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Can Municipal Bonds Hedge US State-Level Climate Risks?

Author

Listed:
  • Onur Polat

    (Department of Public Finance, Bilecik Seyh Edebali University, Bilecik, Turkiye)

  • Rangan Gupta

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

  • Oguzhan Cepni

    (Copenhagen Business School, Department of Economics, Porcelænshaven 16A, Frederiksberg DK-2000, Denmark; Ostim Technical University, Ankara, Turkiye)

  • Qiang Ji

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China)

Abstract

Using daily data on municipal bonds and equity returns from the 50 US states over the period from May 2, 2006, to February 9, 2024, we find that barring extreme periods of financial, macroeconomic, and health crises, the underlying conditional correlation between these two assets is negative, as derived from the Asymmetric Dynamic Conditional Correlations (ADCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. When we utilize the Quantile-on-Quantile (QQ) regression model to capture the effect of climate risk quantiles on the entire conditional distribution of the underlying time-varying stock-bond correlation, we generally observe a negative impact at different levels of climate risks, although this could turn positive in the event of extreme climate disasters. In summary, the role of municipal bonds as a hedge against climate risks cannot be denied, carrying important portfolio allocation implications for investors.

Suggested Citation

  • Onur Polat & Rangan Gupta & Oguzhan Cepni & Qiang Ji, 2024. "Can Municipal Bonds Hedge US State-Level Climate Risks?," Working Papers 202419, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202419
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    References listed on IDEAS

    as
    1. Cepni, Oguzhan & Demirer, Riza & Rognone, Lavinia, 2022. "Hedging climate risks with green assets," Economics Letters, Elsevier, vol. 212(C).
    2. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    3. Darwin Choi & Zhenyu Gao & Wenxi Jiang, 2020. "Attention to Global Warming," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1112-1145.
    4. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2021. "Computing Macro-Effects and Welfare Costs of Temperature Volatility: A Structural Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 347-394, August.
    5. Donadelli, M. & Jüppner, M. & Riedel, M. & Schlag, C., 2017. "Temperature shocks and welfare costs," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 331-355.
    6. Zintle Twala & Riza Demirer & Rangan Gupta, 2018. "Does Liquidity Risk Explain the Time-Variation in Asset Correlations? Evidence from Stocks, Bonds and Commodities," Journal of Economics and Behavioral Studies, AMH International, vol. 10(2), pages 120-132.
    7. George M. Korniotis & Alok Kumar, 2013. "State-Level Business Cycles and Local Return Predictability," Journal of Finance, American Finance Association, vol. 68(3), pages 1037-1096, June.
    8. Michael Donadelli & Marcus Jüppner & Sergio Vergalli, 2022. "Temperature Variability and the Macroeconomy: A World Tour," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 221-259, September.
    9. Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos & Wohar, Mark E., 2018. "News implied volatility and the stock-bond nexus: Evidence from historical data for the USA and the UK markets," Journal of Multinational Financial Management, Elsevier, vol. 47, pages 76-90.
    10. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2023. "Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data," The European Journal of Finance, Taylor & Francis Journals, vol. 29(4), pages 466-481, March.
    11. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
    12. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Reneé van Eyden, 2023. "Climate risks and U.S. stock‐market tail risks: A forecasting experiment using over a century of data," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 228-244, June.
    13. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    14. Painter, Marcus, 2020. "An inconvenient cost: The effects of climate change on municipal bonds," Journal of Financial Economics, Elsevier, vol. 135(2), pages 468-482.
    15. Demirer, Riza & Gupta, Rangan, 2018. "Presidential cycles and time-varying bond–stock market correlations: Evidence from more than two centuries of data," Economics Letters, Elsevier, vol. 167(C), pages 36-39.
    16. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    17. Faccini, Renato & Matin, Rastin & Skiadopoulos, George, 2023. "Dissecting climate risks: Are they reflected in stock prices?," Journal of Banking & Finance, Elsevier, vol. 155(C).
    18. Cepni, Oguzhan & Demirer, Riza & Pham, Linh & Rognone, Lavinia, 2023. "Climate uncertainty and information transmissions across the conventional and ESG assets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
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    More about this item

    Keywords

    Stocks and bonds returns; Time-varying conditional correlation; ADCC-GARCH; Climate risks; QQ regressions; US states;
    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
    • 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
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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