aversion to extreme temperature climate change and quality of life n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Aversion to Extreme Temperature, Climate Change, and Quality of Life PowerPoint Presentation
Download Presentation
Aversion to Extreme Temperature, Climate Change, and Quality of Life

Loading in 2 Seconds...

play fullscreen
1 / 89

Aversion to Extreme Temperature, Climate Change, and Quality of Life - PowerPoint PPT Presentation


  • 87 Views
  • Updated on

Aversion to Extreme Temperature, Climate Change, and Quality of Life. Preliminary – Comments Wanted!. David Albouy, University of Michigan and NBER Walter Graf, University of Michigan Ryan Kellogg, University of Michigan and NBER Hendrik Wolff, University of Washington September 14, 2014.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Aversion to Extreme Temperature, Climate Change, and Quality of Life


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. Aversion to Extreme Temperature, Climate Change, and Quality of Life Preliminary – Comments Wanted! David Albouy, University of Michigan and NBER Walter Graf, University of Michigan Ryan Kellogg, University of Michigan and NBER Hendrik Wolff, University of Washington September 14, 2014

    2. 2009: atmospheric • CO2 = 383ppm

    3. Present and Future Temperature Data

    4. Future Temperature Data Future temperatures in 2100: IPCC Assessment Report • A2 scenario: +3.5°C/6.3°F • “moderate” compared to MIT model (2009): +5.2°C/ 9.4°F

    5. Will Higher Temperatures from Climate Change be Good or Bad in the Daily Lives of Americans? • Reduces the severity of cold winters: GAIN • Increases the severity of hot summers: LOSS. • Will the loss outweigh the gain? Depends on • How much people value (i.e. are willing to pay) those changes per unit (reduction in cold or heat), which may vary by person. • Changes in the climate, which varies by location and scenario.

    6. Average Daily Temperature Distribution RED: 2090-2100 Projected A2 scenario from CCSM 3.0 in IPCC (2007) BLUE: 1960-90 Normals San Francisco

    7. Average Daily Temperature Distribution Boston Houston RED: 2090-2100 Projected A2 scenario from CCSM 3.0 in IPCC (2007) BLUE: 1960-90 Normals San Francisco

    8. County Temperature Data

    9. County Temperature Data • Drawback: • 1 day of 115 F & 4 days of 65 F  50 CDD • 5 days of 75 F  50 CDD

    10. 33% Decrease 116% Increase

    11. How Important Are These Temperature Changes? • Price of consumption of climate amenities? • We talk about weather all the time… • Outdoor recreation, skiing, BBQ…. • In 2005 the U.S. spent ~$180bn on heating and cooling • 1.5% of GDP  willingness to pay for comfort • Welfare changes may be at least as important as value of climate change to agriculture (ag = 1.2% of GDP)

    12. Existing climate change literature has generally not focused on amenity values From a recent review of the literature on estimating damages from climate change: “The effects of climate change that have been quantified and monetized include the impacts on agriculture and forestry, water resources, coastal zones, energy consumption, air quality, and human health….Many of the omissions seem likely to be relatively small in the context of those items that have been quantified.” • (Tol, 2009, J Econ Perspectives)

    13. Existing climate change literature has generally not focused on amenity values From a recent review of the literature on estimating damages from climate change: “The effects of climate change that have been quantified and monetized include the impacts on agriculture and forestry, water resources, coastal zones, energy consumption, air quality, and human health….Many of the omissions seem likely to be relatively small in the context of those items that have been quantified.” • (Tol, 2009, J Econ Perspectives)

    14. Existing literature on climate amenity values • Wage-only hedonic regressions (low wage  high amenity) • Hoch and Drake (1974): 2.25 ºC cooling reduces real income by 2% • Moore (1998): 4.5 ºC warming benefits workers by $30-100 billion • Hedonics including local prices and wages • Nordhaus (1996): doubling of CO2 -0.17% of GDP (noisy) Adjusts w for cost of living (29 regions “issue should be flagged”) • Cragg and Kahn (1999) : over 1940-1990, mild weather has been capitalized more into prices, less into wages • Discrete choice of migrants’ location decisions (state level) • Cragg and Kahn (1997) finds high WTP for mild climate (~$1000 to $20000 for a 5.2oC reduction in July temperature) • Timmins (2007) forecasts migration in Brazil.

    15. Existing literature on climate amenity values • Wage-only hedonic regressions (low wage  high amenity) • Hoch and Drake (1974): 2.25 ºC cooling reduces real income by 2% • Moore (1998): 4.5 ºC warming benefits workers by $30-100 billion • Hedonics including local prices and wages • Nordhaus (1996): doubling of CO2 -0.17% of GDP (noisy) Adjusts w for cost of living (29 regions “issue should be flagged”) • Cragg and Kahn (1999) : over 1940-1990, mild weather has been capitalized more into prices, less into wages • Discrete choice of migrants’ location decisions (state level) • Cragg and Kahn (1997) finds high WTP for mild climate (~$1000 to $20000 for a 5.2oC reduction in July temperature) • Timmins (2007) forecasts migration in Brazil.

    16. Existing literature on climate amenity values • Wage-only hedonic regressions (low wage  high amenity) • Hoch and Drake (1974): 2.25 ºC cooling reduces real income by 2% • Moore (1998): 4.5 ºC warming benefits workers by $30-100 billion • Hedonics including local prices and wages • Nordhaus (1996): doubling of CO2 -0.17% of GDP (noisy) Adjusts w for cost of living (29 regions “issue should be flagged”) • Cragg and Kahn (1999) : over 1940-1990, mild weather has been capitalized more into prices, less into wages • Discrete choice of migrants’ location decisions (state level) • Cragg and Kahn (1997) finds high WTP for mild climate (~$1000 to $20000 for a 5.2oC reduction in July temperature) • Timmins (2007) forecasts migration in Brazil.

