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How Do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch

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  • Afees A. Salisu
  • Rangan Gupta

Abstract

In this study, we examine the response of housing returns in China, India and Russia to different oil shocks, generated from a more accurate estimation approach. Given the available data for the relevant variables, the MIDAS approach which helps circumvent aggregation problem in the estimation process is employed. We also extend the MIDAS framework to account for nonlinearities in the model. Expectedly, the housing returns of the countries considered respond differently to the variants of oil shocks. More importantly, the result indicates that housing returns in Russia serve as a good hedge against oil price risk while housing returns in China and India do not. We also find that modeling with the MIDAS framework offers better predictability than other variants with uniform frequency.

Suggested Citation

  • Afees A. Salisu & Rangan Gupta, 2021. "How Do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4286-4311, December.
    • Handle: RePEc:mes:emfitr:v:57:y:2021:i:15:p:4286-4311
    DOI: 10.1080/1540496X.2020.1807322
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    Cited by:

    1. Salisu, Afees A. & Adediran, Idris, 2020. "Gold as a hedge against oil shocks: Evidence from new datasets for oil shocks," Resources Policy, Elsevier, vol. 66(C).
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    3. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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