Partisan alignment, clientelism and intergovernmental
transfers: evidence from Spanish municipalities∗
Marta Curto-Grau, Albert Solé-Ollé and Pilar Sorribas-Navarro
Universitat de Barcelona & Institut d’Economia de Barcelona
This draft: May 2011
Abstract
In this study we provide additional and robust evidence of the impact of partisan alignment on
intergovernmental transfers to municipalities. In addition, we study several mechanisms through
which this impact could be affected by clientelism. The empirical strategy consists on applying a
regression discontinuity design on capital grants to Spanish municipalities over the period 20022007. The results show that municipalities politically aligned with upper tiers do benefit from
larger transfers, especially in the case of regional grants. When clientelist tactics are introduced in
our framework, the allocation of grants is no longer based only on partisan politics but also on
two other factors: the political credit that “political machines” can claim and their ability to
monitor who their constituents vote for. In this sense, we find that in smaller municipalities –
where monitoring costs are lower- the discontinuity on transfers due to partisan ties is larger.
Keywords: intergovernmental transfers, partisan alignment, clientelism, regression discontinuity
JEL classification: H77, D72
∗
This paper has benefited from the financial support of ECO2009-12680/ECON (Spanish Ministry
of Education and Science) and project 2009 SGR 102 (Generalitat de Catalunya). We are also
grateful to Jonathan Rodden for his helpful comments.
E-mail addresses: [email protected] (M. Curto-Grau), [email protected] (A. Solé-Ollé),
[email protected] (P. Sorribas-Navarro).
1
1. Introduction
A good process of fiscal decentralization has to ensure that constituent units within a
federal system are provided with enough resources to meet their expenditure responsibilities.
In most federations, local governments have a weak tax base so in order to provide public
goods and services to their citizens they rely significantly on transfers from upper-level
governments. According to the normative criterion of fiscal federalism, the allocation of
grants has to guarantee economic efficiency and equity amongst the members of the
federation (Musgrave, 1959, 1983; Oates, 1972). Nonetheless, the positive approach claims
that transfers are distributed by non-benevolent agents who are not driven by economic but
political interests (Grossman, 1994). In line with this last view, our paper evaluates to which
extent the distribution of grants is largely conditional on the partisan alignment between
donor and recipient.
The political economy literature has identified four main political determinants of the
regional allocation of national resources. The first one is legislative representation
(Ansolabehere, Gerber, and Snyder, 2003; Porto and Sanguinetti, 2003). A second factor is
the share of “swing voters” versus “core voters” in constituencies. This idea has been
analyzed in different ways: through theoretical papers based on electoral competition
(Lindbeck and Weibull, 1987; Dixit and Londregan, 1998; Cox and McCubbis, 1986);
through theoretical papers based on legislative bargaining (Weingast, Shepsle, and Johnsen,
1981); through empirical studies (Schady, 2000; Case, 2001; Strömberg, 2001; Johansson,
2003) which have provided mixed and inconclusive evidence until now. Another determinant
is the citizens’ level of information and participation in the electoral system (Besley and
Burgess, 2002; Strömberg, 2004). And last but not least, it is also relevant the party affiliation
of the different government tiers (Grossman, 1994; Levitt and Snyder, 1995; Worthington and
Dollery, 1998; Khemani, 2003; Arulampalam et al. 2009). Two main problems arise from
this literature. The first one is that measuring the concept of core and swing voters has proven
to be a difficult task. The second issue is that whenever election results are used as variables
to explain the regional distribution of transfers, one should correct for endogeneity problems.
Our study presents an empirical analysis that aims at overcoming the two
aforementioned problems. Firstly, instead of taking a “swing vs. core voter” approach, the
explanatory variable for intergovernmental transfers is the political alignment between
municipalities and their upper-tiers. There are two main reasons to believe that the
2
distribution of transfers may be biased towards co-partisans. On the one hand, following the
intuition beneath Diaz-Cayeros, Magaloni and Weingast (2006), in certain circumstances the
incumbent party may have strong incentives to use a mechanism of punishments and rewards
to maintain electoral support. Hence, municipalities who defect to the opposition (i.e.
unaligned municipalities) should receive lower transfers as means of punishment. This idea is
at odds with the swing voter models of Dixit and Londregan and Lindbeck and Weibull. On
the other hand, the distribution of grants on partisan grounds is also influenced by the fact that
voters have incomplete information about which tier of government is the source of the grant.
In this situation, the grantor may not be able to claim much (or even none) political credit for
the grant. If there is no credit leakage (i.e. the grantor cannot claim his credit) he finds it more
profitable to distribute grants to aligned municipalities. However, if the leakage is large
enough, the incumbent grantor may consider sending funds to unaligned municipalities as he
could still get some electoral reward from that. The empirical evidence extracted from some
of the above mentioned studies concludes that the allocation of intergovernmental grants is,
indeed, skewed in favor of aligned municipalities. For instance, Khemani (2003) finds that
transfers subject to less stringent rules (more discretionary) are positively affected by
alignment while Arulampalam et al. (2009) observe that being an aligned and swing state
translates into 16% higher center-state transfers (compared to being unaligned and nonswing).
The second aforesaid concern that we want to solve is to isolate the effect that
alignment per se has on transfers and to ensure that causality runs in the desired direction. To
do that, we apply a regression discontinuity design (RDD)1, which allows us to benefit from
the relatively milder assumptions that it requires.
The empirical strategy of our paper relies on data on capital transfers received by
Spanish municipalities during two legislatures (2000-2003 and 2004-2007) from three
different upper-level administrations (central, regional and upper-local). Although there are
two recent contributions studying the effect of partisan alignment on intergovernmental
transfers in Spain, Solé-Ollé and Sorribas Navarro (2008a, 2008b)2 their main limitation is
the inability to disentangle if larger transfers are explained by higher political support (larger
1
This strategy is described in detail in Lee and Lemieux (2010).
2
Both studies are based on a model of political competition where grants to aligned municipalities are assumed
to be capable to extract more votes than grants to municipalities represented by opposition parties. As proven in
Solé-Ollé and Sorribas-Navarro (2008a), the relatively higher electoral reward of politically aligned
municipalities leads upper layer governments to transfer larger grants to them.
3
winning margins) or merely by partisan alignment. Furthermore, the RD estimates that we
obtain are more credible than the ones from “natural experiments” 3, like the differences-indifferences used in Solé-Ollé and Sorribas-Navarro (2008a), because the RDD can be
considered as a local randomized experiment in which the (randomized) variation observed in
the political alignment of municipalities is imprecisely controlled by individuals. Therefore,
the contribution of our paper is not merely to present additional empirical evidence on the
Spanish case but, more importantly, to provide more robust results through a neat explanatory
variable (partisan alignment).
