Political Dynasties, Term Limits and Female Political Empowerment:Evidence from the Philippines⇤

Julien Labonne†Sahar Parsa ‡

Pablo Querubin§

February 2017

We study female representation in the Philippines. We first provide evidence for a previouslyunderstudied channel for female access to office: binding term limits constitute critical juncturesin which dynastic women are 240 percent more likely to access political office. We then showthat in municipalities where a term-limited incumbent was replaced by a relative, there are nodifferences in policy outcomes between those governed by a male or female mayor. We argue thatthe channel through which women enter elected office matters for whether female descriptive rep-resentation translates into substantive female representation. When women access office througha dynastic channel there is no gender mandate. Female politicians may be more responsive to theinterests of their family (rather than those of other women) or may be unable to represent femalepreferences, as they are often figureheads or benchwarmers of previous relatives.

⇤We thank Cesi Cruz, Olle Folke, Johanna Rickne and participants in seminars at CUNY, NEUDC 2015, the Univer-sity of Oxford and the Political Dynasties workshop in Oslo for constructive feedback. All remaining errors are ours.

†Assistant Professor, Blavatnik School of Government, University of Oxford: Radcliffe Observatory Quarter, Wood-stock Road, Oxford, OX2 6GG. Email: julien.labonne@bsg.ox.ac.uk

‡Assistant Profesor, Tufts University: Department of Economics, 301 Braker Hall, 8 Upper Campus Rd., Medford,MA 02155. E-mail: sahar.parsa@tufts.edu

§Assistant Professor, New York University: 19 W 4th Street, Room 208, New York, NY 10012. E-mail:pablo.querubin@nyu.edu

1 Introduction

Women are under-represented in the political sphere all over the world. In 2014, only 22 percent of

legislators around the world were women (UN Women, 2014). This underrepresentation is even more

severe for top elected executive positions such as presidents, heads of state and mayors; for example,

in 2014 only 9 out of 152 countries (5.9 percent) had a female head of state. As a result, there has been

an increased interest in the adoption of female quotas or reservation policies that mandate increased

access of women to political office at different levels of government across the world (Krook, 2009).

Beyond normative issues of fairness in political representation, the interest in increasing female

access to government positions is often premised on the idea that a higher number of female politi-

cians will translate into the adoption of more pro-women policies (Chattopadhyay and Duflo, 2004;

O’Brien, 2012; Bhalotra and Clots-Figueras, 2014). In other words, an increased female descriptive

representation will translate into substantive representation (Pitkin, 1967). The link between descrip-

tive and substantive representation, however, requires that elected women are more likely to reflect

the interests and preferences of other women and that once in office, their actions reflect those prefer-

ences.1

In this paper, we argue that the channel through which women enter elected office matters for

whether this translates into increased substantive female representation. Institutions such as quotas or

reservation policies may both select women who are more likely to share other women’s preferences

and introduce a “mandate effect” that exerts additional pressure on them to adequately represent

those preferences (Franceschet and Piscopo, 2008). On the other hand, when women access office

through their association with their families, political parties or other interest groups, they may have

an allegiance to represent those special interests rather than those of other women. Similarly, they may

be constrained in their ability to enact pro-female policies even if they wanted to, as other relatives or

party elites might remain in control.

We study these questions in the context of the Philippines, which ranks among the top countries

in the world in terms of female political representation. Between 2013 and 2016, women held 25 and

27 percent of the seats in the Senate and the House of Representatives, respectively, and around 20

percent of the municipal mayorship positions.

1See Phillips (1995, 1998) and Mansbridge (1999) for a theoretical discussion on the link between descriptive andsubstantive female representation.

1

We first provide evidence for a previously understudied channel for female access to elected of-

fice. We show that binding term limits constitute critical junctures in which dynastic women are

disproportionately more likely to access political office; this explains the relatively high numbers of

women elected to executive offices in Philippine municipalities. For example, in 1998, when the first

cohort of mayors elected after the 1987 Constitution became term limited, the share of female mayors

jumped from 9 percent to 15 percent. Among women who were elected in open-seat races following

binding term limits, 70 percent were relatives of the term-limited incumbent. We test this more for-

mally by showing that the probability of a municipality having a female mayor is highest following

a binding term limit and when a relative of the incumbent wins the election. Relative to the baseline

probability in races that do not follow a binding term limit, and where an incumbent relative is not

running (0.12), female relatives of the incumbent are 27 percentage points (almost 240 percent) more

likely to get elected as mayors in open-seat races following binding term limits. This result reflects

the adaptive strategies of political dynasties to circumvent term-limits. Previous studies have docu-

mented the existence of a strong incumbency advantage in the Philippines (Querubin, 2011, 2016).

This makes it very important for politicians to avoid losing incumbency to their rivals in an open seat

race. The weakness of political parties in the Philippines, together with high levels of trust amongst

family members, makes families important units of political organization. Thus, following binding

term limits, relatives emerge as natural candidates to keep power in the family, either to start a po-

litical career of their own, or to allow the original incumbent to run again after serving for one term.

Independent of the mechanism, an important contribution of this paper is documenting the effective-

ness of term limits in increasing female representation in an executive position (municipal mayorship)

in which women tend to be particularly underrepresented (UNRISD, 2005; Jalalzai, 2013).

Next, we show that the gender of the relative who runs for office following a binding term limit

is uncorrelated with characteristics of the municipality, the popularity of the term-limited incum-

bent, and other attributes of his family. In municipalities with a successful dynastic succession, 50.7

percent of incumbents are replaced by male relatives and 49.3 percent by female relatives. This

gender-neutral nature of dynastic successions allows us to explore the effect of female mayors on

economic and policy outcomes by comparing municipalities that elected dynastic women as opposed

to dynastic men. More concretely, we use the seemingly idiosyncratic gender of relatives elected fol-

lowing dynastic successions to perform a difference-in-differences analysis in which we compare the

2

change in outcomes during the first term of the dynastic mayor and the last term of the term-limited

incumbent, in municipalities where a female relative was elected vs. those in which a male relative

was elected. We first provide evidence in support of parallel trends, a key identification assumption

in difference-in-differences settings. We then show that electing a dynastic female has no short-term

effect on economic and policy outcomes compared with electing a dynastic male. Similarly, we find

no evidence of long-term effects of female mayors on policies and economic outcomes. Nor do we

find evidence of a role-model effect (Phillips, 1995, 1998) – that dynastic female mayors encourage

other women to run for other local offices or encourage voters to vote for women in other offices. We

can reject very small effects since all our point estimates are very small and tightly estimated.2

We argue that the absence of an effect of dynastic female mayors on policy outcomes can be

explained by the fact that they owe their office to family connections, and are therefore expected

to continue their predecessor’s work. Moreover, they may function as figureheads and have no real

power of their own. Indeed we provide evidence that dynastic female mayors are three times more

likely to be benchwarmers – that is, to serve in office for only one term, after which the previously

term-limited incumbent can run again – than their male counterparts. As such, dynastic women may

have limited power to start a political career of their own and often run simply to keep the office

in the family. Moreover, when women enter politics thanks to their family ties, there may not be

a “mandate effect” that encourages them to implement pro-female policies, as may be the case for

measures intended to increase female representation such as gender quotas (Franceschet and Piscopo,

2008). Therefore in dynastic contexts, family identity and allegiance may prevail over the gender

identity, which implies that both male and female relatives will enact similar policies (Thompson,

2002). As a result, increased descriptive representation through the election of dynastic women will

not necessarily translate into more substantive representation for other women in society.

If, as we conjecture, the null differential effect of female mayors on policy outcomes is explained

by their dynastic status, then we should observe a different pattern for non-dynastic female mayors

who are not constrained by their families. To study this, in Appendix Section A.1.2 we report sugges-

tive evidence that non-dynastic women are more likely to affect some economic outcomes associated

with women’s preferences such as education.

While our empirical analysis is limited to local elections in the Philippines, the patterns we docu-

2The challenges of publishing null results are discussed by Findley et al. (forthcoming).

3

ment are likely to have external validity for higher levels of government3 and for other democracies

where dynasties play an important political role. Previous studies have documented the importance of

political dynasties and how family ties are an important vehicle for women’s access to office both for

executive positions and for legislatures in both developed and developing countries such as Argentina,

Australia, Brazil, Canada, Finland, Iceland, India, Ireland, Israel, Italy, Japan, New Zealand, Norway,

Switzerland, United Kingdom and the United States (Werner, 1966; Kincaid, 1978; Dal Bo, Dal Bo

and Snyder, 2009; Jalalzai, 2013; Asako et al., 2014; Bohlken and Chandra, 2014; Rossi, 2015; Bra-

ganca, Ferraz and Rios, 2015; Smith and Martin, forthcoming; Basu, 2016; Folke, Rickne and Smith,

2016; van Coppenolle, 2017).

Our paper contributes to several strands of literature. First, our paper contributes to the literature

on the determinants of women’s access to office. Several studies bring attention to structural char-

acteristics of the political environment such as the ideological stance of the majority party, political

competition (Maria Escobar-Lemmon, 2005; Folke and Rickne, 2016) and the existence of cross-

cutting cleavages such as ethnicity (Arriola and Johnson, 2014). Other studies analyze the effect

of particular institutions such as gender quotas (Krook, 2009; Pande and Ford, 2012; O’Brien and

Rickne, 2016) or political reservations (Chattopadhyay and Duflo, 2004; Bhavnani, 2009).4 We bring

attention to a specific individual attribute of women that makes them more likely to access office –

their family ties to previous incumbents – and in this way contribute to the nascent literature on the

dynastic background of female politicians.

Our study adds to this existing literature in several ways. First, contrary to existing studies that

focus mostly on legislatures for developed countries, our paper is the first one to study the role of

dynasties in access of women to local executive office (mayorship), a type of office for which women

tend to be particularly underrepresented. Moreover, the Philippines political system is characterized

3Term limits exist in the Philippines for all elected offices, including provincial governors, congress and the senate.A similar pattern of female dynastic candidates entering office following binding term limits can be documented for theseoffices as well. Moreover, the two former female presidents of the Philippines, Corazon Cojuangco-Aquino (1986-1992)and Gloria Macapagal-Arroyo (2004-2010) are dynastic (relatives of previous politicians).

4Our results are also related to the literature on “token” or “puppet” candidates that studies the failure of quotas to in-crease female political representation in a number of countries. Studies on “token” candidates argue that women represen-tation needs to exceed a certain threshold for descriptive representation to map into substantive representation, see Kanter(1977); Dahlerup (1988); Saint-German (1989); Thomas (1994); Taylor-Robinson and Heath (2003); Michelle Heath,Schwindt-Bayer and Taylor-Robinson (2005). Closely related to our results on “benchwarmers”, some studies argue thatwomen are often used as “puppets” or figureheads for male politicians who have reached their term limits, or for partiessimply wishing to fill their female quotas, see Monasterios and Mealla (2001); Miguel (2008).

4

by very weak parties with limited programmatic differences and thus parties are unlikely to explain

women’s access to elected office. Finally, we bring attention to the role of term limits, a previously

understudied channel of female access to elected office.

