2019The Stata Journal Promoting communications on statistics and StataOpen access

Estimation methods in the presence of corner solutions

Alfonso Sánchez-Peñalver

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Abstract

In this article, I introduce a new command, nehurdle, that collects maximum likelihood estimators for linear, exponential, homoskedastic, and heteroskedastic tobit; truncated hurdle; and type II tobit models that involve explained variables with corner solutions. I review what a corner solution is as well as the assumptions of the mentioned models.

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What this paper is about

In this article, I introduce a new command, nehurdle, that collects maximum likelihood estimators for linear, exponential, homoskedastic, and heteroskedastic tobit; truncated hurdle; and type II tobit models that involve explained variables with corner solutions. I review what a corner solution is as well as the assumptions of the mentioned models.

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Available abstract

In this article, I introduce a new command, nehurdle, that collects maximum likelihood estimators for linear, exponential, homoskedastic, and heteroskedastic tobit; truncated hurdle; and type II tobit models that involve explained variables with corner solutions. I review what a corner solution is as well as the assumptions of the mentioned models.

Key concepts: Heteroscedasticity, Tobit model, Estimator, Mathematics, Maximum likelihood, Econometrics, Exponential function, Estimation

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