A Vector Autoregression Analysis of Quantitative Easing's Housing Sector Impacts in the United States

Abstract

We investigate the effects of Federal Reserve quantitative easing (QE) on the U.S. housing sector. Using vector autoregression (VAR) models, we conditionally forecast building permits, starts, and completions for privately-owned housing units, as well as new single-family home sales, over QE-on and QE-o scenarios. We assume the transmission mechanism for QE to be its compression of the 10-year-3-month Treasury yield spread, which we vary between our forecasting scenarios. We take the difference of our forecasted housing variables over these QE-on and QE-o scenarios to be the quantified effect of QE, and find that QE1 on average lifted permits about 2%, starts and completions around 3%, and new home sales by half a percent for each month of its duration. We additionally find that QE2 had similar but smaller effects, on average raising permits about 1%, starts about 2%, completions a few tenths of a percent, and sales around 1% for each month of its duration.