fiscal imbalance and scal performance of local governments: … · 2016. 1. 7. · fiscal imbalance...
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Fiscal imbalance and fiscal performance of local governments:empirical evidence from Italian municipalities
Giuseppe Di Liddoa, Ernesto Longobardib, Francesco Porcellic
aUniversity of Salento, Department of Economics, Italy;University of Bari, DISAG, Italy.e-mail: [email protected]
bUniversity of Bari, Depertment of Economics and Mathematical Methods, Italy.e-mail: [email protected]
cCentre for Competitive Advantage in the Global Economy - University of Warwick, UK.e-mail: [email protected]
Abstract
Recent empirical research (Eyraud and Lusinyan 2013) based on national data suggests thatthe combination of vertical and horizontal imbalances is particularly damaging to fiscal out-comes. In particular fiscal discipline is strengthened as the sub-national governments’ relianceon transfers diminishes.
This paper provides a theoretical framework to describe the interaction between the verticaland the horizontal fiscal imbalances in determining fiscal behaviour of local jurisdictions.
Furthermore, we test whether the financing structure of sub-national governments affectsfiscal performance using different indices of vertical and horizontal fiscal imbalance. The empiricalanalysis is conducted using a panel data on a large sample of Italian municipalities between years2002-2010.
Our results suggest that the horizontal fiscal imbalance has a positive direct effect on taxand fees burden, that is, “poorest” jurisdictions (in terms of fiscal capacity) exert a greater fiscaleffort. On the other hand, the horizontal fiscal imbalance also presents an indirect effect, thatis, it magnifies the negative effect of the vertical fiscal imbalance on the fiscal effort of localgovernments.
Keywords: Fiscal imbalance; decentralization; municipal equalization.JEL Classification: D72 H77
1. Introduction
The focus of this paper is on the two main forms of fiscal imbalances discussed in the literatureon fiscal federalism. Vertical Fiscal Imbalance (VFI), i.e. the difference between sub-nationalgovernments’ expenditures and sub-national governments’ own fiscal revenues, and HorizontalFiscal Imbalances (HFI), i.e. the difference between sub-national revenue-raising capacity.
VFI is due to fact that usually a portion of local government’s expenditure is financed byintergovernmental grants rather than through local taxes. HFI are due to the fact that richestjurisdictions are characterized by a larger amount of local tax bases that others, hence, exertingthe same fiscal effort, they have the possibility to spend more than poor jurisdictions (Martinez-Vazquez et al. 2006).
Large VFI may relax fiscal discipline. Although some degree of mismatch between sub-national own revenue and expenditure is inevitable and may even be desirable, large gaps present
Preprint submitted to no journals May 14, 2015
risks. A common view in the normative literature is that a high reliance on intergovernmentaltransfers or borrowing “softens” the budget constraint of sub-national governments, reducingfiscal effort.
HFI result in differences in net fiscal benefits, for this reason equalization matters not merelyof horizontal equity but it also indirectly influences the allocative efficiency. In fact differencesin net fiscal benefits between jurisdictions could theoretically lead to an inefficient allocation ofproductive resources (Boadway and Flatters 1982, Boadway 2004, Smart 2007).
The combined effect of HFI and VFI has not been deeply investigated in literature. Recently,the combined effect of HFI and VFI on fiscal behaviour has been tested by Eyraud and Lusinyan(2013), without providing a theoretical model on the interaction between HFI and VFI. Theyprovide evidence regarding the fact that the negative impact on fiscal performance of the verticalimbalances and the horizontal fiscal imbalance strengthen each other. In particular, Eyraud andLusinyan (2013) show that VFI is more detrimental to general governments’ deficits in countrieswith high HFI (measured as income disparity).
However, even if the cross-country approach provides a valuable comparative perspective onthe VFI, it has also some limitations. In fact working with national data we need the implicitassumption that the effect the VFI is identical across sub-national governments in each country.Eyraud and Lusinyan (2013) admit the need of more accurate estimates working on sub-nationallevel data. Furthermore, they suggest to test different VFI indicators and to split own revenuesinto taxes and fees.
This paper provides a theoretical framework to describe the interaction of VFI and HFI indetermining the fiscal effort of local jurisdictions. Furthermore, we test empirically the combinedeffect of vertical and horizontal fiscal imbalance on the local tax burden and the local fees burden,using a panel data on a large sample of Italian municipalities over a nine years period between2002 and 2010.
We believe that our research is important for many reasons. First of all, as far as we couldverify, almost all the empirical literature on fiscal federalism investigates the role played by thevertical fiscal imbalances (Martinez-Vazquez et al. 2006) and only few papers have studied therole played by horizontal imbalances for both practical and theoretical reasons (Eyraud andLusinyan 2013).
Finally, while the literature on fiscal decentralisation provides many empirical and theoreticalanalysis on the relationship between the degree of VFI and the behaviour of sub-national gov-ernments (Shankar and Shah 2003, Villaverde 2006), very little is known, from the theoreticalpoint of view, on the impact that HFI may exert on the behaviour of sub-national governments.
