This paper uses recent data for Germany and a new outcome variable to assess the consequences of parental separation on the well-being of youths. In particular, it is considered how subjective well-being, elicited from an ordinal 11-point general life satisfaction question, differs between youths living in intact and non-intact families, holding many other potential determinants of well-being c...

I consider the problem of evaluating the effect of a health care reform on the demand for doctor visits when the effect is potentially different in different parts of the outcome distribution. Quantile regression is a useful technique for studying such heterogeneous treatment effects. Recent progree has been made to extend such methods to applications with a count dependent variable. An analysi...

This paper introduces a Lagrange Multiplier (LM) test for testing an autoregressive structure in a binary time series model proposed by Kauppi and Saikkonen (2008). Simulation results indicate that the two versions of the proposed LM test have reasonable size and power properties when the sample size is large. A parametric bootstrap method is suggested to obtain approximately correct sizes also...

We present a new prior and corresponding algorithm for Bayesian analysis of the multinomial probit model. Our new approach places a prior directly on the identi"ed parameter space. The key is the speci"cation of a prior on the covariance matrix so that the (1,1) element if "xed at 1 and it is possible to draw from the posterior using standard distributions. Analytical results are derived which ...

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...

Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the corresponding distribution of the number of events during a fixed period and extend it to account for obse...

Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the corresponding distribution of the number of events during a fixed period and extend it to account for obse...

This paper examines GMM and ML estimation of econometric models and the theory of Hausman tests with sampling weights. Weighted conditional GMM can be more e$cient than weighted conditional MLE, an ine$cient alternative to full information MLE under choice-based sampling, unless regressions have homoscedastic additive disturbances or sampling weights are independent of exogenous variables. GMM ...

We use panel probit models with unobserved heterogeneity and serially correlated errors in order to analyze the determinants and the dynamics of current-account reversals for a panel of developing and emerging countries. The likelihood evaluation of these models requires high-dimensional integration for which we use a generic procedure known as Efficient Importance Sampling (EIS). Our empirical...

Four model selection methods are applied to the problem of predicting business cycle turning points: equally-weighted forecasts, Bayesian model averaged forecasts, and two models produced by the machine learning algorithm boosting. The model selection algorithms condition on different economic indicators at different forecast horizons. Models produced by BMA and boosting outperform equally-weig...