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Time Horizons in Interdependent Security

This research explores cooperation in Interdependent Security (IDS) scenarios involving stochastic losses and precommitment strategies in risky investments. Findings suggest uncertainty decreases individual cooperation, while precommitment can raise it. The study investigates how subjective probabilities and time horizons influence decision-making in IDS contexts.

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Time Horizons in Interdependent Security

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  1. Time Horizons in Interdependent Security David Hardisty, Howard Kunreuther, David Krantz, & Poonam Arora Columbia University International Conference on Social Dilemmas Kyoto, Japan August 24, 2009

  2. Co-Authors NSF Grants SES-0345840 & SES-0820496 Howard Kunreuther Dave Krantz Poonam Arora

  3. Thank You ICSD 2009 Organizing Committee • Satoshi Fujii • Toshio Yamagishi • Tsuyoshi Hatori • Akira Kikuchi • Haruna Suzuki

  4. IDS Background • Interdependent Security (IDS) is a social dilemma with stochastic losses examples: • border security • pest/disease control • risky investment

  5. Previous Findings on IDS • Individuals cooperate less in IDS than in a typical repeated PD (Kunreuther et al, in press) • However groups cooperate more in IDS (Gong, Baron & Kunreuther, in preparation)

  6. Research Motivation (1) • Previous studies used probabilities of 20% to 80% • Real life risks are often much lower

  7. Research Motivation (2) • In real life, players often precommit their strategy (whether to invest in protection) for several years in advance at a time • example: CO2 reductions

  8. Research Motivation (2) • Normally, greater delay is associated with increased uncertainty • example: $10 promised today or in 20 years • However, with repeated low probability events, increasing time horizon may increase subjective probability • example: chance of fire today or in the next 20 years

  9. Study 1 Question 1: Do previous findings of low (~30%) cooperation under uncertainty hold with low probabilities? Or will it be even lower? Question 2: Does precommitment raise investment rates?

  10. IDS instructions (pg 1) Scenario: Imagine you are an investor in Indonesia and you have a risky joint venture that earns 8,500 Rp per year. However, there is a small chance that you and/or your counterpart will suffer a loss of 40,000 Rp in a given year. You have the option to pay 1,400 Rp for a safety measure each year to protect against the possible loss. However, you will only be fully protected if both you and your counterpart invest in protection. The loss has an equal chance of happening each year, regardless of whether it occurred in the previous year.

  11. IDS payoff matrix

  12. PD payoff matrix

  13. IDS: Choices Will you invest in protection this year? INVEST | NOT INVEST Do you think your counterpart will invest in protection this year? DEFINITELY | PROBABLY | PROBABLY NOT | DEFINITELY NOT

  14. Precommitted Condition Will you invest in protection in year 1? INVEST | NOT INVEST Do you think your counterpart will invest in protection in year 1? DEFINITELY | PROBABLY | PROBABLY NOT | DEFINITELY NOT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Will you invest in protection in year 2? INVEST | NOT INVEST Do you think your counterpart will invest in protection in year 2? DEFINITELY | PROBABLY | PROBABLY NOT | DEFINITELY NOT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~[...] Will you invest in protection in year 20? INVEST | NOT INVEST Do you think your counterpart will invest in protection in year 20? DEFINITELY | PROBABLY | PROBABLY NOT | DEFINITELY NOT

  15. Feedback Year 1 Results Your choice: INVEST Your counterpart's choice: NOT INVEST The random number was: 88 This Means For you, the large loss: did not occur For your counterpart, the large loss: did not occur Result: You lost 1,400 Rp, and your counterpart lost 0 Rp

  16. Design Details • participants played blocks of 20 rounds (“years”) with an anonymous partner • 4 blocks total • random pairing before each block • 1 block paid out for real money • all manipulations between subject, 30 subjects per group

  17. PD vs IDS 1 0.9 0.8 0.7 0.6 IDS rep Investment Proportion 0.5 PD rep 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  18. PD vs IDS 1 0.9 0.8 0.7 0.6 IDS rep Investment Proportion 0.5 PD rep 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  19. PD vs IDS 1 0.9 0.8 0.7 0.6 IDS rep Investment Proportion 0.5 PD rep 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  20. Conclusion 1 • Uncertainty lowers cooperation between individuals playing loss framed dilemma • Why? - Perhaps uncertainty makes players more greedy (Johansson & Svedsater, yesterday)- Perhaps uncertainty transforms the game from a social dilemma to a game of chance