Our paper also contributes to the empirical literature on the effect of female descriptive represen-

tation on various policy outcomes. Several studies find a positive effect of female representation on

a wide range of policy outcomes associated with female preferences such as child care and maternity

leave (Bratton and Ray, 2002; Schwindt-Bayer, 2006; Kittilson, 2008), health (Bhalotra and Clots-

Figueras, 2014), the environment (Funk and Gathmann, 2015), drinking water (Chattopadhyay and

Duflo, 2004) and crime (Iyer et al., 2012). On the contrary, studies by Tolbert and Steuernagel (2001),

Grey (2002) and Ferreira and Gyourko (2014) find no effects of women representation on a variety

of policy outcomes. Other studies focus on the effect of female incumbents on different political and

electoral outcomes. The study by Brollo and Troiano (2016) finds that female Brazilian mayors are

less likely to engage in corruption, hire temporary public employees and get reelected than their male

counterparts, a finding that the authors interpret as suggestive of women being less likely to engage

in strategic clientelistic practices. On the other hand, Bhavnani (2009), Beaman et al. (2009, 2012),

Broockman (2014) and Bhalotra, Clots-Figueras and Iyer (forthcoming) study whether female lead-

ership plays and important role model effect and leads to the election of more women in the future or

to changing aspirations and educational attainment of other women. Also related to our study, Dube

and Harish (2015) find that queens (one particular type of dynastic female rulers) are more likely to

participate in inter-state conflict than kings.5

We add to these existing studies by focusing on a local executive office (mayorship) in which

the incumbent has wide discretion to influence policy. Thus, arguments relevant for the study of

legislatures such as the preferences of party elites, or the existence of a critical mass of women, are

less likely to play a role in our context. We argue that the channel through which women access

office mediates their potential effect on policy outcomes. Whenever women access office thanks to

their family ties, they may be unwilling or unable to enact policies preferred by other women. In this

5However, queens are very different from elected female officials in contemporary democracies. First, monarchiesrarely face junctures like term limits in which they face the risk of losing power to a rival family. Often their monopolyover power is secure. Most importantly, while some queens may be subject to the influence of other family members,their tenure in power is not subject to short term electoral decisions (i.e. they are rarely used as benchwarmers) whichgives them more independence and power to pursue their preferred policies. Thus, our results are not directly comparableto Dube and Harish (2015).

5

sense, our paper is closely related to Clots-Figueras (2011) that finds that in India, female legislators

of lower castes, but not those of higher castes, are more likely to enact female friendly-policies.

This is consistent with our interpretation that dynastic women often have an allegiance to protect the

interests of their family rather than those of other women in society.

2 Background and Data Sources

In this section, we describe the institutional context, focusing on the importance of families in politics

and the mayoral responsibilities following the 1987 constitution and the 1991 Local Government

Code, which delegated many responsibilities to municipal governments. We then present the different

data sources we use in our analysis.

2.1 Institutional Setting

In the Philippines, families play an important role in politics at both the national and local levels

(McCoy, 2009). Political dynasties have persisted across many decades and are present in most

elected offices across the country’s provinces and municipalities. It is common for relatives to take

turns holding the same office, and for the same family to control multiple elected offices at the same

time.

The 1987 constitution (unsuccessfully) attempted to curb the power of political dynasties in two

ways. First, it prohibited them outright, yet a dynasty-controlled Congress has failed to define what

constitutes a political dynasty, making the ban ineffective. Second, the constitution introduced term

limits for all elected offices. At the municipal level, a politician can only be elected to the same office

three times consecutively (not counting elections before 1987). However, there is very little evidence

that term limits have made politics more competitive in the Philippines or that they have promoted the

alternation in office of different families. Querubin (2011) shows that term limits led to an increase

in incumbency advantage and made politics more dynastic, as term-limited incumbents often run for

a different position and/or have a relative run for the position they are exiting.

Municipalities are governed by a mayor, a vice-mayor and eight municipal councilors.6 All mu-

nicipal officials are elected in first-past-the-post elections organized, by law, at fixed intervals of three

6Cities follow a similar pattern, but the number of councilors is determined by population.

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years.7 Political parties tend to be weak and unstable, and there are typically large shifts in party

affiliations after each election (Hutchcroft and Rocamora, 2003).

The 1991 Local Government Code devolved significant responsibilities for the delivery of a num-

ber of social services to municipalities (Llanto, 2012). These include the extension of medical and

health services, implementation of primary health care programs, repair and maintenance of infras-

tructure facilities including schools, provision of agriculture and fishery extension services, mines

and geoscience services. Municipalities are expected to finance these services through yearly trans-

fers from the central government, known as the Internal Revenue Allotment (IRA), which are based

on municipal population and land area (Llanto, 2012). Municipalities can also raise their own rev-

enues through local taxes and other business fees but, on average, the IRA provides 85 percent of

their budgets (Troland, 2014).

The mayor, as the chief executive of the municipal government, enjoys significant discretionary

powers. Previous research has highlighted their often-excessive control over local policies and affairs,

referring to them as “budget dictators” (Hutchcroft, 2012; Capuno, 2012). The average municipality

only spends 90 percent of its budget every year, so mayors are expected to be able to determine how

funds are spent in the short run.

2.2 Data

We compiled the results of all local elections since 1988, including the full names and votes received

for all candidates.8 For each municipal election, we generate measures of electoral competition (num-

ber of candidates and winner’s vote margin) and women’s participation and electoral performance

(number of female candidates, number of women elected and vote share for female candidates). We

compute separate measures for each office at the municipal level (mayor, vice-mayor and councilor).

We take advantage of naming conventions to identify family relations among candidates within

municipalities (Querubin, 2016). More concretely, personal names in the Philippines have the follow-

ing structure:

firstname midname lastname,

7After the fall of Ferdinand Marcos’ autocratic regime, the first municipal elections were organized in 1988. Inaccordance with transitory provisions of the 1987 constitution, the next municipal elections were organized in 1992.

8The only exception is 1988, since we only have data on winning candidates for that election.

7

where firstname corresponds to the individual’s first name, midname corresponds to the mother’s

maiden name (for men and single women) or the father’s family name (for married women) and

lastname corresponds to the father’s family name (for men and single women) or the husband’s family

name (for married women). A candidate is classified as being related to the incumbent if her middle

and/or last name match the incumbent’s middle and/or last name. We then use available information

on first names to code the gender of each candidate.

A natural concern with this matching procedure is that individuals from the same municipality

who share a middle or last name may not necessarily be related to each other.9 While this is certainly

a possibility, it is less of a concern in the Philippines than in other countries due to the unique way in

which family names are distributed across the different municipalities. In 1849, concerned with the

arbitrary way in which Filipinos chose their surnames, Governor Narciso Claveria y Zaldua created

a catalog with a list of 61,000 different surnames.10 A different set of surnames (often starting with

the same letter) was assigned to each town, and local officials had to assign a different surname to

each family head. As a consequence, common last names (such as Smith in the United Kingdom and

United States or Gonzalez in Latin America) are not as prevalent in the Philippines.11 In addition,

(Querubin, 2016) performed a detailed biographical check on a sample of winning congressional and

gubernatorial candidates who shared a family name (within the same province) and was able to verify

an exact family link in 95 percent of the cases. This rate is probably higher within municipalities,

where sharing a family name is more strongly correlated with an actual family tie. In addition,

candidates can - and often do - petition the electoral commission to disqualify candidates with similar

names as this could cause confusion among voters (Section 69 of the Omnibus Election Code). It

makes it even less likely that a candidate unrelated to the incumbent but with a similar last name is

9This matching procedure will identify almost all existing relatives in the dataset, with the exception of sons-in-lawthat from anecdotal evidence, rarely run to replace their fathers in law in office. The main concern is the existence of falsepositives, or matches that do not signify a family relationship.

10Claveria complained that the natives “arbitrarily adopt the names of saints and this practice has resulted in theexistence of thousands of individuals having the same surname.” See (National Archives of the Philippines, 1973).

11Fafchamps and Labonne (forthcoming) compute a Herfindhal Index of name heterogeneity for a large sample of mu-nicipalities in the Philippines. A value of 0 indicates that there is only one family name in the municipality, while a valuevery close to 1 suggests a very low concentration of family names. The overall Herfindhal Index for the municipalities intheir sample is greater than 0.999. The most common surname in their data, De La Cruz, is used by only 0.32 percent ofindividuals. By contrast, they show that the prevalence of common names is much higher in other countries in the region.The percentage of individuals that uses the most common surname is 7 percent in China, 6 percent in India, 11 percent inTaiwan and 38 percent in Vietnam.

8

allowed to run.

We use three additional sources of data. First, we gathered data on employment from the Labor

Force Surveys (LFS), which are collected every quarter by the National Statistics Office to compute

official employment statistics. We build a balanced yearly panel of about 1,100 municipalities over

the period 2003-2009. We compute the share of the working-age population that is in the labor

force, employed, employed in the public sector, employed on a permanent contract or working as

a temporary migrant abroad. We also break these measures down by gender. Starting in 2005, the

LFS also collected information on school enrollment for children in the respondent’s household. We

generate measures of school enrollment for 5 to 11 year olds (primary school), 12 to 16 year olds

(high school) and 5 to 16 year olds (overall) and break them down by gender.

Second, we compiled annual municipal budget data for the period 2000-2009 from the Bureau

of Local Government Finance.12 The data allow us to generate a number of relevant measures: total

municipal budget, fiscal transfers from the central government as a share of the municipal budget, tax

collection as a share of local revenues collected, regulatory fees as a share of local revenues collected,

expenditures as a share of available resources, as well as health and education as a share of total

spending.

Third, we use data from the National Household Targeting System for Poverty Reduction (NHTS-

PR) collected by the Department of Social Welfare and Development to select beneficiaries for a large-

scale conditional cash transfer program. The data, described in Fernandez (2012), include information

on educational attainment and services provided by the municipal government that are received by

households. We restrict the analysis to services that are received by at least 5 percent of the population

and compute the share of households that benefits from PhilHealth (a subsidized health insurance

program for the poor), subsidized rice, feeding programs implemented by the municipality and day

care. We also calculate the average number of services received by households in the municipality.

Importantly, these measures are only available for the year 2009.

We use this dataset to compute two other categories of variables. First, we compute average ed-

ucational attainment for individuals who should have completed their education by the time the first

term limit became binding (1998).13 Second, since we have access to the non-anonymized version of

12The data are available from: http://www.blgf.gov.ph/# visited on March 26, 2012.13Specifically, we only use data on individuals who were older than 20 on May 1, 1998.

9

the dataset, we also identify relatives of the term-limited incumbents (using the same name-matching

algorithm as above) and compute a number of incumbent family characteristics such as gender ratio,

length of stay in the municipality and educational attainment (broken down by gender). Importantly,

since the dataset does not include information on first names, the measures correspond to the candi-

date’s extended (rather than immediate) family.

3 Term limits, Political Dynasties and the Rise of Female Politi-cians

In this section we show that term limits in a political environment dominated by dynasties increase

women’s access to elected office. We refer to open-seat races following binding term limits as “forced

open-seat races” to differentiate them from i) races with an incumbent running for re-election and ii)

open-seat races in which the incumbent was eligible to run but decided not to.

Figure 1 reports the proportion of municipalities that elected a female mayor in each of the eight

elections between 1988-2010. The fraction of female mayors remains relatively constant at around

9 percent during the first three elections, but jumps discontinuously to 15 percent in 1998 after the

first cohort of elected mayors becomes term limited. This proportion maintains an increasing trend

after 1998 and peaks in 2010 at 20 percent. The fact that the fraction of female mayors experienced

the largest discontinuous change in 1998 suggests that the large number of forced open-seat races

allowed many women to enter office. The proportion of female mayors has continued to increase

because many women have been re-elected, and because more women have run for office in each

election year. In fact, the largest increases in the fraction of female mayors take place precisely

in years with a large number of forced open-seat races (in 1998 and 2007). However, such a pattern

could be consistent with other changes in the political environment after 1998 that may have facilitated

women’s access to office. We address some of these issues below.

