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Homework3 - Homework 3 ECO 7427 Prof Sarah Hamersma Due...

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Homework # 3 ECO 7427 Prof. Sarah Hamersma Due Monday, February 28, 2011 (in class) 1. A working paper by Kenneth Chay and Michael Greenstone estimates the effects of certain pollution on the rate of infant mortality (“Air Quality, Infant Mortality, and the Clean Air Act of 1970” – you can find the abstract at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=509182 and can download the paper from there if you are interested). It has been difficult to identify the potential causal relationships between pollution and health because they are likely to be spuriously correlated due to many other variables (ex. poorer areas have more pollution and more health problems/shorter life expectancies, but perhaps that is because poor neighborhoods have more crime, etc.). Chay and Greenstone are able to implement a regression-discontinuity design because of an interesting feature of their pollution data: the Clean Air Act of 1970 (CAA) required pollution levels (total suspended particles, or TSPs) to be under a certain threshold level in order to avoid substantial oversight and regulation by the government. Therefore, counties that were just below this limit were left quite unregulated, and those counties above it were subject to a number of regulations in an attempt to reduce pollution. Not surprisingly, this resulted in substantial decreases in pollution in the regulated counties. Because counties near the threshold were otherwise alike in terms of infant mortality (which usually varies continuously with pollution), one can look for a discontinuous decrease in relative infant mortality rates right after the regulation. If this gap is found, it is likely to establish a causal link between the reduction in pollution and infant mortality. (They do in fact find such a gap). Although I do not have the data from their paper, I have created a simplified artificial data set for this exercise so that you can practice a simple version of the estimation technique used by Chay and Greenstone. Because of this, the results are not necessarily the same as theirs. Also, because the data set is considerably smaller, very few variables will ever be precisely estimated (i.e. statistically significant).
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