The economic analysis of climate change requires estimates at both aggregate and local level. Although there are numerous studies that estimate the global impact of climate change, country-level studies are still rare, particularly as far as Italy is concerned. By exploiting a panel of 110 provinces observed between 1980 and 2014, this paper investigates the impact of variation of weather variables on GDP per capita and agricultural productivity in Italy. To address issues of model uncertainty, the analysis explores to what extent these economic outcomes are affected by weather variables, linearly or non-linearly, as well as how their growth rate and levels are affected as a result. Main findings show that there is considerable model uncertainty. The most robust econometric results showing statistically significant effects of temperature for both the GDP and agricultural reaction function are from a levels specification, where temperature is included in a non-linear form while weather variables and economic outcomes enter in first differences. Projections of the impact of climate change by the end of the century show slight average effects for GDP per-capita, but important losses in agriculture, due to a persistent increase in average temperatures under both the RCPs 4.5 and 8.5.

气候变化的经济分析需要在总体和地方层面进行估计。尽管有许多研究估计气候变化的全球影响，但国家层面的研究仍然很少，尤其是就意大利而言。通过利用 1980 年至 2014 年间观察到的 110 个省的面板，本文调查了天气变量的变化对意大利人均 GDP 和农业生产力的影响。为了解决模型的不确定性问题，分析探讨了这些经济结果在多大程度上受天气变量的影响，线性或非线性，以及它们的增长率和水平如何受到影响。主要发现表明，存在相当大的模型不确定性。显示温度对 GDP 和农业反应函数的统计显着影响的最稳健的计量经济学结果来自水平规范，其中温度包含在非线性形式中，而天气变量和经济结果则进入第一个差异。对本世纪末气候变化影响的预测显示，人均 GDP 的平均影响很小，但由于 RCP 4.5 和 8.5 下平均气温持续升高，农业将遭受重大损失。