Re-electing Politicians and Policy Outcomes Under no Term Limits: Evidence from Peruvian Municipalities
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Re-electing Politicians and Policy Outcomes Under no
Term Limits: Evidence from Peruvian Municipalities∗
Fernando Aragón, and Ricardo Pique
January 2018
Abstract
This paper examines whether, in the absence of term limits, re-elected, more experienced
politicians perform differently than their newly elected peers. Using a sharp regression discon-
tinuity design and data from Peruvian district municipalities, we find that having a re-elected
mayor has few meaningful effects on a broad set of local policy outcomes. Our findings sug-
gest that the potential gains from re-electing more experienced politicians may be offset by
rapid learning-by-doing and diminishing electoral incentives. Re-elected mayors only exhibit
greater capacity and performance levels at the beginning of the mayoral term. Moreover, even
though there are no term limits, newly-elected politicians are more likely to be re-elected for an
additional term. Overall, our results cast doubts on the advantages of re-electing experienced
politicians.
JEL: O12, D72, H7
∗
Aragón: Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada. Email: faragons@sfu.ca. Pique:
Ryerson University, Toronto, Ontario, M5B 2K3, Canada. Email: rpique@ryerson.ca. We are grateful to Lori Beaman,
Stephen Easton, Georgy Egorov, Tim Feddersen, Alexey Makarin, Matt Notowidigdo and Krishna Pendakur for useful
comments and suggestions. We are also thankful to Bruno Barletti and Javier Pique; Luis Bernal and Franco Maldonado
at the Peruvian Ministry of Economy and Finance; Jose Hugo Eyzaguirre and Jose Carlos Hurtado at the National Jury
of Elections and Vladimir Zavala at the Office of the Public Prosecutor Specialized in Corruption Crimes for their help
in accessing and collecting the data.
11 Introduction
Elections allow voters to hold politicians accountable by re-electing those authorities who act in the
voters’ interest. However, term limits, which block the possibility of consecutive re-election, have
been introduced in several democracies. By limiting electoral incentives, these restrictions may
lead to re-elected, term-limited incumbents exerting less effort and implementing policies which
are closer to their party or personal ideology. Empirical evidence supports the claim that “lame
duck” politicians perform differently than newly-elected ones (Besley and Case, 1995; Johnson
and Crain, 2004; Alt et al., 2011).
Less is know about the effect of re-electing incumbents in the absence of term limits. In this
case, both re-elected and new politicians have the incentive to win the next election. Since the for-
mer have greater on-the-job experience, these may perform better than the latter. However, political
continuity may also lead to more corruption (Coviello and Gagliarducci, 2017). To avoid the costs
of political entrenchment, voters may be less willing to give an additional term to re-elected politi-
cians, reducing their incentive to put effort. This ambiguity shows the need for empirical evidence
on the effect of re-electing experienced politicians. This evidence will also be informative for the
debate on the consequences of term limits.
In this paper, we study whether re-elected local politicians perform differently than newly-
elected ones in a setting with no term limits. Our analysis uses data from Peruvian district munic-
ipalities after the 2002 decentralization process. This context has several useful features for this
study. First, unlike other settings, incumbent mayors do not have a strong advantage in terms of
election probabilities. This, together with the large number of political movements, means that
there are multiple competitive elections between incumbents and new candidates. Second, Peru-
vian municipalities are responsible for various local tasks and manage an important share of the
government budget. Hence, a politician’s on-the-job experience should be a key determinant of
local outcomes. Finally, detailed data on municipalities and candidates is available.
To identify the effect of having a re-elected mayor, we use a sharp regression discontinuity
design. Our empirical strategy compares outcomes in municipalities where the incumbent barely
won re-election versus those in which the incumbent barely lost (and thus a new mayor was elected).
These municipalities should have comparable characteristics and only differ in the type of authority.
2Hence, our findings can be interpreted as the causal effect of re-electing the incumbent.
Our results show that re-elected mayors do not systematically differ from newly-elected ones in
terms of a broad set of local government outcomes. We find that having a re-elected mayor has no
significant effects on measures of budget size such as per capita municipal revenue, total spending
and public investment. Our estimates are statistically insignificant and small in magnitude. For all
measures, the effects represent less than 6.5% of a standard deviation.
A similar pattern of results holds for indicators of municipal performance and budget allocation.
Re-elected politicians do not appear to have a significant impact on public investment implementa-
tion rates, a measure commonly used by the central government to evaluate municipal performance.
Moreover, there is no evidence of an effect on the percentage of the budget allocated to sectors
with high social returns such as agriculture, education, health, and social services. However, we
do observe a positive effect on transportation expenditures of around 0.2 standard deviations. This
change appears to come at the expense of a reduction in administrative spending. Hence, there is
some, albeit limited evidence that re-elected mayors use their bureaucratic experience to partially
redirect public spending.
Our results are robust to changes in the polynomial of the treatment assignment variable and to
the inclusion of covariates such as municipal characteristics and past realizations of the outcome
variable. More importantly, the absence of significant effects is not driven by a lack of statistical
power. As aforementioned, our estimates are small in magnitude. The average standardized effect
for our measures of budget size, and for budget allocation and investment performance is less than
6% and 9% of a standard deviation, respectively.
The lack of stronger effects is surprising as political experience is expected to lead to differ-
ent policies and better performance. Hence, we examine several factors that could be smoothing
potential differences between re-elected and newly elected mayors.
We first check whether our results are due to differences in selection. In particular, we analyze
how do politicians differ in terms of age, education and work experience. We find that the only
significant difference is that re-elected politicians are more likely to have worked in the public
sector and have 2.9 more years of public sector experience. This difference is expected as re-
elected incumbents have spent the last 4 years in an elected office. Hence, it is not the case that our
treatment also involves changes in other politician characteristics that may be smoothing the effect
3of tenure in office.
