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1 Wallet Study Reader’s Digest, over a period of years, “lost” more than 1,100 wallets in various cities. Each wallet contained $50 in local currency and.

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Presentation on theme: "1 Wallet Study Reader’s Digest, over a period of years, “lost” more than 1,100 wallets in various cities. Each wallet contained $50 in local currency and."— Presentation transcript:

1 1 Wallet Study Reader’s Digest, over a period of years, “lost” more than 1,100 wallets in various cities. Each wallet contained $50 in local currency and a name and phone number so it could be returned. The wallets were dropped in various places (phone booths, sidewalks, restaurants, etc.).

2 2 Wallets Returned Norway100%Denmark100% Singapore90%New Zealand83% Finland80%Scotland80% Australia70%Japan70% South Korea70%Spain70% Austria 70%Sweden70% U.S.67%England67% India65%Canada64% France60%Brazil60% Netherlands60%Thailand55% Belgium50%Taiwan50% Malaysia50%Germany45% Portugal45%Argentina44% Russia43%Philippines40% Wales40%Italy35% Switzerland35%Hong Kong30% Mexico21%AVERAGE: 56%

3 3 U.S. Cities Wallets Returned Wallets Kept Seattle 9 1 St. Louis 7 3 Atlanta 5 5 Boston* 7 3 Los Angeles* 6 4 Houston* 5 5 Greensboro, N.C. 7 3 Las Vegas 5 5 Dayton, Ohio 5 5 Concord, N.H. 8 2 Cheyenne, Wyo. 8 2 Meadville, Pa. 8 2 (*wallets dropped in suburbs of these cities)

4 4 Neglected Topics Families Norms Social Outputs

5 5 Families Families are associations similar to the ones that Putnam and others measure. If all families were equal, omitting them from analysis would not matter. But families differ a lot: 1. Presence of one or both parents. 2. Inclusion of siblings, grandparents, cousins. 3. Number of siblings.

6 6 Norms Norms are rules that exist independent of enforcement by the government. One way to view them is as equilibria of games such as the prisoner’s dilemma and the coordination game.

7 7 THE TAXONOMY (1) Bilateral Costly Sanctions. One other person incurs the cost of punishing you. (2) Multilateral Costly Sanctions. Many other people incur the cost of punishing you. (3) Automatic Sanctions. Crashing into a driver on the road. (4) Guilt. You feel bad about your sin, even though nobody else knows or cares. (5) Shame. You feel you have lowered yourself. (disapproval) (6) Informational Sanctions. Your action conveys unfavorable info about yourself.

8 8 SIGNALLING GAME 1. Nature chooses 90 percent of workers to be steady, producing x, and 10 percent wild, producing x-y. 2. Each worker decides to marry or not. Marriage adds m to the utility of the steady, and -z to the wild. 3. Employers offer wages conditional on marriage. (Spence won the Nobel Prize in 2001 for signalling)

9 9 EQUILIBRIUM If z>y, so wild workers hatred of marriage is greater than their inferiority in output, then they stay single and the steady get married. If z<.9y, everyone gets married, and the wage is pooling. There is a norm of marriage, enforced by an informational penalty. In between is a mixed-strategy equilibrium.

10 10 WHAT CAN GOVERNMENT DO? 1. Provide supplemental punishments. 2. Provide info on who did what. 3. Be careful about interfering with private sanctions. 4. Supplement incentives for private sanctions. 5. Help in norm creation. 6. Fight bad norms.

11 11 Social Outputs Economic outputs depend on social capital, to be sure, but what crime, illegitimacy, loneliness, etc.? Social outputs can also be modelled using production functions. Social outputs can also be assigned dollars values: how much would people pay to increase a social output? The variability in social outputs from differing levels of social capital may be much greater than the variability in economic outputs.

12 12 Insert a tex slide table Go to the State data tables

13 13 Regressions 1. Specification search (which variables?) 2. Using simple bivariate correlations 3. Weighted regressions 4. Dropping outliers 5. Adding quadratic or log terms for curvature

14 14 Available Data pop malework murder cartheft illegit divorce metro retired midage unemp teachsal homeown income bachelor abortion black southern churchm voting

15 15 Bivariate Correlations with the Murder Rate malework-.25 cartheft.71 illegit.79 divorce.03 metro.27 retired-.03 midage.14 unemp.38 teachsal.15 homeown -.52 income.23 bachelor.32 abortion.84 black.77 southern.38 churchm.06 voting -.27

16 16 Source: Robert Putnam: Bowling Alone, “Selected statistical trend data” http://www.bowlingalone.com/data.php3 (12/8/01)

17 17 Correlation Matrix | putnam orgs member trust ---------------------------------------------------- putnam | 1.00 orgs |.81 1.00 member |.73.58 1.00 trust |.92.73.70 1.00

18 18 Bivariate Correlations with “putnam” Social Capital malework.58 murder-.74 cartheft-.45 illegit-.56 divorce-.35 metro-.36 retired.15 midage-.05 unemp-.44 teachsal-.13 homeown.05 income.09 bachelor.34 abortion-.30 black -.71 southern-.62 churchm-.02 voting.69

19 19 Different Measures Murder = putnam -2.75 (7.55) R 2 =.55 N = 48 Murder = trust -.16 (6.03) R 2 =.48 N=41 Murder = orgs -3.44 (5.17) R 2 =.35 N=50 Murder = member -1.06 (3.35) R 2 =.22 N=40 Murder = putnam orgs trust member -2.60.08 -.03.91 (1.89 ) (0.07) (0.47) (0.71) R 2 =.52 N=40

