The New Zealand Regional Housing Model (NZRHM) includes estimated equations for four key housing market variables: house prices, housing supply (new dwelling consents), residential vacant land (lot) prices, and average rents. Long run (cointegration) relationships and short run (error correction) relationships are estimated for each of these variables across 72 TLAs within New Zealand. The model is designed so that it can be used for short to medium term forecasting. It is also useful for simulating the effects of shocks to the housing market. The paper presents simulations of the impacts of shocks to exogenous variables (population, credit restrictions, construction costs and farm prices) as well as shocks to policy variables (developer contributions, accommodation supplement, and land availability). We also simulate the consequences of the Christchurch earthquakes for Canterbury housing outcomes. The over-arching conclusion across all simulations is that housing markets are very slow to adjust to disequilibria, such that exogenous shocks have very long lasting effects on prices and the housing stock.
We analyze the multiple channels of influence that global financial crisis-induced credit restrictions had on New Zealand's subnational housing markets. The dynamics caused by the credit shock are compared to those caused by a migration shock, a more common form of housing shock in New Zealand. We focus on the impacts on two outcome variables, house prices and housing supply, within a structural time series model of regional housing markets. Both shocks cause substantial and prolonged cyclical adjustments in each variable. Similar cyclical dynamics could complicate the conduct of macroprudential policies designed to affect bank credit allocation. (JEL E32, E44, R21)
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The extent to which exogenous international agricultural price fluctuations are internalised by rural communities is of major interest for policy-makers concerned with regional economic performance. So too is the link between rural sector performance and urban outcomes, especially in agriculturally-based economies. Through vector autoregressive (VAR) modelling we estimate the causal effect of exogenous commodity price innovations on both rural and urban community outcomes. Our analysis demonstrates that restricting the focus to national effects may lead to incorrect inference. We therefore extend the analysis to a VAR using panel data covering all New Zealand districts over 19912011. House prices and housing investment are used as quarterly indicators of regional economic and population outcomes. By exploiting the variation in production bundles across communities we find that an increase in commodity prices leads to a permanent increase in housing investment and house prices across the country. However, we find that rural communities are relatively insulated from commodity price shocks, whereas urban areas are most affected by commodity price shocks. We discuss the reasons why this paradoxical result may arise.
The New Zealand Regional Housing Model (NZRHM) includes estimated equations for four key housing market variables: house prices, housing supply (new dwelling consents), residential vacant land (lot) prices, and average rents. Long run (cointegration) relationships and short run (error correction) relationships are estimated for each of these variables across 72 TLAs within New Zealand. The model is designed so that it can be used for short to medium term forecasting. It is also useful for simulating the effects of shocks to the housing market. The paper presents simulations of the impacts of shocks to exogenous variables (population, credit restrictions, construction costs and farm prices) as well as shocks to policy variables (developer contributions, accommodation supplement, and land availability). We also simulate the consequences of the Christchurch earthquakes for Canterbury housing outcomes. The overarching conclusion across all simulations is that housing markets are very slow to adjust to disequilibria, such that exogenous shocks have very long lasting effects on prices and the housing stock.
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