The rest of the paper is organised as follows: section 2 and section 3 report, respectively, adetailed literature review on vertical fiscal imbalances and horizontal fiscal imbalances; section4 provides the theoretical framework which help to understand the interaction between HFI andVFI; section 5 shows the results of the empirical analysis. Finally, section 6 concludes.
2. Vertical Fiscal imbalance
In a federation, or in a decentralized administrative system, the devolution of spending re-sponsibilities has not been always followed by the devolution of tax revenues, resulting in verticalfiscal imbalances (VFI). That is, sub-national authorities can have access to transfers, and toa lesser extent, on borrowing by the central government in order to finance their expenditure(Gosh and Gosh 2008).
The main reason that justifies the presence of VFI in many countries is that the nationalgovernment is seen as the only level of government capable of addressing national goals of redis-tribution (Persson and Tabellini 1996, Boadway 2005), correcting equity and efficiency distor-
2
tions (Boadway, 2004), insuring regions against shocks (Lockwood 1999) and facilitating equaltreatment in the public sector (Boadway 1998).
The systematic presence of VFI and grants in a federal system has stimulated the academicinterest in investigations about economic performance of countries suffering from VFI and theliterature about VFI is increased over time.
Among others, Jin and Zou (2002), Borge and Ratts�(2003) and Boetti et al. (2012) (forthe Italian case) provide theoretical foundations and empirical evidence about the importance ofVFI in determining the performance of local and national governments.
Apart from the redistributive reasons, the presence of a large VFI: undermines the auton-omy and vitality of decentralized decision-making (Oates 1993); adversely impacts the sub-national government accountability (Bird 2000, 2003) and common pool problems (Weingast etal. 1981); induces the flypaper effect (Gramlich 1977, Fisher 1982); generates “fiscal illusion”, aphenomenon which arises when the link between taxes and benefits is distorted and voters areless likely to sanction overspending politicians (Rodden et al. 2003).
Furthermore, the VFI affects fiscal performance because it leads to the problem of the softbudget constraint. In fact, sub-national governments with high VFI do not have sufficient taxand borrowing authority to cope with idiosyncratic shocks (Von Hagen and Eichengreen 1996)and they may enter into a fiscal crisis (be unable to pay wages or default on loans) when facedwith adverse shocks. As they may claim that they are not responsible, the pressures from voters,civil servants, and creditors will likely be directed at the central government, which will have nochoice but to bail them out. Anticipating this, sub-national governments have an incentive toengage in riskier fiscal policies (Eyraud and Lusinyan 2013). As a result, since transfer-dependentlocal governments face weak incentives to be fiscally responsible, the VFI affects negatively thefiscal performance (Rodden et al. 2003).
Empirical literature provides many tests on the negative relation between vertical imbalancesand fiscal performance, i.e. the existence of the soft budget constraint problem. Rodden (2002)provides evidence that higher reliance on intergovernmental transfers worsens the general gov-ernment’s overall balance. Rodden et al. (2003) show that transfer dependency is associated tolarger fiscal deficits, the negative impact being larger at high levels of decentralization. Jin andZou (2002) find that transfers increase the size of the government at the sub-national, national,and general government levels. Finally, according to De Mello (2007), large VFI could lead tohigher deficits.
Table 1 shows some of the most common measures of VFI (Sharma 2012) that can be appliedto the local level (to the ith local jurisdiction instead of the national aggregate). The followingempirical analysis will be based on the measures of VFI listed in table 1.
Table 1: Common measures of VFI at local level Sharma (2012)
Measuring VFI
V FI1 =Total grants received
Total expenditure
V FI2 = 1−Total own source revenues
Total expenditure
V FI3 =Grants + Tax Sharing
Own revenues
3
3. Horizontal Fiscal imbalance
In general, within each sub-national level of government there are always some jurisdictionsthat are richer than others. The resulting difference in the fiscal capacities (FC) of governmentsat the same level is called horizontal fiscal imbalance (HFI). If resources are not equalized, thepoorest jurisdictions should exert an higher fiscal effort (higher tax rates) in order to reach alevel of expenditures comparable to the richest jurisdictions.
Measuring HFI is not straightforward since it is based on the concept of “fiscal capacity” andthe bast way to measure it. There is a general agreement between scholars and politicians thatthe data series used for measuring capacity should have the following characteristics (Dafflon2012):
- precise and stable over a range of several years;
- not susceptible to manipulation by decision-makers;
- easily verifiable by all government units and parties involved in the equalization process.
It follows that there are two common ways of measuring the fiscal capacity of governmentunits. One is based on macroeconomic indicators, such as the GDP, calculated per governmentunit and per capita or average incomes in jurisdictions if GDP measures are not available.1 Theother is to use the representative tax system (RTS) for an approximation of taxable capacity(Aronson and Hilley 1986).
