This paper focuses on estimating limited dependent variable models with incidentally truncated data and two selection mechanisms. While typical sample selection models have been widely estimated, extensions to multiple selection mechanisms have been sparse due to intractable likelihood functions...

This paper focuses on estimating sample selection models with two incidentally truncated outcomes and two corresponding selection mechanisms. The method of estimation is an extension of the Markov chain Monte Carlo (MCMC) sampling algorithm from Chib (2007) and Chib et al. (2009). Contrary to...