Project Summary: Quantitative Evaluation Field experiments have been used to test the effectiveness of policy nudgesattempts by government to align desirable social behavior with individual incentives in policy areas ranging from retirement planning to tax compliance. Both the Democratic administration of President Obama and the Conservative government of David Cameron in the U.K. have supported this type of research. For your Discussion this week, choose one of the two scenarios provided and complete the corresponding prompts. Scenario 1: Affordable Care Act Assume that the Affordable Care Act (ACA), a landmark healthcare reform act passed by the United States Government in 2012, is still in the process of full implementation. Prior to its passage, earlier versions originally proposed the provision of medical care free of charge to the U.S. population. Suppose that you have been asked to evaluate the potential effects of the ACA nationwide. There are two key issues to consider. One issue has to do with how much more medical care people would use if it could be offered free of charge. The second issue has to do with what effect the medical care would have on the health of the average person. Assume you have 35 years to conduct the evaluation. QUESTION: Response to the following: Assuming no financial restraint, briefly outline what method(s) you would suggest using for assessing the impact of free coverage on usage of medical services and on health outcomes. Use a randomized field experimental design, a cost benefit/effectiveness quantitative evaluation design, or both, and explain your choice. Scenario 2: Nudging QUESTION: Response to the following: Briefly describe a nudging field experiment design focused on encouraging more self-employed taxpayers to file their estimated taxes. Consider both coercive and nudge style mechanisms to accomplish this, with an aim to demonstrate the effectiveness of the methods. _____________________________________________________________________________________ Introduction to Quantitative Evaluation Introduction Some of you may have experience filling out federal forms for student financial aid or have been the recipient of Pell grants. If so, you know it is a complex procedure. What you may not know is that the federal government is implementing simplification procedures that will reduce the complexity of the application process. This activity is the result of quantitative evaluation experiments that documented the direct relationship of simplification of the process to increases in college enrollment, grant awards, and applications in general. In addition to quantitative evaluation, cost benefit and cost effectiveness analysis are also methods that have been used for many decades in policy analysis and program evaluations. In the past decade, there have been several developments in quantitative research design, two of which are particularly significant for evaluation. This week, you review quantitative approaches that range from the traditional to the newer approaches and apply them to specific scenarios. Learning Objectives Students will: Evaluate quantitative design methods for assessing the impact of public programs and initiatives usage of medical services Examine impact and of nudging in quantitative policy evaluation Analyze techniques of quantitative design Analyze internal validity for non-experimental designs ____________________________________________________________________________________ Required Resources Note: To access this week's required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus. Readings Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe. o Chapter 4, Randomized Field Experiments (pp. 73109) o Chapter 5, The Quasi Experiment (pp. 110142) o Chapter 6, The Nonexperimental Design: Variations on the Multiple Regression Theme (pp. 143208) McDavid, J. C., Huse, I., & Hawthorn, L. R. L. (2013). Program evaluation and performance measurement: An introduction to practice (2nd ed.). Thousand Oaks, CA: Sage. o Chapter 7, Concepts and Issues in Economic Evaluation (pp. 271308) Mills, C. (2013). Why nudges matter: A reply to Goodwin. Politics, 33(1), 2836. Retrieved from the Walden Library databases. USAID. (2013). Impact evaluations. Retrieved fromhttp://www.usaid.gov/sites/default/files/documents/1870/IE_Technical_Note_2013_0903_Final.pdf United States Government Accountability Office (USGAO). (2009). Randomized experiments can provide the most credible evidence of effectiveness under certain conditions. In Program evaluation: A variety of rigorous methods can help identify effective interventions (pp. 2026). Retrieved fromhttp://www.gao.gov/assets/300/298907.pdf Optional Resources Green, D., & Winik, D. (2010). Using random judge assignments to estimate the effects of incarceration and probation on recidivism among drug offenders. Criminology, 48, 357359. Institute of Politics. (Producer). (2013). Nudging policy: Behavioral economics in the public square[Video file]. Retrieved from http://forum.iop.harvard.edu/content/%E2%80%9Cnudging%E2%80%9D-policy-behavioral-economics-public-square Johnson, E., & Goldstein, D. (2003). Do defaults save lives? Retrieved fromhttp://www.dangoldstein.com/papers/DefaultsScience.pdf Khandker, S. R., Koolwal, G. B., & Samad, H. A. (2010). Handbook on impact evaluation: Quantitative methods and practices. Retrieved fromhttps://openknowledge.worldbank.org/bitstream/handle/10986/2693/520990PUB0EPI1101Official0Use0Only1.pdf?sequence=1 McKinsey Quarterly. (Producer). (2011, June). Nudging the world toward smarter public policy: An interview with Richard Thaler [Audio podcast]. Retrieved fromhttp://www.mckinsey.com/insights/public_sector/nudging_the_world_toward_smarter_public_policy_an_interview_with_richard_thaler The World Bank Independent Evaluation Group. (2006). Impact evaluation: The experience of the independent evaluation group of the World Bank. Retrieved fromhttp://ieg.worldbank.org/Data/reports/impact_evaluation.pdf