Comovements and asymmetric tail dependence in state housing prices in the USA: A nonparametric approach

B-Tier
Journal: Journal of Applied Econometrics
Year: 2019
Volume: 34
Issue: 5
Pages: 843-849

Authors (3)

Haitao Huang (not in RePEc) Liang Peng (not in RePEc) Vincent W. Yao (Georgia State University)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

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

Abstract

We reexamine the methods used in estimating comovements among US regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi‐maximum likelihood estimator. Hence we propose applying the self‐weighted quasi‐maximum exponential likelihood estimator and a bootstrap method to test and account for the asymmetry of comovements as well as different magnitudes across state pairs. Our results reveal interstate asymmetric tail dependence based on observed house price indices rather than residuals from fitting autoregressive–generalized autoregressive conditional heteroskedasticity (AR‐GARCH) models.

Technical Details

RePEc Handle
repec:wly:japmet:v:34:y:2019:i:5:p:843-849
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-29