PLCY 110 Week 3 Notes
PLCY 110 Week 3 Notes 110
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This 8 page Class Notes was uploaded by Victoria Snow on Monday September 12, 2016. The Class Notes belongs to 110 at University of North Carolina at Chapel Hill taught by Dr. Zimmerman in Fall 2016. Since its upload, it has received 8 views. For similar materials see Global Policy Issues in PLCY at University of North Carolina at Chapel Hill.
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Date Created: 09/12/16
PLCY 110 Week 3 RESEARCH PAPER NOTES 9/6/2016 Overview -Policy issue and response -Comparative case study: 2-4 similar units, at least 1 received study - Diverse outcomes- 4-6 balancing -qualitative/quantitative - short/long term - direct/indirect - intended/unintended - political/economic/social -Difference-in-Differences Design Goal of paper= assess causal impact of policy ****Correlation does not equal causation**** -Need for a causal inference? Counterfactual!!! -Counterfactual: alternative universe, estimate of what of the outcome (Y) would have been for participant in the absence of the program (P) -Difficult for people and countries (because there are no people or countries that are exactly alike) -Ex: plant that you and same species of plant that you do not water. To see the differences of watering the plant, the non-watered plant is the counterfactual. Design of paper- Assess causal impact of a policy by studying a case that received the policy and a “valid” counterfactual case that did not receive the policy Valid Counterfactual- cases similar at baseline on outcomes and contectual factors - Only difference b/w cases is a policy (treatment) - Response to policy is the same - Policy is randomly assigned to 1 case (or group of cases) o Nonhuman process (random generator, coin flip, etc.) o Reduces bias o Every case has equal chance to get policy - Cases have same experiences during period of study o Ex: no wars, world cup, etc. What makes counterfactual in the real world? -Cases need to be similar enough to baseline on relevant outcomes and contextual factors -Only important difference between cases is policy (treatment) -You need to convince that tat the other differences are not important or reagent for the thing you’re studying -One case gets the policy for reason unrelated to the outcomes (Ex: politically- President is trying to get reelected to he makes a policy) -Up to you to argue these things in the paper -Doesn’t have to be different countries -Could be comparing capital cities, schools, villages, etc. -Cannot be individual people or households Dif-in-Dif designs Strengths- - Estimate of over time difference - Estimate of cross country difference - Strong design to estimate effect of policy 3 Subtraction problems (for each outcomes) - In case WITH policy: outcome at the end – outcome at base = change(t) - In case WITHOUT policy: outcome at the end – outcome at base = change(c) - Policy effect: change(t) - change(c) = Effect(t) -Get data on measurements from google, TAs, and prof - Pick points- before and after. Justify it by thinking about how long it might take for an effect to be seen. - Ex: Like life expectancy- can’t be 5 years, needs to be over a few generations -Have a graph (or more) in your paper -time vs outcome Fig: from lecture powerpoint Issue and Policy section: -Relevant to course- global with cause/consequences and concerning outcome -Interests you -Gov. elected- national or sub-national policy -Not from NGO -Specific: AKA can describe it to another country and they could recreate and implement it -Written- find policy document to cite (written by gov. or another source) -Google translate is good to use -Find enough for 1 page for proposal -Google: “Ministry of ______ in ______” - issue (health, education, etc.) in country (Kenya, Nigeria, etc.) 4-6 Outcome selection Guidelines: -Mixed outcomes (listed earlier) - qual=words. Can’t do dif-in-dif design - quan=numbers - Short term=change within a year - Long term=greater than a year - Direct=directly from policy - Indirect=few steps after the policy o ^ judgment call for direct/indirect - Intended - Unintended - Political, economic, social, etc. o Effects of policy Operationalization Translate Figure: from lecture powerpoint Table of identifying outcomes Sources-World Factbook, DHS (demographic health survey), etc. For research proposal: Focus on cases similar enough at baseline on relevant outcomes and contextual factors Only needs to be one page Example: Issue-Violence after soccer game Policy- police in areas after gram Outcomes- DV- - Hospitalization - Non-violent crime - Tourism- unintended Control- (other things that affect DV besides policy_ - Political structure - Social integration Question: How recent does the policy need to be? - The older the better, so we can