The clear advantages of the RDD that we have exposed have made it a popular
econometric tool for researchers. In the political economy field, it has not been widely used
but there are a few studies that apply this strategy to examine the effects of a number of
variables on government expenditures. Albouy (2009), for instance, analyses the effect that
the party-identity of the legislator has on the allocation of federal expenditures. Ferreira and
Gyourko (2009) test for US municipalities if being the mayor a Democrat or a Republican
affects the allocation of local public spending. For Sweden, Pettersson-Lidbom (2008),
presents evidence that party control has a causal effect on economic outcomes, more
precisely, on the level of public expenditures and tax revenues. Additionally, there are two
applied studies that we consider to be close to ours as they both apply a RDD to examine the
effects of partisan alignment on intergovernmental transfers: Migueis (2010), for Portugal,
and Brollo and Nannicini (2010), for Brazil. We consider we improve upon existing literature
for several reasons. First of all, while Migueis (2010) considers the causal effect of alignment
on grants to be homogeneous, we take a more complex approach by testing the possibility that
this effect is heterogeneous. This strategy is also found in the paper by Brollo and Nannicini,
where they focus on two dimensions which could affect the impact of alignment on transfers:
the value of political capital for the central government and the impact of transfers on
electoral outcomes. However, our study differs from the latter because we center in a very
specific and different source of heterogeneity which may be more relevant for the Spanish
case: clientelism. Clientelism is a salient issue in the Spanish socio-economic context and we
think it may be strategically used jointly with partisan tactics to influence electoral results.
When clientelistic strategies are accounted for in our benchmark, “political machines” not
only allocate transfers based on partisan ties but also on the political credit they can claim and
their ability to monitor their constituents’ votes. To undertake this part of our study we draw
3
The formal proof of the ‘superiority’ of RDD over ‘natural experiments’ is in Lee (2008)
4
on ideas from Diaz-Cayeros, Magaloni and Weingast (2006), Stokes (2005, 2007), Brusco,
Nazareno and Stokes (2004) and Solé-Ollé and Sorribas-Navarro (2008a). Based on these
studies we contrast four hypotheses. We examine the possibility that the treatment effect of
political alignment on transfers may be larger in: poorer municipalities; smaller
municipalities; municipalities aligned at all levels of government; and municipalities with
lower reliance on intergovernmental transfers (e.g. those with a lower debt burden).
Moreover, traditionally, Spanish left-wing parties have been accused more often of using
clientelist strategies than right-wing parties, so we also test if the political color of the grantor
has an impact on the causal effect of alignment on grants. Finally, the last hypothesis we
contrast is whether a majority government is more able to allocate transfers on partisan
grounds than a coalition government.
To summarize the findings of our paper, our first set of results show through RD
estimates that being an aligned municipality has a positive effect on the amount of transfers
received by lower-level governments. This impact is the largest in the case of transfers
allocated by the regional governments while the lowest impact is found for central
government transfers. Thanks to an increase on the sample size and to the use of the RDD we
consider these results to be more robust than those in previous studies. Concerning the impact
of clientelism on the causal impact of alignment, we do not find any evidence of it when we
look at central transfers. However, for regional and upper-level transfers we do find evidence
that the sharp increase on transfers observed in aligned municipalities is greater for smaller
municipalities. This effect is also larger for left-wing grantors (compared to right-wing ones)
at the regional level.
The remaining paper is structured as follows. In section 2 we establish the relevance
of clientelism for our analysis. Section 3.1 contains some brief background information on
Spanish institutions (electoral processes) and intergovernmental grants. In section 3.2 we
discuss the empirical strategy. Section 4 presents our main findings as well as the tests that
validate our analysis. We conclude with section 5.
2. The role of clientelism in Spain: heterogeneous effects of partisan alignment
A large part of the Spanish public opinion presumes that the allocation of public
spending in the country is largely influenced by clientelistic ties between voters and
5
politicians. Political clientelism is often cited by Spanish newspapers and its persistence in
this country has its strong roots in the well-known caciquismo of Restoration times -during
the late 19th and early 20th century4. Due to socio-economic changes nowadays traditional
clientelism (based on a peasant clientele system) has been replaced by a modern form of
territorial clientelism, also known as “broker clientelism”. In her study of Spanish clientelism,
Blakeley (2001) explains how the Partido Popular (people’s party) has strategically targeted
Galicia for decades while the Partido Socialista Obrero Español (socialist party) has
traditionally done so in Andalusia. The Andalusian case is frequently illustrated through the
agricultural unemployment payment scheme (PER5) while Galician clientelism is especially
in the form of employment to private business closely linked with the Partido Popular6. In her
text, Blakeley also notices the wide-spread accusations of clientelism posed to a long-lasting
ruling party in Catalonia, Convergència i Unió.
There are two dimensions that one should take into account when distinguishing
between clientelism and other related concepts such as pork-barreling and rent-seeking: the
scope (how narrow the group of beneficiaries is) and the directedness of the exchange7.
Hence, clientelism is based on a quid pro quo arrangement between the patron (politician) and
the client (the voter), where they exchange goods for votes; this is made “not simply to seek,
but rather to directly reward [electoral] support”. All in all, “even a very ‘broad’ policy may
be ‘clientelistic’ while even very narrow targeting may not”. So, even broad project grants,
such as the ones financed through intergovernmental transfers, can be used by governments to
tie the hands of their electorate8.
4
For a broader description of the transition from traditional clientelism to partisan clientelism in Spain, see
Cazorla (1994).
5
This agrarian subsidy was implemented by the Andalusian regional government (Junta de Andalucía). In 1996
it was renamed to AEPSA and it extended its scope to other autonomous communities, although Andalusia still
receives a large share of it.
6
Hopkin (2001) and Corzo (2002) also cite the Galician and Andalusian cases as examples of “modern”
clientelism in Spain. Robles Egea(2003) focuses on political clientelism in Andalusia.
7
See Carroll and Lyne (2006) for further discussion on this issue.
