Despite the importance of foreign aid to many countries, there is little agreement about whether official development aid (ODA) is effective. In particular, it is uncertain whether foreign aid causes long-term increases in growth rates of the receiving country (i.e., the growth rate of the economy, sometimes called the growth of gross domestic product). In this assignment, you will consider research designs that may be used to answer the question of whether or not receipt of foreign aid causes changes in the long-term rate of economic growth in a recipient country.
1. The World Bank collects information on official development assistance and country growth rates. I have compiled the following data in the file aid growth assignment2.csv:
(a) receipts of development aid for each country in the world in the year 2005 as a percent of GDP (this is the variable oda percent gdp 2005. Each country is put into one of five groups: ODA is
(i) 0-5 percent of GDP, (ii) 5-10 percent of GDP, (iii) 10-20 percent of GDP, (iv) 20-30 percent of GDP, (v) 30-40 percent of GDP, or (vi) 40-50 percent of GDP). The GDP is the overall size of the economy, so for a country where ODA is, say, 10% of GDP, this means that 10% of all income in the country comes from development aid. And,
(b) the growth rate of per capita GDP for each country in the world in 2010 (this is the variable gdp per cap growth 2010).
Use a Pivot Table to find the average growth rate of GDP for countries according to how much ODA they receive (Hint: the Pivot Table rows will be the variable oda percent gdp 2005. The pivot table values will be the variable gdp per cap growth 2010. Under the “Values” settings, use the dropdown menu to ensure you are finding the average growth rate.). Plot the data with a well labeled and formatted plot. Is there strong evidence that more foreign aid causes growth? Consider the four elements of good research design described in Chapter 3 of Kellstedt and Whitten. Explain whether this research design satisfies each of these four hurdles, using 1-2 sentences for each hurdle. (I don’t expect you to conduct any statistical tests; just make the plot described above and then use reasoning.)
2. Imagine that official development aid was allocated to countries based on a lottery system, in which each country drew a random number from a hat, and the value of that random number determined how much foreign aid that country would receive. Imagine gathering similar data as above, and replicating the analysis. Explain whether this research design would satisfy each of Kellstedt and Whitten’s four hurdles. (Of course, since you don’t actually have the data, you can’t say anything about the third hurdle, so just focus on the other three.)
3. Briefly describe (in 1-2 paragraphs) one possible (hypothetical) research design that could provide credible real-world evidence on the causal impact of foreign aid on growth using observational data (in the absence of the lottery system described above). You may find reading (the introductions of) one of the following articles useful (these articles are all on the Brightspace website):
Galiani, Sebastian, et al. “The effect of aid on growth: evidence from a Quasi-experiment.”
Journal of Economic Growth 22.1 (2017): 1-33.
Burnside, Craig, and David Dollar. “Aid, policies, and growth.” American economic review 90.4 (2000): 847-868.
Qian, Nancy. “Making Progress on Foreign Aid.” Annu. Rev. Econ. 7.1 (2015): 277-308. (section on “The consequences of foreign aid”)
Nunn, Nathan, and Nancy Qian. “US food aid and civil conflict.” American Economic Review
104.6 (2014): 1630-66.
4. This (link here) news article says that bilingual babies are smarter (the article is also available as a pdf on the course website in the assignment directory). In 1-2 paragraphs, explain your understanding of the strength of evidence about the causal effect of bilingualism on cognitive ability based on this article. Use the ”four hurdles” from Kellstedt and Whitten to organize your answer.
5. A number of news stories have reported that COVID-19 cases and severity are linked to air pollution. The graph below plots data from pollution concentrations in 2019 (before COVID-19) for about 1,000 counties in the US, and shows how pollution is related to the number of COVID cases per person. Based on this data, would you conclude that air pollution causes more spread of COVID-19? Use the ”four hurdles” framework.
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