空间样本选择模型*

IF 1.5 3区经济学 Q2 ECONOMICS

Oxford Bulletin of Economics and Statistics Pub Date : 2024-01-27 DOI:10.1111/obes.12599

Yong Bao, Gucheng Li, Xiaotian Liu

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引用次数: 0

摘要

本文提出了一个选择变量和结果变量具有空间相关性的样本选择模型，并研究了最大似然估计方法。最大似然估计法的一致性和渐近正态性是通过变量的空间近距依赖特性建立起来的。蒙特卡罗模拟显示了其良好的有限样本性能。该模型用于研究气候变化对东南亚谷物产量的影响，预测在最小变化（最大变化）情景下，气候变化可能导致谷物产量减少 7%$$ 7\%$$ （31%$$ 31\%$$ ）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Spatial Sample Selection Model*

This paper presents a sample selection model with spatial correlation in the selection and outcome variables and studies the maximum likelihood method of estimation. Consistency and asymptotic normality of the maximum likelihood estimator are established by the spatial near-epoch dependent properties of the variables. Monte Carlo simulations show its good finite-sample performance. This model is used to examine the impact of climate change on cereal yields in Southeast Asia and projects that climate change may cause a reduction in cereal yields by $7 %$ ( $31 %$ ) in the minimum-change (maximum-change) scenario.

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来源期刊

Oxford Bulletin of Economics and Statistics 管理科学-统计学与概率论

CiteScore

5.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Whilst the Oxford Bulletin of Economics and Statistics publishes papers in all areas of applied economics, emphasis is placed on the practical importance, theoretical interest and policy-relevance of their substantive results, as well as on the methodology and technical competence of the research. Contributions on the topical issues of economic policy and the testing of currently controversial economic theories are encouraged, as well as more empirical research on both developed and developing countries.