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Dinah A. Koehler EPA Bernell K. Stone BYU

THE IMPACT OF AIR POLLUTION EMISSIONS AND RELATED HUMAN HEALTH RISKS ON THE CROSS-SECTION OF STOCK RETURNS. Dinah A. Koehler EPA Bernell K. Stone BYU. CONCERN. For a cross section of companies/industries, does air pollution, especially health damaging air pollution,

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Dinah A. Koehler EPA Bernell K. Stone BYU

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  1. THE IMPACT OF AIR POLLUTION EMISSIONS AND RELATEDHUMAN HEALTH RISKS ON THECROSS-SECTION OF STOCK RETURNS Dinah A. Koehler EPA Bernell K. Stone BYU

  2. CONCERN For a cross section of companies/industries, does air pollution, especially health damaging air pollution, have a systematic effect on valuation?

  3. HYPOTHESES Null: no effect Alternative l: Positive effect, i.e.: More pollution greater value Alternative 2: Negative effect, i.e.: More pollution lower value

  4. HYPOTHESES Null Positive Negative • Comments: • In equilibrium, value and return realization are inversely related. • Revaluation from new information and/or from changes in how stocks are valued can be source of noise, possibly distortion.

  5. ASSESSMENT ISSUES • Fair return for time and risk • Other cross-sectional return dependency variables • Interpretative complexities

  6. FAIR RETURN MODELS CAPM (Capital Asset Pricing Model) 2 return factors: - time (short-term riskless interest rate) - systematic market risk (beta) Rs = Rf + (RM - Rf)βs Multifactor - Endogenous Factors (APT) - Exogenous Factors (specified variables) Example: “Fama-French 3 Factor”

  7. OTHER CROSS SECTIONAL RETURN DEPENDENCY VARIABLES • Other so-called anomaly variables • Taxes and financial structure • Growth, profitability, and other performance attributes • Industry

  8. Summary of Return Impacting Variables

  9. INTERPRETATIVE COMPLEXITIES The usual specification problems • Measurement error • Omitted variables • Improperly specified functional dependencies • Correlation distortion State of the economy State of the market • Changing level of interest rates • Changing term structure • Changing currency values • Hot and cold styles (e.g., growth vs value) Industry-specific effects Arrival of new value changing information

  10. STUDY LOGIC DATA • Rank Order into Industry Portfolios • Step-Wise use of MAP Scatter Plots Regression Fits Hypothesis Tests

  11. STUDY LOGIC DATA • Rank Order into Industry Portfolios • Step-Wise use of MAP • Model 1: No control restrictions • Model 2: CAPM beta • Model 3: Fama-French 3-Factor • Model 4: 7-Factors: EY, DY, FS, ET • Model 5: Add Growth and Profitability

  12. STUDY LOGIC DATA • Rank Order into Industry Portfolios • Step-Wise use of MAP Scatter Plots Regression Fits Hypothesis Tests

  13. Measured Cross Section of Returns on Matched Portfolios

  14. Measured Cross Section of Returns on Matched Portfolios

  15. Measured Cross Section of Returns on Matched Portfolios

  16. Linear Regression Results: 1998-2002

  17. Linear Regression Results: 1998-2002 * p < .01 ** p < .001

  18. Linear Regression Results: 1998-2002 * p < .01 ** p < .001

  19. MAJOR CONCLUSIONS • Tonnage of air pollution is not significant • Cancer health risk is significant • Lung health risk is significant

  20. INTERPRETATIVE COMPLEXITY:EQUILIBRIUM VS REVALUATION “Equilibrium” (no pollution-related revaluation) -market failure in that companies in industry groups producing more health damaging air pollution are more highly valued than otherwise identical companies -there is a need for pertinent regulation Cross-time revaluation -the market believes that there is the possibility that health-related air pollution will be more regulated (with costs to the polluting companies), and/or -the market becomes concerned with health-related legal liability (as occurred for asbestos and tobacco)

  21. METHODOLGY CONCLUSIONS Many variable impacts For pollution, it is crucial to control for • Fair return for time and risk • Taxes and financial structure • Growth and profitability • Industry attributes

  22. ON-GOING AND FUTURE RESEARCH Size scaling alternatives Outlier control Industry impacts/distortion More portfolios per cross-section More sensitivity analysis Additional years?

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