10

0.0

5.1

.15

.2Fr

actio

n of

Firs

t-Tim

e M

ayor

s th

at a

re W

omen

1988 1992 1995 1998 2001 2004 2007 2010

Figure 1: Fraction of Female Mayors

The descriptive statistics presented in Table 1 suggest that women are more likely to run and get

elected in open-seat races when the incumbent is no longer eligible to run for office (rows 1 and 2).

Moreover, a substantial majority of women elected in these races (68 percent) are relatives of the

term-limited incumbent (row 3). A comparison of rows 3 and 4 further reveals that female mayors

(row 3) are more likely to be related to the previous incumbent than male mayors (row 4), and this

gap is larger among those elected in forced open-seat races.

Table 1: Descriptive Statistics

Forced open-seat raceNo Yes

% won by women 0.14 0.25% women ran 0.30 0.46% related to incumbent (among winning women) 0.27 0.68% related to incumbent (among winning men) 0.14 0.29

Note: Forced open-seat races are elections in which the previous incumbent was term limited.

To explore these patterns more systematically, we next estimate regressions for the probability of

having a woman run or win a mayoral election as a function of whether the race is a forced open-seat

race and whether a relative of the term-limited incumbent is running. More concretely, we estimate

11

municipality difference in differences regressions of the form:

Femalemt = a +bTerm Limitedmt +fDynastymt + gTerm Limitedmt ⇤Dynastymt + µm +rt + emt

(1)

In Columns 1-2 (3-5) of Table 2, the dependent variable Femalemt takes a value of 1 if a woman

ran in (or won) the mayoral election in municipality m in election year t. Term Limitedmt is a dummy

equal to 1 if the election in year t in municipality m was an open-seat race in which the incumbent

was no longer eligible to run. In Columns 1-4 Dynastymt is a dummy equal to 1 if a relative of the

incumbent ran in that election. In Column 5, Dynastymt equals 1 if a relative of the incumbent won

the election.14

We include a full set of municipality and year fixed effects (µm and rt) in Columns 2, 4 and

5. Our main coefficient of interest is g , which allows us to test whether term limits have a differ-

ential effect on the probability of a woman running for (winning) office, whenever a relative of the

incumbent runs in the race. More specifically, the interaction term compares the probability of hav-

ing female candidates or elected officials before and after a binding term limit, for municipalities

with and without a relative of the incumbent running in the forced open-seat race. The timing of

binding term limits and the decision of relatives of the incumbent to run for office are not randomly

distributed across municipalities or across time. However, notice that municipality fixed effects ac-

count for all time-invariant municipal characteristics that may simultaneously explain why a given

municipality has binding terms limits (i.e. reelects its incumbent), has dynastic candidates running

for office and has a female candidate/incumbent. Similarly, election year fixed effects account for any

time trends in female representation, dynastic candidacy and binding term limits that could produce a

spurious correlation. Thus, any potential confounder or alternative variable explaining female candi-

dacy/incumbency must change across municipalities and time and be correlated with the occurrence

of a forced open-seat race and the decision of an incumbent’s relative to run for office. While strictly

we cannot give g a causal interpretation regarding the role of term limits and dynasties on female

representation, it is hard to come up with alternative interpretations.

The estimates of b in Columns 1 and 2 show that non-dynastic women are 5 percentage points

more likely to run in forced open-seat races than in other types of races. Open-seat races often attract

14In the context of this exercise, we use the term dynastic in a narrow sense to refer to candidates who are related tothe incumbent.

12

candidates who would not be willing to run against an incumbent. However, the estimates of b in

Columns 3-5 suggest that while non-dynastic women are more likely to run in these races, they are not

more likely to win. The estimates of g in Columns 1-4 are large and statistically significant, which

confirms that the chances of the municipality having a female candidate running, and winning are

much higher if a relative of the incumbent is running. In these specifications however, it is possible

that the woman running for office (or winning) does not coincide with the relative of the incumbent.

However, the estimate of g is largest in Column 5, when the dynastic succession was successful and a

relative of the incumbent won the election. In this case, we can be confident that the female winner is

a relative of the incumbent. This shows that not all women are more likely to get elected when three-

term incumbents are ineligible to run: only relatives of the term-limited incumbent are substantially

more likely to win in forced open-seat races.

Relative to the baseline probability in races that do not follow a binding term limit, and where an

incumbent relative is not running (0.12), female relatives of the incumbent are 27 percentage points

(almost 240 percent) more likely to get elected as mayors in successful dynastic successions following

a binding term limit.

In sum, the descriptive statistics and regressions presented above provide strong evidence that

forced open-seat races constitute critical junctures in which dynastic women are disproportionately

more likely to access political office. We believe this result is important for multiple reasons. First,

most recent research on female descriptive representation focuses on institutions such as quotas that

mandate candidacy or incumbency and are often relevant for legislative bodies. Here we bring at-

tention to term limits, an electoral institution widespread across the world, and most common for

executive offices, for which women are particularly underrepresented. Moreover, unlike quotas, term

limits are often not introduced with the deliberate objective of increasing female representation and

thus the patterns we observe here are unexpected. Finally, while existing research has documented the

higher competitiveness and partisan turnover of open seat races, we find that in our context they only

increase the election probability of dynastic women which may have important consequences for the

extent to which female descriptive representation translates into more substantive representation.

13

Table 2: Election of Women, Term Limits and Political Dynasties

Dependent variable is dummy for:Woman ran Woman elected

(1) (2) (3) (4) (5)

Incumbent Term Limited 0.048*** 0.054*** 0.007 0.008 0.004(0.017) (0.017) (0.013) (0.013) (0.011)

Incumbent’s Relative Ran 0.069*** 0.054*** 0.054*** 0.024**(0.014) (0.015) (0.012) (0.012)

Inc. Term Limited* Incumbent’s Relative Ran 0.167*** 0.156*** 0.150*** 0.148***(0.025) (0.025) (0.020) (0.019)

Incumbent’s Relative Won 0.039**(0.017)

Inc. Term Limited* Incumbent’s Relative Won 0.231***(0.023)

Time Fixed Effects No Yes No Yes YesMunicipality Fixed Effects No Yes No Yes Yes

Observations 10,491 10,491 10,244 10,244 10,244R-squared 0.036 0.313 0.034 0.356 0.368

Notes: Results from municipal*elections regressions. The dependent variable is a dummy for whether awoman ran for mayor (Columns 1-2), or whether a woman was elected mayor (Columns 3-5). Incumbent’sRelative Ran is a dummy for whether a relative of the incumbent ran in the election (Columns 1-4).Incumbent’s Relative Won is a dummy for whether a relative of the incumbent won the election (Column 5).The standard errors (in parentheses) account for potential correlation within province. * denotes significanceat the 10 percent, ** 5 percent and *** 1 percent levels.

4 The Gender Neutral Nature of Dynastic Politics

In Section 3, we showed that term limits increased women’s representation in municipal mayorships

and that this result is driven by the increased access of dynastic women. In this section, we show that

among political dynasties, female access to power not only increases following binding term limits

but that there is gender neutrality. We document this in Table 3, which details the characteristics of

places in which a term-limited incumbent was replaced by a relative. We report differences between

races won by a female (Column 1) or a male (Column 2) relative, and report the p-value of a simple

difference in means.

Row 1 shows that roughly 50 percent of races in our sample are won by male relatives and 50

percent by female relatives. This is remarkable, given that women win only 12 percent of races

14

overall.15

Table 3: Term-Limited Incumbents with Relatives Winning in the Subsequent Forced Open-SeatRace and Relative’s Gender

Relative’s GenderFemale Male p-value N

Term-limited incumbents with a relative winning (serving) after them 0.49 0.51 0.75 626Vote share of term-limited incumbent’s relative 0.59 0.58 0.20 626Winning margin of incumbent’s elected relative 0.26 0.25 0.61 626Number of candidates in race 3.01 2.991 0.83 626Incumbent’s margin of victory in 3rd (last) race 0.46 0.46 0.57 626Incumbent’s margin of victory (average 3 races) 0.36 0.38 0.14 626Number of terms served by incumbent’s elected relative (1998-2004 Races) 1.81 2.23 0.00 361Benchwarmer 0.31 0.10 0.00 498Term-Limited Incumbent Elected Vice-Mayor 0.13 0.12 0.63 626Term-Limited Incumbent Elected Councilor 0.02 0.03 0.30 626

Incumbent’s family’s gender ratio in municipality 0.51 0.49 0.27 256Incumbent’s family’s length of stay in municipality 26.61 27.03 0.70 256Incumbent’s family’s avg. years of education (all) 9.96 9.88 0.80 256Incumbent’s family’s avg. years of education (female) 10.18 10.05 0.70 254

Anecdotal evidence suggests that the reasons behind a term-limited incumbent’s choice of a male

or female successor are highly idiosyncratic. For example, gender choice is often driven by family

structure, such as the gender and age of the incumbent’s children or siblings.16 This finding suggests

that among term-limited incumbents replaced by relatives, the gender of the relative is driven by

idiosyncratic factors and resembles a coin toss.

However, the fact that 50 percent of incumbents are replaced by a female relative does not rule

15Notice that this gender parity amongst elected dynastic mayors could still hide important gender biases at the in-cumbent’s family level. Suppose that an incumbent is gender neutral and selects a successor at random amongst his wifeor children. Data from the 2008 Demographic Health Survey indicates that wealthy Filipino couples have on average oneson and one daughter. Based on these assumptions we should observe about 66% of dynastic candidates to be female andthe remaining 33% to be male. In our sample, 50% of dynastic candidates are male and 50% are female. This may thusreveal a slight male bias amongst term-limited incumbents. At the same time, the gender composition of elected dynasticmayors resembles the gender composition of the pool of dynastic candidates, which suggests that voters are gender neutral– amongst members of dynasties they are equally likely to vote for a man or a woman. This potential gender bias at thefamily level does not affect the selection of women into politics within dynastic families to the extent that all familiessuffer from the same bias and exogenous conditions such as the number of daughters or sons explain the presence ofwomen in power. Unfortunately, our dataset does not allow us to test for this directly.

16For example, incumbents may tend to choose their first-born child to run to succeed them, and the gender of thefirst-born child is as if randomly assigned (Bennedsen et al., 2007; Dube and Harish, 2015). Unfortunately, we do nothave biographical data that would allow us to measure family structure or the gender of the first-born of every incumbent.

15

out the possibility that the gender of the relative is correlated with other municipal characteristics or

other characteristics of the term-limited incumbent or his family. We explore this in Table 3, which

displays the competitiveness of races in which the incumbent’s relative was elected, the term-limited

incumbent’s popularity while in office and other attributes of the incumbent’s family.

One possibility is that the gender of the incumbent’s relative depends on how popular the incum-

bent’s family is in the municipality (i.e., how ‘safe’ the seat is electorally). Incumbents may only

be willing to field female relatives if they are confident that the race will not be very competitive

and thus face lower risks of losing to a challenger. If this is the case, comparing places with female

and male dynastic mayors could confound the effect of the dynasty’s popularity in the municipality.

