The role of real estate uncertainty in predicting US home sales growth: evidence from a quantiles-based Bayesian model averaging approach

C-Tier
Journal: Applied Economics
Year: 2020
Volume: 52
Issue: 5
Pages: 528-536

Score contribution per author:

0.335 = (α=2.01 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper investigates the role of real estate-specific uncertainty in predicting the conditional distribution of US home sales growth over the monthly period of 1970:07 to 2017:12, based on Bayesian Model Averaging (BMA) to account for model uncertainty. After controlling for standard predictors of home sales (housing price, mortgage rate, personal disposable income, unemployment rate, building permits, and housing starts), and macroeconomic and financial uncertainties, our results from the quantile BMA (QBMA) model show that real estate uncertainty has predictive content for the lower and upper quantiles of the conditional distribution of home sales growth.

Technical Details

RePEc Handle
repec:taf:applec:v:52:y:2020:i:5:p:528-536
Journal Field
General
Author Count
3
Added to Database
2026-01-25