8
We quote two examples extracted from Spanish newspapers to illustrate how transfers can be used with
clientelistic purposes; both refer to clientelism at the upper-local level. The first one is a statement made by Enric
Morera, a deputy in Les Corts Valencianes (the Valencian regional government):
“(…) we have three diputaciones with no competencies who only serve to provide jobs for advisors and
trustworthy people who mandate and, in addition, the public funds they have at their disposal are used as a tool
to preform political clientelism and propaganda of those who are in power”. El Periòdic, 17/01/2011
(http://www.elperiodic.com/noticias/102792_morera-psoe-hablan-acabar-autonomias-pero-diputaciones-nidosdeficit-clientelismo-politico.html)
6
To present the above ideas in a formal way we present a model borrowing ideas from
Stokes (2005, 2007) and Diaz-Cayeros, Magaloni and Weingast (2006). We start with a oneshot game with two actors: voters and parties. Voters have ideology xi; there are two parties 1
(incumbent) or 2 (opposition) who compete to head an upper-tier government (in our study:
central, regional or upper-local levels). Voters’ preferences are as follow:
ui= αi × (-1/2(vi-xi)2) + (1- αi ) × gi(θ, µ)
where vi={x1,x2} is the citizen’s decision to vote for the clientelist party or the
opposition, xi represents the voter’s ideology whose weight is α ϵ[0,1] .Voters also get utility
from a potential reward, gi={0, g(θ, µ)}, depending on whether the clientelist party wins or
not. In our study the reward corresponds to intergovernmental transfers. As in Diaz-Cayeros,
Magaloni and Weingast (2006), failure to support the clientelist party translates into lack of
reward, i.e. punishment through lower funds. Furthermore, the reward may, in turn, be
influenced by two factors: the political credit (θ) that the grantor can claim when giving the
reward and the party’s ability (µ) to observe the citizen’s vote. The reward function is
increasing in both factors. Stokes’ model presumes that “a person’s vote is (…) perfectly
observable by political parties”, but in a democracy with secret ballot elections, like Spain,
this is very unlikely to occur. However, as pointed by Brusco, Nazareno and Stokes (2004),
clientelistic strategies can still work under those circumstances. This is possible because
“clientelist parties compensate for the inability to observe the vote directly by observing a
range of other actions and behaviors (…) that allow party operatives to make good guesses”.
In multi-government systems, the lower level representatives (the mayors) may be seen as
intermediaries of the upper-level governments and their proximity to citizens makes them
more capable to perceive their constituents’ actions.
All in all, the timing of the game can be easily summarized in two stages. At the
beginning of the first stage, t=1, electoral campaigns take place and politicians signal their
The second example refers to a complaint raised by a representative in the diputación de Castilla-la-Mancha,
Mario González Somoano (peoples’ party), to the representative of public works of the diputación, Ángel
Moreno(socialist party). González Somoano complains because in his village, Gascueña, there is an emergency
situation as one of the streets is in an extremely bad condition and it needs to be asphalted:
“González Somoano replied that (…) they had undertaken asphalt works in neighboring villages of Gascueña,
but governed by socialist mayors, accusing of acting more in ‘their villages’ than in others and reminding that all
the roads from Cantalojas (municipality whose mayor is Moreno) had been asphalted the previous year”.
Guadaqué,17/07/2009(http://www.guadaque.com/index.php?option=com_content&view=article&catid=3%3Apr
ovincia&id=3682%3Ael-pp-acusa-al-psoe-de-clientelismo-y-rafael-esteban-llama-al-portavozpayaso&Itemid=54)
.
7
willingness to provide rewards (g). During these campaigns candidates express promises
which often have implicit threats indicating that the only way to ensure they get the public
goods/services desired is to vote for them and not for the opposition party. In order to target
their voters more accurately, candidates often promise specific goods, such as infrastructures9.
In this same stage, voters express to candidates their willingness to vote for them in exchange
for goods and at the end of the period they cast their vote; they have two possibilities, either
they renege on their promise or they do not. At a second stage, t=2, parties take action and
implement public policies. Similar to Stokes’ analyses, there are four possible situations with
different payoffs –summarized in the table below-. If the voter complies and votes the
clientelist party, he wins and gets the votes of its constituents (v>0); but if the voter reneges,
this party does not get the vote (v=0) and the party loses the elections. In this case, the party
can still decide whether to pay a reward to the voter or not. On the contrary, if the party wins
it has two possible options: either he complies and rewards its voters (g>0) or it reneges
(g=0).
VOTER
PARTY
Reward
No Reward
Comply
α×(-1/2(xi-x1) ) +(1 α)× g(θ, µ), v- g(θ, µ)
α×(-1/2(xi-x1)2), v
Defect
α×(-1/2(xi-x2)2) +(1 α)× g(θ, µ), - g(θ, µ)
α×(-1/2(xi-x2)2), 0
2
As explained, the amount of the reward (g) is conditional on both θ and µ. So, we
would be in the situation “Comply-No Reward” whenever the system is totally opaque and the
winning party can hardly be monitored (i.e. µ→0) and/or the grantor cannot claim any credit
from the reward (θ=0). Moreover, note that to overcome commitment problems, the above
model needs to be a repeated game in which µ≠0.
From the formal description we can derive four hypotheses on how clientelism could
smooth or exacerbate the impact of political alignment on transfers. There may be a chance
that the treatment effect of political alignment on transfers is larger in:
H1: smaller municipalities. In this case monitoring the voters may be easier (we
expect µ to be higher)
9
In Spain, local infrastructures (like sports centers, swimming pools, roads, hospitals, etc.) are largely financed
through capital transfers from upper-level governments.
8
H2: municipalities aligned at all levels. The credit loss is also lower in this situation (θ
is higher)
H3: in poorer municipalities. This is due to the fact that for poor people the benefits
extracted from the reward outweight the disutility from voting a party whose ideology
is far from ours (αpoor < αrich). Thus, vote buying is easier in this case
H4: municipalities that are more reliant on intergovernmental transfers. This
assumption is closely linked with the previous hypothesis. In municipalities with a
large debt burden, their “patron-dependency” makes voters value more the reward
they would get from voting the clientelistic party than their own ideology
Besides the above-mentioned hypotheses we are also interested in analyzing two other
factors which may affect the use of clientelism: the political color of the grantor and its
relative “freedom” for distributing public resources.
H5: in Spain, left-wing grantors are thought to make more use of clientelist tactics
than right-wing parties, so they may allocate larger transfers to municipalities
politically aligned with them
H6: compared to a coalition government, a majority government may be more able to
divert resources to their aligned municipalities because it enjoys more freedom of
action.
All these hypotheses are contrasted in section 4.2.
3. Empirical Analysis
3.1. Intergovernmental transfers and elections in Spain
Intergovernmental transfers
During the last 25 years, Spain has been involved in an increasing process of fiscal
and political decentralization despite being constitutionally defined as a unitary country10. The
10
The Spanish Constitution contains several provisions that promote federalism. For instance, according to
Article 137 “[t]he State is organized territorially into municipalities, provinces and any Autonomous
Communities that may be constituted. All these bodies shall enjoy self-government for the management of their
respective interests”.
9
central government (the Cortes Generales) consists of the Congress of Deputies (Congreso de
los Diputados) and the Senate (Senado). At the regional level, Spain is composed of
seventeen autonomous communities (AC) and two autonomous cities. At the local level, 85%
(out of over 8,000) of municipalities do not have more than 5,000 inhabitants which makes it
often convenient to have upper-local administrations in order to take advantage of economies
of scale or to use inter-municipal cooperation as a tool for a better governance. This upperlocal level is known as província (province) and its government, Diputación. There is a total
of fifty provinces spread amongst the ACs but seven of these regions consist only of one
province.