However, our data show that female and male relatives obtain similar vote shares (row 2), win by

similar margins (row 3) and face the same number of challengers (row 4). There also seem to be no

differences in the term-limited incumbent’s popularity across places won by a male or female rela-

tive. This holds both when we look at the winning margin in the last (and third) race before becoming

term limited (row 5) and for the average winning margin in the previous three races (row 6). The

estimates in rows 2-6, therefore, suggest that race competitiveness and incumbent popularity are not

major confounders of the gender of the new (dynastic) incumbent. Row 7 demonstrates that male

relatives serve, on average, a slightly higher number of terms, though the difference is small and we

account for it in our subsequent analysis. This difference is partly explained by the fact that female

relatives are three times more likely to be benchwarmers – that is, to retire after one term in order to

allow the previously term-limited incumbent to return to office (row 8). We return to this issue below

in the discussion. Finally, whether term-limited incumbent mayors continue serving as vice-mayors

(row 9) or as councilors (row 10) immediately after they become term-limited is not correlated with

whether they are replaced in office by a female or male relative. Thus, gender differences will not

confound whether the term-limited incumbent remains in power in a different local office.

Next, we show that incumbents who are replaced by female relatives come from similar types of

families.17 We use data from the NHTS-PR to compute different measures of family characteristics

using the sample of the incumbent’s extended family in the municipality (i.e., individuals in the dataset

17Unfortunately we do not have access to any information on individual incumbent characteristics in order to assesswhether female dynastic mayors are more or less qualified or experienced than male dynastic mayors. Thus, we cannotcompare our findings with those of Folke, Rickne and Smith (2016) who find that dynastic women are more qualified thandynastic men in a sample of developed democracies.

16

who share a family name with the incumbent).

Rows 11-14 show that families of incumbents who are replaced by female relatives are not differ-

ent in terms of gender ratio (row 11) or length of stay in the municipality (row 12). Moreover, they

have similar average years of education, a measure strongly correlated with socio-economic status

(rows 13-14).18

Finally, while the gender of the incumbent’s relative is correlated with neither the characteristics of

the incumbent’s family nor the popularity of the dynasty, a final possibility is that it is correlated with

municipal characteristics. For example, term-limited incumbents may be more likely to field a female

relative in wealthier or more educated municipalities that would be more willing to vote for a woman.

To address this concern, we regress 119 baseline municipal characteristics (measured before any term

limits came into effect) on a dummy for whether a female relative won the election. A list of variables

used, their source and year when measured are reported in Appendix Table A.1.19 These include

measures of economic development, socio-demographic characteristics and patterns of municipal

public spending (Appendix Table A.2), women’s electoral success in other local offices (Appendix

Table A.3), labor force participation (Appendix Table A.3) and education (Appendix Tables A.4 and

A.5). The majority of point estimates are statistically insignificant as well as very small in magnitude.

Only two out of 119 coefficients are statistically different from zero at the 5 percent level (and a

further four are significant at the 10 percent level).

In sum, municipalities that elected a female or male relative of the incumbent exhibit no statisti-

cally significant differences across a wide range of measures. Therefore, a comparison of municipal-

ities with female vs. male dynastic mayors will allow us to identify the effect of the mayor’s gender.

Thus, in the next section we test the effect of having a dynastic female mayor (following a binding

term limit) on different policy, economic and electoral outcomes.

18Years of education is computed only for extended family members born before 1978, who should have completedtheir education in 1998 when the first term limits came into effect.

19In order to ensure that the variables are measured before the term limits came into effect, we focus on the sample offorced open-seat races that took place after the earliest year for which data are available for these sources. For example,since 2000 is the earliest date for which budget data are available, all balance tests using budget data focus on racesfollowing a binding term limit in 2001 or later. Similarly, for balance tests using employment variables from LFS, wefocus on races following a binding term limit in 2004 or later. We also construct a wide range of educational attainmentmeasures for individuals who would have completed their education prior to 1998 (when the first forced open-seat racestook place). All regressions using census data refer to variables from the 1990 and/or 1995 censuses (both before thefirst term limits came into effect). Finally, we also measure women’s baseline electoral success in the municipality bycomputing the average number and vote share of female candidates in the vice-mayor and council elections of 1992-1995.

17

5 Female Dynastic Mayors: Effects on Policy and Electoral Out-comes

In this section, we test whether, after binding term limits come into effect, dynastic female mayors

enact different policies, impact economic outcomes or lead to the future election of other women dif-

ferently than dynastic male mayors. In other words, we test whether female descriptive representation

maps into different outcomes.

Estimating the effect of the mayor’s gender on economic and electoral outcomes in this setting is

challenging for multiple reasons. Simply comparing outcomes in municipalities run by female and

male mayors would likely confound many other municipal characteristics. For example, richer or

more educated municipalities may be more likely to elect women. In addition, given that most female

mayors are dynastic and elected following binding term limits, a naive comparison of municipalities

run by women and men would tend to confound the effect of gender with the effects of having a new

incumbent and having a dynastic mayor.20 To address these concerns, we focus on the sample of

municipalities in which an incumbent was term limited and replaced by a relative. This allows us

to partial out (keep constant) the effect of term limits (election of new incumbents) and the effect of

having a dynastic incumbent (male or female). Moreover, the evidence presented in Section 4 shows

that in this sample, the gender of the relative who replaces term-limited incumbents seems to be

driven by idiosyncratic factors, and is not correlated with other municipal and family characteristics

that could also affect policies or economic outcomes. We can thus compare policies and economic and

electoral outcomes in municipalities in which the term-limited incumbent was replaced by a female

relative to those in which he was replaced by a male relative. We are confident that this comparison

will isolate the role of the mayor’s gender, and not of other potentially confounding variables.

Moreover, our main sample is broadly representative of the universe of female mayors in the

Philippines, almost half (45 percent) of whom entered office after a relative was forced to step down

after serving three consecutive terms. In the rest of the paper we further restrict our sample to cases

in which a male incumbent is term limited and replaced by a relative. This is simply for ease of

20For completeness, we present results for the full sample of elections including both dynastic and non-dynastic may-ors, of the naive comparison between municipalities ran by men and women. Results, available in Tables A.6 and A.7,indicate that municipalities headed by women are more reliant on transfers from the central government and have a highershare of the labor force employed in the public sector. However, those estimates are provided for descriptive purposes andshould not be given a causal interpretation.

18

interpretation, so that cases in which a female relative is elected correspond to transitions from a male

to a female mayor (the scenario we are interested in). In any case, a disproportionate majority of

term-limited incumbents are male (around 90 percent). Our results remain unchanged if we use the

sample of both male and female term-limited incumbents.

5.1 Effect on Policy and Economic Outcomes

In this section, we explore whether the election of dynastic women to replace a term-limited incum-

bent leads to different policy or economic outcomes during their first term, relative to the election

of a dynastic male relative. Following existing research for other contexts, we look at a broad set of

outcomes that female politicians could affect either positively or negatively (even if indirectly).

We perform a difference-in-differences analysis in which we compare outcomes during the first

term of the dynastic mayor to those of the last term of the term-limited incumbent in municipalities in

which female vs. male relatives were elected. We restrict our analysis to this window of time around

the first binding term limit in which an incumbent’s relative comes to office.21 Naturally, we can

only perform this analysis for the subset of outcomes/policies for which data is available for multiple

years. More concretely, we estimate municipal fixed-effects regressions of the form:

Ympt = a +bRmpt + gWmpt +fm +rt + umpt , (2)

where Ympt is the outcome of interest in municipality m, in province p at time t; Rmpt is a dummy

that equals 1 during the incumbent’s relative first term, and Wmpt is a dummy that equals 1 if a

female relative of the incumbent was elected.22 Our coefficient of interest is g . In the rest of our

analysis, we normalize all of our outcomes variables (such that mean = 0 and std. dev. = 1) in order

to make the magnitude of the estimates more easily interpretable. We include a set of municipal

dummies (fm) and yearly dummies (rt) in all regressions but the results are also robust to controlling

for province-specific time trends (Panel C of Tables A.10 - A.11). The underlying identification

assumption in difference-in-differences analysis is the existence of parallel trends; that is, that the

change in economic outcomes observed for municipalities that elected a male relative provides a

21This allows us to use the same sample for the long-term analyses discussed in Section 5.3. In those cases, weonly have one outcome per municipality and we want to avoid selecting on cases in which the incumbent’s relative wassuccessful and also became term limited following three consecutive terms in office.

22Since we restrict our analysis to male term-limited incumbents, Wmpt can only equal 1 after the binding term limit,and thus it is equivalent to the interaction between Rmpt and Wmpt

19

counterfactual of what would have happened to municipalities that elected a female mayor, had they

elected a male mayor. For our main budget and employment outcome variables, we are able to

compare the trends in the 3 years of the last term of the term limited incumbents in municipalities

where the incumbent is replaced by a male relative and in municipalities where he is replaced by a

female relative. The results, available in Tables A.8 and A.9, provide strong evidence in favor of the

parallel trend assumption.23 In addition, from the balance tests reported in Table 3 and Appendix

Tables A.1-A.5 we are confident about this assumption.

We start by looking at municipal public finances, both at the amount and sources of revenue and

the composition of expenditures. As discussed in Section 2.1, these variables are directly under the

control of the municipal mayor. Detailed budget data are only available for the years 2000-2009, and

thus we can only study the election of term-limited incumbents’ relatives starting in 2001.24 The

results, reported in Panel A of Table 4, provide no evidence that female mayors raise more or less

revenues (Column 1), rely less on transfers from the central government (Column 2) or raise more

local taxes (Column 4) than their male counterparts. Nor do female mayors run smaller or larger

budget deficits (Column 3). Most importantly, Column 5 shows that female mayors are not more

likely to spend on education and health, policy issues often associated with female preferences (we

return to this issue below). All the point estimates in Table 4 are statistically insignificant as well

as small in magnitude and have small standard errors (i.e., we can reject small effects). The largest

coefficient, in Column 2, corresponds to 5 percent of the dependent variable’s standard deviation. The

rule of thumb for what constitutes a small effect is 20 percent or less of a standard deviation.

In Panel A of Table 5, we report estimates for a wide range of employment outcomes. These come

from the LFS available for the years 2003-2009.25 There are several ways in which a female mayor

can affect employment in general or female employment in particular. First, having a female mayor

can have a role-model effect that encourages women to participate in the labor force (indeed, Alesina,

Giuliano and Nunn, 2013 use female labor force participation as a measure of female empowerment).

23More concretely, taking the 3 years of the term-limited incumbent’s last term, we estimate a regression of the formYmpt = a +b t + gWmpt +lWmpt ⇥ t + fm +rt + vmpt where t corresponds to a linear time trend. We report the estimateof l in Tables A.8 and A.9, where our parallel trends assumption implies that l = 0.

24For incumbent relatives who entered office in 2001, the “pre” years of the term-limited incumbent’s last term are2000 and 2001, while the relative’s first term is 2002-2004.

25For incumbent relatives who entered office in 2004, the “pre” years of the term-limited incumbent’s last term are2003 and 2004, while the relative’s first term is 2005-2007.

20

Table 4: Budget

log Total IRA/ Expenditures / Locally Raised / Edu & Health /Revenues Revenues Revenues Revenues Expenditures

(1) (2) (3) (4) (5)Panel A: Short-term Effects (difference-in-differences)Female 0.02 0.04 -0.02 0.02 -0.03

(0.02) (0.06) (0.08) (0.03) (0.08)

Observations 1,722 1,722 1,722 1,722 1,721R-squared 0.99 0.92 0.56 0.97 0.86Panel B: Long-term EffectsFemale -0.01 0.11 -0.20 -0.12 -0.14

(0.10) (0.11) (0.16) (0.11) (0.11)

Observations 321 321 321 321 320R-squared 0.46 0.46 0.18 0.50 0.47

Notes: Results from municipal-level regressions. In Panel A, regressions include municipal fixed effects. InPanel B, regressions include province fixed effects. The dependent variables are the (log) municipal budget(Column 1), IRA as a share of the municipal budget (Column 2), total expenditures as a share of the municipalbudget (Column 3), revenues collected locally as a share of the municipal budget (Column 4), and educationand health expenditures as a share of total expenditures (Column 5). All dependent variables are normalized tobe mean zero and standard deviation one. The standard errors (in parentheses) account for potentialcorrelation within province. * denotes significance at the 10 percent, ** 5 percent and *** 1 percent levels.

