For this project, you will be required to use data from one of the following articles:
Angrist, J. and V. Lavy (2009). The effects of high stakes high school achievement awards: Evi- dence from a randomized trial. American Economic Review 99(4), 1384 – 1414. [Data]
Banerjee, A., E. Duflo, R. Glennerster, and C. Kinnan (2015). The miracle of microfinance? Evidence from a randomized evaluation. American Economic Journal: Applied Economics 7(1), 22 – 53. [Data]
Banerji, R. J. Berry, and M. Shotland (2017). The impact of maternal literacy and participa- tion programs: Evidence from a randomized evaluation in India. American Economic Journal: Applied Economics 9(4), 303 – 337. [Data]
Bertrand, M., and S. Mullainathan (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review 94(4), 991 – 1013. [Data]
Chong, A. I. Cohen, E. Field, E. Nakasone, and M. Torero (2016). Iron deficiency and school- ing attainment in Peru. American Economic Journal: Applied Economics 8(4), 222 – 255. [Data]
Gneezy, U., J. List, J. Livingston, X. Qin, S. Sadoff, and Y. Xu (2019). Measuring success in education: The role of effort on the test itself. American Economic Review: Insights 1(3), 291 – 308. [Data]
Muralidharan, K. and V. Sundararaman (2011). Teacher performance pay: Experimental evi- dence from India. Journal of Political Economy 119(1), 39 – 77. [Data]
As noted on the syllabus, you are not being asked to replicate the article that you are getting your data from. Instead, once you let me know which of these articles you are interested in, I will suggest a slight variation on it for you to do (e.g., if the original article analyzed performance for all students, I might suggest that you focus only on the performance of boys).
Ultimately, your aim in this project is to answer a causal (not “casual”) question such as the following: Does being placed into a small class cause students to perform better academically? To do so, you will be required to use a regression model of the following form:
Outcomei = α + βTreatmenti + Xiγ + Ui,
where Outcomei is the outcome (e.g., a test score) for the ith individual, Treatmenti is equal to 1 if the ith individual receives the treatment (e.g., being placed into a small class) and 0 otherwise, Xi is a vector of control variables (e.g., age, gender, etc.) for the ith individual, and Ui is an idiosyncratic error term.
The main parameter of interest is β, which is known as the “average treatment effect” or ATE (no one really cares what α or γ are). Thus, the null hypothesis you will want to test is H0 : β = 0. If any of this is unclear to you, please make sure to spend some time watching my videos that review the background material you are expected to be familiar with from your previous courses in statistics/econometrics.
The project will be completed through 4 “instalments” each worth 20% of your final grade (the other 20% is the test). You should think of these instalments not as 4 separate pieces of work, but rather 4 versions of the same piece of work, each one being “better” than the one that came before it. That is, each instalment should not only add new features, but also improve the existing features (this means fixing any technical errors you had previously, making your writing more clear, etc.).