Municipalities are the administration which is closer to citizens and, in Spain, to
provide them with public goods and services their financing comes mainly from own source
revenues and, specially, from intergovernmental transfers11. The formulas used in the
allocation of current revenues reduce the chances of using such funds in a discretionary way.
However, the distribution of resources for capital spending is subject to less stringent rules
which may give rise to different sorts of tactical behavior on the government’s side. This is
one of the main reasons for focusing our analysis on capital transfers. This type of transfers is
meant to finance a large part of earmarked project suggested by municipalities to their upper
tiers, depending on their infrastructure needs. A large share of the capital grants received by
local governments come from the regional and upper-local tiers as shown in table 1.
***Table 1 here***
Electoral processes in Spain
In Spain, general, regional and municipal elections take place, as a rule, every four
years. On the years analyzed, local elections were held in 1999 and 2003, regional elections in
most of ACs were as well in 1999 and 2003, while general elections were in 2000 and 2004.
Electoral districts are equivalent to provinces and representatives in each province are elected
from a closed list presented by each party. Although the political scene is highly polarized (by
the two main parties: PSOE and PP) in general elections, in parliaments we can also find the
presence of several regional parties as well as a limited number of minority parties, hence,
ensuring plurality. Representatives of upper-local governments (Diputaciones) are elected
11
In 2006 intergovernmental transfers accounted for 1/3 of current revenues. In turn, 2/3 of these transfers were
current grants while the remaining were capital grants.
10
indirectly, as an outcome of local elections. This reduces accountability and may generate
undesired incentives.
3.2. Empirical strategy
Econometric specification
To obtain estimates of the impact of partisan alignment on intergovernmental transfers
we use the regression discontinuity technique reviewed extensively in Lee and Lemieux
(2010). The intuition beneath this strategy is that in the neighborhood of a cutoff point of an
assignment variable, there exists a discontinuity (a sharp change) both in the assignment
variable and in average outcomes. The ‘RD’ estimates are seen as a LATE (local average
treatment effect) derived from the comparison of very similar individuals whose main
difference is to be in a different side of the cutoff (i.e. being eligible or non-eligible for
treatment). In terms of internal validity, this econometric technique is considered to be the
best of all quasi-experimental methods. Another advantage of the RDD is that it requires lessstringent identification assumptions. The main disadvantage of using this technique is the loss
of external validity.
In our particular study capital transfers are conditional on treatment status, where
‘treatment’ implies that the local government is aligned with the upper level (central, regional
or upper-local). As shown in equation (1) below, there are two potential outcomes for each
municipality depending on its treatment status:
where gi represents per capita grants to local governments and Alignmenti is a binary variable
to indicate treatment status.
The assignment variable that determines the treatment and control groups is the
electoral margin. This variable, Margini, is computed as follows:
if the party in government at the upper level is a right-wing party, the variable
margin is the difference between the share of votes obtained by right-wing minus leftwing parties in local elections in municipality i
11
if the party in government at the upper level is a left-wing party, the variable margin
is the difference between the share of votes obtained by left-wing minus right-wing
parties in local elections in municipality i
So, if the electoral margin is positive there is a large probability that upper and lower
levels are aligned and the opposite holds if the margin is negative. Therefore, the cutoff that
establishes if a municipality is treated or non-treated is at Margin = 0. The fact that the
probability is simply “large” and not “equal to one” (see equation (2) below) indicates that
we have a fuzzy regression discontinuity design (FRD), as opposed to a sharp RD.
In such case, to estimate the treatment effect that alignment has on the level of
transfers assigned to municipalities, we need to compute the following FRD estimand:
A relatively simple way of estimating the causal effect in equation (3) is by running a
Two-Stage-Least-Squares regression on equation (4):
where Alignment is instrumented by the dummy variable d (i.e. 1{Margini≥0}) and Vi
is the vector of control variables. More precisely, the controls introduced are population
density, property tax rates and debt burden of the municipality.
Data
Grants
As previously stated, due to their high level of discretionality the type of grants chosen
for our analysis is capital grants (chapter 7 of the budget) from upper layer governments. The
regressions are run for each upper layer of government. Like in other studies (Brollo and
Nanicini, 2010; Solé-Ollé and Sorribas-Navarro, 2008a), we add up the transfers
corresponding to the last two years of local legislatures provided that grant budgets tend to
be spent more notoriously in the proximity of elections. The two mayoral terms that we
consider are 2000-2003 and 2004-2007. In this case, the alignment that results from local
12
elections in 1999 affects the aggregate transfers in 2002 and 2003, while alignment from
local elections in 2003 does so to the aggregate transfers of 2006 and 2007. Information on
intergovernmental grants has been obtained from budgetary data from the Ministry of
Economics and Finance and transfers are used in per capita terms, computed with population
data from the National Institute of Statistics (INE).
Alignment, assignment variable and controls
To compute alignment between local governments and each upper-tier (central,
regional and upper-local), we use electoral data from the Ministry of Territorial Policy and
Public Administration and the Ministry of Interior. It is easy to define alignment when there
is only a single-government controlling the upper and lower-tiers. In such situation, a
government is politically aligned when the parties at the two levels coincide. However, when
governments are formed by coalitions, the definition of alignment has to be broadened. We
use the classification of alignment developed in Solé-Ollé and Sorribas-Navarro (2008a) in
which four different types of alignment are distinguished depending on whether the
alignment is between leaders (be it single party leaders or coalition leaders) or between
coalition partners. We focus our attention in two out of their four types of alignment, type-a
and type-b12. As we limit to these two types, we consider a municipality to be aligned if it
meets one of these conditions: (a) the same party controls a single-party government at both
layers; (b) a party controls a single-party government at one layer and leads a coalition at the
other layer or a party leads a coalition at both layers. We have restricted the definition of
alignment to these types for two reasons. On the one hand, coalition leaders are expected to
attract more funds than coalition partners. On the other hand, this narrower definition
represents better the idea of partisan alignment as it only takes into account the party in
control of the government. In the situation in which municipalities are type-c and type-d
aligned we have two options: either we drop these observations (they account for about ¼ of
the sample) or we consider them to be unaligned. Considering them simply as aligned
municipalities would introduce an important error as equation (2) would no longer be valid.
The results presented in section 4 are based on a sample where municipalities with type-c and
type-d alignment are disregarded but we also comment the validity of the results when they
are considered to be unaligned.
12
Type-c and type-d alignment are the ones that take into account coalition partners when computing alignment.
13
In the first mayoral term, around 41% of municipalities were aligned with the central
level, 58% with the regional level and 60% with the upper-local level, while in the second
term the shares were 45%, 58% and 63%, respectively.