Given this, why is it that greater political experience does not translate to differences in policy
outcomes? A possible explanation is that the returns to experience quickly diminish. Relevant
knowledge may be learned in the first year of the mayoral term and experience gained in latter
years may be redundant. To provide evidence on this, we evaluate how differences in municipal
performance and capacity fluctuate by term year. We find that re-elected mayors lead to a significant
increase in public invest implementation rates in the first year of the term. The effect is equivalent
to more than 0.2 standard deviations. However, in latter years, the effect is insignificant and close
to 0. A similar pattern holds for an index of municipal needs for assistance and personnel training,
which we use as a proxy for municipal capacity. Re-elected mayors have significantly lower needs
in the first term year but this difference gradually disappears.
An alternative explanation is that re-elected politicians face lower electoral incentives. If this
holds, the gains from experience may be assuaged by re-elected mayors exerting less effort. Lower
incentives for re-elected incumbents are usually linked to term limits. However, in the absence of
term limits, lower electoral incentives may arise from voters trying to avoid the perils of political
entrenchment or from re-elected politicians focusing on a higher elected office or a career outside
politics.
Our analysis on re-election rates supports this explanation. We find that re-elected incumbents
are 17 p.p. less likely to run for the same office in the next election than newly elected ones.
Moreover, the former are 16.1 p.p. less likely to gain re-election. If we condition this probability
on those incumbents running for re-election, re-elected mayors are 19.6 p.p. less likely to win the
electoral contest. This last finding is particularly important as, to the best of our knowledge, it is the
first evidence of an electoral disadvantage for re-elected incumbents vis-á-vis newly-elected ones.
Taken together, the above results suggest that, even under no term limits, re-elected politicians may
face lower electoral incentives.
While we do not disregard alternative explanations, our results show that rapid learning of
administrative tasks and lower electoral incentives for re-elected incumbents may be smoothing the
effect of politician experience. These findings shed light on how the absence of term limits need
not translate into a difference in policy outcomes between re-elected and newly elected mayors.
Our study relates to two strands of the literature. First, our results complement findings related
4to the effect of tenure in office and the returns to experience. In the private sector, on-the-job
experience is considered an important contributor to human capital and performance. A body of
evidence finds significant returns to experience and seniority in the form of higher wages, and
better promotion prospects.1 Less is known about how political tenure affects performance. To the
best of our knowledge, Coviello and Gagliarducci (2017) provide the only causal evidence on the
topic. Their study focuses on public procurement outcomes in Italy and finds that tenure reduces
the number of bidders and the cost of public works. Our study complements theirs in several
ways. First, we analyze the effect of tenure in a context with no term limits. Hence, the effect of
additional tenure is not confounded by restrictions on electoral accountability.2 Second, we study
the impact on a broad set of outcomes that are relevant in the many decentralized contexts where
local governments have a substantial role in public spending. Most importantly, we find opposite
results and provide evidence on two novel mechanisms that may smooth the effect of tenure. These
highlight that the value of political experience may differ in developing countries and that factors
such as learning of administrative tasks and electoral incentives have to be accounted for.
This paper also relates to a broader literature on the effect of politicians’ incentives and selection
on policy outcomes. Empirical studies have shown that factors that shape politicians’ incentives,
such as term limits (Alt et al., 2011; Besley and Case, 1995), informed voters (Besley and Burgess,
2002), political competition (Besley et al., 2010), or monetary rewards (Ferraz and Finan, 2009),
can affect government policy. Similarly, evidence suggests that leaders’ identity and education mat-
ter for economic growth (Jones and Olken, 2005; Besley et al., 2011). In this literature, the study
most related to ours is that of Alt et al. (2011). The authors analyze the effect of electoral account-
ability and competence of U.S. governors on state government outcomes. They find evidence of
higher economic growth under term-limited and re-elected incumbents. Our findings complement
their results by studying the relative performance of re-elected politicians in a different scenario:
a developing country context with no term limits. Most importantly, our methodological approach
allow us to avoid confounding the effect of experience with that of other factors such as politician
selection. This means we can provide causal evidence on the effect of re-electing politicians under
no term limits.
1 For a review of the literature, see Buchinsky et al. (2010), Dustmann and Meghir (2005) and references therein.
2 Coviello and Gagliarducci (2017) studies mayors who may not be restricted to run for immediate re-election but
will be term-limited in a future term.
5The rest of the paper is organized as follows. Section 2 provides background information on
Peruvian district municipalities and local elections. Section 3 describes the data and the empirical
strategy. Section 4 discusses the main results while section 5 provides evidence on the mechanisms
that can be driving our findings. Finally, Section 6 presents some concluding remarks.
2 Background
District municipalities are the lowest tier of autonomous sub-national government in Peru. In 2014,
the year of the last municipal election, there were 1647 district municipalities. Most of these are
small, rural and relatively poor. For instance, in 2007, the time of the last census in the period
of analysis, the median municipality had around 4,300 inhabitants, out of which 56% live in rural
areas, 34% do not have access to water and 38% do not have access to electricity.
Peruvian municipalities had a marginal role in local development during most of the country’s
history. This changed in early 2002 when the country underwent a process of political and fiscal
decentralization. Additional competences were transferred to municipal governments and central
government transfers increased.3 Among those transfers is a percentage of corporate tax revenues
and royalties from extractive companies operating in the municipality’s region. The commodity
boom in the mid 2000s led to a drastic increase in this source of revenue. Due to these transfers,
local governments now play an important role in local development, particularly with respect to
public investment. Currently, municipalities account for around 20% of the total government budget
and close to 40% of national public investment.
Municipal government has various roles. They are in charge of providing local services (such
as waste collection, and civil register), managing urban planning and business licensing, and par-
ticipating as local liaisons in central government programs related to poverty reduction and food
assistance. They are also in charge of the construction and maintenance of local infrastructure,
such as roads, market places, and parks. In addition, they collaborate with other public agencies
to develop basic infrastructure, such as piped water, sewage and electricity, as well as schools and
health centers.
