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Measuring Time Preference and the Elasticity of Intertemporal Substitution with Web Surveys

Measuring Time Preference and the Elasticity of Intertemporal Substitution with Web Surveys. Miles S. Kimball, Claudia R. Sahm and Matthew D. Shapiro. October 31, 2007. Motivation. Wide range of estimates for these key parameters Limitations to existing survey data

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Measuring Time Preference and the Elasticity of Intertemporal Substitution with Web Surveys

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  1. Measuring Time Preference and the Elasticity of Intertemporal Substitution with Web Surveys Miles S. Kimball, Claudia R. Sahm and Matthew D. Shapiro October 31, 2007

  2. Motivation • Wide range of estimates for these key parameters • Limitations to existing survey data • Web surveys enable new formats for intertemporal choice

  3. Behavioral Model of Intertemporal Consumption • c : consumption, • r : real interest rate, • s : elasticity of intertemporal substitution • ρ: subjective discount rate

  4. Vary Treatment : r Observe Response : c1, c2 Research Design Estimate Parameters : s, ρ

  5. Previous Implementation Discrete choice: spending before and after retirement in Health and Retirement Study • 1992 HRS Module • Barsky, Kimball, Juster, and Shapiro (QJE 1997) • Estimates: s = 0.18, -sρ = 0.78% • 1999 HRS Mailout • Compares to a version in Internet survey • Anchoring in discrete choice

  6. Mail Survey • Question with 0% interest rate • Consumption growth choices: -2.2%, 0%, 2.2%, 4.6%, and 7.3%

  7. Internet Implementation • Web Graphics to Visualize Intertemporal Trade-offs • New Continuous Choice and Improved Discrete Choice Versions • Two Waves of Responses in American Life Panel began in 11/2004 and 8/2006

  8. Outline of Talk • Internet Versions • Summary Statistics • Preference Parameter Estimates • Ongoing Analysis

  9. Hypothetical Scenario

  10. Web Versions • Moveable Bars • Vary Spending Trade-off • Wide Bars • Vary Length of Periods • Discrete Choice • Vary Spending Trade-off

  11. Moveable Bars: r = 0% • Spending tradeoff implies 0% interest rate • 4 questions with different interest rates of r = {0%, 4.6%, 9.2%, 13.9%}

  12. Moveable Bars: r = 0% • Initial value randomized • Click buttons or drag bars

  13. Moveable Bars: r = 0% • $200 more early, $200 less later • Tradeoff visualized

  14. Moveable Bars: r = 13.9% • Spending tradeoff implies 13.9% interest rate

  15. Moveable Bars: r = 13.9% • Same saving  more spending later

  16. Moveable Bars: r = 13.9% • $200 more early, $1600 less later

  17. Wide Bars: r = 13.5% • Length of periods implies 13.5% interest rate • 5 questions with different interest rates of r = {-13.5%, -4.8%, 0%, 4.8%, 13.5%}

  18. Wide Bars: r = 13.5% • $100 less for 5 years, $100 more 25 years

  19. Discrete Choice: Situation 1 • Spending tradeoff implies 0% interest rate • 4 questions with different interest rates of r = {0%, 4.6%, 9.2%, 13.9%}

  20. Discrete Choice: r = 0% • Choose A or E, see 3 more options • Randomize discrete choice set

  21. Respondent Characteristics • Large differences in education and income by Internet use

  22. Technical Issues with Web • Moveable and wide bars need Java • Rounding and other coding issues

  23. Active Responses • Active response: move bars, check box • Web survey prompts after inactive response

  24. Slope of Desired Consumption Path at 0% Interest Rate • Mail respondents strongly favor upward slope • Web respondents favor downward slope

  25. Why Is Mail Survey So Different? Priming Effects • Compare discrete choice • Mail survey 3 of 5 “Up” options • Internet randomizes

  26. Change in Consumption Ratio as Interest Rate to 14% from 0% • Internet react more to interest rate change • But more also move in the “wrong” direction

  27. Again, Why Is Mail So Different? Anchoring Effects • Compare discrete choice • Mail survey 5 ratios static • Internet randomizes ratios

  28. Estimates: Annual Consumption Growth at Zero Interest Rate • Web: flat path • Mailout: upward slope

  29. Estimates: Average Elasticity of Intertemporal Substitution • Internet: higher elasticities, well below log utility

  30. Upper Bound on Elasticity? • Average of positive elasticities well below 1.0 • Similar consumption path at zero rate

  31. Heterogeneity I • Consumption path steeper for older respondents • No effect statistically different from zero

  32. Heterogeneity II • Older respondents, less elastic • Higher income, less elastic

  33. Ongoing Work • Improve the Moveable Bar Version • In 2008 Cognition Survey • Estimate Statistical Model • Repeat observations address response errors • External Check on Responses • “Reverse” question: vary spending growth and elicit desired interest rate

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