In section 3.1 we argued that the assignment variable of this model, which indicates
whether a municipality is aligned or unaligned, is the electoral margin that upper-tier
governments obtain in municipal elections. The validity of this variable is discussed in
further detail in section 5. To construct the Margin variable we use the municipal electoral
outcomes of 1999 and 2003 to compute the difference in vote shares between right and left
wing parties.
In order to provide more robust estimates we include three additional control
variables: population density, debt burden over current revenues and property tax rates. The
effect of population density on capital grants may be negative or positive because this type of
grants tend to favor small municipalities (Solé-Ollé and Bosch, 2005), but at the same time
they are biased towards more extensive municipalities were urban sprawl generates higher
expenditure needs. The property tax rate can also have a positive or negative effect as
explained in Solé-Ollé and Sorribas-Navarro (2008a). Lastly, the ratio of debt burden over
current revenues is included as a proxy for fiscal effort.
Sample
Out of the approximately 8,000 Spanish municipalities, in order to have information
on all the above variables for the two terms analyzed, we limit our sample to 1,828
municipalities for the analysis of regional and central transfers. In the case of upper-local
transfers the sample reduces to 1,607 municipalities given that we omit the autonomous
regions with only one province. All the municipalities of our study have more than 1,000
inhabitants due to restrictions on socio-economic data. We also had to restrict our sample to
those municipalities for which we had disaggregated data on transfers. We end up with a
representative sample of around 70% of Spanish municipalities of over 1,000 inhabitants.
Table 2 contains descriptive statistics of all the variables.
***Table 2 here***
14
4. Results
4.1. Discontinuity on transfers: homogeneous treatment effects
One of the main advantages of the RD technique is that it is very intuitive since it can
easily be conveyed by a picture. The first graphics to present are the ones showing the
“jump” on the assignment variable. To graph a plot of the assignment variable (Margin)
against the forcing variable (Alignment), the sample is divided into a number of bins of equal
size. Then, we plot the average value of the assignment and forcing variable in each bin and
we fit a polynomial model for a better visual inspection.
If the bins are too narrow, the estimates are quite imprecise and if they are too wide,
estimates may be biased. So, to choose the right width of the bin we conduct an F-test for
nested models comparing the fit of a regression with K’ bins with the fit of a regression with
2K’ bins. The choice of the optimal polynomial is made upon evaluation of the Akaike’s
information criterion. Figures 1, 2 and 3 show these plots for regional and upper-local
transfers and the bin width used is the optimal one indicated from the F-test.
As explained in section 3.1, a relatively simple way to estimate equation (4) is to run a
TSLS instrumenting the forcing variable (Alignment) with a dummy (d) of the assignment
variable (Margin). We present the first stage estimates in table 3. The results (jointly with a
test for weak instruments) prove that a dummy equal to one when Margin is positive is a
strong instrument of the Alignment variable. Panel A and C do not contain neither territorial
nor time effects while Panel B and D do so. Panel C and D contain control variables (debt
burden, property tax rate and population density). Figures in bold correspond to the estimates
of the optimal polynomial.
***Table 3 here***
Both the graphs and the figures on table 3 confirm the existence of a sharp change on
the assignment variable at the threshold. To demonstrate whether the same occurs with the
outcome variable (per capita grants) we plot the assignment variable against the outcome
variable following the same procedure than before. Not observing a graphical “jump” on
transfers rules out any possibility of having a significant treatment effect of alignment.
Figures 4, 5 and 6 show the causal relationship between alignment and transfers at central,
regional and upper-local levels. From these three pictures we would expect the treatment
15
effect of alignment on transfers to be the highest in the case of regional transfers, while the
impact is clearly reduced for central and upper-local transfers.
RD estimates are shown in tables 4 and 513. Table 4 presents the reduced form (i.e.
intention to treat) estimates while table 5 shows IV estimates. The table is structured in four
panels (A, B, C and D) which have the same structure than the ones in table 3. The choice of
the optimal polynomial is based on the AIC values, in the case of the reduced form, and on
an F-test for joint significance of the polynomial, in the case of the IV regression.
***Table 4 and 5 here***
The results on table 4 and 5 confirm the ideas extracted from the previous
graphs: the amount of per capita grants received by municipalities is statistically larger for
aligned municipalities (relative to unaligned ones). In turn, the estimates show that the
impact of political alignment is greater in the case of regional transfers. This is consistent
with the findings of Solé-Ollé and Sorribas-Navarro (2008a) who show that “a municipality
aligned with Central, Regional and Upper-local grantors will receive additional grants of 5.1,
12 and 5.7 euros per capita, respectively”.
As previously noted, the sample from which we extract the results in tables 4 and 5
disregards those municipalities with alignment type-c and type-d. In addition, we have
obtained the RD estimates from a sample where these municipalities are considered
unaligned and we find that the significance and sign of the coefficients remain unaltered14.
4.2. Discontinuity on transfers: heterogeneous treatment effects
In section 2 we have argued why we believe clientelism could be an important source
of heterogeneity for the treatment effect of partisan alignment on transfers. To test this idea
we focus on six different dimensions: the size of the municipality; the alignment at all levels
of government; the poverty level; the reliance on intergovernmental transfers; the political
color of the grantor; and the “majority” status of the grantor government. In the first case, we
use population data to split the observations into two subsamples: municipalities below and
13
We have performed the same analysis using as a dependent variable the logarithm of capital transfers per
capita. Although we do not show the results for the sake of brevity, we can confirm the overall result hold:
partisan alignment has a positive and significant impact on the distribution of central, regional and upper-local
transfers.
14
Results are available upon request.
16
over 5,000 inhabitants15 and then we use a Wald test to establish whether the differences are
statistically significant. In the second case, we follow a similar procedure but we separate the
sample into municipalities that are aligned at all levels of government and municipalities who
are not. That is, the control group in both subsamples is the same (unaligned municipalities)
but the treatment group in the first subsample contains only municipalities aligned with all the
upper tiers (central, regional and upper-local).
To study the third dimension of interest, we use unemployment rates as a proxy for
poverty levels; we separate the sample into municipalities with unemployment rates over and
below the average at time t of the region (province or AC) they belong to. To test the fourth
hypothesis, we use the average debt burden of the municipalities of our study to divide the
sample into those who are indebted over or below the average. Finally, to study the impact of
the political color of the grantor the sample is split into municipalities with a left-wing grantor
and municipalities with a right-wing grantor, while to study the hypothesis of the “majority
status” effect we divide the sample into majority and coalition grantors.