Municipalities are governed by a mayor and local council members. The mayor holds executive
3 The Municipal Compensation Fund (FONCOMUN) is the main transfer scheme. It redistributes a percentage of
sales tax revenues to local governments.
6powers and plays a crucial managerial role. They are elected in municipal elections using a simple
majority rule and serve a 4-year term. The mayor’s party is also guaranteed at least a simple
majority in the local council independent of its vote share. Throughout the period of analysis, there
were no term limits for local authorities.4 However, it should be noted that their terms can end
prematurely due to a recall vote.5 Almost 60 % of incumbent mayors run for re-election. Success
is, however, limited. Conditional on running for re-election, the re-election rate is around 31%.
Municipal elections are organized and overseen by central government offices, such as the Na-
tional Elections Procedures Office (ONPE) and the National Jury of Elections (JNE).6 These tend
to be quite competitive. For instance, the average winning margin is 9 p.p. and the median election
has more than 8 candidates. Candidates need to meet only basic requirements, such as being a local
resident and not hold positions that may create a conflict of interest. There is no need, however,
to belong to a national political party or to have a minimum level of education or working experi-
ence. In addition, it is important to note that voting is mandatory and failure to do so is subject to
penalties.
Local elections run smoothly and electoral fraud does not seem to be a problem(OAS, 2003;
ONPE, 2003).7 This is important since manipulation of electoral outcomes could invalidate the
identification strategy. We do, however, explore empirically the validity of this assumption.
3 Data and Method
3.1 Data
This paper uses a sample of Peruvian district municipalities. We focus on the last three com-
plete mayoral terms (2003-2006, 2007-2010, and 2011-2014) and their corresponding municipal
elections which took place in 2002, 2006 and 2010.8 Naturally, our sample is restricted to munic-
4 After the 2014 municipal elections, the Peruvian Congress passed a law that prohibits immediate reelection of
municipal mayors.
5 Recalls are requested by local citizens and can be carried out during the second and third years of the mayor’s
term.
6 Elections take place in the same date during the last quarter of the year before the beginning of a new mayoral
term.
7 For instance, in the 2002 elections there were only 13 districts in which elections were invalid due to violence,
low turnout, or large share of null votes.
8 We do not include information on the current ongoing term as mayors are now term limited.
7ipalities in which the incumbent ran for re-election. We aggregate annual observations by taking
the average over the term period. Hence, each observation corresponds to a municipality-term pair.
The final pooled sample includes around 2,700 observations.
Our dataset contains information on electoral results, local fiscal outcomes, municipal attributes
and politician characteristics. The data come from several sources. Electoral results for all mu-
nicipal elections between 1998 and 2014 were provided directly by the JNE or extracted from
the JNE’s data management system INFOGOB.9 It includes information on electoral population,
turnout, party vote shares, null and blank votes, among other variables. We match these results
with lists of mayoral candidates and elected authorities, which come from the same sources, in
order to determined each candidate’s vote share, including that for the incumbent. In addition,
based on recall voting results, we determine which incumbents were recalled and were unable to
conclude their term. Finally, for all mayors in our final sample, we extracted information on their
electoral history from INFOGOB. This data, which goes beyond 1998, allows us to check whether
newly-elected mayors have previous mayoral experience.
As indicators of budget size, we use per capita amounts of total revenue, local tax collection,
total spending and public investment. We also check the effects on local budget allocation across
sectors such as administration, education, health, and transport. The data is obtained from annual
municipal accounts collected and provided by the Ministry of Economy and Finance.10 These
include both budgeted and actual expenditures at the account level of disaggregation.
In addition, we compute measures of municipal performance and capacity. First, based on
municipal accounts, we calculate implementation rates of the public investment budget. This is the
percentage of the municipal investment budget that is actually spent and is frequently used by the
central government to measure municipal performance. Second, as a proxy for municipal capacity,
we construct an index of self-reported needs of technical assistance and training. It is based on
information collected as part of an annual survey of municipalities called RENAMU.11 The survey
provides municipalities with a set of municipal tasks and asks them to state, separately, for which
9 The INFOGOB website provides data on electoral results and the electoral history of localities, parties, and
politicians.
10 These budget reports have official status and are used for national accounting and auditing.
11 The name of the survey stands for Registro Nacional de Municipalidades or National Registry of Municipalities.
This mandatory survey is collected and processed by the National Statistics Institute.
8do they require and training help.12 We calculate the percentage of tasks for which a municipality
requests assistance and the percentage of tasks for which it requires training. The index we use is
the average of these two numbers. We interpret higher values of the index as an indicator of lower
municipal capacity.
To analyze potential differences in politician characteristics, we use data from mayoral candi-
dates’ curriculum vitae. Under the electoral law, submitting a curriculum vitae in a standardized
format is a requirement for candidacy. From this, we obtain characteristics such as age, education
level and previous public sector experience. It should be noted that information is self-reported but
penalties are imposed for misrepresentation.13 Data is available for elections from 2006 onward.14
Finally, the dataset includes information on municipal sociodemographic characteristics such
as life expectancy, education levels, and family income. This data has been drawn from the UNDP.
Table 1 presents summary statistics for the main variables. The sample only includes munic-
ipalities where the incumbent run for re-election. As aforementioned, incumbents have limited
success. Only 31.8% manage to get reelected and, on average, incumbents lose the election by 5
p.p. Elections are competitive and have high participation levels. On average, 7.2 parties present
mayoral candidates, the margin of victory is less than 10% and turnout is around 85%. The average
winning candidate is 44 years old, has a 0.36 probability of having a university degree and has
more than 7 years of public sector experience. An average municipality has revenues of 740 Peru-
vian Nuevos Soles (PEN) per capita, out of which only 4.5 PEN come from local taxes. However,
this amount varies significantly as predominantly urban municipalities tend to collect significantly
higher amounts. Around 34% of its budget is allocated to administrative duties, 17% to health
expenditures, 13.5% to transportation and 11.8% to education.
