Data
The data used for the investigation of political considerations in the allocation of funding from the state to municipalities combine electoral results (at both the state and local government level) with budget information at the municipal level for the period 2003-2010. Three parliamentary elections (2004, 2007 and 2009) and two local elections (2006 and 2010) were held during this period. These data are supplemented by local authority fiscal data, outlining municipality revenues and their breakdown into own revenues, grants and loans.
National and local elections
Local elections are held exactly on the same day of the year by all municipalities, defining a clear electoral period for all candidates. The local and parliamentary elections’ data setFootnote 3 used in our analysis reports the political affiliation of the winners in the relevant elections. The data on mayors’ affiliation predominantly cover the most populous municipalities. However, our sample still accounts for the majority of the population and government transfers.
For example, in 2003, the 199 municipalities with affiliation information account for 7.17 million citizens (about two-thirds of the total population of Greece at that time) and correspond to more than two-thirds of the total local budget of all municipalities.Footnote 4 Similar are the sample sizes for the rest of the years in our data. Thus, municipalities with no available data on affiliation are omitted from the remaining analysis.
Figure 1 shows the electoral timeline and the number of aligned and non-aligned mayors with the national government during the period 2003–2010. In the parliamentary elections of 2004 and 2009, the opposition party won and the government changed during the respective calendar year; since the focus of this study is the local budget that is approved in the parliament at the end of each calendar year, we consider that the budget follows the affiliation of the incumbent government at the end of each last calendar year and the beginning of each current year (i.e. PASOK (henceforth Social Democrats) for 2004 and ND (henceforth Conservatives) for 2009). For the remaining years, the active incumbent party is considered the full controller of the government budget each year. Consequently, in the period between 2005 and 2009 (blue part of the timeline), Conservatives is considered the incumbent party and therefore mayors originating or supported by Conservatives are consider aligned (blue bar). In the same period, non-aligned mayors supported either by Social Democrats (green (dashed) part of the two-coloured bar) or any other smaller opposition party (yellow (light and striped) part of the two-coloured bar). Accordingly, for the years 2003, 2004 and 2010 when Social Democrats was governing (green part of the timeline), aligned mayors were those originating or supported by Social Democrats (green (dashed) colour bar) and non-aligned, those supported by either Conservatives (blue part of the two-coloured bar) or any other small opposition party (yellow (light and striped) part of the two-coloured bar). As can be seen below, the variables of interest will be based on the data above and will capture the effect of political alignment and the electoral business cycle on municipality funding. We apply a fixed-effects econometric model to neutralize the effect of unobserved time-invariant differences between municipalities and focus on the impact of mayors’ political affiliation on the municipality budget at two different instances:
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(a)
when a municipality switches from aligned to non-aligned and vice versa due to a change in the national government
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(b)
when a municipality switches from aligned to non-aligned and vice versa (e.g. change of mayor), whilst the national government remained the same.
Municipality finances
The local budget data setFootnote 5 contains analytical information on the revenues (regular and extraordinary) of all municipalities, annually for the period 2003–2010. We group these subcategories into three principal revenue categories which, together with total revenues, are the dependent variables of the analysis: grants, own revenues and loans.Footnote 6 In Fig. 2, we show the annual data of these three revenue groups together with the total annual revenues (in billion €) of all affiliated (pooled) municipalities. There are eight actual data points (one for each year) that are connected with a line to highlight the overall trend. The data are also projected to the electoral time line which is also approximating the dates of the parliamentary and local elections. At first glance, we can observe that government grants are on average the principal source of municipality revenues, reaching in 2009 about 2.52 billion € which corresponds to the 59.8% of the total budget.
The intergovernmental grants to municipalities involve transfers (regular or extraordinary) for operational and investment costs. The majority of this funding comes from the KAP based on a formula and several distribution criteria.Footnote 7 The final formula is decided annually by the Ministers of Internal Affairs, Finance (and Economy if funding is intended for investment) after suggestions from the union of local government representatives (K.E.D.K.E.). Similarly, but at a smaller scale, municipal loans (5.6% of the total) are an additional source of funding that is dependent on central budget and decision making. Laws 2503/1997 and 3463/2006 allow municipalities to independentlyFootnote 8 apply and obtain a loan from a national financial institution by using part of KAP or other special grants assigned to their budget for its repayment or guarantee.
