{"title":"Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter","authors":"Sayed Morteza Malaekeh, Layla Shiva, Ammar Safaie","doi":"10.1111/agec.12821","DOIUrl":null,"url":null,"abstract":"<p>In this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non-climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year-to-year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer-term cross-sectional analysis and shorter-term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands’ net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"433-453"},"PeriodicalIF":4.5000,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Economics","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/agec.12821","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non-climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year-to-year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer-term cross-sectional analysis and shorter-term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands’ net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model.
期刊介绍:
Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.