We find no evidence of higher overall or female labor participation in municipalities governed by

women (Columns 1-2). Second, if female mayors are better at stimulating the economy, this could

translate into higher levels of employment. In addition, a common practice in the Philippines is

for mayors to write reference letters for citizens looking for a job. Similarly, female mayors could

decide to employ more women as public servants. However, the estimates in Columns 3-6 provide

no evidence of higher employment in the private or public sectors for either men or women. The

estimates in Columns 7-10 also reveal that female mayors have no impact on the probability that

citizens from their municipalities will take jobs as overseas foreign workers (jobs often pursued by

women), and do not influence the type of jobs (permanent vs. temporary). Importantly, these results

do not reflect an overall inability of mayors to impact employment outcomes. For example, Labonne

(2016) finds that municipal mayors can influence the overall level of employment throughout the

electoral cycle.

The null results in Panel A of Tables 4-5 are robust to estimating the short-term effects using a sim-

21

Tabl

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22

ple OLS cross-sectional regression in which we compare outcomes during the first terms of dynastic

female vs. male mayors (without taking into account the change relative to the term-limited incum-

bent’s last term). These results are discussed in more detail in the Online Appendix and presented in

Appendix Tables A.10-A.11.

5.2 Demonstration Effects: Electoral Outcomes

We now look at electoral outcomes and test whether female mayors had a role-model or demonstration

effect on women’s political participation and electoral success in other local offices – see Phillips

(1995, 1998); Bhavnani (2009), Beaman et al. (2009, 2012), Broockman (2014) and Bhalotra, Clots-

Figueras and Iyer (forthcoming).

To test for this possibility, in Panel A of Table 6 we report difference-in-differences estimates

based on Equation (2) but using different measures of female political participation and electoral

success in vice-mayoral races (Columns 1-4) or councilor races (Columns 5-8) as dependent variables.

We compare the first local elections held after the incumbent’s relative came to office with the previous

election. We find no evidence that female mayors led to an increase in the number of candidates

running for local offices (male or female – Columns 1-2 and 5-6), the number of women elected

(Columns 3 and 7) or the total vote share of all female candidates running in these races (Columns

4 and 8). The point estimates are very small and statistically insignificant. As above, the results are

very similar if we estimate the short-term effects based on a simple OLS cross-sectional regression

and if we control for province-specific time trends (see Appendix Table A.12).

5.3 Discussion

The evidence presented in Sections 5.1 and 5.2 suggests that dynastic female mayors in the Philippines

have no differential effect on policy, economic or electoral outcomes during their first term, relative

to their male counterparts. In other words, descriptive representation of dynastic women does not

translate into substantive representation on several policy outcomes, and we find no evidence of role

model effects either. In this section, we rule out some alternative explanations for our null results and

offer a potential interpretation rooted in the dynastic nature of the Philippines’ political environment.

The simplest explanation is that our null results are consistent with the predictions of the median

voter theorem. In a Downsian world, policy outcomes are independent of the identity of the politi-

23

Tabl

e6:

Elec

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Vic

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date

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Obs

erva

tions

1,08

51,

085

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24

cian: male and female candidates should converge their policy platforms to cater to the preferences

of the median voter. Yet this interpretation is inconsistent with existing evidence on how politics is

conducted in the Philippines. First, since the median voter in a Filipino municipality is a very poor

citizen, it is hard to reconcile the under-provision of basic public goods and services with the pref-

erences of the median voter. Second, contrary to the predictions of this theorem, a large fraction of

races are non-competitive: the average win margin (difference in vote share between the winner and

runner-up) is 27 percentage points. There is also evidence that incumbents and dynastic candidates

have a significant electoral edge (Querubin, 2016). Finally, political competition in the Philippines

is clientelistic and relies on personalized transactions that are inconsistent with the assumptions and

predictions of the median voter theorem. For example, Fafchamps and Labonne (forthcoming) find

evidence that relatives of an incumbent have better employment. Similarly, Cruz (2013) and Khemani

(2013) provide evidence of high levels of vote buying in local elections.

An alternative interpretation of our results is that men and women in the Philippines share the same

policy preferences. In order to rationalize differences in policy outcomes according to the gender of

the incumbent, it may be better to resort to the citizen-candidate model (Osborne and Slivinski, 1996;

Besley and Coate, 1997). According to this model, in a world with limited to no commitment, policies

should correlate with the preferences of elected officials.

To address this possible interpretation, we use survey data to compare the policy preferences of

men and women collected for 3,400 households in 12 municipalities in the provinces of Ilocos Norte

and Ilocos Sur (Cruz, Keefer and Labonne, 2014). Respondents were asked to indicate the share of

the municipal budget that they would like to spend across 10 sectors. The results, reported in Table 7,

show that women report a stronger preference than men for expenditures on health, education, emer-

gencies and business loans, and a lower preference for roads, community facilities and agriculture

assistance. Naturally, one caveat of this comparison is that preferences of survey respondents may

not be representative of the preferences of dynastic politicians. However, we obtain similar results

when we restrict the sample to individuals with some college education (columns 4-6), a sample that

is more likely to reflect the preferences of wealthier dynastic politicians. These findings suggest that

our null results cannot be explained by similar policy preferences between men and women.

A third interpretation is that one term is not enough for female mayors to influence policies/economic

outcomes or even to have demonstration effects and encourage other women to run for office. There

25

Table 7: Comparing Male and Female Preferences (Ilocos)

Full Sample Some CollegeFemale Male OLS Female Male OLS

(1) (2) (3) (4) (5) (6)Health 19.34 18.31 1.00 19.83 17.80 2.02

(13.49) (12.42) [0.02] (13.04) (10.98) [0.01]Education 18.15 17.29 0.91 19.12 19.62 -0.35

(13.23) (12.29) [0.04] (11.97) (12.76) [0.66]Emergencies 9.28 7.01 2.29 8.55 6.25 2.32

(10.73) (8.39) [0.00] (9.25) (7.36) [0.00]Water and Sanitation 8.16 8.17 0.01 8.22 8.14 0.12

(7.91) (8.81) [0.96] (7.62) (8.82) [0.82]Roads 6.18 7.67 -1.49 6.92 8.03 -1.17

(7.51) (9.03) [0.00] (8.79) (7.54) [0.03]Community Facilities 4.56 5.00 -0.40 4.93 5.65 -0.69

(5.81) (6.45) [0.06] (5.80) (7.26) [0.11]Business Loans 6.17 5.28 0.91 5.78 4.64 1.16

(10.39) (9.02) [0.01] (9.34) (6.85) [0.03]Agriculture Assistance 20.11 23.30 -3.28 17.71 21.33 -3.74

(17.07) (19.04) [0.00] (14.56) (18.59) [0.00]Peace and Security 5.36 5.31 0.02 6.26 6.01 0.17

(6.24) (6.77) [0.92] (6.09) (7.26) [0.69]Festivals 2.69 2.67 0.02 2.68 2.54 0.15

(4.51) (5.09) [0.90] (4.06) (4.21) [0.57]

Notes: n = 3,404 (Columns 1-3), n = 936 (Columns 4-6). Each variable is the share of the Local Development Fund thatthe respondent would like the municipal government to spend on that sector. The standard deviations are in parentheses(Columns 1-2 and 4-5). Each cell in Columns 3 and 6 is either the coefficient on the dummy variable indicating whetherthe respondent is a female from a different OLS regression with municipal fixed effects or the associated p-value inbrackets.

may be a lag in the extent to which female mayors’ efforts translate into different policies and out-

comes. To address these issues, we study long-run effects by estimating cross-sectional OLS regres-

sions of the form:

Ymp = a + gWmp +fp + ump, (3)

where Ymp is the outcome of interest in municipality m, in province p around 2009/2010 (approxi-

mately, depending on the variable). All regressions include a full set of province dummies. We focus

on races following a binding term limit in the years 1998-2004, so that the outcomes are measured

at least two terms after the incumbent’s relative came to office. By focusing on long-term outcomes

we can also test the effect of dynastic female mayors on other relevant outcomes from the NHTS-PR,

26

which are only available for 2009.26

In Panel B of Tables 4-6 we find that dynastic female mayors have no long-term effects on the set

of budget, employment and electoral outcomes used in the short-term analysis, relative to their male

counterparts. We also find no long-run effects of having a dynastic female mayor on the provision of

a wide range of social services (such as health, nutrition services and day care, all services usually

associated with women’s preferences) or school enrollment (see Table 8).

Table 8: Other Long-term Results

Services Education# Services PhilHealth Feeding Day Care In school 5-16

Overall Female(1) (2) (3) (4) (5) (6)

Female -0.00 0.05 0.01 0.11 -0.07 -0.09(0.14) (0.17) (0.16) (0.23) (0.10) (0.10)

Observations 111 111 111 111 263 263R-squared 0.79 0.78 0.69 0.63 0.53 0.51

Notes: Results from municipal-level regressions with province fixed effects. The dependent variables are the averagenumber of services households receive from the municipal government (Column 1), the share of households that benefitfrom the subsidized health insurance program (Column 2), from supplementary feeding program for children (Column 3)and from day care centers (Column 4), the share of children age 5-16 that is enrolled in school (Column 5) and the shareof girls age 5-16 that is enrolled in school (Column 6). All dependent variables are normalized to be mean zero andstandard deviation one. Regressions include province fixed effects. The standard errors (in parentheses) account forpotential correlations within province. * denotes significance at the 10 percent, ** 5 percent and *** 1 percent levels.

Another possible explanation of our null results is that some women are not in office long enough

to have an effect on policy or economic outcomes. We may expect a female relative of an incumbent

who served for three terms (9 years) to have a greater impact than one who served only one term (3

years). Changes in economic outcomes and electoral behavior tend to happen slowly, and may not

change after only one term.

Thus, in Panel B of Appendix Tables A.10 - A.12 and in Appendix Table A.14, we interact our

female dummy with the number of terms served. Overall, the estimates confirm our previous results.

26Since the NHTS-PR variables are only available for one point in time (either 2009 or 2010), we could not usethem as outcome variables in the difference-in-differences regression described by Equation (2) that we used to estimateshort-term effects. Nor can we include municipal fixed effects in these regressions; we include province fixed effectsinstead.

27

We find no differential effects of having a dynastic female mayor in office, irrespective of how many

terms she served.

In sum, we find no evidence that dynastic female mayors in the Philippines have any differential

impact on policy, economic or electoral outcomes in the short or long run. We argue that our null

results are driven by the fact that in our sample, female mayors are dynastic and came to office via

association with their family. This has several implications. First, while dynastic female mayors may

identify with (and even share the preferences of) other women, they have a competing source of iden-

tity and allegiance – the family – which may dominate because their relationship with the previous

incumbent, rather than their gender, brought them to power (Thompson, 2002). When family pref-

erences prevail, both male and female relatives will choose the same policies (those that benefit the

interests of their family). Moreover, while women elected through gender quotas may be encouraged

to implement pro-female policies, this mandate effect is likely absent for women who are elected due

to family ties.

