Fighting Crime with a Little Help from my Friends ... - Sciences Po

More documents

Recommendations

Info

from zero. This confirms that politically aligned municipalities experienced a decrease inhomicide rate only after the party governing the majority of its neighbors had come to power.The binary nature of the dependent variable used in Table 4 makes it rather hard to interpretthe magnitude of the effect of political alignment on homicide rate. To give a better sense ofthis magnitude, and given the highly skewed distribution of the homicide rate in our sample,in Table 6 we re-estimate equation (1) using the log of one plus the homicide rate after theelection as the dependent variable. In Table 7 we report the analogous results for the threeyears prior to the election. Controls in each column are the same included in Tables 4 and5. Based on the results in Table 6, we estimate that the improved cooperation resulting frompolitical alignment between a municipality and its neighbors decreases the log of one plusthe homicide rate by 0.73 to 1.05. Given the observed mean in homicide rates (45.4/100,000inhabitants), these coefficients suggest a reduction in murder rates corresponding to a 52 to65 percent reduction. Once again, political alignment does not appear to be correlated withthe murder rate recorded in the three years prior to the election: the estimated coefficients inTable 7 are very close to zero and statistically insignificant.5. DISCUSSIONThe results presented thus far indicate that municipalities that are politically aligned withtheir neighbors experience significantly lower murder rates than those that are not. Althoughthese findings may be explained by better cooperation among local police forces when mayorsof neighboring municipalities belong to the same party, they are also consistent withalternative explanations. For instance, the close election of a mayor from a specific partymay have an impact on crime prevention in a municipality for reasons other than better coordinationwith same-party neighboring mayors, e.g. because crime prevention is a priorityfor that party, or because it supports more effective anti-crime policies. Alternatively, if theparty that governs most of a municipality’s neighbors is also in power at the state or federallevel, political alignment with neighbors may in fact reflect improved cooperation of mu-14
nicipal police with state or federal authorities (as suggested by Dell, 2011) rather than withmunicipal polices in neighboring jurisdictions.In this section we present additional evidence of the robustness of our baseline results and testsome of these alternative explanations. In particular, we test whether the effect of politicalalignment: (i) is larger the higher the share of neighboring municipalities governed by thesame party (in line with an explanation based on improved inter-jurisdictional cooperation),(ii) is not contingent on the identity of the party winning the election; (iii) is not contingenton the identity of the party in power at the state level; and (iv) is not contingent on the factthat the winning party is the same as the incumbent.To test these hypotheses, we turn to a parametric estimation, restricting the sample to municipalitiesfor which the party governing the majority of neighbors won or lost by a marginsmaller than 5%. Equation (2), below, summarizes our empirical strategy which is basedon testing whether the impact of political alignment varies when the latter is interacted withother characteristics:C is = α 0 + α 1 Mwin is + ∑t=1 4 (α 2,tMwin ∗ Sp t is + α 3,t(1 − Mwin) ∗ Sp t is )+(2)α 4 Mwin is ∗Y is + α 5 Sp is ∗Y is ∗ Mwin is + α 6 Sp is ∗Y is ∗ (1 − Mwin is ) + δX is ′ + γ s + ε isThe notation largely reproduces the one used in equation (1); however, because the specificationis parametric, we include a fourth order polynomial of the vote spread on each side ofthe discontinuity. In addition, Y is denotes each of the variables used to separately test each ofthe hypotheses spelled above, namely: (i) the share of neighboring municipalities governedby the party in power in most of them; (ii) a dummy variable indicating whether the partygoverning most of the neighbors is the PAN (in power at the federal level during the periodof interest); (iii) a dummy variable indicating whether the party governing most of the neighborsis also in power at the state level; and (iv) a dummy variable indicating whether theparty governing most of the neighbors is also the incumbent. In this context, the coefficient15
Page 1: Laboratoire interdisciplinaire d'
Page 4 and 5: «[Mexican] municipal police forces
Page 6 and 7: political alignment with state or f
Page 8 and 9: on the functioning, priorities, and
Page 10 and 11: immediate re-election; hence, they
Page 12 and 13: 4. EMPIRICS4.1. EMPIRICAL STRATEGYO
Page 14 and 15: Our empirical specification is then
Page 18 and 19: α 4 captures whether the effect of
Page 20 and 21: nificantly lower homicide rates in
Page 22 and 23: Lee, D. S. (2001). The electoral ad
Page 24 and 25: Figure 2: Municipalities by Mayor
Page 26 and 27: Figure 4: RDD Graphical Analysis% o
Page 28 and 29: Table 2: Descriptive Statistics (Ov
Page 30 and 31: Table 4: Non-Parametric (local line
Page 32: Table 8: OLS Regression ResultsOLS

Fighting Crime with a Little Help from my Friends ... - Sciences Po

Create successful ePaper yourself

Delete template?

Save as template?