The RTS may be defined as a hypothetical tax system that is representative or typical of allthe taxes actually levied by sub-national governments of a country. By other words it consists inthe calculations of the per capita tax amounts that jurisdictions could raise if each jurisdictionimposed taxes at the standard tax rate, that is, in the absence of fiscal effort.
The macro indicators present a theoretical limit. They involve some macro indicators relatedto incomes or local GDP as proxies for the fiscal capacity but in many cases this could leadto a biased measure of real revenue-raising capacity. For example, if a region is a significanttourist attraction place, that region could collect significant amounts of revenues from tourists(sales taxes, hotel taxes etc.). This revenues are not captured by indicators like the averagejurisdictional income.
On the other hand, the macro measures would be simpler or more transparent to applyin econometric estimations. The statistic procedure to calculate macro measures is simplercompared to the RTS approach since it needs less data. Furthermore, in many cases there is astrong correlation between the macro measures and the fiscal capacity computed by means ofthe RTS (Shankar and Shah 2003).
Different purposes leads to different measures fiscal capacity (RTS, GDP, income etc.). Onceobtained the fiscal capacity’s measure it is possible to evaluate the HFI using common inequalityindices.
The most frequent global measures, i.e. relative to the entire country, of the degree of HFIused in literature are the usual inequality or variability indices (between local jurisdictions) ofthe variable chose as proxy of the fiscal capacity (Shankar and Shah 2003).
4. Interaction between HFI and VFI in determining jurisdictional tax effort
In general there is a lack of empirical tests on the combined impact of the HFI and the VFIon sub-national governments’ fiscal performance.
1See, for example, Eyraud and Lusinyan (2013).
4
To the best of our knowledge, the most complete empirical study about the combined impactof VFI and HFI on fiscal performance is provided by Eyraud and Lusinyan (2013). They adopta cross-country approach using panel data, using aggregate data, in contrast to the prolific case-study literature on VFI. They use several macro indicators of fiscal capacity, such as income level,income per capita and population associated to different measures of HFI (variance, coefficientof variation, min-max ratio, max-average ratio).
The results of the empirical analysis of Eyraud and Lusinyan (2013) suggest that VFIs andHFIs may interact with each other, and their combination could be particularly damaging tofiscal performance, measured by the primary balance of the general government as a share ofGDP.
However, Eyraud and Lusinyan (2013) do not conduct empirical analyses on the effect of HFIon the fiscal effort (local tax burden) even if the positive effect of equalizing transfers on localtax rates (Buettner 2006, Snoddon 2004) provides indirect evidence about the negative effect offiscal disparities on tax effort if not completely equalized. Furthermore, irrespective of whetherexplicitly labelled “fiscal equalization” or embedded in a system of revenue sharing, the commoncharacteristic is that transfers are inversely related to the tax base or some corresponding measureof “fiscal capacity”. As a consequence, those schemes will tend to compensate jurisdictions forthe adverse impact of higher taxing efforts on the tax base (Buettner 2006).
Standard theoretical models of tax competition argue that in a decentralized setting the mo-bility of the tax base will tend to increase the marginal cost of raising public funds. Redistributivetransfers aim to decrease the marginal cost of raising public funds (Bucovetsky and Smart 2006).
Some empirical studies provides ambiguous evidence about the incentive effect in raisingrevenues due to fiscal equalization. Snoddon (2004) finds support for incentive effects of fiscalequalization. Dahlby and Warren (2003) find some limited support for an incentive effect ontaxing decisions. Buettner (2006) finds evidence about the fact that the marginal contributionrate of equalizing transfers exerts a significantly positive impact on the local tax rate.
Switching the focus from equalization to fiscal capacities’ disparities, we expect that fiscaldisparities, net of the equalizing transfers, exert a negative effect on local tax burden. Castelset al. (2004) confirm this theory. They find that negative shocks in fiscal capacities of somemunicipalities (increased inequality without increasing equalization) are internalized through anincrease in tax effort.
On the other hand, equalizing transfers, which aim to reduce the HFI enforce the negativeeffect due to the VFI since they increase the total amount of grants in the poorest jurisdictions,increasing the transfer dependence of local jurisdictions which leads to the problem of the softbudget constraint.
Consequently, we expect that HFI enforces the negative impact of the VFI on fiscal effortsince it increases the transfer dependence. Furthermore HFI has a negative effect on fiscal effort,this negative effect should be mitigated by transfers.
To better understand the problem we will present a simple theoretical model which explainsthe interaction between the HFI and the VFI in determining the tax effort.
4.0.1. HFI and fiscal effort: a theoretical model
The negative impact of fiscal disparities on fiscal effort could be described by means of asimple theoretical model.
Consider a decentralized economy divided into two districts or jurisdictions: one denoted byR, and the other denoted by P . Each district has a continuum of individuals and the populationsize is the same for both districts and normalized to one NP = NR = 1.
