Finally, we implement a test inspired by Benford’s law to detect electoral manipulation in villages won by the incumbent (see Mebane, 2006, 2011). In Appendix Figure A.2, we plot the distribution of the first, second, third, and last digits of candidate vote tallies separately for villages won and villages lost by the incumbent. Using a Kolmogorov-Smirnov test, we cannot reject the null of equal distributions across the two types of villages for any of the four digit distributions—the p-values from these tests are reported at the bottom of each panel. Nonetheless, panels (c) and (d) of Appendix Figure A.2 show significant heaping of candidate vote tallies at zero, plausibly as a result of rounding. Thus, in Appendix Table A.1, we also show that the number of candidate vote tallies with a trailing zero is not significantly associated with turnovers (column 13). Overall, we find no evidence of manipulation of election results.

# **4 Impacts on Bureaucratic Organization and Information Flows**

We now present our estimates of the effects of turnover in village elections. In this section, we highlight three main shifts. First, turnover reshapes village bureaucracies, improves staff morale, and increases effort exerted by bureaucrats, as reflected in more frequent interactions with citizens (Section 4.1). Second, turnover reduces the presence of bureaucrats with nepotistic ties (Section 4.2). Third, turnover improves information flows between officials and citizens. This improves the bureaucracy’s understanding of citizens’ preferences and leads to stronger alignment regarding policy priorities (Section 4.3).

## **4.1 Organizational Changes**

**Leader Turnover.** Our main specification examines the impact of an incumbent’s electoral defeat in the most recent election on village-level and individual-level outcomes. Using our survey data, we first verify that these electoral results induce a leadership change, as expected. Specifically, we show that an incumbent’s defeat increases the likelihood that the village head in our survey is someone different from the incumbent candidate who competed in the most recent election. The RD point estimate is 83.5 p.p., significant at the 1% level (see Table 2, column 1, and Figure 2, panel a). We also estimate the effect of a turnover on the village head’s tenure. The RD point estimate is roughly (minus) five years, slightly less than the _de jure_ term of six years (see Table 2, column 2, and Figure 2, panel b).

Thus, electoral turnovers translate into leader turnovers at the village level, but there is imperfect compliance. While our baseline specification is a sharp RD estimation of the effect of turnovers ( _γ_ in equation 1), in the Appendix we also report fuzzy RD estimates where we use 1 ( _marginjt >_ 0) as an instrument for village head turnover to account for this imperfect compliance. In this case, the endogenous regressor is a dummy equal to 1 if the village head in our survey sample is a different individual from the incumbent who competed in the most recent election—the dependent variable in column 1 of Table 2. Thus, the sample for this fuzzy RDD estimation is restricted to the _N_ =443 villages in which an incumbent competed in the most recent election and we were able to survey the current village head.

**Bureaucratic Turnover.** Although the majority of village officials have tenured positions, newly elected village heads may seek to reorganize the village government by appointing new officials or by reshuf-

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