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How effective is public spending in reducing vulnerability to natural hazards?
How much are communities investing out of their own budget and from federal grants?
What are key driving factors?
GRI Faculty Affiliate, Ivan Petkov, brings his expertise in macroeconomics to find answers as to why differences in cultural and institutional endowments in U.S. counties affect communities’ capabilities to mitigate environmental hazards. To set the stage, Ivan distinguishes federally- and county-funded projects and relied on a quasi-experimental strategy, matching counties by economic development, population, and weather risk, to estimate the loss-reducing effect of local public investments.
Using Microsoft’s spatial building data to predict resident vulnerability and severe weather frequency, Ivan was able to provide precise measures of local vulnerability to weather losses. This is reflected in severe-weather risk measure, which is based on predictions from the Random Forest learning algorithm.
Ivan further finds that the effectiveness of investments based on different funding can vary by the weather risk of the county: federal spending is most effective in high-risk areas, while local spending is effectively implemented in medium-risk counties. Finally, it is shown that fractionalization among residents about the priority of climate-change policy can be a limiting factor in adaptation spending.

Total spending is significantly lower in areas with high diversity in policy preferences, and more so when opinions are equally split. This can explain why counties with similar weather risk may end up with different amount of public spending to reduce vulnerability