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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

    (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam and Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

Abstract

In this study, we utilize the recent oil shock data of Baumeister and Hamilton (2019) to analyze how housing returns in China, India and Russia respond to different oil shocks. 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 specifically, we find that the housing returns of India and China which are net oil-importing countries do not seem to possess oil risk hedging characteristics albeit with the converse for Russia which is a major net oil-exporter. 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, 2019. "How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Working Papers 201946, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201946
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    1. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    2. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    3. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2019. "Another look at the energy-growth nexus: New insights from MIDAS regressions," Energy, Elsevier, vol. 174(C), pages 69-84.
    4. Aye, Goodness C. & Balcilar, Mehmet & Bosch, Adél & Gupta, Rangan, 2014. "Housing and the business cycle in South Africa," Journal of Policy Modeling, Elsevier, vol. 36(3), pages 471-491.
    5. Rangan Gupta & Faaiqa Hartley, 2013. "The Role of Asset Prices in Forecasting Inflation and Output in South Africa," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 12(3), pages 239-291, December.
    6. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    7. Nazlioglu, Saban & Gormus, N. Alper & Soytas, Uğur, 2016. "Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis," Energy Economics, Elsevier, vol. 60(C), pages 168-175.
    8. Khiabani, Nasser, 2015. "Oil inflows and housing market fluctuations in an oil-exporting country: Evidence from Iran," Journal of Housing Economics, Elsevier, vol. 30(C), pages 59-76.
    9. Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2017. "Improving the Predictive ability of oil for inflation: An ADL-MIDAS Approach," Working Papers 025, Centre for Econometric and Allied Research, University of Ibadan.
    10. Nikolaos Antonakakis & Rangan Gupta & John W. Muteba Mwamba, 2016. "Dynamic Comovements Between Housing and Oil Markets in the US over 1859 to 2013: a Note," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 377-386, September.
    11. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta, 2019. "Does inequality really matter in forecasting real housing returns of the United Kingdom?," International Economics, CEPII research center, issue 159, pages 18-25.
    12. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    13. Lutz Kilian & Xiaoqing Zhou, 2022. "The Propagation of Regional Shocks in Housing Markets: Evidence from Oil Price Shocks in Canada," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 953-987, June.
    14. Hamilton, James D., 2011. "Nonlinearities And The Macroeconomic Effects Of Oil Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 364-378, November.
    15. Chan, Kam Fong & Treepongkaruna, Sirimon & Brooks, Robert & Gray, Stephen, 2011. "Asset market linkages: Evidence from financial, commodity and real estate assets," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1415-1426, June.
    16. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    17. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    18. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    19. Narayan, Paresh Kumar & Liu, Ruipeng, 2015. "A unit root model for trending time-series energy variables," Energy Economics, Elsevier, vol. 50(C), pages 391-402.
    20. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    21. Agnello, Luca & Castro, Vitor & Hammoudeh, Shawkat & Sousa, Ricardo M., 2017. "Spillovers from the oil sector to the housing market cycle," Energy Economics, Elsevier, vol. 61(C), pages 209-220.
    22. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2015. "Does data frequency matter for the impact of forward premium on spot exchange rate?," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 45-53.
    23. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    24. Sakaki, Hamid, 2019. "Oil price shocks and the equity market: Evidence for the S&P 500 sectoral indices," Research in International Business and Finance, Elsevier, vol. 49(C), pages 137-155.
    25. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    26. Afees A. Salisu & Umar B. Ndako & Tirimisiyu F. Oloko & Lateef O. Akanni, 2016. "Unit root modeling for trending stock market series," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(2), pages 82-91, June.
    27. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    28. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    29. Breitenfellner, Andreas & Crespo Cuaresma, Jesús & Mayer, Philipp, 2015. "Energy inflation and house price corrections," Energy Economics, Elsevier, vol. 48(C), pages 109-116.
    30. Goodness C. Aye & Matthew W. Clance & Rangan Gupta, 2019. "The Effect of Economic Uncertainty on the Housing Market Cycle," Journal of Real Estate Portfolio Management, Taylor & Francis Journals, vol. 25(1), pages 67-75, January.
    31. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
    32. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    33. Barsoum, Fady & Stankiewicz, Sandra, 2015. "Forecasting GDP growth using mixed-frequency models with switching regimes," International Journal of Forecasting, Elsevier, vol. 31(1), pages 33-50.
    34. Kaufmann, Robert K. & Gonzalez, Nancy & Nickerson, Thomas A. & Nesbit, Tyler S., 2011. "Do household energy expenditures affect mortgage delinquency rates?," Energy Economics, Elsevier, vol. 33(2), pages 188-194, March.
    35. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    36. Jung, Alexander, 2017. "Forecasting broad money velocity," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 421-432.
    37. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    38. Salisu, Afees A. & Adeleke, Adegoke I., 2016. "Further application of Narayan and Liu (2015) unit root model for trending time series," Economic Modelling, Elsevier, vol. 55(C), pages 305-314.
    39. Killins, Robert N. & Egly, Peter V. & Escobari, Diego, 2017. "The impact of oil shocks on the housing market: Evidence from Canada and U.S," Journal of Economics and Business, Elsevier, vol. 93(C), pages 15-28.
    40. N. Kundan Kishor & Hardik A. Marfatia, 2018. "Forecasting house prices in OECD economies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(2), pages 170-190, March.
    41. Tsai, Chun-Li, 2015. "How do U.S. stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis?," Energy Economics, Elsevier, vol. 50(C), pages 47-62.
    42. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    43. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
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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).
    2. Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
    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

    Keywords

    Housing return; Oil shock; MIDAS regression; Nonlinearities; Forecasting;
    All these keywords.

    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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