Extended Data Fig. 1: Constraining the persistence of historical climate impacts on economic growth rates.

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature (a), daily temperature variability (b), total annual precipitation (c), the number of wet days (d) and extreme daily precipitation (e) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a–e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R², Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2. The resulting models without later lags are shown in Supplementary Figs. 1–3.