Forecasting US real house price returns over 1831–2013 : evidence from copula models

Loading...
Thumbnail Image

Authors

Gupta, Rangan
Majumdar, Anandamayee

Journal Title

Journal ISSN

Volume Title

Publisher

Routledge

Abstract

Given the existence of non-normality and nonlinearity in the data generating process of real house price returns over the period of 1831-2013, this paper compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1859-2013, based on an in-sample of 1831-1873. Overall, our results provide overwhelming evidence in favor of the copula models (Normal, Student’s t, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’s t copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for non-normality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data.

Description

Keywords

House price, Copula models, Forecasting

Sustainable Development Goals

Citation

Rangan Gupta & Anandamayee Majumdar (2015) Forecasting US real house price returns over 1831–2013: evidence from copula models, Applied Economics, 47:48, 5204-5213, DOI:10.1080/00036846.2015.1044648.