U.S. Economic Sensitivity to Weather Variability

Abstract

To estimate the economic effects of weather variability in the United States, the authors define and measure weather sensitivity as the variability in economic output that is attributable to weather variability, accounting for changes in technology and changes in levels of economic inputs (i.e., capital, labor, and energy). Using 24 yr of economic data and weather observations, quantitative models of the relationship between state-level sectoral economic output and weather variability are developed for the 11 nongovernmental sectors of the U.S. economy; temperature and precipitation measures were used as proxies for all weather impacts. All 11 sectors are found to have statistically significant sensitivity to weather variability. Economic inputs were then constant and economic output was estimated in the 11 estimated sector models, varying the weather inputs only using 70 yr of historic weather observations. It was found that U.S. economic output varies by up to $485 billion yr−1 of 2008 gross domestic product, about 3.4%, owing to weather variability. U.S. states that are more sensitive to weather variability are identified and sectors are ranked by their degree of weather sensitivity. This work illustrates a valid approach to measuring the economic impact of weather variability, gives baseline information and methods for more detailed studies of the sensitivity of each sector to weather variability, and lays the groundwork for assessing the value of current or improved weather forecast information given the economic impacts of weather variability.

Evaluation of the ECMWF Sub-seasonal to Seasonal Precipitation Forecasts during the Peak of West Africa Monsoon in Nigeria

“…These time-scales range from short range (1-5 days), to medium range (7-15 days), and long range (3-12 months) (Robertson and Wang, 2012;Vitart et al, 2014;Lawal, 2015). For the past several decades, forecasts of weather, ocean and other environmental phenomena made on short and medium range time-scales have yielded invaluable information to improve decision making across many socioeconomic sectors (Lazo et al, 2011). Yet, there are some fundamental problems that limit the use of these forecasts.…”

Effectiveness of weather derivatives as a hedge against the weather risk in agriculture

“…Lazo et al (2011) confirmed it to be the second most weather sensitive sector of the US economy, following mining, with 12.1% of output being exposed to weather. Within the EU project "Weather Impacts on Natural, Social and Economic Systems -WISE", the impact of weather on agriculture has been studied in the United Kingdom (Subak et al 2000), Netherlands (Tol 2000), Germany (Flechsig et al 2000) and Italy (Galeotti et al 2004).…”

“…If the volatility of output of a certain sector is caused by the changes in weather, the sector is said to be weather sensitive. Studies show that weather sensitivity varies between the economic sectors and geographical areas and that all economic sectors are to some extent weather sensitive (Larsen 2006, Lazo et al 2011.…”

Monitoring of GPS Precipitable Water Vapor During the Severe Flood in Kelantan

“…Nowadays, the accurate weather information is demand due to the strong influence of the weather condition to social and economic activities (Lazo et al, 2011). The information is not only used in weather alert for safety reason, but the more important is for long-term planning such as Southwest Monsoon (SWM) from the end of May to September and the Northeast Monsoon (NEM) from November to March.…”