The celebrated Heckman selection model yields a selection correction function (control function) proportional to the inverse Mills ratio, which is monotone. This paper studies a sample selection model which does not impose parametric distributional assumptions on the latent error terms, while...

This paper is concerned with the semiparametric estimation of function means that are scaled by an unknown conditional density function. Parameters of this form arise naturally in the consideration of models where interest is focused on the expected value of an integral of a conditional...

The most-noted studies on the impact of microcredit on households are based on a survey fielded in Bangladesh in the 1990s. Contradictions among them have produced lasting controversy and confusion. Pitt and Khandker (PK, 1998) apply a quasi-experimental design to 1991–92 data; they conclude...

This paper presents maximum score type estimators for linear, binomial, tobit and truncated regression models. These estimators estimate the normalized vector of slopes and do not provide the estimator of intercept, although it may appear in the model. Strong consistency is proved. In addition,...

This paper presents maximum score type estimators for linear, binomial, tobit and truncated regression models. These estimators estimate the normalized vector of slopes and do not provide the estimator of intercept, although it may appear in the model. Strong consistency is proved. In addition,...

A new approach to limited-dependent variable count data or other model types is considered. Instead of adopting maximum likelihood estimation based on a full distributional assumption or smoothing techniques and semiparametric estimation, the novel idea is to use an approximation to the...

In this paper we provide semiparametric estimation strategies for a sample selection model with a binary dependent variable. To the best of our knowledge, this has not been done before. We propose a control function approach based on two di erent identifying assumptions. This gives rise to...

This paper analyzes spatial Probit models for cross sectional dependent data in a binary choice context. Observations are divided by pairwise groups and bivariate normal distributions are specified within each group. Partial maximum likelihood estimators are introduced and they are shown to be...

We replicate and reanalyse the most influential study of microcredit impacts (Pitt and Khandker, 1998). That study was celebrated for showing that microcredit reduces poverty, a much hoped-for possibility (though one not confirmed by recent randomized controlled trials). We show that the...

This paper is concerned with the semiparametric estimation of function means that are scaled by an unknown conditional density function. Parameters of this form arise naturally in the consideration of models where interest is focused on the expected value of an integral of a conditional...