The results of our empirical analysis are in table 6 where we present the reduced form
estimates of each subsample, taken into account the six dimensions we have discussed. The
regressions in Panel 1 -where the dependent variable is central transfers per capita- show that
the casual effect of alignment on transfers is homogeneous amongst municipalities and that
clientelism does not have a significant impact. In the case of regional transfers (Panel 2 in
table 6) we do find empirical evidence that for smaller municipalities the impact of partisan
alignment on grants is larger than for bigger municipalities and this impact is also larger when
the grantor is left-wing (compared to a right-wing grantor).
Finally, Panel 3 presents the
results for upper-local transfers, where we also observe that being a small municipality
compared to being a big one translates into a larger treatment effect of alignment on transfers.
4.3. Validity tests
There are two main concerns that may question the validity of our results. The first
one is the possibility of manipulation of the forcing variable (Margin). If this was the case, it
would mean that political parties can influence in some way the electoral results in close
15
We could split the sample into municipalities with population above or below the mean but for the Spanish
case this separation is less relevant given that a large share of municipalities are small municipalities and we
would end up with two subsamples where one of them is not representative. We have chosen the 5,000
inhabitants threshold because this figure is also used to allocate competencies to municipalities so city councils
above or below this threshold may have similar competencies to fulfill.
17
races. In this situation we would observe an abnormal concentration of observations near the
threshold. In Figure 7 we present the histogram of the assignment variable to show that this is
not the case and that the results of elections in close races in Spain cannot be precisely
controlled by agents, that is, they are “as good as randomized”.
The second concern that may affect the validity of the results is the possibility that
other covariates experience a sharp change (a discontinuity) at the cutoff. To rule out this
option we estimate the 2SLS coefficients of equation (4) but we switch the dependent variable
to different covariates: population density (columns 1 and 4 in table 6), unemployment rates
(columns 2 and 5 in table 6) and debt burden (columns 3 and 6 in table 6). The figures in table
6 show that in any case there exists a discontinuity for these covariates.
5. Conclusions
In a system of multi-level governments, the normative rationale beneath the
distribution of intergovernmental transfers may be offset by the effects of partisan ties
between grantor and recipient. This has been claimed in several analyses in the political
economy field and in this paper we have presented empirical evidence of the existence of this
phenomenon in Spain. Our results are obtained from applying a regression discontinuity
design in a database of around 2,000 Spanish municipalities over two mayoral terms, 20002003 and 2004-2007. The use of this econometric technique allows us to obtain more robust
estimates than those in previous studies. Furthermore, we believe we improve upon existing
literature by linking partisan ties with clientelism, a salient issue in Spain. Adding this factor
in our analysis makes it possible to study a possible heterogeneous effect of partisan
alignment on grants.
The findings presented in this paper have shown that aligned municipalities which had
close electoral races, do indeed receive larger transfers (in the last two years of the electoral
term) than unaligned municipalities. This discontinuity in the amount of transfers is
especially sharp in the case of regional transfers, compared to central and upper-local grants.
This confirms the findings of previous studies but, in addition, we believe we are able to
isolate better the effect of partisan ties per ser. Lastly, we also find evidence that the
discontinuity in grants is larger for smaller municipalities (in the case of regional and upperlocal grants) and for municipalities with a left-wing grantor at the regional level.
18
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22
Table 1. Capital transfers to Spanish municipalities (2002-2007)
Transfers to local governments
From State
From Autonomous Communities (AC)
From Diputaciones (Upper-local)
2002
13%
46%
20%
2003
14%
47%
20%
2004
11%
48%
19%
2005
10%
49%
19%
2006
10%
52%
18%
2007
11%
55%
18%
Source: Ministry of Economics and Finance
Table 2. Descriptive statistics and data sources
Description
Mean
(S.D)
Central grants
Per capita capital grants assigned from
central government (item 7.2 of the revenue
budget)
33.05
(78.26)
Regional grants
Per capita capital grants assigned from
regional government (item 7.5 of the
revenue budget)
159.94
(196.54)
Upper-local grants
Per capita capital grants assigned from
upper- local government (item 7.6.1 of the
revenue budget)
76.07
(94.82)
Debt burden
Debt service (capital, item 9 of the spending
budget, +interest, item 3) as a share of
current revenues
0.062
(0.08)
Margin
Vote share of right-wing parties if upper-tier
is right-wing; vote share of left-wing parties
if upper-tier is left-wing; 0 otherwise
0.09
(0.35)
Population density
Population / Km2
Property tax rate
Nominal property tax rate (IBI)
Variable
Ministry of Economics and
Finance
414.76
(1388.92)
0.59
(0.16)
23
Source
Ministry of Territorial
Policy and Public
Administration and
Ministry of Interior
National Institute of
Statistics (INE)
Cadastre (Catastro)
Table 3: Partisan alignment and electoral margin (1st stage estimates).
Polynomial
degree
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
0
1
2
3
4
5
6
0
1
2
3
4
5
6
Panel A
Central
d(C)
Regional
d(R)
Upper-local
d(UL)
Territorial d.
Controls
Central
d(C)
Regional.
d(R)
Panel B
0.751
(0.0114)***
0.655
(0.0219)***
0.654
(0.0218)***
0.550
(0.0275)***
0.549
(0.0276)***
0.491
(0.0325)***
0.491
(0.0325)***
0.738
(0.0117)***
0.650
(0.0222)***
0.651
(0.0221)***
0.540
(0.0276)***
0.540
(0.0276)***
0.486
(0.0320)***
0.485
(0.0319)***
0.769
(0.0115)***
0.680
(0.0224)***
0.636
(0.0223)***
0.548
(0.0271)***
0.539
(0.0271)***
0.479
(0.0321)***
0.475
(0.0323)***
0.774
(0.0117)***
0.655
(0.0223)***
0.628
(0.0220)***
0.530
(0.0269)***
0.527
(0.0267)***
0.471
(0.0315)***
0.468
(0.0316)***
0.766
(0.0127)***
No
No
0.648
(0.0241)***
No
No
0.609
(0.0245)***
No
No
0.535
(0.0291)***
No
No
Panel C
0.525
(0.0295)***
No
No
0.479
(0.0346)***
No
No
0.478
(0.0350) ***
No
No
0.781
(0.0126)***
Yes
No
0.620
(0.0238)***
Yes
No
0.600
(0.0243)***
Yes
No
0.515
(0.0292)***
Yes
No
Panel D
0.510
(0.0294)***
Yes
No
0.480
(0.0340)***
Yes
No
0.476
(0.0343)***
Yes
No
0.766
(0.0115)***
0.680
(0.0226)***
0.677
(0.0220)***
0.566
(0.0283)***
0.568
(0.0279)***
0.505
(0.0331)***
0.506
(0.0328)***
0.760
(0.0116)***
0.667
(0.0227)***
0.665
(0.0222)***
0.554
(0.0281)***
0.557
(0.0278)***
0.501
(0.0325)***
0.503
(0.0322)***
0.768
(0.0117)***
0.679
(0.0231)***
0.633
(0.0229)***
0.542
(0.0277)***
0.533
(0.0278)***
0.468
(0.0328)***
0.467
(0.0329)***
0.776
(0.0117)***
0.649
(0.0230)***
0.622
(0.0226)***
0.524
(0.0276)***
0.521
(0.0275)***
0.460
(0.0321)***
0.458
(0.0322)***
Upper-local
d(UL)
0.767
0.649
0.610
0.537
0.526
0.478
0.780
0.619
0.601
0.516
0.510
0.476
0.480
0.481
(0.0126)***
(0.0241)***
(0.0244)***
(0.0290)***
(0.0293)***
(0.0349)***
(0.0126)***
(0.0237)***
(0.0242)***
(0.0291)***
(0.0293)***
(0.0343)***
(0.0345)***
(0.0339)***
Territorial d.