3.2 Empirical strategy
The empirical analysis aims to identify the effect of re-electing the incumbent on local outcomes.
The main empirical challenge is that municipalities with and without re-elected incumbents may
12 These tasks include, for instance, management and accounting, planning, municipal legislation, project manage-
ment, IT services, statistics, etc.
13 This means that response rates are relatively high. For example, 74% and 84% of mayors in our sample reported
at least one job position in 2006 and 2010, respectively.
14 However, the availability of certain characteristics depends on the election year. For example, data on candidates’
sentences is only available for 2010.
9have different unobservable characteristics.15 These differences can confound our estimates.
To address this concern, we use a sharp regression discontinuity design (RDD) in which the
treatment is having the incumbent mayor re-elected. The assignment of the treatment depends on
the incumbent’s electoral results. Let us define the assignment or running variable for municipality
i in electoral period t as W Mit = vit,m − max j {vit, j6=m }, where vit,m is the vote share obtained by
the running incumbent and max j {vit, j6=m } is the largest vote share obtained by any other candidate.
W Mit represents the “previous incumbent’s margin”. It measures by how much the previous in-
cumbent won (or lost) the re-election. Given this definition, a municipality is treated (i.e., has a
re-elected mayor) if W Mit > 0.16
The regression discontinuity estimand is then defined as:
τRD = lim E [Yit |W Mit > 0] − lim E [Yit |W Mit < 0] (1)
W Mit ↓0 W Mit ↑0
where Yit is the observed outcome of municipality i in electoral period t.
We estimate τRD using local linear regressions. In particular, we use the robust bias-corrected
estimator with a data-driven bandwidth selector suggested by Calonico et al. (2014b).17 Following
Calonico et al. (2014a), our results report the conventional estimate of τ pRD and standard errors but
present the robust bias-corrected p-value levels.
In our main analysis, we exclude municipalities in which the previous incumbent was recalled.
This allow us to focus on the effect of re-elected mayors who have served a complete term. Includ-
ing recalled incumbents may assuage the effect of political experience for two reasons. First, we
would be considering re-elected mayors who may only have 2 or 3 years of experience. Second, we
would be including newly-elected mayors that may have some immediate mayoral experience after
replacing the recalled authority for the remainder of the previous term. However, we still present
the estimates for when all mayors are considered.
The validity of the sharp RD design relies on the assumption that the expected outcome condi-
15 For instance, municipalities that re-elect mayors may have weaker opposition candidates, fewer informed voters,
or better bureaucracies. Similarly, re-elected mayors may be different from newly-elected one in terms of honesty, and
voter preference alignment.
16 In case of a tie, elections are decided by a random draw among tied candidates. In our sample, this scenario only
occurs 3 times. We account for these by assigning a negligible winning margin of 0.0001 if the incumbent wins the
toss and -0.0001 otherwise. Results are robust to excluding these observations.
17 The estimator is implemented by the STATA package rdrobust.
10tional on treatment status is continuous on the running variable. This assumption may not hold if
there is manipulation of treatment status (i.e. if incumbents are able to precisely control their vote
share) or if other treatments depend on the same threshold. We check the validity of the our de-
sign by testing for manipulation of the treatment assignment variable and for balance of covariates
around the treatment cut-off.
To check for manipulation, we first use the conventional McCrary (2008) test. Figure 1 shows
the estimated density function of the assignment variable for our complete sample and for that
which excludes recalled mayors. For the former, we find no evidence of a discontinuity of the
density of municipalities at the treatment cut-off. The McCrary (2008) discontinuity estimate is
negative and insignificant. For the latter, the equivalent estimate is also negative but significant
at the 10% level. This last result is surprising and not consistent with the qualitative evidence
on lack of electoral fraud (OAS, 2003; ONPE, 2003).18 Moreover, the estimate sign does not
fit expectations. On average, incumbents should have more power to alter their vote shares as
they control local government institutions. Hence, if electoral results are manipulable, a positive,
significant discontinuity would be expected.
We further test for manipulation by calculating an empirical p-value based on carrying out the
McCrary (2008) test at 200 equally spaced cut-offs in the interval [−10%, 10%] of the forcing
variable. The p-value is around 0.25 for the full sample and close to 0.23 for the restricted sample.
The lack of significance supports the claim that there is no manipulation of the running variable.
Finally, we perform a recent test proposed by Cattaneo et al. (2016) which has better size properties
than the McCrary (2008) one.19 In both cases, the test fails to reject the null hypothesis of no
discontinuity with p-values of 0.27 for the full sample and 0.17 for the restricted one.
Second, we examine whether there are discontinuities at the cut-off in covariates and past re-
alizations of our main outcomes. As before, we do this analysis for both the full sample and
that which excludes previously recalled mayors. Table 2 shows the RD estimates for these vari-
ables. Consistent with the identification assumption, there are no significant treatment effects on all
pseudo-outcomes for both samples.In Figure A1 in the Appendix, we depict the relation between
the assignment variable and selected placebo outcomes using a 4th degree polynomial fit on each
18 In
Figure 1, no clear discontinuity is observed by comparing the bins around the cut-off. It appears that the result
may be
19 The test is implemented using the STATA package rddensity.
11side of the discontinuity. The graphs illustrate that there are no significant jumps at the cut-off. In
addition, we perform a permutation test proposed by Canay and Kamat (2016). Using permutations
of a small number of observations, this test checks for the continuity of the distribution of outcomes
at the cut-off.20 Columns 2 and 4 in Table 2 report the test p-values. We consistently fail to reject
the hypothesis of continuity in the distribution of placebos at the threshold.
Taken together, these two set of results yield support to the validity of the identification assump-
tion.
4 Main Results
Table 3 presents the effects of having a re-elected mayor on our main outcomes under various spec-
ifications. Panels A and B show the estimates for measures of budget size and spending patterns,
respectively. The analysis excludes incumbents who were recalled in the preceding term. Hence,
we focus on the effect of re-elected mayors who successfully completed their past term.
