This exercise analyzes the data from a paper that studies whether additional government revenues affect political corruption or the quality of politicians. The paper can be found at: Brollo, Fernanda,...

This exercise analyzes the data from a paper that studies whether additional government revenues affect political corruption or the quality of politicians. The paper can be found at: Brollo, Fernanda, et al. “The political resource curse.” The American Economic Review 103.5 (2013): 1759-1796. The authors argue that a “political resource curse” exists - that an increase in non-tax government revenues leads to more corruption and lowers the quality of politicians. First, with a larger budget size, incumbent politicians are more able to grab political rent without being noticed by the electorate. Second, a larger budget attracts challengers with poorer quality so that incumbents’ misbehavior is punished less frequently. The authors wish to identify the causal effect of additional federal transfers on corruption and candidate quality. Their theory states that additional non-tax revenues cause corruption, so they use transfers (the treatment) from the federal government to municipal governments as exogenous increases in non-tax revenues. The authors ask whether or not larger transfers lead to corruption, so the outcome is the occurence of bad administration or overt corruption. Since corruption is a somewhat vague concept, the authors use two measurements to make sure that their results do not depend on a particular definition of corruption. To avoid this, the authors use two separate definitions of corruption to avoid this - ‘narrow’ corruption includes severe irregularities in audit reports, while ‘broad’ corruption is a looser interpretation “which includes irregularities [in audit reports] that could also be interpreted as bad administration rather than as overt corruption” (p. 1774). The data can found in corruption.csv in the data folder. Name Description broad Whether any irregularity (this might include bad administration rather than corruption) was found or not. narrow Whether any severe irregularity that is more likely to be visible to voters was found or not. fpm The FPM transfers, in $100,000 at 2000 prices. pop Population estimates. pop_cat Population category with respect to FPM cutoffs. Question 1 First, let’s perform a simple RD analysis to test whether the cutoffs were properly utilized. One of the population thresholds used for FPM transfers was 10188. This means that villages with a population slightly above 10188 received different amounts of transfers to villages slightly below this population. For this analysis, we will use all villages within 500 people of this cutoff. Specifically, this means to take two separate subsets: one subset of villages with populations larger but less than 500 larger than 10188 and another subset of villages with populations smaller but less than 500 smaller than 10188. Then, create a plot showing the relationship between population and fpm transfers for these villages. Please add a dotted vertical line to show the location of the cutoff (10188) on the x-axis. Additionally, fit two regressions and visualize them on the plot: one showing the relationship between population and FPM transfers for the subset of villages above the cutoff and another showing the relationship between population and FPM transfers for the subset of villages below the cutoff.