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Katie Dickinson Working with Hannah Brenkert -Smith, Patricia Champ, and Nicholas Flores

Wildfire in Colorado: Understanding the role of social interactions and risk perceptions in shaping households’ mitigation behaviors. Katie Dickinson Working with Hannah Brenkert -Smith, Patricia Champ, and Nicholas Flores. Katie Dickinson , environmental economist.

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Katie Dickinson Working with Hannah Brenkert -Smith, Patricia Champ, and Nicholas Flores

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  1. Wildfire in Colorado: Understanding the role of social interactions and risk perceptions in shaping households’ mitigation behaviors Katie Dickinson Working with Hannah Brenkert-Smith, Patricia Champ, and Nicholas Flores

  2. Katie Dickinson, environmental economist Research interest: What motivates individual actions that affect environmental, health, and economic outcomes? • Past projects: • Sanitation choices in India • Malaria prevention and treatment behaviors in Tanzania • Mosquito control in Wisconsin • Current projects at NCAR: • Wildfire mitigation behaviors in Colorado • Cookstove use and meningitis in Ghana • Urban vulnerability to climate change • Hurricane warning information and evacuation decisions in Miami Overarching questions: What benefits and costs do people consider when making decisions in the face of risk? How do social networks shape behaviors? How can a better understanding of human behaviors inform more effective policies and programs? Relevance to NCAR: Understanding the societal impacts of weather and climate requires an understanding of behavioral responses to risk

  3. Background on Wildfire • Wildfire as part of the natural regime in CO, but combination of factors affecting frequency and impacts • Centralized policies & government action can’t fix the problem… homeowners’ behaviors on private property are key • What drives these behaviors?

  4. A Simple Economic Model • If the perceived probability of having a fire on your property is pf, you will choose to mitigate if: • Cm< pf(D – Dm) • Cost of mitigation < Prob of fire * ∆ in damages • We can get more people to mitigate by: • Decreasing mitigation costs (cm) • Increasing perceived probability of fire (pf) • Increasing perceived damages from fire (D) and/or perceived effectiveness of mitigation (D – Dm)

  5. The Role of Social Interactions Cm < pf (D – Dm) • Mitigation choices of neighbors and social contacts can affect risk perceptions: • How likely is it that a fire will occur? (pf) • How bad will it be if it does? (D – Dm) • How much will my actions decrease damages in the event of a fire? (D, D – Dm) • But social interactions can also affect costs: • What kinds of mitigation options are available? • How do I go about mitigating? • How much will mitigation decrease the quality of my landscape? • Will I face social costs if I do/don’t mitigate? • Will you help me?

  6. R Risk Perceptions The Role of Social Interactions M Fire Mitigation Behaviors S Social Interactions effects operating through other social pathways, e.g., learning, norms effects operating through risk perceptions

  7. Wildfire Study Overview • Phase 1: Analysis of 2007 and 2010 Boulder & Larimer County datasets (now – Spring 2012) • What relationships between S, R, and M do we observe in a sample of 700 homeowners? • Phase 2: Experimental studies in 3-4 Western Slope communities (site selection and initial interviews Summer 2011, NSF proposal Nov ’11) • If we change S, R , or M for some people, how do others’ behaviors change?

  8. Boulder/Larimer County Analysis Variables: M Structural Defensive space (30 ft) Defensive space (30-100 ft) R Fire probability Fire impacts S Physical proximity “Generic” social interactions (participation in community groups) Fire-related interactions (talking about fire, attending fire events) Perceptions of neighbors’ behaviors X County, Age, Gender, • Analyses: • Social amplification of risk? • R=f(S, X) • Determinants of mitigation? • M=f(S, X) • M=f(R, X) • M=f(S, R, X)

  9. Results: Social Amplification of Risk • Both formal and informal interactions associated with risk perceptions • Fire-related interactions matter more than generic interactions • What neighbors do may matter more than what we talk about… actions speak louder than words?

  10. Results: Mitigation Behaviors • Results depend on how mitigation is measured: • Neither S nor R strongly associated with structural • Both S and R associated with dspace30 • Only S associated with dspace100 • Evidence for substitution? As neighbors do more, I do less?

  11. R Boulder/Larimer Limitations and Opportunities M S • Cross sectional data makes causality very hard to determine • Possible solution: 2010 data… Looking at changes in behavior over time • An alternative direction… cluster analysis • Are there different types of individuals that show different S-R-M patterns?

  12. Experiments • Computer-based experiments: • Participants choose mitigation on parcel • Fire simulated & respondents observe results • Experimental conditions: • Collaboration between participants? • Decisions simultaneous or in sequence? • Aid of wildfire expert? • Field experiments • Baseline data includes full census with all social linkages • Incentives randomly provided to community members, then observe how incentives affect own & contacts’ behaviors

  13. Questions or suggestions welcome!

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