and two stage least squares. The distribution of the model’s latent variable error is unknown and may be related to the regressors, e.g., the model could have errors that are heteroscedastic or correlated with regressors. The est...