On the other hand, ‘own revenues’ is a more autonomous source of income for the municipalities. They are mostly derived from user fees, charges and taxes, which have been established and defined by the central government, following specific conditions on their level and increases. Local authorities are fully responsible for their collection and therefore can enjoy some degree of freedom. Own revenues is the mechanism that allows mayors to take initiatives and acquire additional funds to either replace reduced grants or to meet municipal needs without (to some extent) the central government’s approval. In contrast with government grants and loans, increasing own revenues could bear political costs for local authorities if they are to come by raising additional taxes, fees and penalties.
Method and model
Given the large differences in municipality size (μ = 10691.37, S.D. = 30522.77), the data on local revenues are highly skewed towards larger local authorities. In order to correct for skewness towards larger municipalities, we attempt two basic transformations on the dependent variables (total revenues, grants, loans and own revenues); we analyse either their natural logarithm (log_Total, log_Grants, log_RevOwn and log_Debt), or their ratio to total revenues (Grants Dependency, Revenue Autonomy and Debt Dependency).Footnote 9
Whilst the logarithmic transformation is a standard corrective approach, commonly used in similar studies (e.g. Rodríguez-Pose et al. (2016b)), the ratio to the total has only been used to approximate fiscal decentralization (Psycharis et al. 2016). Here, total revenues are used to normalize each variable under investigation (e.g. own revenues) in order to perform a between-municipalities comparison (aligned vs. non-aligned), as well as providing evidence of municipality dependency on specific types of income (grants, own, loans). Following Psycharis et al. (2016), the ratio of own revenues to the total is named Revenue Autonomy to signal the degree to which municipality finances are independent of central government decision making. Accordingly, the ratios of government grants and loans to the total revenues are called Grants Dependency and Debt Dependency to reflect how dependent local government finances are on revenues that are not within their control. Such a normalization is superior to per-capita transformations since it accounts not only for several within-municipality heterogeneity (e.g. population, geographical characteristics, etc.) but also for intertemporal effects or shocks that could disproportionately affect municipalities (e.g. financial crisis, political shocks, Olympic Games, etc.).
Under the electoral politics prism in Greece, the main hypothesis is that because of their capacity to increase the effectiveness of vote-buying strategies, aligned municipalities enjoy preferential treatment from the government with respect to financing. It is expected that this favourable treatment will be more intense in the run-up to elections due to vote-seeking behaviours. In connection with this, it is in the interest of the incumbent party in central government to support aligned mayors in their bid to be re-elected. The fixed-effect specification on our panel data allows us to investigate the effect of political changes (at local or at national level) on the budget of municipalities (i.e. within municipalities’ effect across time). Our main hypothesis can be sub-categorized as follows (for both transformations τ: log or ratio to total):
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A.
Municipalities receive more grants when mayors are politically aligned to the central government;
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B.
Municipalities receive more loans when mayors are politically aligned to the central government;
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C.
Municipalities raise equal or less own revenues when mayors are politically aligned to the central government;
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D.
If all the above hypotheses hold, then total revenues will be significantly higher when municipalities are aligned.
As a result, the dependent variables will be analysed in two main dimensions, namely the municipalities’ political alignment and time (year). The political alignment will be captured by variable:
In order to analyse the time dimension, two new variables are generated as follows:
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pre_parl: a dummy variable indicating the period prior to parliamentary elections. It takes value 1 for the years 2003 and 2007 and 0 for the rest.
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pre_local: a dummy variable accounting for the period before local elections held in 2006. It takes value 1 for this year and 0 for the rest.