For simplicity, we assume that income is the proxy of the tax base present in the localsystem (macro measure of fiscal capacity). The two jurisdictions are characterized by uniform
5
distribution of incomes and yi, with i ∈ (P,R), indicates the average (and median) income. Thatis, each voter in jurisdiction R has income yR and each voter in jurisdiction P has income yP .We assume that yR > y > yP , where yR = y + ∆
2 and yR = y − ∆2 , y is the average income in
the society. That is, we are assuming the presence of horizontal fiscal imbalance due to differenttax bases in the two jurisdictions. Note that the value assumed by ∆ doesn’t influence the totalamount of income in the national territory.
We also assume the presence of vertical fiscal imbalance and the existence of a vertical systemof intergovernmental transfers.
In particular we assume the presence of equalizing transfers T e = hτ̄∆, that aim to reducethe existence of disparities in fiscal capacity ∆ ∈ [0, y]. The parameter τ̄ is the standard taxrate, while h is the degree of equalization decided exogenously by the CG. When h = 1 there isfull equalization.
We also assume the presence of generic transfers T v related to other purposes, such as, fillingthe VFI, financing specific local investments or other special purposes local expenditures. Thetransfers’ amount and the tax rate t that finance grants are set by the central government (CG).For simplicity we assume that transfers must be used exclusively to finance the local public good.
Each jurisdiction provides a certain amount of the local public goods gi, with i ∈ {P,R}.The amount of the public good is given by the sum of transfers and the autonomous componentof revenues. That is, the product between the local tax base yi and t the local tax rate τi (forsimplicity we are assuming that local public goods are not financed by fees). Furthermore, weassume that the tax autonomy of local jurisdiction is limited, i.e. 0 ≤ τi ≤ τmax.
We suppose that the cost of the local public goods are the same in both jurisdictions andthat the cost is normalized to one.
For simplicity we assume that individuals in both jurisdictions are characterized by quasi-linear utility functions. That is, representable by utility functions that are linear in private goodsand strictly concave in the public good.
Quasi-linearity has strong implications. It implies a zero income elasticity of demand for pub-lic goods, that is, the income distribution doesn’t affect the aggregate demand of the local publicgoods. By other words, we are separating the allocation problem from the income distribution(Bergstrom and Cornes 1983).
The utility function of jurisdiction R is:
UR =√gR + yR − τRyR − t yR, (1)
that is,
UR =√gR +
(y +
∆
2
)(1− τR − t). (2)
The budget constraint of jurisdiction R is:
gR = τR
(y +
∆
2
)+ T v, (3)
Substituting equation (3) into equation (2) we obtain:
UR =
√τR
(y +
∆
2
)+ T v +
(y +
∆
2
)(1− τR − t). (4)
The fiscal effort, given by the tax rate τ∗R, exerted by jurisdiction R will be:
τ∗R = arg maxτR
(√τR
(y +
∆
2
)+ T v +
(y +
∆
2
)(1− τR − t).
)(5)
6
That is:
τ∗R =1− 4T v
4(y + ∆
2
) . (6)
It is apparent from equation (6) that τ∗R is greater than zero only if T v is smaller than athreshold value T̃ = 1
4 . If T v > T̃ , then jurisdiction R will finance the local public good withoutown source revenues. Furthermore, the local tax rate τ∗R, i.e. the fiscal effort of jurisdiction R,is decreasing in transfers T v.
The utility function of jurisdiction P is:
UP =√gP + yP (1− τP − t), (7)
that is,
UP =√gP +
(y − ∆
2
)(1− τP − t), (8)
The budget constraint of jurisdiction P is:
gP = τP
(y − ∆
2
)+ T v + hτ̄∆, (9)
where T e = hτ̄∆ is the amount of the equalizing transfer.Substituting equation (9) into equation (8) we obtain:
UP =
√τP
(y − ∆
2
)+ T v + hτ̄∆ +
(y − ∆
2
)(1− τP − t). (10)
The fiscal effort τ∗P exerted by jurisdiction P is
τ∗P = arg maxτP
√τP
(y − ∆
2
)+ T v + hτ̄∆ +
(y − ∆
2
)(1− τP − t). (11)
That is:
τ∗P =1− 4T v − 4hτ̄∆
4(y − ∆
2
) . (12)
Note that τ∗P is positive only if T v is smaller that a threshold value T̄ = 14 −hτ̄∆. If T v > T̄ ,
then jurisdiction P will finance the local public good without own source revenues.Equations (6) and (12) lead to the following proposition.
Proposition 1. In the absence of equalization, the jurisdiction with the lowest fiscal capacityexerts a greater fiscal effort, compared to the jurisdiction with the highest fiscal capacity. Thatis, τ∗P > τ∗R.
Proof. From equations (6) and (12), we know that, in the absence (h = 0) of fiscal equalization,τ∗P > τ∗R when
1− 4T v
4(y − ∆
2
) > 1− 4T v
4(y + ∆
2
) , (13)
that is satisfied for any positive value of ∆.
