Experimental Insights in Social Sciences

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Gain valuable insights into the world of social sciences through experimental mechanisms and policy evaluations. Explore the evolving field of experimental action-oriented studies and the quest for policy-relevant information within a budget. Delve into the applications of experimental design, the dynamics of policy outcomes, and the significance of mechanistic experiments in advancing social programs.

  • Social Sciences
  • Experimental Mechanisms
  • Policy Evaluation
  • Mechanism Experiments
  • Policy Relevance

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  1. Mechanism experiments Jens Ludwig University of Chicago & National Bureau of Economic Research

  2. The social sciences, like the physical or biological sciences, are intellectual subjects, directed primarily toward understanding than action action Henry Reicken, 1969. President, Social Science Research Council understanding rather

  3. Increasingly experimental action- oriented field

  4. Experimental design problem: How to get as much policy-relevant info for given level of spending?

  5. Y = outcome P = policy Usual approach: Test a P as close to real-world large- scale implementation as possible P Y Policy evaluation

  6. $2 billion

  7. Peter Rossis Iron Law of Evaluation The expected value of any net impact assessment of any social program is zero

  8. PMY P = small schools Small school theory Y = student outcomes M = Greater school autonomy Peers with aligned interests Greater bonding with teachers & school staff

  9. A tale of two possible experiments Policy evaluation P Y Mechanism experiment M Y Level of randomization could be either student or school Level of intervention is school Hence the $2 billion cost Get a sample of charter schools already have autonomy (one M) Randomize students to after school / weekend bonding time with school staff Group students by interests Cost < $2 billion

  10. PY not always best way to get policy-relevant information We could look at P M We could look at M Y For testing P M we don t need same power as for P Y For testing M Y, don t need feasible, scalable real-world policies Mechanism experiments

  11. What are mechanism experiments good for? Function Rule out policies Example Small schools

  12. What are mechanism experiments good for? Function Rule out policies Expand set of policies for which we can forecast effects Example Small schools Moving to Opportunity (MTO)

  13. The MTO Experiment MTO demonstration authorized by U.S. Congress -- Housing and Community Development Act of 1992 -- A randomized social experiment Open to families with children living in: -- public housing or in project-based assisted housing -- high-poverty neighborhoods (poverty rate >= 40%) 5 Sites: Baltimore, Boston, Chicago, Los Angeles, and New York -- 4600 families enrolled from 1994 to 1998 13

  14. Random Assignment to 3 Groups Control No vouchers remain eligible for current project-based housing assistance Low poverty voucher (LPV) Restricted Section 8 voucher (<10% Poverty Census Tract) + Mobility Counseling Traditional voucher (TRV) Conventional Section 8 vouchers 14

  15. Neighborhood Poverty Distribution (Weighted by time spent in each neighborhood during study period) Traditional Voucher Compliers vs Control Compliers 5 4 3 Density 2 1 0 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Neighborhood Poverty Rate Con Compliers (TRV) TRV Compliers 15

  16. Neighborhood Poverty Distribution (Weighted by time spent in each neighborhood during study period) Low-Poverty Voucher Compliers vs Control Compliers 5 4 3 Density 2 1 0 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Neighborhood Poverty Rate Con Compliers (LPV) LPV Compliers 16

  17. MTO effects on student test scores

  18. What are mechanism experiments good for? Function Rule out policies Expand set of policies for which we can forecast effects Concentrate resources where there is greatest uncertainty Example Small schools Moving to Opportunity (MTO) Poverty / achievement link

  19. P MY P = poverty M = stress Y = student achievement Policy evaluation (P Y) Mechanism experiment (M Y) Vs.

  20. What are mechanism experiments good for? Function Rule out policies Expand set of policies for which we can forecast effects Concentrate resources where there is greatest uncertainty Strengthen causal inference Example Small schools Moving to Opportunity (MTO) Poverty / achievement link Schooling / crime link

  21. Source: Swisher and Dennison LSE

  22. Mechanism experiment Sample Vocational curriculum Executive functioning curriculum Control

  23. Barriers to mechanism experiments

  24. Lots of barriers to doing mechanism experiments are generic to all experiments Barrier to experimentation Randomization aversion Long-term outcomes (e.g. crime) Potential solution Incentives or clarify practical value Intermediate outcomes (school disciplinary actions) Etc.

  25. Unique barrier for mechanism experiments

  26. Basic research in medical sciences (good-to-great reputation) Basic research in social sciences (bad-to-terrible reputation)

  27. Need to figure out how to get more from less

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