Since the parliamentary elections were held during the first quarter of 2004 (7 March) and the second half of 2007 (16 September) (Fig. 2), it was considered appropriate to use 2003 and 2007 as the pre-election years. Assuming that the budgets are determined at the beginning of the year, an incumbent government could not expect to significantly impact the election results by pork-barrelling in 3 months (as is the case for the 2004 national election), whilst this would be possible in 9 months (as in the case of the 2007 election). In addition, pre_parl does not account for the 2009 parliamentary elections (4 October). This is because these elections were not planned (next ones expected to be in 2011) and were called for in September 2009 and with the national economy about to enter its long-lasting debt crisis. As a result, even if pork-barrelling was an option, the incumbent party would not have the time to target funding to specific municipalities. In a similar vein, 2010 has been excluded from pre_local. During this year, the country was already facing the financial crisis which had a significant impact on the level of government transfers to municipalities (Fig. 2). As a result, funding for pork barrel politics would be expected to be significantly diminished. Two robustness checks are being performed (supplementary material SM2 and SM4) in order to test these two assumptions. They largely confirm the results and provide some interesting findings on the 2008 crisis impact on distributive politics in the run-up to local elections (see Results section).
The variables of interest are the revenues of aligned municipalities during the pre-electoral years. For this reason, the following two interactions are examined:
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aligned_pre_parl: a dummy variable taking value 1 if both aligned and pre_parl are equal to 1, and 0 otherwise.
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aligned_pre_local: a dummy variable taking value 1 if both aligned and pre_local are equal to 1, and 0 otherwise.
A panel, fixed-effects econometric model is used to uncover the variation within municipalities across time whilst accounting for unobserved heterogeneity.Footnote 10 The fixed effect controls for all time-invariant characteristics of municipalities. Consequently, the coefficients cannot be biased due to omitted time-stable characteristics or measurement issues. We also use regionally clustered robust standard errors to allow for intragroup correlation at the level of prefecture (the observations are independent across prefectures but not necessarily within prefectures), a model specification which minimizes the problems of heteroscedasticity and autocorrelation usually observed in panel data sets.
The main independent variables are complemented by controls for the following time-variant characteristics: (a) gover, a dummy variable to control whether different political parties have followed different policies with regards to local authority financing (i.e. focus on own revenues vs focus on grants) when they were in power; (b) gdp_cap, a continuous variable indicating the GDP/capita of the prefectureFootnote 11 in which a municipality belongs. This variable aims to control for the efficiency vs equity nexus on the distribution of public resources. Considering GDP/capita as a proxy for more (or less) economically successful areas, this variable could indicate whether government grants are directed to more efficient areas or places with greater need; (c) conservative_party and (d) other_party, two dummies indicating the specific affiliation of the mayor, using social_democrats as a reference group; (e) yr2004, (f) yr2005, (g) yr2009 and (h) yr2010, four single-year dummies controlling for the corresponding year and using yr2008 as reference group (variables pre_parl and pre_local already account for years 2003, 2006 and 2007). 2008 is selected as a reference year since there was not any substantial political (e.g. elections) or economic (e.g. crisis, Olympic Games) shock taking place. For the same reasons, 2005 could also be used as a reference group (see supplementary material SM1 for robustness check).
Equation (1) describes the main empirical model (including interactions) of our analysis:
$$\begin{aligned} {\text{Rev}}_{it} & = \beta_{1} {\text{aligned}}_{it} + \beta_{2} {\text{pre}}\_{\text{parl}}_{it} + \beta_{3} {\text{aligned}}_{it} * {\text{pre}}\_{\text{parl}}_{it} + \beta_{4} {\text{pre}}\_{\text{local}}_{it} \\ & \quad + \beta_{5} {\text{aligned}}_{it} * {\text{pre}}\_{\text{local}}_{it} + \beta_{6} {\text{gover}}_{t} + \beta_{7} {\text{gdp}}\_{\text{cap}}_{it} \\ & \quad + \beta_{8} {\text{liberal}}\_{\text{party}}_{it} + \beta_{9} {\text{other}}\_{\text{party}}_{it} + \beta_{10} {\text{yr}}2004_{t} + \beta_{11} {\text{yr}}2005_{t} \\ & \quad + \beta_{12} {\text{yr}}2009_{t} + \beta_{13} {\text{yr}}2010_{t} + \alpha_{i} + \varepsilon_{it} \\ \end{aligned}$$
(1)
where
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Revit is the dependent variable (log_Total, log_Grants, log_OwnRev, log_Loans, Grants Dependency, Revenue Autonomy, or Debt Dependency), where i = municipality and t = time.
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β(1–13) are the coefficients of the explanatory and control variables
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αi (i = 1….n) is the unknown intercept for each municipality
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εit is the error term