20 20 Weighting Murder = putnam income -2.69(7.51) -.00012(1.75) Murder = putnam income -2.48(5.58) -.00014(2.05) (weight = pop) Murder = putnam income -2.46(8.00) -.00018(2.38) (weight = 1/pop) Murder = putnam income -2.69(9.97) -.00012(1.60) ( White robust standard errors )

21 21 A Regression Murder =.68* Illegit -.25*Homeown (7.78) (2.89)

22 22 Residuals from Illegit,Homeown state v1 1. AL 1.313196 2. AK -.0083414 3. AZ -3.002368 4. AR -.3776368 5. CA.1270525 6. CO 4.011913 7. CT.6871804 8. DE -8.302368 9. DC 20.62919 10. FL -3.582326 11. GA -1.276142 12. HA -4.394481 13. ID 5.293575 14. IL.9854771 15. IN -.028383 16. IA -.3358477 17. KA 2.801039 18. KE.0886737 19. LA -3.010255 20. ME -3.217509 21. MD 1.957757 22. MA.5488002 23. MI.6701256 24. MN 1.619589 25. MS -5.27337 26. MO -.1145223 27. MT -.0974675 28. NE 2.119589 29. NV 1.030039 30. NH 1.85349 31. NJ.9795045 32. NM -5.145649 33. NY -4.276142 34. NC 1.391659 35. ND -1.135848 36. OH -3.414522 37. OK -.6083413 38. OR -.7113263 39. PA -1.172947 40. RI -5.171453 41. SC -3.259298 42. SD -4.209833 43. TN.614687 44. TX 1.582491 45. UT 9.338348 46. VT -1.134354 47. VA 2.237926 48. WA 1.193363 49. WV -1.231369 50. WI.0302502 51. WY 1.387181

23 23 Residuals from putnam, income 1. AL -.87 2. AK. 3. AZ 2.44 4. AR.35 5. CA.83 6. CO.64 7. CT.66 8. DE -2.40 9. DC. 10. FL -.25 11. GA -.58 12. HA. 13. ID -2.94 14. IL 2.70 15. IN 1.76 16. IA -1.22 17. KA 1.26 18. KE -3.59 19. LA 4.01 20. ME -2.42 21. MD 4.29 22. MA -1.98 23. MI 1.78 24. MN.974 25. MS 1.86 26. MO 1.85 27. MT 1.40 28. NE.63 29. NV.63 30. NH -1.57 31. NJ -1.60 32. NM 3.75 33. NY -.65 34. NC.18 35. ND -.31 36. OH -2.08 37. OK -.44 38. OR -.26 39. PA -.62 40. RI -3.05 41. SC -.40 42. SD.11 43. TN.13 44. TX -.35 45. UT -1.59 46. VT.28 47. VA.01 48. WA.42 49. WV -4.27 50. WI -.37 51. WY.87

24 24 Dropping Outliers Murder = putnam income -2.69 (7.51) -.00012 (1.75) R 2 =.55 Murder = putnam income -2.81 (8.20) -.00016 (2.33) R 2 =.63 (WV dropped) Murder = putnam income -2.61 (8.37) -.00016 (2.66) R 2 =.65 (WV,MD,LA dropped) Not much happens if outliers are dropped.

25 25 Dropping Outliers Murder = illegit homeown -0.68 (7.78) -0.25 (2.89) R 2 =.67 Murder = illegit homeown -0.37 (7.31) 0.05 (0.98) R 2 =.53 (DC dropped) The effect of illegitimacy becomes smaller, and home ownership becomes insignificant.

26 26 Squared and Log Terms Murder = illegit homeown -0.68 (7.78) -.25 (2.89) R 2 =.67 Murder = log(illegit) homeown 19.20 (5.56) -.33 (3.33) R 2 =.55 Murder = illegit illegit 2 homeown -1.61.03 -.07 (6.27) (9.14) (1.23) R 2 =.88

27 27 Murder Regression 1 R 2 =.55 Putnam -2.75 (7.55) Regression 2 R 2 =.68 Putnam -1.62 (3.06) Income -0.00028 (2.75) Black 0.15 (3.45) Metro 0.024 (1.18) Southern -1.58 (1.83)

28 28 Illegitimacy Regression 1 R 2 =.34 Putnam -4.23 (4.91) Regression 2 R 2 =.50 Putnam -1.82 (1.40) Income -0.00046 (1.81) Black 0.34 (3.16) Metro 0.021 (0.42) Southern -2.79 (1.32)

29 29 Male Labor Participation Regression 1 R 2 =.35 Putnam 2.60 (5.08) Regression 2 R 2 =.42 Putnam 2.45 (2.89) Income 0.00012 (0.74) Black 0.007 (0.11) Metro 0.013 (0.42) Southern -0.76 (0.55)

30 30 Car Theft Regression 1 R 2 =.21 Putnam -103.86 (3.53) Regression 2 R 2 =.61 Putnam -37.03 (1.04) Income -0.02 (2.92) Black 0.13 (0.04) Metro 8.03 (5.76) Southern -47.85 (2.97)

31 31 Aristotle contra Kelvin Kelvin: ``When you measure what you are speaking about and express it in numbers, you know something about it, but when you cannot express it in numbers your knowledge about is of a meagre and unsatisfactory kind.'’ Aristotle: ``...it is the mark of an educated man to look for precision in each class of things just so far as the nature of the subject admits; it is evidently equally foolish to accept probable reasoning from a mathematician and to demand from a rhetorician scientific proofs.'’ Kelvin: ``In science there is only physics; all the rest is stamp collecting.'' Kelvin: ``I can state flatly that heavier than air flying machines are impossible.'’


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