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Monetary policy and housing sector dynamics in a large-scale Bayesian vector autoregressive model

    Rangan Gupta Affiliation
    ; Marius Jurgilas Affiliation
    ; Alain Kabundi Affiliation
    ; Stephen M. Miller Affiliation

Abstract

Our paper considers the channel whereby monetary policy, a federal funds rate shock, affects the dynamics of the US housing sector. The analysis uses impulse response functions obtained from a large-scale Bayesian vector autoregressive model that incorporates 143 monthly macroeconomic variables over the period of 1986:01 to 2003:12, including 21 variables relating to the housing sector at the national and four Census regions. We find at the national level that housing starts, housing permits, and housing sales fall in response to the tightening of monetary policy. Housing sales react more quickly and sharply than starts and permits and exhibit more duration. Housing prices show the weakest response to the monetary policy shock. At the regional level, we conclude that the housing sector in the south drives the national findings in the sense that the response patterns in the South most closely match the response patterns in the nation as a whole. The West's responses differs the most from the other regions, especially for the impulse responses of housing starts and permits.


First Publish Online: 12 Apr 2012

Keyword : Monetary policy, Housing sector dynamics, Large-Scale BVAR models

How to Cite
Gupta, R., Jurgilas, M., Kabundi, A., & M. Miller, S. (2012). Monetary policy and housing sector dynamics in a large-scale Bayesian vector autoregressive model. International Journal of Strategic Property Management, 16(1), 1-20. https://doi.org/10.3846/1648715X.2011.621466
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Apr 12, 2012
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This work is licensed under a Creative Commons Attribution 4.0 International License.