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Proposition 1 shows that disadvantaged administrators (in terms of tax bases availability)must exert a greater tax effort in order to maximize voters’ utility. As a consequence, adminis-trators of jurisdictions with small tax bases face greatest political costs (Kenny and Winer 2006),in terms of electoral support, of taxation.
It follows that equalization is not just a matter of equity between jurisdictions, equaliza-tion transfers also improve the yardstick competition between local administrators, eliminatingdisparities on available resources (Borge 2011).
In the presence of equalization transfers, the effect of fiscal disparities ∆ on the fiscal effortτ∗P of the poorest jurisdiction is ambiguous. In fact, the indirect effect of fiscal disparity ∆ isgiven by a relative decrease of the tax base in poorest jurisdictions; the indirect effect is givenby an increase in horizontal transfers h∆ that, in turn, leads to an increase in the VFI. Thetotal effect will depend on the degree of equalization h. In particular, equation (12) leads to thefollowing proposition.
Proposition 2. Fiscal disparities decrease the fiscal effort of poorer jurisdictions in the presenceof high equalization transfers. The amount of resources necessary to decrease the fiscal effortin jurisdictions with lower fiscal capacity decreases with the average national tax base and theamount of general purpose transfers.
Proof. From equation (12), we know that τ∗P = τ∗R when
∂τ∗P∂∆
=1− 4T v − 8hτ̄ y
2(2y −∆)2. (14)
From equation (14) it follows that:
∂τ∗P∂∆
> 0⇔ h <1− 4T v
8τ̄ y(15)
From equation 15 it is apparent that, when h is lower than a threshold value h̄ = 1−4Tv
8τ̄y , thenfiscal disparities lead to higher fiscal effort.
It follows that equalization could help in reducing the gap between tax rates in differentjurisdictions. The degree of equalization necessary to reduce fiscal effort in poorer jurisdictionsdecrease on the average national tax base and on the vertical fiscal imbalance. The intuition isthat in richest countries, characterized by a large local tax base, also poorest local jurisdictionshave more expenditure autonomy and are less dependent on equalization transfers. That is, localjurisdiction are likely to satisfy their expenditure needs independently on the inequality withinthe national territory.
The same hold when the system is characterized by high vertical fiscal imbalance, due to thepresence of high generic grants. In this case the large presence of generic grants provide enoughresources to poorest jurisdictions too and, in a certain sense, it compensate the lack of tax basein poorest jurisdiction. In cases like these, there is less need of high equalization transfers.
Given that the effect of fiscal disparities on the fiscal performance of local government de-pends on the equalization degree, it is interesting to examine when local jurisdictions exert thesame fiscal effort, choosing the same tax rate. In particular the following proposition can bestated.
Proposition 3. The degree of equalization h∗ that ensures the same fiscal effort for both juris-dictions doesn’t necessary correspond to full equalization (h∗ = 1) and it is function of the VFI(T v) and HFI (∆). In particular, h∗ decreases when T v and ∆ increase.
8
Proof. From equations (6) and (12), we know that τ∗P = τ∗R when
1− 4T v − 4hτ̄∆
4(y − ∆
2
) =1− 4T v
4(y + ∆
2
) , (16)
that is, when
h∗ =1− 4T v
2τ̄(2y + ∆). (17)
From equation 17 it comes straightforwardly that ∂h∗
∂Tv < 0 and ∂h∗
∂∆ < 0.
From equation (17), it is apparent that the degree of equalization that ensures an uniformfiscal effort between jurisdictions is decreasing in the standard tax rate and the average income.The intuition is that, the higher the standard tax rate decided by the central government, thelower will be the general fiscal effort of local jurisdictions. Furthermore, the higher the averagenational income, the higher will be the probability that local jurisdictions will satisfy theirspending needs without exerting fiscal effort and equalization. As a consequence, equalizationwill be less important in determining the local fiscal behaviour
In the following section we will test empirically the joint impact of VFI and HFI on thefiscal effort of local jurisdictions in the Italian context. Differently from Eyraud and Lusinyan(2013) we don’t use local deficits as explanatory variable. Instead, we use the tax/fees burdenas proxies of the fiscal effort of local jurisdictions. In fact, in the Italian municipal context thetax burden better indicates the fiscal behaviour of local administrators, since the local budgetsare constrained by the Internal Stability Pact and Italian municipalities must achieve a balancedbudget.
We expect to observe a positive estimated point coefficient associated to the HFI measure(direct effect of the HFI) and a negative coefficient associated to the VFI measure. In additionwe expect to observe a negative coefficient associated to the interaction between HFI and VFI(indirect effect of the HFI).
5. Empirical analysis
There is a lack of analyses on the combined effect of VFI and HFI using sub-national data.We choose to focus our analysis on the Italian municipal framework since Italy is a country whichis implementing a series of reforms concerning the decentralization of expenditure and decisionalcompetencies and the debate on the new mechanism of financing local expenditures is still open.
