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Housing Market Shocks in Italy: a GVAR approach

Author

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  • Andrea Cipollini
  • Fabio Parla
Abstract
In this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004 - 2016. In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the GVAR model is identified by using theory-driven sign restrictions. The spatio-temporal analysis carried through impulse response functions shows that there is evidence of a “ripple effect” mainly occurring through transaction volumes.

Suggested Citation

  • Andrea Cipollini & Fabio Parla, 2018. "Housing Market Shocks in Italy: a GVAR approach," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0069, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Handle: RePEc:mod:wcefin:0069
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    6. Chiara Pederzoli & Costanza Torricelli, 2019. "The impact of the Fundamental Review of the Trading Book: A preliminary assessment on a stylized portfolio," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0075, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    7. Costanza Torricelli & Fabio Ferrari, 2022. "Climate Stress Test: bad (or good) news for the market? An Event Study Analysis on Euro Zone Banks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0086, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    8. Ryan R. Brady, 2021. "Direct Forecasting for Applied Regional Analysis," Departmental Working Papers 67, United States Naval Academy Department of Economics.
    9. Costanza Torricelli & Beatrice Bertelli, 2022. "ESG compliant optimal portfolios: The impact of ESG constraints on portfolio optimization in a sample of European stocks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0088, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
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    More about this item

    Keywords

    Ripple effect; housing market prices and volumes; Global VAR; sign restrictions;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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