    17. This paper contributes to the literature by… • Richer hedonic model based on housing costs and wages • Cost of living approximates housing & non-housing costs • Wage differences taken after federal taxes • Based on Albouy (NBER, 2008, JPE, 2009) • Uses climate change projections that vary by county • Allows for distributional analysis of welfare impact • Parallels literature on agricultural impacts (Deschênes and Greenstone 2007, Schlenker et al. 2006, Fisher et al. 2009) • Preference heterogeneity across households, sorting! • Recover distribution of marginal willingness to pay for climate • Method follows IO lit., Bajari and Benkard (2005)

    18. This paper contributes to the literature by… • Richer hedonic model based on housing costs and wages • Cost of living approximates housing & non-housing costs • Wage differences taken after federal taxes • Based on Albouy (NBER, 2008, JPE, 2009) • Uses climate change projections that vary by county • Allows for distributional analysis of welfare impact • Parallels literature on agricultural impacts (Deschênes and Greenstone 2007, Schlenker et al. 2006, Fisher et al. 2009) • Preference heterogeneity across households, sorting! • Recover distribution of marginal willingness to pay for climate • Method follows IO lit., Bajari and Benkard (2005)

    19. This paper contributes to the literature by… • Richer hedonic model based on housing costs and wages • Cost of living approximates housing & non-housing costs • Wage differences taken after federal taxes • Based on Albouy (NBER, 2008, JPE, 2009) • Uses climate change projections that vary by county • Allows for distributional analysis of welfare impact • Parallels literature on agricultural impacts (Deschênes and Greenstone 2007, Schlenker et al. 2006, Fisher et al. 2009) • Preference heterogeneity across households, sorting • Recover distribution of marginal willingness to pay for climate without relying on functional form assumption for utility • Method follows IO lit., Bajari and Benkard (2005)

    20. Our approach broadly proceeds via two stagesStage 1 Hedonics: estimate preferences for climate Stage 2: using estimated preferences: predict welfare loss/gain for 2100

    21. Stage 1 - Hedonics • Core idea: use cross-sectional variation in climate, wages, and prices to identify preferences • Benefits of cross-section vs. time series approach • No substantial longitudinal variation in climate • Cross-section allows for climate adaptation • Cost: concerns regarding omitted variables • No instrument available for climate • Will examine robustness of results to different specifications and control variables

    22. Stage 2 welfare loss/gain predictions • Use spatially heterogeneous climate change predictions from the IPCC (A2 scenario) for 2100 • Account for migration responses, mitigating welfare impacts. • We do NOT account for: - discounting and population growth issues. - We hold preferences and technology constant until 2100!

    23. A Hedonic Model of Welfare Changes • Value of a location depends on amenities Zk e.g. heating degree days, distance to water body etc. • Price of amenity k = βk = (∂U/∂Zk) / (∂U/∂income) • Change in household amenity value = Σk(βk x ΔZk) • Gains and losses do not show up in GDP *There may be effects on firm productivity that would be in GDP

    24. Estimates of Amenity Values and Quality of Life Standard equilibrium assumption Households are homogenous and fully mobile, and thus receive the same utility u in any inhabited city j.

    25. Estimates of Amenity Values and Quality of Life Standard equilibrium assumption Households are homogenous and fully mobile, and thus receive the same utility u in any inhabited city j. Log-linearize around the national average

    26. Estimates of Amenity Values and Quality of Life Standard equilibrium assumption Households are homogenous and fully mobile, and thus receive the same utility u in any inhabited city j. Log-linearize around the national average Second-stage regression

    27. Wage and Housing-Cost Differentials Data (2000) Calculated in wage and price regressions from 5% Census IPUMS using county dummies (derived from PUMAs). Wage differential • Sample: full-time workers (male & female) 25 to 55 • Controls: education, experience, industry, occupation, race, immigrant, language ability, etc. interacted with gender Housing-cost (rent or imputed-rent) differential • Sample: moved within last 10 years • Controls: Type and age of building, size, rooms, acreage, kitchen, etc. interacted with tenure.

    28. Homogenous-Taste Results Suggest that CDDs Have Larger QOL Impact than HDDs

    29. Homogenous-Taste Results Suggest that CDDs Have Larger QOL Impact than HDDs

    30. Homogenous-Taste Results Suggest that CDDs Have Larger QOL Impact than HDDs

    31. Homogenous-Taste Results Suggest that CDDs Have Larger QOL Impact than HDDs

    32. Effect on Overall Welfare Relatively Stable across Specifications with Controls

    33. The Estimated Temperature Loss Function is Asymmetric Second Law of Thermodynamics: Cheaper to heat than to cool. Second Law of Wardrobes: Clothing is bounded below by zero. Slope = βhdd Slope = -βcdd = -1.9βhdd Avg. Daily Temp 7ºF 58 HDD January in Fargo 23ºF 42 HDD January in Ann Arbor 50ºF 15 HDD January in Austin 65ºF 0 80ºF 15 CDD July in Atlanta 111ºF 36 CDD July in Death Valley

    34. Step 2: Predict Welfare changes in 2100

    35. Welfare Change, Population Growth and Discounting

    36. Welfare Change, Population Growth and Discounting

    37. Mobility Response

    38. Loss from Hotter Summer Exceeds Gain from Warmer Winters