5.1. Description of data
We have assembled a dataset that is, at the moment, the most complete “unofficial” dataseton local public finance for Italy. We collected data on all Italian municipalities, excluding mu-nicipalities of special status regions2 over the period 2002-2010.
Table 5 in appendix shows the variables included in the econometric model (after the elimi-nation of outliers and incoherent data) and a list of summary statistics.
Data are grouped in seven categories. Category Y contain data on municipal revenues andborrowing. Categories B and G include other indicators of municipal finance (expenditure com-position, transfers etc.). These data have been collected from the final budget accounts providedby the Italian Ministry of Interior.
2Municipalities of Trentino-Alto Adige, Valle d’Aosta, Friuli-Venezia Giulia, Sicily and Sardinia are character-ized by different rules on intergovernmental transfers, compared to ordinary regions’ municipalities.
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Category C reports data on average municipal incomes from official tax returns, providedby the Ministry of Economy and Finance. Category D includes variables about the cadastralincome and the market values of the estate market, provided by the Agency of Territory at theMinistry of Economy and Finance.
Category E includes a set of demographic and geographic control variables provided by IS-TAT (Italian National Institute of Statistics) and category F data about electoral preferences inregional elections provided by the Ministry of Interior. We have used regional elections, insteadof municipal ones, because in latter case it is often not possible to assign a political colour toall local political movements or citizens associations. We have included both demographic andgeographic controls together with electoral variables, in order to capture local preferences ontaxation.
Other variables that provide useful informations are included in table 5 under the category“other”.
5.2. The empirical model
For estimations, we use an econometric model to test the combined impact of VFI and HFIon local governments’ tax and fees burden (computed as the percentage of local fees and taxeson average income).
The baseline econometric models relates the local tax burden and fees burden of Italianmunicipalities to a long series of explanatory variables, which include data on tax bases ofdifferent revenues and a wide set of control variables.
The econometric specification is:
dit = β′Bit+γ′Cit+δ
′Dit+η′Eit+ζ
′Fit+ν V FIit+ξ V FIit∗HFIlocit+υHFIlocit+ui+eit, (18)
where variable d is the local tax/fees burden. The matrices B, C , D, E and F represent thecorrespondent categories of variables described in table 5. The variables VFI and HFI are, inturn, indices of vertical and horizontal fiscal imbalance included in the various estimates.
Table 2 lists the measures of VFI and HFI included in the various model specifications.
Table 2: Measures of VFI and HFI
VFI measures Local HFI measures
V FI1 =Total grants received
Total expenditureHFIloc1 = Max average income − average income
V FI2 =Total grants received + tax sharing
Total expenditureHFIloc2 = Mean of average income − average income
V FI3 =Total grants received
Total revenueHFIloc3 = Median of average income − average income
V FI4 =Total grants received + tax sharing
Total revenue
Panel analyses3 have been conducted through Generalised Methods of Moments (GMM)estimation for panel data.
3For a detailed analysis of panel modelling used see, among others: Baltagi (2005), Wooldridge (2002), andRoodman (2009).
10
The use of the dynamic estimations by GMM estimator is necessary because, when workingwith data on tax revenues and tax bases, problems of endogeneity and autocorrelation are likelyto arise.
The presence of the lagged dependent variables in our regressions may give rise to autocor-relation. Furthermore, the fiscal imbalance variables can be endogenous, because causality withthe dependent variables may run in both directions. Finally, time-invariant country characteris-tics (fixed effects), such as geography and demographics, may be correlated with the explanatoryvariables.
When such econometric problems exist, the traditional panel data estimators (Pooled OLS,Fixed Effects or Least Suqares Dummy Variables (LSDV) and Random Effects) do not yieldconsistent estimates.
To cope with this eventual problems we use the Arellano - Bond Dynamic Panel GMMestimator with robust standard errors (Roodman 2009).4 In fact, the GMM dynamic panel datamethods can simultaneously deal with the problem of persistence and endogeneity. In particular,as GMM-style instruments (endogenous covariates) we use the differences of the fees/tax burdenand of the variables related to decentralization (VFI, HFI and their interaction terms).
5.3. Results
Tables 3 and 4 show the coefficient point estimates relative to equation (18) using the taxburden and the fees burden as dependent variable, respectively.
The full estimates, including the complete set of regressors are reported in appendix by tables6 and 7. Tables 6 and 7 also report the value of the Hansen J statiscs used to test the exogeneityof the included instruments.5
As we can see from table 3, all VFI measures included in the models show negative andsignificant estimated coefficients. That is, our results confirm the negative direct impact of theVFI on the local tax burden.
The interaction terms between VFI and HFI shows negative and significant estimated coef-ficients with all the measures adopted and all the possible combinations. These results suggestthe existence of a negative indirect effect on the fiscal effort due to the interaction between theVFI and the HFI. That is, we find empirical evidence that the negative impact of the VFI isgreater in municipalities characterized by a greater HFI.