A related but somewhat different mechanism is that even if dynastic female mayors wanted to

change policies towards the preferences of other women, they simply cannot. Both male and female

dynastic officials might have little real power, as they could be figureheads of the previous incumbent

and face serious constraints in implementing their favored policies. Dynastic political families also

likely select family members who are more likely to carry on the family’s work as candidates and may

have other ways of enforcing the alignment of its members to the family interests. Finally, female

mayors might have less scope and incentives to make a difference, as they are more likely than men

to be selected as benchwarmers. This may give women fewer incentives (and fewer means) to shape

policies during their first term.

One implication of our theory is that we should expect different results whenever a non-dynastic

woman is elected mayor. Non-dynastic mayors are not as strongly constrained by their family’s

interests since they come to office based on their own merit rather than to replace a term-limited

incumbent. The previous incumbent is also much less likely to interfere with their decisions.

Unfortunately, estimating the effect of electing non-dynastic women on policies is very challeng-

ing in the Philippines since non-dynastic women rarely run for office and get elected. However, to

test this possibility, in Appendix Section A.1.2 we exploit an RDD based on close elections in which

28

a non-dynastic woman barely wins or loses an election against a non-dynastic man.27 The underlying

identification assumption is that the outcome of close races is as good as random, and thus municipal-

ities in which a non-dynastic woman wins are comparable to those in which a non-dynastic man wins.

The estimates, shown in Appendix Table A.15 tentatively suggest that in the long run, municipalities

with non-dynastic female mayors are less dependent on transfers from the central government (IRA

- Column 1), raise more local revenues (Column 2) and generate an increase in female enrollment in

secondary school (Column 7). However, these estimates should be interpreted cautiously since they

rely on a very small sample of races and thus some of the estimates are unstable. Nonetheless, they

provide suggestive evidence that non-dynastic women have a differential effect on some economic

outcomes. This is consistent with our theory regarding the importance of the channel through which

women access elected office.

6 Conclusion

In this paper, we show that political dynasties in the Philippines have led to an increased participation

of women in politics. Following binding term limits, large numbers of dynastic women ran for office

to take the seat of their term-limited relatives. This is related to the adaptive strategies of political

dynasties to circumvent term-limits, (Querubin, 2011), where elected officials are often replaced by

their relatives. This phenomenon explains to a large extent why the Philippines ranks so high in terms

of female political representation.

However, we also show that dynastic women do not seem to implement different policies than their

male counterparts, or encourage more women to run for local offices. In other countries, women who

were elected to office via reservations or gender quotas, for example, have enacted different policies

and have had demonstration effects on the political participation of other women. We conjecture

that the channel through which women access office affects the extent to which female descriptive

representation translates into substantive representation. Women elected through the dynastic channel

may be unwilling to steer policy away from their family’s interests and closer to their own preferences

(or the preferences of other women) or may be unable to do so as they are often figureheads or

benchwarmers for their relatives, who constrain their decisions and retain de facto power. Similarly,

27Naturally, this RDD analysis cannot be conducted for our sample of dynastic candidates since having two relativesof the incumbent, of different gender, run against each other in the same race occurs very, very rarely.

29

if they are elected through the dynastic channel, women may not have a mandate that enables (or

encourages) them to prioritize women’s needs and preferences, in contrast to previous work where

women are elected via gender quotas.

Our results highlight the importance of the broader social context through which women access

elected offices in order to understand the extent to which holding such offices empowers women and

allows them to shape policies and economic outcomes. As stated by Jalalzai (2013), “in spite of the

rising numbers of women executives, we should question women’s ultimate progress in achieving

powerful positions” (p. 114). Where women’s increased access to elected office is mainly driven by

family connections, we may fail to observe, at least in the short run, a change in policy outcomes or

in the empowerment of other women.

Importantly, the positive effect of term limits on female representation may be very specific to

dynastic settings in general, or to the Philippines in particular. In fact, we do not find that term limits

increase the probability of electing non-dynastic women in the Philippines. Future research should

study the effect of term limits on female representation in less dynastic settings, as well as the effect

of political dynasties on the political empowerment of other groups such as the youth.

30

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37

A.1 Online Appendix: Balance Tests and Additional Results

A.1.1 Alternative Specification for Short-Term Effects

The null results in Tables 4 and 5 are robust to estimating the short-run effects based on Equation (3),

where Ymp is the outcome of interest in municipality m, in province p at the end of the incumbent’s

relative’s first term in office and Wmp is a dummy that equals 1 if a female relative of the incumbent

was elected following the first binding term limit. fp corresponds to province fixed effects. Recall

from section 4 that 50 percent of the municipalities in our sample elect a female relative of the incum-

bent, and that Wmp does not seem to be correlated with either municipal or incumbent characteristics.

This makes us confident that g in this case captures the effect of the mayor’s gender. One advantage of

the specification in Equation (3) over that of Equation (2) is that for some dependent variables (such

as those based on the budget data) it allows us to include municipalities that first became term limited

in 1998 (and when the largest number of women entered office). Finally, it also allows us to look

at other relevant economic outcomes such as education, for which we have yearly data only for later

years. Estimates based on Equation (3) reported in Appendix Tables A.10-A.11 for the budget and

employment variables, respectively, are again very small and statistically insignificant. In addition,

the estimates in Appendix Table A.13 show that female mayors do not have an effect on elementary

or secondary school enrollment (male or female) even though education is partly a responsibility of

municipal governments and education is often associated with women’s preferences. This result is

consistent with the lack of effect we found on the fraction of total expenses on health and education.

A.1

Table A.1: List of Variables for Balance Tests

Domain Variable Source YearAsset % HH who own

Their house Census 1990Their lot Census 1990Residential land Census 1990Agricultural land Census 1990Other land Census 1990A radio Census 1990A TV Census 1990A phone Census 1990A car Census 1990A fridge Census 1990

% HH withan iron roof Census 1990a concrete roof Census 1990

Budget Municipal Budget (log) BLGF 2000IRA as a % of total budget BLGF 2000Local revenues as a % of total budget BLGF 2000Expenditures as a % of budget BLGF 2000Expenditures on health and education (% of budget) BLGF 2000

Education* Avg. years of education NHTS 1998Share of the working-age population that : Census 1990 and 1995

Never completed a grade LFS 2003/4Attended elementary schoolGraduated from elementary schoolAttended high schoolGraduated from high schoolAttended college

Employment* % working-age populationin the labor force LFS 2003employed LFS 2003employed in public sector LFS 2003employed in permanent contract LFS 2003employed as an OFW LFS 2003

Population Population Census 1990 and 1995% population living in urban areas Census 1990% population that has not migrated over the past 5 years Census 1990% individuals who are Catholic Census 1990% individuals who are Muslim Census 1990

Electoral** Number of female candidates COMELEC VariousNumber of elected femalesVote share of female candidates

Notes: * Variables are broken down by gender ** Variables are broken down by office (vice-mayor and mu-nicipal councilor) and are computed for the pre-1998 period, the three elections before the incumbent was termlimited and the election when the incumbent was term limited.A.2

Table A.2: Balance Tests: Economic Development, Basic Demographics and Municipal Spending

Domain Variable Point Estimate Std. Error p-valueAsset % HH who own

Their house 0.06 (0.07) [0.36]Their lot 0.14 (0.06) [0.02]**Residential land -0.01 (0.08) [0.91]Agricultural land 0.08 (0.07) [0.26]Other land 0.15 (0.08) [0.07]*A radio -0.08 (0.06) [0.23]A TV -0.05 (0.04) [0.23]A phone -0.03 (0.07) [0.65]A car -0.10 (0.07) [0.14]A fridge -0.06 (0.05) [0.22]

% HH withan iron roof -0.02 (0.04) [0.67]a concrete roof -0.08 (0.05) [0.13]

Budget Municipal Budget (log) -0.03 (0.11) [0.77]IRA as a % of total budget 0.05 (0.11) [0.63]Local revenues as a % of total budget -0.04 (0.11) [0.70]Expenditures as a % of budget -0.12 (0.15) [0.41]Expenditures on health and education (% of budget) 0.02 (0.12) [0.86]

Population Population (1990) 0.06 (0.08) [0.42]Population (1995) 0.06 (0.07) [0.39]Share female (1990) 0.03 (0.07) [0.66]Share female (1995) 0.09 (0.08) [0.23]Share with relatives overseas (1990) 0.01 (0.05) [0.87]Share with relatives overseas (1995) -0.02 (0.06) [0.70]% population living in urban areas -0.03 (0.07) [0.65]% population that has not migrated in the past 5 years -0.01 (0.01) [0.33]% individuals who are Catholic -0.11 (0.06) [0.05]**% individuals who are Muslim 0.06 (0.04) [0.14]

Poverty Poverty incidence (2000) 0.09 (0.08) [0.27]Poverty incidence (2003) 0.08 (0.08) [0.36]

Notes: Each row reports the point estimate (its standard error and associated p-value) on the dummy “Female”in a different regression. The sample is restricted to municipalities where a term-limited incumbent was re-placed in office by a relative. The outcome of interest listed in the column “Variable” is regressed on a dummyequal to 1 if the relative was female. All regressions include province fixed effects.

A.3

Table A.3: Balance Tests: Female Electoral Performance and Labor Force Participation

Domain Variable Point Estimate Std. Error p-valueElections vice-mayorAll previous elections

# Female candidates 0.04 (0.09) [0.69]Vote share female candidates 0.03 (0.09) [0.76]# Female winners -0.02 (0.09) [0.86]

Election prior to the term limit# Female candidates 0.08 (0.09) [0.38]Vote share female candidates -0.02 (0.09) [0.84]# Female winners -0.04 (0.09) [0.61]

1992-1995 Elections# Female candidates -0.03 (0.09) [0.73]Vote share female candidates -0.06 (0.09) [0.52]# Female winners -0.06 (0.09) [0.49]

Elections councilorAll elections prior to the term limit

# Female candidates 0.15 (0.08) [0.06]*Vote share female candidates -0.03 (0.09) [0.73]# Female winners 0.00 (0.09) [0.97]

Election prior to the term limit# Female candidates 0.04 (0.09) [0.64]Vote share female candidates -0.02 (0.09) [0.86]# Female winners 0.02 (0.09) [0.86]

1992-1995 Elections# Female candidates 0.06 (0.08) [0.42]Vote share female candidates -0.02 (0.09) [0.85]# Female winners 0.01 (0.09) [0.90]

Employment In labor force 0.05 (0.12) [0.68]Employed 0.09 (0.12) [0.45]Employed (non-casual) -0.17 (0.15) [0.27]Employed (public) 0.12 (0.16) [0.45]Working overseas -0.05 (0.16) [0.75]

Female In labor force 0.00 (0.13) [0.97]Employed 0.03 (0.13) [0.82]Employed (non-casual) -0.27 (0.16) [0.09]*Employed (public) 0.03 (0.15) [0.81]Working overseas 0.05 (0.13) [0.73]

Male In labor force 0.11 (0.15) [0.45]Employed 0.14 (0.14) [0.33]Employed (non-casual) -0.08 (0.16) [0.63]Employed (public) 0.19 (0.18) [0.30]Working overseas -0.14 (0.18) [0.43]

Notes: Each row reports the point estimate (its standard error and associated p-value) on the dummy “Female”in a different regression. The sample is restricted to municipalities where a term-limited incumbent was re-placed in office by a relative. The outcome of interest listed in the column “Variable” is regressed on a dummyequal to 1 if the relative was female. All regressions include province fixed effects.A.4

Table A.4: Balance Tests: Education (from NHTS and LFS)

Domain Variable Point Estimate Std. Error p-valueEducation From NHTS

Years -0.11 (0.11) [0.31]Years (female) -0.11 (0.11) [0.29]Years (male) -0.10 (0.11) [0.35]

Education From LFSOverall No formal schooling -0.10 (0.10) [0.29]

Some primary school 0.00 (0.12) [1.00]Primary school graduate -0.01 (0.17) [0.95]Some high school -0.07 (0.16) [0.66]High school graduate 0.05 (0.12) [0.65]Some college 0.03 (0.15) [0.82]

Female No formal schooling -0.08 (0.11) [0.48]Some primary school -0.02 (0.12) [0.86]Primary school graduate -0.08 (0.17) [0.66]Some high school 0.02 (0.15) [0.89]High school graduate 0.04 (0.13) [0.76]Some college 0.06 (0.16) [0.71]

Male No formal schooling -0.11 (0.08) [0.18]Some primary school 0.02 (0.12) [0.89]Primary school graduate 0.05 (0.16) [0.78]Some high school -0.14 (0.16) [0.38]High school graduate 0.06 (0.12) [0.63]Some college 0.01 (0.15) [0.96]

Notes: Each row reports the point estimate (its standard error and associated p-value) on the dummy “Female”in a different regression. The sample is restricted to municipalities where a term-limited incumbent was re-placed in office by a relative. The outcome of interest listed in the column “Variable” is regressed on a dummyequal to 1 if the relative was female. All regressions include province fixed effects.

