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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. • We study the economic impact of weather variation on GDP and agriculture in Italy • We exploit a rich panel dataset across 110 territorial units over 1980–2014 period • To address problems of model uncertainty, we compare several different specifications • The "best" performing model is a non-linear specification estimated in first differences • End of the century predictions, suggest nil effects on GDP, but important loss in agriculture. [ABSTRACT FROM AUTHOR]