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Title: A Vector Autoregression Analysis of Quantitative Easing's Housing Sector Impacts in the United States
Authors: Feng, James
Advisors: Fan, Jianqing
Department: Operations Research and Financial Engineering
Class Year: 2014
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.
Extent: 101
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2017

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