A.5

Table A.5: Balance Tests: Education (from the 1990 and 1995 Censuses)

Domain Variable Point Estimate Std. Error p-valueEducation From 1990 CensusOverall No formal schooling 0.00 (0.06) [0.98]

Some primary school 0.07 (0.06) [0.27]Primary school graduate -0.03 (0.06) [0.60]Some high school -0.01 (0.07) [0.94]High school graduate -0.06 (0.06) [0.29]Some college -0.11 (0.07) [0.14]

Female No formal schooling 0.00 (0.06) [0.94]Some primary school 0.06 (0.06) [0.30]Primary school graduate -0.02 (0.06) [0.73]Some high school 0.02 (0.07) [0.80]High school graduate -0.08 (0.06) [0.18]Some college -0.13 (0.07) [0.09] *

Male No formal schooling -0.01 (0.06) [0.89]Some primary school 0.07 (0.06) [0.24]Primary school graduate -0.04 (0.06) [0.48]Some high school -0.03 (0.07) [0.72]High school graduate -0.04 (0.06) [0.48]Some college -0.08 (0.07) [0.24]

Education From 1995 CensusOverall No formal schooling 0.01 (0.08) [0.90]

Some primary school 0.03 (0.06) [0.61]Primary school graduate -0.07 (0.07) [0.36]Some high school 0.01 (0.05) [0.92]High school graduate -0.07 (0.06) [0.27]Some college -0.08 (0.09) [0.39]

Female No formal schooling 0.00 (0.08) [0.97]Some primary school 0.02 (0.06) [0.76]Primary school graduate -0.06 (0.07) [0.38]Some high school 0.02 (0.05) [0.71]High school graduate -0.08 (0.06) [0.19]Some college -0.09 (0.09) [0.36]

Male No formal schooling 0.02 (0.08) [0.75]Some primary school 0.04 (0.06) [0.50]Primary school graduate -0.08 (0.08) [0.34]Some high school -0.01 (0.05) [0.87]High school graduate -0.05 (0.06) [0.37]Some college -0.06 (0.09) [0.48]

Notes: Each row reports the point estimate (its standard error and associated p-value) on the dummy “Female”in a different regression. The sample is restricted to municipalities where a term-limited incumbent was re-placed in office by a relative. The outcome of interest listed in the column “Variable” is regressed on a dummyequal to 1 if the relative was female. All regressions include province fixed effects.

A.6

Table A.6: Budget Results on the Full Sample

log Total IRA/ Expenditures / Locally Raised / Edu & Health /Revenues Revenues Revenues Revenues Expenditures

(1) (2) (3) (4) (5)Female -0.01 0.04** 0.01 -0.00 -0.00

(0.01) (0.02) (0.02) (0.01) (0.03)

Observations 13,100 13,100 13,100 13,100 13,095R-squared 0.98 0.86 0.17 0.93 0.75

Notes: Results from municipal-level regressions. Regressions include municipal fixed effects and year fixedeffects. The dependent variables are the (log) municipal budget (Column 1), IRA as a share of the municipalbudget (Column 2), total expenditures as a share of the municipal budget (Column 3), revenues collectedlocally as a share of the municipal budget (Column 4), and education and health expenditures as a share oftotal expenditures (Column 5). All dependent variables are normalized to be mean zero and standard deviationone. The standard errors (in parentheses) account for potential correlation within province. * denotessignificance at the 10 percent, ** 5 percent and *** 1 percent levels.

A.7

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A.8

Table A.8: Testing the Parallel Trend - Budget

log Total IRA/ Expenditures / Locally Raised / Edu & Health /Revenues Revenues Revenues Revenues Expenditures

(1) (2) (3) (4) (5)Female x Pre-trend -0.00 0.08 -0.03 -0.02 0.02

(0.02) (0.07) (0.05) (0.03) (0.07)

Observations 595 595 595 595 595R-squared 0.99 0.95 0.72 0.98 0.93

Notes: Results from municipal-level regressions. Regressions include municipal fixed effects and year fixedeffects. The sample includes the last term of the term-limited incumbent. The dependent variables are the(log) municipal budget (Column 1), IRA as a share of the municipal budget (Column 2), total expenditures asa share of the municipal budget (Column 3), revenues collected locally as a share of the municipal budget(Column 4), and education and health expenditures as a share of total expenditures (Column 5). All dependentvariables are normalized to be mean zero and standard deviation one. The standard errors (in parentheses)account for potential correlation within province. * denotes significance at the 10 percent, ** 5 percent and*** 1 percent levels.

A.9

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A.10

Table A.10: Additional Budget Results

log Total IRA/ Expenditures / Locally Raised / Edu & Health /Revenues Revenues Revenues Revenues Expenditures

(1) (2) (3) (4) (5)

Panel A: ST results (not difference-in-differences)Female -0.05 0.04 0.10** 0.06 -0.03

(0.09) (0.10) (0.04) (0.09) (0.11)

Observations 360 360 360 360 360R-squared 0.50 0.58 0.35 0.63 0.63Panel B: Long-term results (interaction with number of terms)Female 0.14 -0.03 -0.21 0.04 -0.08

(0.11) (0.11) (0.17) (0.11) (0.11)Nb terms 0.03 -0.18 0.15 0.20* 0.11

(0.11) (0.11) (0.13) (0.12) (0.10)Interaction 0.03 0.27* -0.27 -0.26 -0.03

(0.14) (0.15) (0.22) (0.16) (0.15)

Observations 321 321 321 321 320R-squared 0.55 0.53 0.20 0.58 0.49Panel C: ST results in difference-in-differences with province-specific time trendsFemale 0.02 0.05 -0.02 0.02 0.00

(0.03) (0.07) (0.08) (0.04) (0.09)

Observations 1,722 1,722 1,722 1,722 1,721R-squared 0.99 0.92 0.60 0.98 0.87

Notes: Results from municipal-level regressions. The dependent variables are the (log) municipal budget(Column 1), IRA as a share of the municipal budget (Column 2), total expenditures as a share of the municipalbudget (Column 3), revenues collected locally as a share of the municipal budget (Column 4), and educationand health expenditures as a share of total expenditures (Column 5). All dependent variables are normalizedto be mean zero and standard deviation one. Regressions in Panels A and B control for province fixed effects.In Panel C, regressions include from municipal fixed-effects and province-specific time trends. The standarderrors (in parentheses) account for potential correlations within province. * denotes significance at the 10percent, ** 5 percent and *** 1 percent levels.

A.11

Table A.11: Additional Employment Results

LFP Employed Public OFW PermanentOverall Female Overall Female Overall Female Overall Female Overall Female

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Panel A: Short-term results (not difference-in-differences)Female -0.14 -0.12 -0.07 -0.05 0.05 0.02 -0.02 -0.07 0.01 0.01

(0.25) (0.23) (0.24) (0.21) (0.20) (0.18) (0.20) (0.21) (0.04) (0.05)

Observations 121 121 121 121 121 121 121 121 121 121R-squared 0.75 0.68 0.78 0.68 0.47 0.47 0.79 0.69 0.61 0.53Panel B: Long-term results (interaction with number of terms)Female -0.06 -0.14 -0.06 -0.15 -0.04 -0.05 0.08 -0.06 0.02 0.00

(0.10) (0.10) (0.09) (0.10) (0.11) (0.13) (0.21) (0.15) (0.02) (0.02)Nb terms -0.09 -0.06 -0.08 -0.09 0.09 0.01 -0.02 -0.05 -0.01 -0.02

(0.10) (0.10) (0.10) (0.10) (0.14) (0.12) (0.08) (0.08) (0.02) (0.02)Interaction 0.14 0.01 0.17 0.08 -0.14 -0.02 -0.06 0.02 0.03 0.04

(0.13) (0.13) (0.14) (0.14) (0.17) (0.16) (0.14) (0.11) (0.02) (0.02)

Observations 263 263 263 263 263 263 263 263 263 263R-squared 0.57 0.52 0.64 0.54 0.44 0.43 0.57 0.59 0.60 0.51Panel C: ST results in difference-in-differences with province-specific time trendsFemale -0.09 -0.10 -0.13 -0.13 -0.01 0.01 -0.02 0.03 0.02 0.04

(0.15) (0.14) (0.13) (0.14) (0.12) (0.15) (0.14) (0.10) (0.02) (0.03)

Observations 922 922 922 922 922 922 922 922 922 922R-squared 0.87 0.85 0.89 0.86 0.89 0.83 0.90 0.85 0.85 0.82

Notes: Results from municipal-level regressions. The dependent variables are the share of the working-age population that is in the labor force (Columns1 and 2), employed (Columns 3 and 4), employed in the public sector (Columns 5 and 6), working as a temporary migrant abroad (Columns 7 and 8)and employed on a permanent contract (Columns 9 and 10). In even-numbered columns, the share is computed for the working-age female population.All dependent variables are normalized to be mean zero and standard deviation one. Regressions in Panels A and B control for province fixed effects. InPanel C, regressions include from municipal fixed-effects and province-specific time trends. The standard errors (in parentheses) account for potentialcorrelations within province. * denotes significance at the 10 percent, ** 5 percent and *** 1 percent levels.