These results are robust to all different measures of HFI and VFI used for the estimates.Furthermore, the estimated coefficients associated to the HFI measures are positive and signif-
icant only for the measure HFI1. That is, the existence of a positive direct effect (disadvantagedjurisdiction should increase the tax burden in order to offer a local services’ quality comparableto the advantaged ones) of the HFI on the tax burden is not robust to all specifications.
Looking at table 4, we can see that all VFI measures included in the models show no significantestimated coefficients. That is, our results suggest that the VFI doesn’t affect the fees burdendirectly.
The interaction terms between VFI and HFI shows negative and significant estimated co-efficients with all the measures adopted in all the possible combinations. It follows that thecombination of high HFI and high VFI disincentive the effort in raising fees.
these results are robust to all different measures of HFI and VFI used for the estimates.
4The estimates based on the GMM system by Blundel and Bond (1998) produce results that are qualitativelyin line with our baseline model, however we prefer to base our analysis on the GMM-DIFF estimates given thesmall time span of the dataset. To save space we provide these results on request.
5For robust GMM, the Sargan test statistic is inconsistent.
11
Tab
le3:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
tax
bu
rden
.A
rellan
o-
Bon
dD
yn
am
icP
an
elG
MM
Est
imato
r.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
LA
G1
Local
tax
burd
en
0.3
95830***
0.2
73916***
0.2
78325***
0.4
17388***
0.3
00390***
0.3
04772***
0.3
66406***
0.1
98869***
0.2
03271***
0.3
93545***
0.2
55303***
0.2
57147***
(0.0
67)
(0.0
61)
(0.0
61)
(0.0
64)
(0.0
76)
(0.0
75)
(0.0
69)
(0.0
55)
(0.0
54)
(0.0
68)
(0.0
64)
(0.0
64)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%-0
.010372**
-0.0
28380***
-0.0
27930***
(0.0
05)
(0.0
05)
(0.0
05)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.016423**
-0.0
22800***
-0.0
22249***
(0.0
08)
(0.0
08)
(0.0
08)
VF
I3-
Gra
nts
/O
wn
Revenues
%-0
.009460*
-0.0
39294***
-0.0
38896***
(0.0
05)
(0.0
05)
(0.0
05)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%-0
.018290**
-0.0
43420***
-0.0
43759***
(0.0
08)
(0.0
08)
(0.0
08)
VF
I1xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00004***
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00004***
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000*
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00003**
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00003**
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00006***
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00006***
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00006***
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00006***
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e0.0
00014***
0.0
00013**
0.0
00017***
0.0
00015***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e-0
.000022
0.0
00365
0.0
00200
0.0
00425
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e-0
.000943
0.0
01393
-0.0
00105
0.0
01169
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Obse
rvati
ons
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
Munic
ipali
ties
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
AR
(1)
test
stati
stic
-7.5
06
-10.2
7-1
0.2
8-8
.386
-10.1
2-1
0.0
8-7
.167
-9.6
32
-9.5
80
-7.3
49
-9.7
23
-9.6
05
p-v
alu
eof
AR
(1)
stati
stic
00
00
00
00
00
00
AR
(2)
test
stati
stic
0.6
99
-0.2
34
-0.2
28
0.3
57
-0.8
66
-0.8
57
1.2
23
-1.1
77
-1.1
41
0.6
27
-0.7
29
-0.7
10
p-v
alu
eof
AR
(2)
stati
stic
0.4
84
0.8
15
0.8
19
0.7
21
0.3
86
0.3
91
0.2
21
0.2
39
0.2
54
0.5
31
0.4
66
0.4
78
Hanse
nJ
stati
stic
63.8
484.7
084.2
666.9
892.2
791.7
567.1
778.9
977.6
065.6
388.7
986.8
5D
egre
es
of
freedom
for
Hanse
nst
ati
stic
73
73
73
73
73
73
73
73
73
73
73
73
p-v
alu
eof
Hanse
nJ
stati
stic
0.7
69
0.1
65
0.1
73
0.6
76
0.0
634
0.0
682
0.6
70
0.2
95
0.3
34
0.7
18
0.1
01
0.1
28
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
12
Tab
le4:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
fees
bu
rden
.A
rellan
o-
Bon
dD
yn
am
icP
an
elG
MM
Est
imato
r.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
LA
G1
Local
fees
burd
en
0.2
08170***
0.2
20444***
0.2
20721***
0.2
00950***
0.1
99821***
0.2
00281***
0.2
14666***
0.2
25462***
0.2
25884***
0.2
06891***
0.2
13706***
0.2
14118***
(0.0
74)
(0.0
77)
(0.0
77)
(0.0
72)
(0.0
72)
(0.0
72)
(0.0
76)
(0.0
77)
(0.0
77)
(0.0
74)
(0.0
73)
(0.0
73)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%0.0
02288
-0.0
03115
-0.0
02838
(0.0
04)
(0.0
05)
(0.0
05)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.002081
-0.0
06362
-0.0
06052
(0.0
07)
(0.0
08)
(0.0
08)
VF
I3-
Gra
nts
/O
wn
Revenues
%0.0
03340
-0.0
00051
0.0
00247
(0.0
04)
(0.0
06)
(0.0
