This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has non- and semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern applied analysis and econometrics syllabus. We describe the implementation of these models in the package sampleSelection and illustrate the usage of the package on several simulation and real data examples. Our examples demonstrate the effect of exclusion restrictions, identification at infinity and misspecification. We argue that the package can be used both in applied research and teaching
Sample selection models attempt to correct for non-randomly selected data in a two-model hierarchy w...
This paper develops methods of Bayesian inference in a sample selection model. The main feature of t...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...
This paper describes the implementation of Heckman-type sample selection models in R. We discuss the...
This paper describes the implementation of Heckman-type sample selection models in R. We discuss the...
The aim of this paper is to describe the implementation and to provide a tutorial for the R package ...
The aim of this paper is to describe the implementation and to provide a tutorial for the R package ...
We provide a detailed hands-on tutorial for the R package SemiParSampleSel (version 1.5). The packag...
Sample selection arises when the outcome of interest is partially observed in a study. A common cha...
Sample selection models deal with the situation in which an outcome of interest is observed for a re...
Sample selection models deal with the situation in which an outcome of interest is observed for a r...
This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979)...
The problem of non-random sample selectivity often occurs in practice in many different fields. In p...
Sample selection arises when the outcome of interest is partially observed in a study. Although soph...
The problem of non-random sample selectivity often occurs in practice in many fields. The classical ...
Sample selection models attempt to correct for non-randomly selected data in a two-model hierarchy w...
This paper develops methods of Bayesian inference in a sample selection model. The main feature of t...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...
This paper describes the implementation of Heckman-type sample selection models in R. We discuss the...
This paper describes the implementation of Heckman-type sample selection models in R. We discuss the...
The aim of this paper is to describe the implementation and to provide a tutorial for the R package ...
The aim of this paper is to describe the implementation and to provide a tutorial for the R package ...
We provide a detailed hands-on tutorial for the R package SemiParSampleSel (version 1.5). The packag...
Sample selection arises when the outcome of interest is partially observed in a study. A common cha...
Sample selection models deal with the situation in which an outcome of interest is observed for a re...
Sample selection models deal with the situation in which an outcome of interest is observed for a r...
This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979)...
The problem of non-random sample selectivity often occurs in practice in many different fields. In p...
Sample selection arises when the outcome of interest is partially observed in a study. Although soph...
The problem of non-random sample selectivity often occurs in practice in many fields. The classical ...
Sample selection models attempt to correct for non-randomly selected data in a two-model hierarchy w...
This paper develops methods of Bayesian inference in a sample selection model. The main feature of t...
In this thesis estimators for "fixed-effects" panel data sample selection models are discussed, most...