2008•Applied EconomicsRequires access

Determinants of housing price volatility in Canada: a dynamic analysis

Belayet Hossain, Ehsan Latif

Open publisher page 71 citations

Abstract

This article tries to identify the determinants of housing price volatility and to examine the dynamic effects of these determinants on volatility using quarterly data for Canada. The Generalized Autoregressive Conditional Heteroskedastic (GARCH) and the Vector Autoregressive (VAR) models have been employed to analyse possible time variation of the housing price volatility and the interactions between the volatility and the key macroeconomic variables. We find the evidence of time varying housing price volatility for Canada. Our VAR, Granger causality and variance decomposition (VDC) analyses demonstrate that housing price volatility is affected significantly by gross domestic product (GDP) growth rate, housing price appreciation rate and inflation. On the other hand, volatility affects GDP growth rate, housing price appreciation and volatility itself. The impulse response analysis reveals the asymmetric of the positive and negative shocks. The findings of this article have important implications, particularly for those seeking to develop derivatives for housing market prices.

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What this paper is about

This article tries to identify the determinants of housing price volatility and to examine the dynamic effects of these determinants on volatility using quarterly data for Canada. The Generalized Autoregressive Conditional Heteroskedastic (GARCH) and the Vector Autoregressive (VAR) models have been employed to analyse possible time variation of the housing price volatility and the interactions between the volatility and the key macroeconomic variables. We find the evidence of time varying housing price volatility for Canada. Our VAR, Granger causality and variance decomposition (VDC) analyses demonstrate that housing price volatility is affected significantly by gross domestic product (GDP) growth rate, housing price appreciation rate and inflation. On the other hand, volatility affects GDP growth rate, housing price appreciation and volatility itself. The impulse response analysis reveals the asymmetric of the positive and negative shocks. The findings of this article have important implications, particularly for those seeking to develop derivatives for housing market prices.

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Available abstract

This article tries to identify the determinants of housing price volatility and to examine the dynamic effects of these determinants on volatility using quarterly data for Canada. The Generalized Autoregressive Conditional Heteroskedastic (GARCH) and the Vector Autoregressive (VAR) models have been employed to analyse possible time variation of the housing price volatility and the interactions between the volatility and the key macroeconomic variables. We find the evidence of time varying housing price volatility for Canada. Our VAR, Granger causality and variance decomposition (VDC) analyses demonstrate that housing price volatility is affected significantly by gross domestic product (GDP) growth rate, housing price appreciation rate and inflation. On the other hand, volatility affects GDP growth rate, housing price appreciation and volatility itself. The impulse response analysis reveals the asymmetric of the positive and negative shocks. The findings of this article have important implications, particularly for those seeking to develop derivatives for housing market prices.

Key concepts: Economics, Volatility (finance), Econometrics, Variance decomposition of forecast errors, Autoregressive conditional heteroskedasticity, Heteroscedasticity, Skewness, Volatility swap

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