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  • two-sided logit model (tslogit) in Stata

    Dear Stata users,

    Firstly, let me briefly introduce two-sided logit (TSL) model. In 1996 John Allen Logan introduced TSL model which
    is a new multivariate method for simultaneously investigating the determinants of individual opportunity and the determinants of choice given opportunity, while giving equal weight to both aspects. The parameters estimated by the model represent the preferences of employers that determine workers' opportunities and the preferences of workers that determine their choices among opportunities. The data requirement is any random sample of individuals, both working and not working, that records their employment-relevant characteristics and the characteristics of jobs they hold. Estimating the preferences of employers using such data requires controlling for selection effects due to individuals' preferences, and vice versa. The model that is developed to make such doubly controlled estimations is called a two-sided logit (TSL) model and is based on an underlying random matching model of the labor market, which itself is a stochastic variant of deterministic models studied in game theory (e.g., Roth and Sotomayor 1990). Though the underlying model represents individual jobs being evaluated by workers, actual estimation makes use of the average characteristics of jobs within broad occupational categories rather than the characteristics of particular jobs.
    The original article can be found here https://www.jstor.org/stable/2782189 The difference between TSL model and multivariate log-linear models is that the former takes account of demand insensitivity when applied to labor market outcomes, including occupational mobility tables.
    John Logan had developed a DEC/SUN version program (http://lib.stat.cmu.edu/general/tslogit), and a compiled Fortran version. Both versions are environment dependent, thus difficult to be run in computer nowadays. I eagerly hope that someone in this Forum can hack and rewrite the program in Stata if it is allowed in copyright framework.
    Last edited by Chen Samulsion; 02 Apr 2019, 10:13.
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