A.12

Table A.12: Additional Electoral Results

Vice-Mayor Councilor# of Candidates # of Female Vote Share # of Candidates # of Female Vote ShareTotal Female Elected Female Total Female Elected Female(1) (2) (3) (4) (5) (6) (7) (8)

Panel A: Short-term results (not difference-in-differences)Female 0.05 0.02 0.04 0.05 0.06 -0.04 -0.05 -0.08

(0.07) (0.09) (0.10) (0.09) (0.05) (0.08) (0.09) (0.09)

Observations 464 464 464 456 464 464 464 456R-squared 0.22 0.12 0.14 0.13 0.35 0.21 0.20 0.20Panel B: Long-term results (interaction with number of terms)Female -0.06 0.01 0.15 0.16 0.09 0.15 0.04 0.03

(0.15) (0.13) (0.13) (0.14) (0.12) (0.14) (0.11) (0.11)Nb terms -0.13* -0.12 -0.11 -0.07 -0.08 0.02 0.02 0.02

(0.07) (0.10) (0.10) (0.09) (0.07) (0.12) (0.11) (0.12)interaction -0.15 0.23 0.19 0.19 -0.04 0.05 0.12 0.14

(0.12) (0.14) (0.13) (0.15) (0.12) (0.13) (0.15) (0.16)

Observations 360 360 360 341 360 360 360 341R-squared 0.33 0.25 0.22 0.25 0.42 0.23 0.18 0.19Panel C: ST results in difference-in-differences with province-specific time trendsFemale -0.10 -0.08 0.04 -0.06 -0.10 -0.13 -0.13 -0.10

(0.09) (0.16) (0.15) (0.16) (0.07) (0.10) (0.16) (0.13)

Observations 1,144 1,144 1,144 1,134 1,144 1,144 1,144 1,134R-squared 0.71 0.61 0.63 0.64 0.82 0.70 0.70 0.73

Notes: Results from municipal-level regressions. The dependent variables are the number of candidates(Columns 1 and 5), the number of female candidates (Columns 2 and 6), the number of females elected(Columns 3 and 7) and the average vote share of female candidates (Columns 4 and 8). In Columns 1-4,the variables are for the vice-mayoral races, while in Columns 5-8 they are defined with respect to councilorraces. All dependent variables are normalized to be mean zero and standard deviation one. Regressions inPanels A and B control for province fixed effects. In Panel C, regressions include from municipal fixed-effectsand province-specific time trends. The standard errors (in parentheses) account for potential correlations withinprovince. * denotes significance at the 10 percent, ** 5 percent and *** 1 percent levels.

A.13

Table A.13: Education

In School 5-16 In School 5-11 In School 12-16Overall Female Overall Female Overall Female

(1) (2) (3) (4) (5) (6)Panel A: Short-term results (not difference-in-differences)Female -0.00 0.01 -0.02 0.01 0.02 0.02

(0.04) (0.04) (0.04) (0.05) (0.04) (0.03)

Observations 121 121 121 121 121 121R-squared 1.00 1.00 1.00 0.99 0.99 0.99

Notes: Results from municipal-level regressions with province fixed effects. The dependent variables are theshare of children age 5-16 that is enrolled in school (Column 1), the share of girls age 5-16 that is enrolled inschool (Column 2), the share of children age 5-11 that is enrolled in school (Column 3), the share of girls age5-11 that is enrolled in school (Column 4), the share of children age 12-16 that is enrolled in school (Column 5)and the share of girls age 12-16 that is enrolled in school (Column 6). All dependent variables are normalized tobe mean zero and standard deviation one. All regressions control for province fixed effects. The standard errors(in parentheses) account for potential correlations within province. * denotes significance at the 10 percent, **5 percent and *** 1 percent levels.

A.14

Table A.14: Other Long-term Results: Interaction with Number of Terms

Services Education# Services PhilHealth Feeding Day Care In school 5-16

Overall Female(1) (2) (3) (4) (5) (6)

Female -0.08 0.03 -0.10 0.02 -0.01 -0.04(0.15) (0.17) (0.18) (0.24) (0.10) (0.09)

Nb terms -0.25* -0.09 -0.34** -0.34** 0.09 0.01(0.14) (0.11) (0.14) (0.15) (0.13) (0.14)

Interaction 0.11 0.07 0.22 0.05 -0.10 0.04(0.13) (0.15) (0.20) (0.19) (0.18) (0.17)

Observations 111 111 111 111 263 263R-squared 0.82 0.78 0.75 0.69 0.59 0.56

Notes: Results from municipal-level regressions with province fixed effects. The dependent variables are the average number of services householdsreceive from the municipal government (Column 1), the share of households that benefit from the subsidized health insurance program (Column 2), fromsupplementary feeding program for children (Column 3) and from day care centers (Column 4), the share of children age 5-16 that is enrolled in school(Column 5) and the share of girls age 5-16 that is enrolled in school (Column 6). All dependent variables are normalized to be mean zero and standarddeviation one. Regressions include province fixed effects. The standard errors (in parentheses) account for potential correlations within province. *denotes significance at the 10 percent, ** 5 percent and *** 1 percent levels.

A.15

A.1.2 RDD Results for Non-Dynastic Candidates

In this section we exploit an RDD based on close elections in which a non-dynastic woman barely

wins or loses an election against a non-dynastic man.28 The underlying identification assumption is

that the outcome of close races is as good as random, and thus municipalities in which a non-dynastic

woman wins are comparable to those in which a non-dynastic man wins.29 More concretely we

estimate a regression of the form:

Ymp = a + gWmp +bXmp + f (marginmp)+fp + ump, (4)

where we restrict the analysis to races with non-dynastic winners and runners-up of different genders.

Ymp corresponds to the outcome variable in municipality m, in province p in the year 2009. Wmp takes

a value of 1 if a woman wins the election and 0 otherwise. f (marginmp) is a local linear polynomial

in the forcing variable, which in this case is the winning margin – the difference between the vote

share of the winner and the runner-up – which takes a positive value if the winner is female and a

negative value if the winner is male. In some specifications, we include province fixed effects (fp)

and control for the year of the election and some baseline characteristics of the municipalities (Xmp).

Recall that we normalize all of our outcomes variables to be mean zero and standard deviation one,

such that the magnitude of the estimates is more easily interpretable.

Our sample size for this exercise is rather limited. Between 1992 and 2007, only 75 out of 9,000

mayoral races had non-dynastic winners and runners-up of different genders and were decided by a

margin of less than 5 percent.30 This illustrates how rare and difficult it is for non-dynastic women to

access elected office in the Philippines. Our effective sample size becomes even smaller since we do

not have outcome data for all 75 municipalities. Thus, given the small sample size, our results should

be interpreted with caution.31 Due to data limitations, we only estimate the long-run effects using

outcomes measured in 2009 – the year for which the largest number of outcome variables is available.

28Naturally, this RDD analysis cannot be conducted for our sample of dynastic candidates since having two relativesof the incumbent, of different gender, run against each other in the same race occurs very, very rarely.

29For a general discussion of RDD designs based on close elections, see Lee (2008).30Unfortunately, for the 1988 elections we do not have electoral outcomes for winning and losing candidates, only the

names of elected incumbents.31Moreover, dynastic and non-dynastic candidates may differ along characteristics other than their dynastic status.

Unfortunately, we do not have any data on the individual characteristics of the candidates in our sample to address thispossibility. This adds yet another reason to interpret our RDD estimates with caution.

A.16

Women won 38 (50.6 percent) of the 75 close races, which gives us further confidence that their

outcome is as good as random. This is confirmed by a McCrary (2008) density test illustrated and

reported in Figure 2. The plot illustrates the distribution of women’s win margins in races in which

they were either winners or runners-up. If women are more likely to lose in close races, then we should

observe a discontinuous jump in the density function across the threshold. There is no evidence of

such discontinuity, and the estimate reported at the bottom of the graph is small and not statistically

significant.

0.0

1.2

2.5

Den

sity

-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3Win Margin

Discontinuity est. = -0.018, s.e. = 0.200

Figure A.1: Mc Crary Density Test

We report our estimates of g in Table 9. We use a local linear polynomial on either side of the

threshold and further restrict our analysis to races in which the margin of victory was less than 5

percent, and control for province and year fixed effects. In Panel B, we add municipal characteristics

from the 1990 census that exhibit discontinuity at the threshold: the share of men that attended pri-

mary school and college, females who graduated from primary school, and the share of households

that own a TV, a fridge and a car.

The estimates tentatively suggest that in the long run, municipalities with non-dynastic female

mayors are less dependent on transfers from the central government (IRA - Column 1) and raise more

local revenues (Column 2), though the estimates are not stable and lose significance when municipal

controls are included in Panel B. The estimates in Columns 3 and 5 suggest that non-dynastic female

mayors reduce the size of public employment (total and female). This is consistent, for example, with

A.17

Tabl

eA

.15:

RD

Dfo

rNon

-dyn

astic

wom

en(2

009

Out

com

es)

IRA

/Lo

cally

Rai

sed

/O

vera

llFe

mal

esR

even

ues

Rev

enue

sPu

blic

Empl

oym

ent

Publ

icIn

scho

ol5-

11In

scho

ol12

-16

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Pane

lA:L

inea

rRD

D(s

ampl

e:+/

-5pe

rcen

tvot

em

argi

n)Fe

mal

e-1

.18*

*0.

93*

-1.2

3**

0.37

-1.3

0**

0.12

1.08

*(0

.47)

(0.4

9)(0

.56)

(0.5

9)(0

.56)

(0.5

9)(0

.57)

Obs

erva

tions

6363

4646

4646

46R

-squ

ared

0.14

0.08

0.12

0.01

0.13

0.01

0.09

Pane

lB:L

inea

rRD

Dw

/con

trols

(sam

ple:

+/-5

perc

entv

ote

mar

gin)

Fem

ale

-0.1

8-0

.06

-1.1

6*0.

88-1

.21*

-0.1

91.

09(0

.34)

(0.3

4)(0

.66)

(0.7

2)(0

.64)

(0.6

6)(0

.68)

Obs

erva

tions

6060

4444

4444

44R

-squ

ared

0.70

0.69

0.28

0.12

0.31

0.27

0.22

Not

es:R

esul

tsfr

omm

unic

ipal

regr

essi

ons.

The

depe

nden

tvar

iabl

esar

eIR

Aas

ash

are

ofth

em

unic

ipal

budg

et(C

olum

n1)

,rev

enue

sco

llect

edlo

cally

asa

shar

eof

the

mun

icip

albu

dget

(Col

umn

2),t

hesh

are

ofth

ew

orki

ng-a

gepo

pula

tion

that

isem

ploy

edin

the

publ

icse

ctor

(Col

umn

3),t

hesh

are

ofw

orki

ng-a

gew

omen

that

isem

ploy

ed(C

olum

n4)

,in

the

publ

icse

ctor

(Col

umn

5),t

hesh

are

ofgi

rlsag

e5-

11th

atis

enro

lled

insc

hool

(Col

umn

6)an

dth

esh

are

ofgi

rlsag

e12

-16

that

isen

rolle

din

scho

ol(C

olum

n7)

.All

depe

nden

tvar

iabl

esar

eno

rmal

ized

tobe

mea

nze

roan

dst

anda

rdde

viat

ion

one.

InPa

nels

Ban

dC

,the

regr

essi

ons

cont

rolf

orpr

ovin

cefix

edef

fect

s,an

dth

est

anda

rder

rors

(inpa

rent

hese

s)ac

coun

tfor

pote

ntia

lcor

rela

tions

with

inpr

ovin

ce.*

deno

tes

sign

ifica

nce

atth

e10

perc

ent,

**5

perc

enta

nd**

*1

perc

entl

evel

s.

A.18

non-dynastic female mayors engaging less in patronage, which has been found in previous studies

(Goertzel, 1983; Dollar, Fisman and Gatti, 2001; Brollo and Troiano, 2016). Moreover, as Column

4 shows, this does not reflect an overall decrease in female employment since it is limited to public

sector jobs. Finally, the estimates in Columns 6 and 7 show that while non-dynastic female mayors do

not have an effect on female enrollment in elementary school (there is close to universal elementary

school enrollment in the Philippines), they do seem to generate an increase in female enrollment in

secondary school (this estimate is only statistically significant in the local linear specification in Panel

A).

While we only have a very small number of races with these characteristics, our RDD estimates

provide suggestive evidence that non-dynastic women have a differential effect on some economic

outcomes. This is consistent with our theory regarding the importance of the channel through which

women access elected office.

A.19