Blame It On the Rain: Weather Shocks and Retail Sales
70 Pages Posted: 28 May 2019
Date Written: January 12, 2016
Failure to attribute retail sales variation to weather shocks can result in biased demand forecasts, misinterpretation of nancial indicators, and undue volatility in commission-based pay. I estimate retail sales responses to weather shocks using proprietary national daily store-level apparel and sporting goods sales data combined with a weather index. Developed using the lasso method, this index allows for seasonally and regionally heterogeneous nonlinear responses. The worst 5 percent of weather shocks decrease daily store sales by 20 percent. These losses are permanent with limited shifting of sales between indoor and outdoor malls and no substitution to e-commerce.
Keywords: Weather, lasso, machine learning, retail sales, adaptation
JEL Classification: Q54, L81, C5
Suggested Citation: Suggested Citation