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Contagious Diseases and Gold: Over 700 Years of Evidence from Quantile Regressions

Author

Listed:
  • Elie Bouri

    (Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Jacobus Nel

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Sisa Shiba

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

Using annual data on real gold returns and the probability of fatality due to contagious diseases over the period of 1258 to 2020, we detect nonlinearity and regime changes in the relationship between the two variables of concern, over and above the existence of non-normality in the data. In light of these issues, we rely on a quantile regression model to show that real gold returns can hedge against risks associated with such rare disasters, but primarily when the market is in its bullish-state, with it being negatively impacted in its bearish-phase. Understandably, our results have important implications for investors seeking refuge in the safe haven of gold during rare disaster events.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Jacobus Nel & Sisa Shiba, 2022. "Contagious Diseases and Gold: Over 700 Years of Evidence from Quantile Regressions," Working Papers 202233, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202233
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    References listed on IDEAS

    as
    1. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    2. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    3. Ali, Mohsin & Alam, Nafis & Rizvi, Syed Aun R., 2020. "Coronavirus (COVID-19) — An epidemic or pandemic for financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    4. Bouri, Elie & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "Forecasting power of infectious diseases-related uncertainty for gold realized variance," Finance Research Letters, Elsevier, vol. 42(C).
    5. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    6. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    7. Dawar, Ishaan & Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression," Renewable Energy, Elsevier, vol. 163(C), pages 288-299.
    8. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    9. Tanin, Tauhidul Islam & Sarker, Ashutosh & Hammoudeh, Shawkat & Shahbaz, Muhammad, 2021. "Do volatility indices diminish gold's appeal as a safe haven to investors before and during the COVID-19 pandemic?," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 214-235.
    10. Zhang, Hongwei & Hong, Huojun & Guo, Yaoqi & Yang, Cai, 2022. "Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 267-285.
    11. Salisu, Afees A. & Raheem, Ibrahim D. & Vo, Xuan Vinh, 2021. "Assessing the safe haven property of the gold market during COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 74(C).
    12. Salisu, Afees A. & Gupta, Rangan & Nel, Jacobus & Bouri, Elie, 2022. "The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model," Resources Policy, Elsevier, vol. 78(C).
    13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    14. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    15. Abdallah Dah & Ali Fakih, 2016. "Decomposing Gender Wage Differentials Using Quantile Regression: Evidence from the Lebanese Banking Sector," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(2), pages 171-185, May.
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    Cited by:

    1. Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Onur Polat, 2024. "Climate Risks and Real Gold Returns over 750 Years," Working Papers 202436, University of Pretoria, Department of Economics.
    2. Thanoj K. Muddana & Komal S.R. Bhimireddy & Anandamayee Majumdar & Rangan Gupta, 2024. "Forecasting Gold Returns Volatility Over 1258-2023: The Role of Moments," Working Papers 202421, University of Pretoria, Department of Economics.
    3. Karmakar, Sayar & Gupta, Rangan & Cepni, Oguzhan & Rognone, Lavinia, 2023. "Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model," Resources Policy, Elsevier, vol. 82(C).
    4. Bruno Coric & Rangan Gupta, 2022. "Economic Disasters and Inequality," Working Papers 202255, University of Pretoria, Department of Economics.
    5. Balcilar, Mehmet & Gupta, Rangan & Nel, Jacobus, 2022. "Rare disaster risks and gold over 700 years: Evidence from nonparametric quantile regressions," Resources Policy, Elsevier, vol. 79(C).
    6. Feng, Qianbin & Hu, Xiao & Deng, Xinyi & Lu, Jun, 2023. "Anti-corruption campaign and capacity utilization of state-owned enterprises: Evidence from China’s central committee inspection," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 319-346.
    7. Bruno Ćorić & Rangan Gupta, 2023. "Economic disasters and inequality: a note," Economic Change and Restructuring, Springer, vol. 56(5), pages 3527-3543, October.

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    More about this item

    Keywords

    Real gold returns; Contagious Diseases; Probability of fatality; Quantile regression;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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