论文信息 - A nested Tobit analysis for a sequentially censored regression model

A nested Tobit analysis for a sequentially censored regression model

Abstract This paper proposes a nested Tobit analysis for a sequentially censored regression model. This model is useful for the design and analysis of multiple-step contingent valuation surveys. A consistent maximum likelihood estimation is proposed, and the proper log-likelihood function is derived.

Byung-Joo Lee | Byung-Joo Lee

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