Muni Climate Spreads

Climate finance research investigating whether physical climate risk prices into municipal bond yield spreads.

Research Question

Do municipal bonds issued by entities in counties with higher physical climate risk (sea-level rise, extreme heat, wildfire WUI exposure) trade at wider yield spreads, after controlling for credit quality, maturity, sector, and issuer fixed effects?

Methodology

Matched-pair hedonic regression with issuer fixed effects, following Goldsmith-Pinkham, Gustafson, Lewis, and Schwert (2023):

spread_i = alpha_j + beta * hazard_exposure_i + gamma * X_i + epsilon_i

• alpha_j: issuer fixed effects (absorb time-invariant issuer characteristics)
• hazard_exposure_i: county-level physical risk score (SLR, heat, wildfire)
• X_i: bond-level controls (maturity, rating, sector, log amount, callable flag)
• Standard errors clustered at the issuer level

Three Core Analyses

1. SLR Replication: Replicate the G-P et al. finding that SLR exposure commands ~5-15 bps of additional spread
2. Heat Extension: Test whether extreme heat exposure (the frontier) is similarly priced
3. Anomalous Issuers: Identify high-risk issuers with anomalously low spreads (potential climate mispricing)

Data Sources

Source	Coverage	Access
MSRB EMMA	Primary/secondary muni market data	Free API (registration required)
First Street Foundation	Property/county-level flood, heat, fire, wind risk	API key (academic license)
FEMA National Risk Index	County-level composite + 18 hazard risk scores	Free bulk download
NOAA Climate Data	Historical + projected temperature/precipitation	Free API

Setup

# Clone and install
cd muni-climate-spreads
pip install -e ".[dev]"

# Run tests
pytest

# Run analysis with synthetic data
python -c "from municlimate.analysis import run_all_analyses; run_all_analyses()"

Project Structure

muni-climate-spreads/
  src/municlimate/
    models.py            # Pydantic domain models
    data_acquisition.py  # Data source clients and loaders
    data_processing.py   # Merge, match, control construction
    regression.py        # Hedonic regression with FE
    analysis.py          # High-level analysis workflows
    visualization.py     # Publication-quality figures
  notebooks/
    01_data_exploration.qmd
    02_slr_replication.qmd
    03_heat_extension.qmd
    04_anomalous_issuers.qmd
  tests/
  data/raw/
  data/processed/

Key References

• Goldsmith-Pinkham, P., Gustafson, M. T., Lewis, R. C., & Schwert, M. (2023). Sea-level rise exposure and municipal bond yields. The Review of Financial Studies, 36(11), 4588-4635.
• Painter, M. (2020). An inconvenient cost: The effects of climate change on municipal bonds. Journal of Financial Economics, 135(2), 468-482.
• Bernstein, A., Gustafson, M. T., & Lewis, R. (2019). Disaster on the horizon: The price effect of sea level rise. Journal of Financial Economics, 134(2), 253-272.