Semi-Parametric and Parametric Estimations and Tests of Adoption: An Application to Bovine Somatotropin Technology

半參數與參數估計法之比較與檢定：以荷爾蒙生長激素之採用為例

張宏浩(Hung-Hao Chang) ； Loren W. Tauer

《農業與經濟》 35期 (2005/12) Pp. 1-26

摘要

在許多實證領域中，參數估計法已經普遍地應用到二維選擇模型之探討，但是研究者往往忽略檢定此模型背後之基本假設。本文以紐約州酪農之生長賀爾蒙激素採用為例，來說明檢定參數二維選擇模型之重要性，並對傳統模型與限制較少的半參數估計法之估計結果加以比較。本文顯示，傳統的Probit模型不但高估了實際的賀爾蒙生長激素採用率，並且高估了此賀爾蒙生長激素對牛奶產量之成效。

關鍵字

賀爾蒙生長激素 ； 模型辨識檢定 ； 半參數估計法

並列摘要

Although the parametric model is widely used for analyzing binary choice behavior, that approach is sensitive to model misspecification. We use the rBST adoption behavior of New York State dairy farms as an application to illustrate the impact of this misspecification. In our application the conventional Probit model over predicts the adoption rate, and over estimates the impact of rBST on milk production per cow; almost twice the impact compared to the semi-parametric estimation.

並列關鍵字

rBST ； specification test ； semi-parametric estimation

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