  21. IDS: repeated vs precommitted 1 0.9 0.8 0.7 0.6 IDS rep Investment Proportion 0.5 IDS pre PD rep 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  22. IDS: repeated vs precommitted 1 0.9 0.8 0.7 0.6 IDS rep Investment Proportion 0.5 IDS pre PD rep 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  23. Conclusion 2 • Under uncertainty, precommitment raises cooperation • Why? Perhaps precommitment raises subjective probability of the loss

  24. Precommitted Participants Estimated Higher Cumulative Probability

  25. Interesting results, but a major confound: Feedback

  26. Study 2 Question: Do individuals playing a (non-dilemma) solo game invest more often when precommitting?

  27. Solo payoff matrix

  28. IDS repeated vs Solo repeated

  29. IDS repeated vs Solo repeated

  30. Conclusion 3 • IDS players are mostly playing a game of chance, showing risk-seeking for losses

  31. Support 3

  32. Solo: repeated vs precommited

  33. Solo: repeated vs precommited 1 0.9 0.8 0.7 0.6 IDS rep IDS pre Investment Proportion 0.5 Solo rep 0.4 Solo pre 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  34. Conclusion 4 • Precommitment raises investment rates by individuals • Why? Perhaps subjective probability is increased

  35. How else can we improve investment under uncertainty? • Perhaps environmental framing can highlight social goals and raise investment rates • However, earlier results are mixed

  36. Study 3 Question: Will environmental framing will increase investment rates?

  37. IDS environmental instructions Scenario: Imagine you are a farmer in Indonesia. You get an annual yield of 8,500 Rupiah (Rp) from your potato crops.Both you and a neighboring farmer use the pesticide Aldicarb on your potato crops. However, there is a small risk of groundwater contamination each year from this pesticide, which is toxic.If contamination occurs, you and/or your neighboring farmer will suffer a loss of 40,000 Rp, to pay for groundwater cleanup. You have the option to switch to a more expensive, though safer, pesticide, at the cost of 1,400 Rp annually, to avoid groundwater contamination. However, you will only be fully protected if both you and your counterpart invest in the safer pesticide. The groundwater contamination has an equal chance of happening each year, regardless of whether it occurred in the previous year.

  38. IDS environmental payoff matrix

  39. IDS Environmental: Choices Will you invest in the safer pesticide this year? INVEST | NOT INVEST Do you think your counterpart will invest in the safer pesticide this year? DEFINITELY | PROBABLY | PROBABLY NOT | DEFINITELY NOT

  40. Feedback Year 1 Results Your choice: INVEST Your counterpart's choice: NOT INVEST The random number was: 88 This Means For you,groundwater contamination: did not occur For your counterpart,groundwater contamination : did not occur Result: You lost 1,400 Rp, and your counterpart lost 0 Rp

  41. Environmental Frame Results

  42. Environmental Frame Results

  43. Environmental Frame Results

  44. Conclusion 5 • Environmental framing may not have a significant effect on investment rates

  45. Study 4 Question: How does precommitment affect investment rates in a deterministic prisoners dilemma

  46. IDD payoff matrix

  47. PD: Repeated vs Precommitted 1 0.9 0.8 0.7 0.6 PD rep Investment Proportion 0.5 PD pre 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  48. PD: Repeated vs Precommitted 1 0.9 0.8 0.7 0.6 PD rep Investment Proportion 0.5 PD pre 0.4 0.3 0.2 0.1 0 Block 1 Block 2 Block 3 Block 4

  49. Conclusion 6 • Precommitment reduces investment rates in deterministic social dilemmas • Why? Perhaps individuals realize there is no opportunity for reciprocity and are worried about being a sucker

  50. Summary • Precommitment lowers cooperation in regular prisoner’s dilemma, but raises it in interdependent security situations • Why? In IDS, precommitment raises subjective probability of loss, but in the deterministic case it removes the possibility of reciprocity

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