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DOI	10.1016/j.jeconom.2023.105511
	On model selection criteria for climate change impact studies
	Cui, Xiaomeng; Gafarov, Bulat; Ghanem, Dalia; Kuffner, Todd
发表日期	2024
ISSN	0304-4076
EISSN	1872-6895
起始页码	239
结束页码	1
卷号	239 期号:1
英文摘要	Climate change impact studies inform policymakers on the estimated damages of future climate change on economic, health and other outcomes. In most studies, an annual outcome variable is observed, e.g. agricultural yield, along with a higher -frequency regressor, e.g. daily temperature. Applied researchers then face a problem of selecting a model to characterize the nonlinear relationship between the outcome and the highfrequency regressor to make a policy recommendation based on the model -implied damage function. We show that existing model selection criteria are only suitable for the policy objective if one of the models under consideration nests the true model. If all models are seen as imperfect approximations of the true nonlinear relationship, the model that performs well in the historical climate conditions is not guaranteed to perform well at the projected climate. We therefore propose a new criterion, the proximity -weighted mean squared error (PWMSE) that directly targets precision of the damage function at the projected future climate. To make this criterion feasible, we assign higher weights to historical years that can serve as weather analogsto the projected future climate when evaluating competing models using the PWMSE. We show that our approach selects the best approximate regression model that has the smallest weighted squared error of predicted impacts for a projected future climate. A simulation study and an application revisiting the impact of climate change on agricultural production illustrate the empirical relevance of our theoretical analysis. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
英文关键词	Mixed frequency data; Monte Carlo cross-validation; Information criteria; Aggregation
语种	英语
WOS研究方向	Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences
WOS类目	Economics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods
WOS记录号	WOS:001199467400001
来源期刊	JOURNAL OF ECONOMETRICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/308438
作者单位	University of Jinan; University of California System; University of California Davis; Washington University (WUSTL)
推荐引用方式 GB/T 7714	Cui, Xiaomeng,Gafarov, Bulat,Ghanem, Dalia,et al. On model selection criteria for climate change impact studies[J],2024,239(1).
APA	Cui, Xiaomeng,Gafarov, Bulat,Ghanem, Dalia,&Kuffner, Todd.(2024).On model selection criteria for climate change impact studies.JOURNAL OF ECONOMETRICS,239(1).
MLA	Cui, Xiaomeng,et al."On model selection criteria for climate change impact studies".JOURNAL OF ECONOMETRICS 239.1(2024).