{"title":"气候变化、国家能力和不平衡增长:对印度的分类分析","authors":"Naveen Kumar, Dibyendu Maiti","doi":"10.1016/j.econmod.2025.107311","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines how rising temperatures affect India’s long-term economic growth, both at aggregate and disaggregated levels across regions, sectors, and seasons. Existing research has predominantly relied on pooled estimation with panel data that inadequately address heterogeneity, temperature dynamics, and underlying transmission mechanisms, particularly at disaggregated levels. A cross-sectionally augmented auto-regressive distributed lag model (CS-ARDL) is estimated using panel data that capture state-specific weather-output relationships, long-term impacts, temperature persistence, intra-annual variability, unobserved heterogeneity, and cross-regional spillovers. The findings reveal that, on average, a 1 °C annual temperature variation reduces economic growth by 3.89%, nearly twice the previous estimate. Second, results suggest that annual temperature variation diminishes growth by damaging productivity through reduced ecosystem services, labour, and capital efficiency. Third, state capacity plays a moderating role in shaping regional vulnerability to temperature shocks. Fourth, impacts are heterogeneous, varying by season (greater in winter), region (higher in southern and hotter regions), and across sectors.</div></div>","PeriodicalId":48419,"journal":{"name":"Economic Modelling","volume":"153 ","pages":"Article 107311"},"PeriodicalIF":4.7000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Climate change, state capacity and uneven growth: A disaggregated analysis of India\",\"authors\":\"Naveen Kumar, Dibyendu Maiti\",\"doi\":\"10.1016/j.econmod.2025.107311\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study examines how rising temperatures affect India’s long-term economic growth, both at aggregate and disaggregated levels across regions, sectors, and seasons. Existing research has predominantly relied on pooled estimation with panel data that inadequately address heterogeneity, temperature dynamics, and underlying transmission mechanisms, particularly at disaggregated levels. A cross-sectionally augmented auto-regressive distributed lag model (CS-ARDL) is estimated using panel data that capture state-specific weather-output relationships, long-term impacts, temperature persistence, intra-annual variability, unobserved heterogeneity, and cross-regional spillovers. The findings reveal that, on average, a 1 °C annual temperature variation reduces economic growth by 3.89%, nearly twice the previous estimate. Second, results suggest that annual temperature variation diminishes growth by damaging productivity through reduced ecosystem services, labour, and capital efficiency. Third, state capacity plays a moderating role in shaping regional vulnerability to temperature shocks. Fourth, impacts are heterogeneous, varying by season (greater in winter), region (higher in southern and hotter regions), and across sectors.</div></div>\",\"PeriodicalId\":48419,\"journal\":{\"name\":\"Economic Modelling\",\"volume\":\"153 \",\"pages\":\"Article 107311\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Economic Modelling\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0264999325003062\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Modelling","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0264999325003062","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Climate change, state capacity and uneven growth: A disaggregated analysis of India
This study examines how rising temperatures affect India’s long-term economic growth, both at aggregate and disaggregated levels across regions, sectors, and seasons. Existing research has predominantly relied on pooled estimation with panel data that inadequately address heterogeneity, temperature dynamics, and underlying transmission mechanisms, particularly at disaggregated levels. A cross-sectionally augmented auto-regressive distributed lag model (CS-ARDL) is estimated using panel data that capture state-specific weather-output relationships, long-term impacts, temperature persistence, intra-annual variability, unobserved heterogeneity, and cross-regional spillovers. The findings reveal that, on average, a 1 °C annual temperature variation reduces economic growth by 3.89%, nearly twice the previous estimate. Second, results suggest that annual temperature variation diminishes growth by damaging productivity through reduced ecosystem services, labour, and capital efficiency. Third, state capacity plays a moderating role in shaping regional vulnerability to temperature shocks. Fourth, impacts are heterogeneous, varying by season (greater in winter), region (higher in southern and hotter regions), and across sectors.
期刊介绍:
Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling. The journal prime objective is to provide an international review of the state-of-the-art in economic modelling. Economic Modelling publishes the complete versions of many large-scale models of industrially advanced economies which have been developed for policy analysis. Examples are the Bank of England Model and the US Federal Reserve Board Model which had hitherto been unpublished. As individual models are revised and updated, the journal publishes subsequent papers dealing with these revisions, so keeping its readers as up to date as possible.