Purpose
The purpose of this study is to assess the symmetric and asymmetric impact of a measure of policy uncertainty on house permits issued in each state of the USA.
Design/methodology/approach
To assess the symmetric effects, the authors use Pesaran et al.’s (2001) linear autoregressive distributed lag (ARDL) approach to error-correction modeling. To assess the asymmetric effects, they rely upon Shin et al.’s (2014) nonlinear ARDL approach to error-correction modeling. Both approaches have the advantage of producing short-run and long-run effects in one step.
Findings
The authors find short-run symmetric effects of policy uncertainty on house permits issued in 22 states that lasted into the long run in three states only. However, the numbers were much higher when they estimated the possibility of asymmetric effects of policy uncertainty. Indeed, they found short-run asymmetric effects in 38 states and long-run asymmetric effects in 18 states.
Originality/value
Some previous studies assessed the effects of a measure of policy uncertainty on house prices. In this paper, the authors extend the same analysis to the supply side of the housing market by assessing the effects of policy uncertainty on house permits in each state of the USA.
Increased issuance of housing permits is said to move house prices in either
direction. If perceived as an indication of a growing housing supply, house prices are
expected to decline (supply hypothesis). However, a larger number of housing permits can
also reflect positive expectations about future housing demand which would drive house
prices upwards (demand hypothesis). We test these two competing hypotheses by using data
from each state in the United States. We estimate linear and non-linear models to test
if housing permit issuance determines house prices. The results show support for both
the supply and demand hypotheses in the short run for most states but only for the
demand hypothesis in the long run. We also uncover asymmetric short run and long-run
effects in 21 states
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