look at the outcomes and long term effects Similarities in cases need to be: Economic structure Political structure Aid and Effects on Poverty 9/8/16 Foreign aid- Transfer-who? Gov. org, or individual (to/from combo) What? Transfer of resources (money, materials, skills) Everyone has participated in aid- taxes go to it Main Goal- -To accelerate growth achieved in aggregate, ambiguous results for many specific cases Does aid lead to growth? - Almost flat line no relationship - In another graph, as aid increases, growth decreases - Collier- aid tends to speed up growth o Only looking at the bottom billion o The view we take in this class - Colllier does not have great counterfactual - Easterly takes viewpoint of the poor individual: aggregate doesn’t matter to them- they don’t see it and still suffer. It’s not what, it’s how: Aid Approach: Budget support- Money $$ very efficient. Less transaction cost Aid selectivity- $$ in certain places, super poor but have the potential for success Aid agencies- $$ and procedures Contingent aid- $$ for performance (policies, gov.) o Common: audit your gov and you get $ o If you repeal and a bad law (like illegalization of homosexuals), you get $ Earmarked aid- $$ for sectors/projects- like AIDS or climate change projects Aid for capacity building- $$ and training. Helps them make $ later Aid as investment- aid for politics (not where they think it is a good idea, but where they can get political gain) Aid outside of government- Like all of the above, but not to government o NGOs o FBOs (faith based) o Short term volunteers Loans vs Grants o Loans you pay back o Grants- apply and you use them for a certain purpose and can just keep it Factors determining aid approach - Diminishing returns- first million is usually the most valuable (gets the most done) - Moral hazard- countries slack off on their own development, the more aid they receive - Time inconsistency- aid given at time X to pay for changes, but aid often given contingent on changes occurring…Give conditions, if not met, there are no real consequences for the recipient. Effects of Aid (outcomes) 1. Intended- a. Growth b. Self-sufficiency c. Increased quality of life d. Stopping cycles of poverty e. Consumption f. Diversification g. Opportunities h. Economic development i. Political development j. Sustainable development k. Achieving MDGs (or other specific benchmarks) 2. Unintended- a. State capture b. Dependency/free riding c. International priorities vs local needs d. One size fits all (macro vs micro) e. Cultural insensitivity f. Religion and politics g. Negative externalities-behavior’s negative effect on other people (but person behaving does not have to pay/bear social cost) i. Ex: motorcycles- everyone else has to hear the loudness of their engines, and driver doesn’t have to pay Aid dependency- Micro -Little girl got a new pen with a lot of excitement, but would choose it over the counting device she made Aid dependency- Macro -Run out of things like-passport covers, gas, etc. -Can’t function without aid Aid Politics Research - Aid to government is allocated by real people - Sometimes allocate aid according to political factors rather than need o When does one win out over the other? - Ancient question, but difficult to study - Black box process - Post-hoc measurement of “need-based” vs. “politics-based” allocation Our theory- -Making allocation decisions transparent should make aid go to people who really need it -People may feel it’s more fair -People might take action against political allocation Case context- Malawi- - Poor - Dependent on aid-37% of gov budget - Corrupt, aid theft Subject- ward councilors - New - Elected in 462 single-member wards - Authority over development decisions, particularly aid allocation - Accountable to citizens, political superiors (MPs, DCs), donors Design: factorial field exp. with 4 2-factor treatment Sample- 310 councilors (93%) Interaction- asked how to allocate education across constrained choice of schools (needy/political gain) Primary outcome- whether high-need or high-politics schools are more likely to be chosen This is a real decision: a lottery was being held to determine which politicians receive the goods This is a meaningful decision: councillors invested in decision and remain engaged in the aid delivery process. Schools received: iron sheets for roofs, solar lamps, and teacher kits (notebook, chalk, and pen) ½: no one knew about decision ½: sent letter to ADC with decision Findings: used both political and programmatic criteria in decisions Transparency- neediest 20% schools were 40% more likely to receive aid Schools with >50% votes were 12% less likely to be selected **This means that transparency increased the likelihood for needy schools to receive resources**
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