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Controls
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Note: (1)The table reports first stage estimates of the effect of partisan alignment on intergovernmental transfers); (2) robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; (3) SE clustered by municipality, (4) D(.) is an
indicator for electoral margin below the eligibility threshold; (5) no interactions of the polynomials with the eligibility indicator; (6) regressions for central and regional transfers are on a sample of 3,657 observations (with no controls) and 3,477
(with control variables) while regressions for upper-local transfers are on a sample of 3,215 observations (with no controls) and 3,208 (with control variables); (7) panel A and C do not contain neither time nor territorial effects, while panel B
and D contain both.
24
Table 4: Electoral margin and intergovernmental transfers (reduced form)
Polynomial
d
(1)
(2)
(3)
(4)
(5)
(8)
(9)
(10)
(11)
(12)
0
1
2
3
4
0
1
2
3
4
Panel A
Central
d(C)
Regional
d(R)
Upper-local
d(UL)
Territorial
d.
Controls
Central
d(C)
Regional.
d(R)
Upper-local
d(UL)
Panel B
6.630
(2.125)***
3.882
(3.591)
4.683
(3.585)
12.84
(4.392)***
12.83
(4.402)***
3.974
(2.070)*
7.030
(3.379)**
7.427
(3.371)**
11.40
(4.108)***
11.45
(4.129)***
60.34
(6.318)***
47.55
(10.67)***
61.60
(11.07)***
51.12
(13.11)***
49.68
(13.35)***
57.80
(6.234)***
48.76
(9.986)***
57.17
(10.28)***
48.45
(12.51)***
47.99
(12.70)***
12.80
(3.561)***
No
6.434
(5.584)
No
17.21
(5.793)***
No
15.65
(6.635)**
No
19.23
(6.847)***
No
20.51
(3.744)***
Yes
11.39
(5.189)**
Yes
19.23
(5.305)***
Yes
17.79
(6.172)***
Yes
17.95
(6.341)***
Yes
No
No
No
Panel C
No
No
No
No
No
Panel D
No
No
6.665
(2.177)***
4.369
(3.748)
8.510
(3.666)**
10.84
(4.581)**
10.67
(4.585)**
4.653
(2.159)**
6.964
(3.494)**
8.679
(3.473)**
10.46
(4.263)**
10.14
(4.257)**
58.31
(6.018)***
44.33
(10.25)***
57.24
(10.40)***
52.20
(12.75)***
51.95
(12.84)***
54.41
(5.896)***
47.45
(9.826)***
55.91
(9.965)***
52.73
(12.33)***
53.02
(12.40)***
11.20
(3.546)***
No
4.322
(5.540)
No
14.72
(5.709)**
No
12.99
(6.605)**
No
16.61
(6.787)**
No
20.26
(3.656)***
Yes
11.64
(5.080)**
Yes
18.18
(5.211)***
Yes
16.64
(6.076)***
Yes
17.21
(6.251)***
Yes
Territorial
d.
Controls
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Note: (1)The table reports reduced form estimates of the effect of partisan alignment on intergovernmental transfers); (2) robust standard errors in parentheses,
*** p<0.01, ** p<0.05, * p<0.1; (3) SE clustered by municipality, (4) D(.) is an indicator for electoral margin below the eligibility threshold; (5) no interactions
of the polynomials with the eligibility indicator; (6) regressions for central and regional transfers are on a sample of 3,657 observations (with no controls) and
3,477 (with control variables) while regressions for upper-local transfers are on a sample of 3,215 observations (with no controls) and 3,208 (with control
variables); (7) panel A and C do not contain neither time nor territorial effects, while panel B and D contain both.
Table 5: Intergovernmental transfers and partisan alignment (2SLS estimates)
Polynomial d
Central
Alignment(C)
Regional
Alignment (R)
Upper-local
Alignment
(UL)
Territorial d.
Controls
Central
Alignment (C)
Regional.
Alignment (R)
Upper-local
Alignment
(UL)
(1)
0
(2)
1
(3)
2
Panel A
(4)
3
(5)
4
(6)
0
(7)
1
(8)
2
Panel B
(9)
3
(10)
4
8.831
(2.829)***
5.929
(5.480)
7.157
(5.475)
23.34
(8.028)***
23.36
(8.069)***
5.383
(2.795)*
10.81
(5.188)**
11.42
(5.177)**
21.11
(7.644)***
21.22
(7.697)***
78.43
(8.212)***
69.96
(15.61)***
96.87
(17.27)***
93.29
(23.76)***
92.16
(24.62)***
74.72
(7.990)***
74.40
(15.04)***
91.02
(16.10)***
91.37
(23.24)***
91.06
(23.76)***
16.71
9.933
28.25
29.26
36.63
26.27
18.38
32.06
34.52
35.19
(4.650)***
No
No
(8.611)
No
No
(9.554)***
No
No
Panel C
(12.41)**
No
No
(13.08)***
No
No
(4.794)***
Yes
No
(8.352)**
Yes
No
(8.865)***
Yes
No
Panel D
(12.00)***
Yes
No
(12.48)***
Yes
No
8.705
(2.840)***
6.424
(5.506)
12.57
(5.416)**
19.15
(8.112)**
18.77
(8.091)**
6.119
(2.829)**
10.44
(5.229)**
13.04
(5.214)**
18.88
(7.718)**
18.22
(7.667)**
75.90
(7.799)***
65.33
(14.95)***
90.43
(16.22)***
96.26
(23.22)***
97.38
(23.76)***
70.11
(7.539)***
73.17
(14.89)***
89.86
(15.74)***
100.6
(23.11)***
101.8
(23.40)***
14.61
6.660
24.11
24.20
33.74
25.97
18.80
30.26
32.23
33.71
(4.619)***
(8.520)
(9.359)**
(16.00)**
(4.677)***
(8.169)**
(8.675)***
(12.27)**
(11.75)*** (12.26)***
Territorial d.
