

Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community for help and clear up your study doubts
Discover the best universities in your country according to Docsity users
Free resources
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
The winter 2007 labor economics field exam, focusing on questions related to income support programs and their impact on work participation, as well as the estimation of the effect of high-school graduation on crime committal. Students are required to answer all questions using equations and well-labeled graphs, demonstrating a clear understanding of the problems.
Typology: Exams
1 / 3
This page cannot be seen from the preview
Don't miss anything!
Be as formal and precise as you can in all of your answers, using equations (and well-labeled graphs, where appropriate). Your will be graded on the extent to which you demonstrate your understanding of the problem, and the clarity and precision of your answers. ANSWER ALL THE QUESTIONS. YOU HAVE 3 HOURS
(a) Describe how you would produce this number if you were only given CPS-type data on income, earnings, etc., and specify the assumptions that need to hold (however potentially unrealistic) for the estimate to be valid. (b) Now suppose the government gives you the authority to run a so- cial experiment. Given this ability, describe how you would run the experiment, what data you would collect, and how you would ana- lyze the data to better answer the question. In particular, describe how you might try to separate costs due to “mechanical” effects from those due to behavioral responses to the program, and compare the magnitudes of these two components. (c) Consider an alternative scenario: the government does not let you run an experiment, because they have done so already... sort of. They tell
you that they carried out an experiment as you would have (in ques- tion b), but did not use simple random assignment. Instead, treat- ment and control status were assigned with different probabilities, based on a number of pre-experimental demographic characteristics X (e.g. family size, education, age, earnings histories). Describe why it would be problematic to do simple treatment-control comparisons in analyzing the data from this experiment, and propose a way to adjust for this non-standard assignment mechanism, assuming that you know the exact treatment probability for each value of X. Can you generalize your estimates to the overall population? Why or why not? (d) Now suppose that they ran the experiment in question c, but some important information was lost: the mapping between X and the probability of assignment to treatment. You still have all the other data from the experiment. Describe in detail what you could do to nonetheless obtain sensible estimates, and what further assumptions (if any) are needed. As with question c, can you generalize your estimates to the overall population? Why or why not?
(1) You are interested in estimating the effect of high-school graduation, HS, on the probability of committing a crime, Y. You do not have credible exclusions restrictions and you are therefore concerned with the potential endogeneity of HS. Assume that the latent propensity to commit a crime is Y ∗^ = W Γ + αHS where W is the full set of variables, both observed and unobserved, that determine Y ∗. Call X the subset of W that includes observable variables. (a) In this context, present a framework that formalizes the notion that selection on observables is the same as selection on unobservables to address the potential endogeneity of HS. To get credit, make sure to use formulas, and to give the intuition for the formulas. Be very specific. Make sure to formally characterize all the necessary assumptions. (b) Are these assumptions realistic for the type of datasets that are typically available in labor economics? Using a couple of examples of datasets, explain why you think the assumptions are or are not realistic. (c)Under what conditions can this model be used to identify bounds for the effect of high-school graduation in propensity to commit crime? (d) In the framework developed in point (a), what are the assumptions that you need for the OLS estimator to be consistent?