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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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    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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