The results in Column 1 of Panel A show that, under our baseline specification, re-electing the
incumbent has no significant effects on per capita municipal revenue, spending, local tax collection,
and public investment. The estimates are not only statistically insignificant but small in magnitude.
In all cases, they represent less than 7% of a standard deviation. Moreover, the average standardized
effect for all four measures is less than 6% of a standard deviation. Figure A2 in the Appendix
presents the graphical representation of these results. The graphs illustrate that there is no sizable
discontinuity in outcomes at the assignment variable cut-off.
We check the lack of significant effects on budget size indicators by carrying out the Canay and
Kamat (2016) permutation test. The test p-values are shown in Column 5. While all of our RD
estimates are small and statistically insignificant, the permutation test does find discontinuities in
the distribution of outcomes for three of our four measures. Note that the test evaluates changes
in the distribution rather than discontinuities in the mean. Hence, even though we fail to reject
the latter, we cannot disregard the possibility of changes in higher order moments of budget size
measures.
20 Following Canay and Kamat (2016), we use a rule-of-thumb formula to determine the number of observations
used in the test and report the test p-values.
12We also find that re-electing the incumbent has limited effects on how mayors spend their
budgets. The results in Panel B of Table 3 show that there are no significant effects on the public
investment implementation rate, a commonly used measure to evaluate municipal performance21
and on the percentage of the budget allocated to agriculture, education, health, and social services.
All of these effects are less than 6% of a standard deviation.
However, we do find a significant effect on transportation expenditures of around 2 p.p. or
0.2 standard deviations. This increase appears to be coming at the expense of a reduction in ad-
ministrative spending.22 The permutation test and the graphical representation of the analysis in
Figure A3 in the Appendix portray a similar picture. The test rejects the null of no discontinuity
for transportation expenditures at the 10% significance level and barely fails to reject it for the case
of administrative spending.
The above results are robust to changes in the order of the assignment variable polynomial and
to the introduction of covariates. Columns 2 to 4 in Table 3 show our estimates for alternative spec-
ifications. The only discrepancy that we observe is that the effects are larger in terms of magnitude
when we introduce a second order polynomial and do not control for covariates. Under this spec-
ification, the average standardized effects for our measures of budget size and spending patterns
are 12.5% and 10.7% of a standard deviation, respectively. Most importantly, the pattern of results
holds when we introduce covariates such as the past value of the outcome variable and basic munic-
ipal sociodemographic characteristics. This exercise increases the precision of our estimates. As
before, under these specifications, we only find a significant effect for transportation expenditures.
Moreover, our results hold for different samples. First, we check whether the exclusion of
observations where the mayor was recalled in the previous term has a sizable effect on our results.
The estimates for when these are included are shown in columns 1 and 2 of Table 4. These reveal
that our results are similar under the full sample. We still observe that the only significant impact of
having a re-elected mayor is on transportation expenditures, though the permutation test still finds
discontinuities in the distribution of three budget size measures. That is, including incumbents with
partial term experience has no significant impact on our findings.
We then check whether the results hold when we further restrict the baseline sample by exclud-
21 SeeLoayza et al. (2014) for further discussion on this measure.
22 While the effect on administrative spending is statistically insignificant, its magnitude is around 0.15 standard
deviations.
13ing where the newly-elected mayor has previous mayoral experience.23 This allow us to compare
re-elected mayors with a completed term with newly-elected mayors who assume mayoral office
for the first time. The results for these sub-sample are shown in columns 3 and 4 of Table 4. As be-
fore, there is a lack of sizable and statistically significant effects. Hence, it appears that our findings
are not driven by some municipalities on the left side of the cut-off being treated with an authority
with previous mayoral experience.
A possible concern is that the lack of significant effects may be due to mayors having limited
discretion over local policy outcomes. As documented in Section 2, Peruvian municipalities obtain
a significant share of their resources from government transfers. These are set based on prede-
fined rules and indicators. Hence, local authorities are generally unable to change these amounts.
However, while this may affect our estimates for municipal revenue, other outcomes should be
largely unaffected. In particular, this concern is not relevant for our measures of spending patterns
as mayors have control over public investment implementation rates and budget allocation.
Overall, the estimates point to re-elected mayors not having meaningful effects on government
outcomes. This contrasts with the expectation that political experience should lead to differences
in policy making. However, we do find some evidence that tenure in office may matter for specific
outcomes.
5 Mechanisms
Reelected mayors appear to have a limited effect on local government outcomes. In this section, we
explore possible explanations for the lack of stronger effects. First, we explore whether reelected
and newly elected mayors share similar characteristics, except for their differences in political
experience. Second, we check whether inexperienced mayors gain relevant political experience at
a rapid pace. We do by examining how differences in outcomes vary throughout the mayoral term.
Third, we analyze whether, even in the absence of term limits, reelected mayors face lower electoral
incentives that may be reducing their incentive to exert effort and profit from their experience.
23 We
define mayoral experience as having served as a mayor in any district or province. Mayors need not have
completed an entire term to be excluded.
145.1 Politician Characteristics
We first explore how reelected an new mayors compare in terms of their individual characteristics.
In particular, we check whether they differ in terms of age, education level, gender and work
experience. This exercise is important to understand if personal characteristics other than political
experience are changing at the treatment cut-off.
The results are shown in Panel A of Table 6. We observe that there are no significant differences
in age and gender. In terms of education levels, mayors do not differ in terms of the probability
of having completed university studies. However, re-elected mayors are more likely to have com-
pleted secondary education. This last result should be interpreted with caution as information is
only available for candidates in the 2010 election and the permutation test clearly fails to find a
discontinuity.24 In addition, we find that mayors do not differ in the likelihood of having a previous
sentence.25
As expected, the key difference between re-elected and newly elected mayors is in their public
sector experience. Reelected politicians are 14.7 p.p. more likely to have worked in the public
sector. Moreover, they have 2.9 more years of public sector experience.26 Note that while the
estimate is marginally insignificant, new mayors appear to be more likely to have private sector
experience. This is expected as new mayors may have spent part of the previous electoral term
working in the private sector.