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Controls
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Note: (1)The table reports 2SLS estimates of the effect of partisan alignment on intergovernmental transfers); (2) robust standard errors in parentheses, ***
p<0.01, ** p<0.05, * p<0.1; (3) SE clustered by municipality, (4) Alignment(.) is a binary variable equal to 1 if the municipality is aligned with the upper tier; (5)
no interactions of the polynomials with the eligibility indicator; (6) regressions for central and regional transfers are on a sample of 3,657 observations (with no
controls) and 3,477 (with control variables) while regressions for upper-local transfers are on a sample of 3,215 observations (with no controls) and 3,208 (with
control variables); (7) panel A and C do not contain neither time nor territorial effects, while panel B and D contain both.
25
Table 6: Intergovernmental transfers and partisan alignment (reduced form estimates). Heterogeneous effects
Municipality
type
(1)
(2)
(3)
(4)
Small
Big
High debt
Low debt
(5)
(6)
High
Low
unemployment unemployment
(7)
(8)
(9)
(10)
(11)
(12)
Alligned 3
levels
Not alligned
3 levels
Right-wing
grantor
Left-wing
grantor
Majority
grantor
Coalition
grantor
PANEL 1
Central
D(C)
Observations
R-squared
Polynomial d
% Aligned
municipalities
8.038
(6.155)
10.55
(4.742)**
20.32
(7.178)***
5.153
(5.422)
6.538
(5.642)
15.06
(6.449)**
5.350
(5.956)
14.08
(7.074)**
--
--
--
--
1,949
0.298
3
42%
1,445
0.208
3
46%
1,210
0.245
3
46%
2,184
0.248
3
43%
1,486
0.194
3
44%
1,908
0.286
3
44%
2,042
0.255
3
38%
1,628
0.229
3
22%
--
--
--
--
PANEL 2
Regional
D(R)
Observations
R-squared
Polynomial d
% Aligned
municipalities
77.68
(15.11)***
35.97
(9.900)***
56.12
(15.50)***
59.35
(13.62)***
58.44
(14.10)***
56.27
(14.15)***
83.06
(14.49)***
69.57
(13.45)***
86.78
(17.62)***
36.29
(12.58)***
76.16
(17.13)***
33.65
(40.66)
2,160
0.143
3
57%
1,497
0.193
3
55%
1,364
0.151
3
55%
2,293
0.138
3
57%
1,687
0.157
3
54%
1,970
0.108
3
58%
1,793
0.126
3
43%
1,628
0.091
3
37%
1,690
0.086
3
57%
1,967
0.145
2
55%
1,181
0.110
2
63%
554
0.099
2
36%
PANEL 3
Upper-local
D(UL)
Observations
R-squared
Polynomial d
% Aligned
municipalities
22.03
(6.986)***
4.840
(5.233)
27.55
(7.216)***
13.39
(7.282)*
12.95
(7.816)*
23.89
(6.809)***
29.18
(7.549)***
21.29
(8.334)**
19.37
(7.751)**
17.67
(7.100)**
17.96
(5.244)***
57.41
(29.61)*
1,928
0.331
2
62%
1,287
0.299
2
60%
1,204
0.178
2
60%
2,011
0.277
2
62%
1,486
0.207
2
62%
1,729
0.249
2
61%
1,615
0.293
2
48%
1,629
0.217
2
48%
1,394
0.212
2
67%
1,821
0.220
2
57%
2,932
0.195
2
62%
283
0.308
2
52%
Note: (1)The table reports reduced form estimates of the effect of partisan alignment on intergovernmental transfers); (2) robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1; (3) SE clustered by municipality, (4) D(.) is an indicator
for electoral margin below the eligibility threshold; (5) no interactions of the polynomials with the eligibility indicator; (6) all regressions contain time and territorial effects; (7) dependent variable is central transfers per capita in Panel 1, regional
transfers per capita in Panel 2, and upper-local transfers per capita in Panel 3; (8) columns 9 to 12 in panel 1 contain no observations because the year when the central government was left-wing, it held a majority, while the year when it was rightwing it formed a coaliton. Thus, we cannot distinguish between the two factors.
26
Table 7: Discontinuity in other covariates (2SLS estimates)
Central
Alignment(C)
Regional
Alignment (R)
Upper-local
Alignment (UL)
Territorial d.
Controls
(1)
(2)
Panel A
(3)
(5)
(6)
Panel B
(7)
-231.2
(158.9)
-9.35e-05
(0.00187)
0.00101
(0.00975)
-163.6
(162.2)
-0.000987
(0.00172)
-0.00135
(0.00976)
-187.6
(174.6)
-0.00391
(0.00084)
-0.00395
(0.00900)
-187.3
(174.5)
-0.00257
(0.00164)
0.000523
(0.00883)
-432.4
(116.2)
No
No
-0.00569
(0.00017)
No
No
-0.0120
(0.0104)
No
No
-229.8
(201.9)
Yes
No
-0.00204
(0.00170)
Yes
No
-0.00907
(0.0104)
Yes
No
Note: (1)The table reports 2SLS estimates of the effect of partisan alignment on several covariates; (2) robust standard errors in
parentheses, ***p<0.01, ** p<0.05, * p<0.1; (3) SE clustered by municipality, (4) Alignment(.) is a binary variable equal to 1 if
the municipality is aligned with the upper tier; (5) no interactions of the polynomials with the eligibility indicator; (6) dependent
variable: for columns 1 and 5, population density, for columns 2 and 6 unemployment level, for columns 3 and 7, debt burden, for
columns 4 and 8, level of studies
0
.2
Alignment Central-Local
.4
.6
.8
1
Figure 1
-.5
0
Electoral margin
Note: bin window=5 percent
27
.5
0
Alignment Regional-Local
.2
.4
.6
.8
1
Figure 2
-.5
0
Electoral margin
.5
Note: bin window=5 percent
0
Alignment Upper Local-Local
.2
.4
.6
.8
1
Figure 3
-.5
0
Electoral margin
Note: bin window=5 percent
28
.5
0
20
Central transfers
40
60
80
Figure 4
-.5
0
Electoral margin
.5
Note: bin window=5 percent
50
Regional transfers
100
150
200
Figure 5
-.5
0
Electoral margin
Note: bin window=5 percent
29
.5
40
60
Upper-local transfers
80
100
120
140
Figure 6
-.5
0
Electoral margin
.5
Note: bin window=5 percent
Figure 7
1.5
Frequency
.5
1
0
0
Frequency
.5
1
1.5
Figure: Histograms of the margin
-.5
0
.5
Margin Central gov't party
1
-1
-.5
0
.5
Margin Upper-local gov't party
1
-1
0
Frequency
.5
1
1.5
-1
Note: bin=5 percent
30
-.5
0
.5
Margin State gov't party
1