Effect of temperature on spanish production

Autores: Pablo-Romero, M.P.; Sánchez-Braza, A.; González-Jara, D.

Datos de publicación: Environment, Development and Sustainability, 2025.

https://doi.org/10.1007/s10668-025-06307-z

Abstract

Tackling climate change is one of the most important issues facing the world nowadays. Understanding the impact of rising temperatures on vulnerable territories is crucial. The main objective of this study is to analyze the influence of temperature on the on production per person employed in the Spanish provinces and to assess whether the effect is uniform across temperature levels and territories. A panel data econometric analysis of the Spanish provinces is conducted. The analysis is conducted using an extended translog production function that incorporates cooling and heating degree days and their squares as measures of cold and hot temperatures, respectively. The Driscoll and Kraay standard errors estimator and the generalized method of moments are used to account for the cross-sectional dependence and to tackle potential endogeneity. Furthermore, a quantile model is employed to analyze whether temperature variables affect the Spanish provinces differently. The findings show that average temperatures above 22 °C are detrimental to production, while below 15 °C have a positive effect. Moreover, the adverse impact of high temperatures on production becomes more pronounced as temperatures rise. The findings also demonstrate significant variations in the impact of temperature across territory, with the influence of temperature on production varying according to the geographical location of the provinces, and the most productive provinces being most negatively affected by high temperatures. It is considered appropriate to prioritize efforts in areas with higher temperatures, where greater negative impacts are observed, without using economic prosperity as a guideline for not applying adaptation policies.

Keywords

  • GDP
  • Temperature
  • HDD
  • CDD
  • Inland and coastal zones
  • Spain
  • Local analysis
  • Quantile regression

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