TY - JOUR
T1 - Are housing price cycles asymmetric? Evidence from the US States and metropolitan areas
AU - André, Christophe
AU - Gupta, Rangan
AU - Muteba Mwamba, John W.
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/11
Y1 - 2019/11
N2 - This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.
AB - This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.
KW - Asymmetry
KW - House prices
KW - US economy
UR - http://www.scopus.com/inward/record.url?scp=85064611235&partnerID=8YFLogxK
U2 - 10.3846/ijspm.2019.6361
DO - 10.3846/ijspm.2019.6361
M3 - Article
AN - SCOPUS:85064611235
SN - 1648-715X
VL - 23
SP - 1
EP - 22
JO - International Journal of Strategic Property Management
JF - International Journal of Strategic Property Management
IS - 1
ER -