The evidence supports the claim that the dominant distinction between mayors is the difference
in their political experience. It also motivates the analysis of alternative mechanisms that may be
driving the lack of stronger effects in policy outcomes. However, we cannot rule out that mayors
may substantially differ in other unobservable characteristics that may affect policy.
5.2 Learning and Experience
At the start of the electoral cycle, reelected mayors are more experienced. However, it is possible
that relevant political experience is quickly gained in the first part of the mayoral term. That is,
24 We obtain a p-value of around 0.6.
25 As with the case of secondary education, data for this outcome is only available for the 2010 election.
26 Notice that spending the last four years in elected office need not translate into four more years of public sector
experience as the new mayor may have spent those years as a public sector employee.
15reelected and rookie mayors would have similar levels of expertise by the latter part of the term. In
this case, differences in average policy outcomes for the entire electoral cycle may be small.
To test for this hypothesis, we check how the mayors’ administrations differ in terms of munic-
ipal capacity and performance in each year of their term. As a measure of municipal capacity, we
use the index of municipal needs for technical assistance and training in municipal tasks described
in Section 3.1. As in Section 4, we use municipal public investment implementation rates as a
measure of performance.
The results are shown in Table 5 and are illustrated graphically in Figure A4. For both municipal
performance and capacity, the general pattern is clear. The largest and most significant differences
are observed in the first year of the mayoral term. Reelected mayors perform better in terms of
investment implementation. They also appear to be better able to run the municipal governments
as they have lower needs for assistance and training. This first-year estimates are equivalent to 0.23
and 0.42 standard deviations for investment implementation and municipal needs, respectively. For
the case of investment performance, there are no other significant differences in latter years, though
there is a smaller spike in the third year. As for municipal capacity, there is a gradual decline in the
estimates. For both measures, mayors are statistically indistinguishable by the end of their terms.
Hence, it appears that relevant experience on municipal tasks is gained relatively quickly. This
rapid learning by new mayors can help explain why we do not observe more meaningful differences
in terms of government outcomes. However, this evidence does not rule out that other factors may
be smoothing differences throughout the term.
5.3 Electoral Accountability
Under no term limits, both reelected and new mayors can run for consecutive additional terms.
However, this need not imply that both face similar electoral incentives. One reason for this is that
re-elected mayors may assign a lower value to an additional term. These may be focused on running
for higher office or on an alternative career path. Most importantly, it is plausible that re-election
probabilities depend on the number of consecutive terms the mayor has already been elected for.
This could be due to the possible consequences of political entrenchment. If re-elected mayors face
lower re-election probabilities, they may exert less effort than their newly elected peers. Lower
electoral incentives could help explain why more experience does not translate to more local tax
16collection, higher investment implementation rates, or more spending towards high social return
sectors.
To check for differences in electoral incentives, we estimate the effect of having a re-elected
mayor on the probability that the mayor runs in the next election and on re-election probabilities.
Panel B of Table 6 shows the results. First, we find that re-elected mayors are 17 p.p. less likely to
run for an additional term. Second, we find a large drop in re-election probabilities for re-elected
mayors. The unconditional probability, which does not condition on whether the incumbent runs
in the next election, decreases by around 16 p.p. The size of the drop highlights that this is not only
due to re-elected incumbents pursuing re-election at lower rates. When we condition the re-election
probability on those incumbents that opt to run, the drop is slightly bigger and stands at 19.6 p.p.
The above results may be due to voters conditioning their behavior on the incumbent’s number
of terms. This behavior can be rationalize by considering the possible negative effects of political
entrenchment. Coviello and Gagliarducci (2017) finds that increased tenure in office reduces the
number of bidders and the cost of public works. That is, experienced politicians may be better
at capturing resources. In a context with term limits, voters need not worry about this as those
politicians will not be able to run for more consecutive periods. In the absence of these restrictions,
voters may anticipate that giving an additional term to an already re-elected mayor implies a high
risk of political capture in the next period. Hence, voters may offer re-election probabilities which
depend on the number of periods the incumbent has been in office. In particular, they may be more
willing to re-elect a one-term than a two-term incumbent. This effect can be particularly important
in a weak institutional context where local governments have large budgets.
An alternative explanation is based on the observation that re-elected mayors are less likely to
run for an additional term. This could be a response to voter’s offering lower re-election probabil-
ities to experienced incumbents. However, it could also be due to re-elected mayors being more
likely to seek other elected positions or career paths. If those who do not run for an additional
term are those whose better attributes lead them to have a higher opportunity cost, then it is pos-
sible that the average quality of re-elected mayors who seek an extra term is lower than that of
new incumbents seeking re-election. Voters would then be more likely to re-elected a one-term
incumbent.
We provide evidence on this by estimating the effect on the probability that the incumbent runs
17for provincial mayor in the next election.27 We find that re-elected mayors are more likely to focus
on pursuing a higher elected office as they are 7 p.p. more likely to run for provincial mayor.
Independent of the explanation, the evidence supports the claim that re-elected incumbents may
face lower incentives to exert effort for their current job. These lower levels of effort may dampen
the gains from greater political experience and help explain the lack of stronger effects of having a
more experienced mayor.
6 Conclusion
This paper examines the effect of re-electing incumbents on local government outcomes in the
absence of term limits. Using the case of Peruvian local mayors and a regression discontinuity
design, we find that having a re-elected mayor has limited effects on a broad set of measures of
budget size and budget allocation.
We find that re-electing mayors leads to sizable improvements in municipal capacity and per-
formance in the first term year. However, these differences later disappear. Moreover, we show
that re-elected mayors are less likely to run for an additional term and obtain a new electoral vic-
tory. Re-election rates for re-elected incumbents are significantly lower even when conditioning
for those mayors who decide to run. Hence, our results suggest that the lack of more sizable ef-
fects may be due to rapid learning among newly elected mayors and lower electoral incentives for
re-elected incumbents offsetting the effect of political experience.
