Estimating Macro-Fiscal Effects of Climate Shocks From Billions of Geospatial Weather Observations

IMF Working Papers, July 29, 2022

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Global daily weather measurements with a 30-km spatial resolution from 1979 to 2019.
Constructed 164 weather variables and their lags.
Selected a parsimonious subset of relevant weather variables using an algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO).
Analysis expands beyond GDP per capita to include government revenue, expenditure, and debt.

An increase in the occurrence of high temperatures reduces GDP.
An increase in the occurrence of droughts reduces GDP.
More frequent mild temperatures have a positive impact on GDP.
The share of GDP variations explained by weather, as captured by the handful of selected variables, is much higher than previously implied by using annual temperature and precipitation averages.
Evidence of counter-cyclical fiscal policies that mitigate adverse weather shocks, especially excessive or unusually low precipitation episodes.

High-frequency, high-resolution weather information reveals macroeconomic and fiscal vulnerabilities that annual country-level averages may miss.
Fiscal authorities can and do exhibit counter-cyclical responses to weather shocks; this behavior can mitigate the macro-fiscal consequences of extreme precipitation events.
Incorporating granular weather indicators into macro-fiscal risk assessments may improve identification of climate-related exposures for revenue, expenditure, and debt dynamics.

Source: IMF Working Paper — "Estimating Macro-Fiscal Effects of Climate Shocks From Billions of Geospatial Weather Observations" (July 29, 2022).