The previous results are informative for the debate on the costs and benefits of term limits for
local politicians. Our findings indicate that the gains from tenure in office are not sizable. Moreover,
the highest returns to experience appear to occur in the first term year. Hence, while introducing
term limits restrict electoral accountability, any negative effect on outcomes due to lower politician
experience may be small. This will be particularly so in contexts with long electoral cycles. Finally,
our result on the electoral disadvantage that re-elected incumbents face vis-á-vis newly elected ones
shows that the former may face lower electoral incentives even under no term limits.
There are, however, certain caveats that should be considered when interpreting our findings.
First, the results report the average effect of having a re-elected politician. This may be hiding
27 Provincial office is the usual next step for a local politician.
18heterogeneity across municipalities which we may not be able to accurately characterize. Second,
there are outcomes such as quality of public goods which we are not able to observe and for which
there can be an effect of tenure in office.
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20Tables and Figures
Table 1: Summary Statistics
Variables Nr. Obs. Mean S.D. Min Max
Incumbent is reelected 2817 0.318 0.466 0 1
Winning margin of incumbent 2817 -5.084 15.32 -61.83 97.65
Log of municipal revenue p.c. 2813 6.606 0.911 4.278 11.26
Log of local tax revenue p.c. 2813 1.495 1.510 0 7.934
Log of municipal spending p.c. 2813 6.351 0.847 4.199 10.04
Log of municipal investment p.c. 2813 5.815 1.078 1.989 9.799
Investment execution rate % 2813 74.68 13.71 14.35 100
Administrative spending, % 2812 34.02 11.45 4.063 76.79
Agriculture spending, % 2812 5.538 8.126 0 73.32
Education spending, % 2812 11.77 8.844 0 53.62
Health spending, % 2812 16.95 12.72 0 84.38
Social services spending, % 2812 10.57 7.550 0.190 54.65
Transportation spending, % 2812 13.54 9.987 0 71.40
Turnout 2817 85.41 5.806 53.17 98.81
Number of parties 2817 7.162 2.814 2 20
Margin of victory 2817 9.417 9.168 0 97.65
Winner’s vote share 2817 34.63 10.50 14.47 98.82
Mayor subject to recall 2817 0.197 0.398 0 1
Mayor recalled 2817 0.0536 0.225 0 1
Mayor’s Age 1979 44.62 8.809 21.43 76.06
Mayor has university degree 1967 0.358 0.480 0 1
Mayor completed tertiary education 1967 0.533 0.499 0 1
Mayor’s years of public service 960 7.270 9.063 0 50.25
Mayor’s number of corruption complaints 965 0.846 1.830 0 28
Mayor has a sentence 960 0.0729 0.260 0 1
Life expectancy, 2003 2814 67.86 3.669 53.33 74.01
% with high school diplomas, 2003 2814 45.49 23.20 0.178 99.93
Average years of education, 2003 2814 6.178 2.187 1.907 13.94
Family income per capita, 2003 2814 283.7 143.8 76.53 1219
Notes: Summary statistics are based on all municipality-year observations in which the in-
cumbent ran for re-election. Monetary variables, such as revenue or investment per capita,
are measured in Nuevos Soles (PEN).
21Table 2: Balance on Placebo Outcomes
Full Sample Excluding Previously Recalled
Permutation Permutation Dep. Var.
RD Estimate RD Estimate
p-value p-value Mean SD
(1) (2) (3) (4) (5) (6)
A. Socioeconomic Characteristics
Life expectancy, 2003 0.040 0.416 0.035 0.455 67.86 3.669
(0.387) (0.383)
% with high school diplomas, 2003 0.346 0.652 0.317 0.685 45.49 23.20
(2.434) (2.368)
Years of education, 2003 -0.113 0.196 -0.110 0.223 6.178 2.187
(0.222) (0.231)
Family income per capita, 2003 -16.371 0.580 -15.492 0.545 283.7 143.8
(16.299) (16.534)
B. Public Finance
Log of municipal revenue p.c. in previous term 0.039 0.135 0.030 0.285 5.898 0.936
(0.098) (0.096)
Log of local tax revenue p.c. in previous term -0.054 0.465 -0.046 0.639 1.318 1.381
(0.152) (0.152)
Log of municipal spending p.c. in previous term 0.040 0.215 0.029 0.410 5.698 0.869
(0.092) (0.011)
Log of municipal investment p.c. in previous term 0.075 0.279 0.058 0.515 5.058 1.088
(0.123) (0.120)
C. Electoral Outcomes
Turnout in t 0.477 0.622 0.437 0.667 85.41 5.806
(0.630) (0.631)
Number of Parties in t -0.212 0.901 -0.199 0.981 7.162 2.814
(0.291) (0.296)
HHI of Parties in t 118.581 0.279 113.166 0.456 2493 924.1
(90.638) (91.086)
Notes: * denotes significance at 10%, ** significance at 5% and *** significance at 1%. Standard errors in brackets are calculated using
a heteroskedasticity-robust nearest neighbor variance estimator with the minimum number of neighbors equal to three. Column 1 shows
conventional RD estimates under our baseline specification excluding municipality-years where the previous incumbent was recalled.
Significance levels are based on robust standard errors following Calonico et al. (2014b). Column 2 shows the p-values for the Canay
and Kamat (2016) permutation test. Columns 3 and 4 report the mean and standard deviation for the outcome variable based on all
municipality-years excluding those where the previous incumbent did not run or where he was recalled.
22Figure 1: Estimated Density Function of Assignment Variable
Full Sample
.04
.03
.02
.01
0
-100 -75 -50 -25 0 25 50 75 100
Previous Incumbent's Winning Margin
Excluding Recalled Incumbents
.04
.03
.02
.01
0
-100 -75 -50 -25 0 25 50 75 100
Previous Incumbent's Winning Margin
Estimated density 95% C.I.
23Table 3: Effect of Re-elected Mayor on Government Outcomes
Permutation Effective Dep. Var.
RD Estimates
p-value N. Obs Mean SD
(1) (2) (3) (4) (5) (6) (7) (8)
Polynomial order 1st 2nd 1st 2nd 1st
Baseline Covariates No No Yes Yes No
A. Local Budget Size
Log of municipal revenue p.c. 0.052 0.126 0.055 0.045 0.0450 1573 6.589 0.907
(0.089) (0.122) (0.049) (0.064)
Log of local tax revenue p.c. -0.075 -0.066 -0.023 -0.013 0.650 1492 1.497 1.508
(0.164) (0.217) (0.061) (0.084)
Log of municipal spending p.c. 0.055 0.148 0.054 0.036 0.0420 1524 6.335 0.843
(0.084) (0.118) (0.043) (0.057)
Log of municipal investment p.c. 0.066 0.153 0.058 0.042 0.0410 1467 5.797 1.076
(0.112) (0.151) (0.061) (0.082)
B. Spending Patterns
% of investment budget implemented 0.781 1.798 0.208 0.918 0.635 1291 74.72 13.71
(1.754) (2.346) (1.582) (2.220)
Administrative spending, % -1.681 -2.520 -1.010 -1.768 0.104 1716 33.97 11.43
(1.247) (1.696) (1.159) (1.669)
Agriculture spending, % -0.390 -0.305 -0.578 -0.887 0.360 1804 5.522 8.153
(0.970) (1.308) (1.008) (1.273)
Education spending, % 0.490 0.782 0.599 0.580 0.296 1812 11.77 8.862
(0.860) (1.174) (0.867) (1.080)
Health spending, % -0.731 -0.109 -1.428 -1.468 0.655 1737 16.90 12.74
(1.249) (1.801) (1.284) (1.666)
Social services spending, % 0.333 0.306 0.392 0.260 0.613 1467 10.64 7.563
(0.759) (0.883) (0.644) (0.832)
Transportation spending, % 2.004* 2.218 2.087* 2.379* 0.0691 1396 13.54 9.988
(1.122) (1.320) (1.143) (1.330)
Average Standardized Effect (joint for A) 0.058 0.125 0.048 0.035
Average Standardized Effect (joint for B) 0.087 0.107 0.088 0.112
Notes: * denotes significance at 10%, ** significance at 5% and *** significance at 1%. Standard errors in brackets are calculated
using a heteroskedasticity-robust nearest neighbor variance estimator with the minimum number of neighbors equal to three.
Significance levels are based on robust standard errors following Calonico et al. (2014b). Column 1 shows conventional RD
estimates under our baseline specification. Columns 2 to 4 present conventional RD estimates under a 2nd order polynomial with
no covariates, a 1st order polynomial with covariates and a 2nd order polynomial with covariates, respectively. Covariates used in
Columns 3 and 4 include previous value of the outcome variable, and 2003 values of human development index, life expectancy,
% with high school diplomas, average years of education, and family income per capita. Column 5 shows the p-values for the
Canay and Kamat (2016) permutation test. Column 6 displays the number of observations chosen by the bandwidth-selection
algorithm used to compute Column 1 estimates. Columns 7 and 8 report the mean and standard deviation for the outcome variable
based on all municipality-years in the sample which excludes those observations where the mayor was recalled in the previous
term. All estimates are based on this restricted sample.
24Table 4: Effect of Re-elected Mayor on Government Outcomes under Different Samples
Excluding New Mayors
Full Sample with Previous Mayoral Experience
Permutation Permutation Dep. Var.
RD Estimate RD Estimate
p-value p-value Mean SD
(1) (2) (3) (4) (5) (6)
A. Local Budget Size
Log of municipal revenue p.c. 0.055 0.0450 0.082 0.101 6.606 0.911
(0.090) (0.094)
Log of local tax revenue p.c. -0.075 0.650 -0.056 0.872 1.495 1.510
(0.164) (0.165)
Log of municipal spending p.c. 0.060 0.0541 0.082 0.103 6.351 0.847
(0.085) (0.089)
Log of municipal investment p.c. 0.074 0.0290 0.113 0.0711 5.815 1.078
(0.113) (0.120)
B. Spending Patterns
% of investment budget implemented 0.877 0.638 0.673 0.513 74.68 13.71
(1.735) (1.782)
Administrative spending, % -1.699 0.105 -1.676 0.274 34.02 11.45
(1.246) (1.309)
Agriculture spending, % -0.404 0.345 -0.527 0.609 5.538 8.126
(0.883) (1.024)
Education spending, % 0.619 0.298 0.589 0.457 11.77 8.844
(0.861) (0.891)
Health spending, % -0.708 0.648 -0.420 0.976 16.95 12.72
(1.273) (1.271)
Social services spending, % 0.274 0.615 0.012 0.522 10.57 7.550
(0.770) (0.829)
Transportation spending, % 1.958* 0.0651 1.997* 0.237 13.54 9.987
(1.109) (1.146)
Average Standardized Effect (joint for A) 0.062 0.082
Average Standardized Effect (joint for B) 0.089 0.080
Notes: * denotes significance at 10%, ** significance at 5% and *** significance at 1%. Standard errors in brackets are calculated
using a heteroskedasticity-robust nearest neighbor variance estimator with the minimum number of neighbors equal to three. Signifi-
cance levels are based on robust standard errors following Calonico et al. (2014b). Columns 1 and 2 show conventional RD estimates
and p-values for the Canay and Kamat (2016) permutation test for the full sample which also includes incumbents recalled in the
previous term. Columns 3 and 4 show conventional RD estimates and p-values for the Canay and Kamat (2016) permutation test for
the sample which excludes newly-elected mayors that have previous mayoral experience in any province or district. Columns 7 and 8
report the mean and standard deviation for the outcome variable based on all municipality-years in our sample. Average standardized
effects in columns 1 and 3 are calculated based on standard deviations in the respective sample.
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