06)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%0.0
00961
-0.0
01440
-0.0
01035
(0.0
07)
(0.0
08)
(0.0
08)
VF
I1xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00002*
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00002*
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00002
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00002
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00001
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00001
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00001
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00001
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e0.0
00006
0.0
00005
0.0
00008
0.0
00007
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e0.0
01597**
0.0
01441*
0.0
01666**
0.0
01442*
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e0.0
09098*
0.0
08080*
0.0
09683**
0.0
08305*
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
Obse
rvati
ons
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
Munic
ipali
ties
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
AR
(1)
test
stati
stic
-5.7
65
-6.0
80
-6.0
89
-5.9
86
-6.3
24
-6.3
20
-5.7
49
-5.8
41
-5.8
60
-5.8
88
-5.6
13
-5.6
25
p-v
alu
eof
AR
(1)
stati
stic
8.1
4e-0
91.2
0e-0
91.1
4e-0
92.1
5e-0
92.5
5e-1
02.6
1e-1
08.9
5e-0
95.1
8e-0
94.6
3e-0
93.9
1e-0
91.9
9e-0
81.8
6e-0
8A
R(2
)te
stst
ati
stic
1.2
05
1.2
98
1.2
66
0.4
94
0.9
73
0.9
43
1.6
69
1.1
29
1.1
21
0.9
67
0.4
42
0.4
23
p-v
alu
eof
AR
(2)
stati
stic
0.2
28
0.1
94
0.2
05
0.6
21
0.3
31
0.3
46
0.0
952
0.2
59
0.2
62
0.3
34
0.6
58
0.6
72
Hanse
nJ
stati
stic
64.3
862.0
561.9
261.7
260.6
460.8
467.6
059.1
558.6
464.9
957.5
957.2
2D
egre
es
of
freedom
for
Hanse
nst
ati
stic
73
73
73
73
73
73
73
73
73
73
73
73
p-v
alu
eof
Hanse
nJ
stati
stic
0.7
54
0.8
16
0.8
19
0.8
24
0.8
49
0.8
44
0.6
57
0.8
79
0.8
89
0.7
37
0.9
07
0.9
13
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
13
Furthermore, the estimated coefficients associated to the HFI measures are positive andsignificant in almost all specification. This result suggests the existence of a positive direct effectof the HFI on the fees burden. It follows that high HFI leads to an increase in fees instead oflocal taxes.
As a robustness check, we also estimate a Fixed Effect (FE) model by feasible generalized leastsquares (FGLS) estimator with robust standard errors. It follows that ui in equation (18) is theunobserved time-invariant individual effect and eit is the error term. Common interpretations fortime-invariant effects ui are innate ability for individuals or historical and institutional factorsfor countries.
Unlike the Random effects (RE) model where the unobserved ui is independent of the otherregressors, the FE model allows ui to be correlated with the regressor matrix. Strict exogeneity,however, is still required.
Tables 8 and 9 in appendix show the coefficient point estimates of the same models, obtainedusing the Fixed effect FGLS estimator. In this way we can also observe estimated coefficientsassociated to time invariant control variables. The results remain qualitatively comparable ineach specification.
6. Final remarks
This paper contributes to the existing literature about the effect of the horizontal fiscalimbalance on fiscal performance of the local government.
We provide a theoretical framework to describe the interaction of VFI and HFI in determiningthe fiscal effort of local jurisdictions.
In particular, we show that the direct effect of fiscal disparities between sub-national gov-ernments on the local fiscal effort is positive. That is, fiscal disadvantaged jurisdiction shouldexert an higher fiscal effort in order to provide local services comparable to the fiscal advantagedjurisdictions.
On the other hand, the interaction between VFI and HFI leads to a negative indirect effect inpresence of fiscal equalization. In fact, since the horizontal transfers due to the horizontal fiscalimbalance increase the total amount of transfers, they increase the VFI in some jurisdictions andnegative effect of grants is accentuated.
We also show that the amount of equalization necessary to ensure the neutrality in the localtax effort, i.e. to induce the local governments to exert the same fiscal effort, doesn’t necessarycoincide to the full equalization. On the contrary, it is function of the HFI and the amount ofnot-equalizing transfers.
Furthermore, we provide empirical evidence on the negative impact of the HFI on fiscalperformance of local government, using a panel data on a large sample of Italian municipalitiesover a nine years period between 2002 and 2010.
In particular, we estimates the combined effect of HFI and VFI on the municipal local tax andfees burden and our results suggests that the horizontal fiscal imbalance magnify the negativeeffect of the vertical fiscal imbalance on the fiscal effort of local jurisdictions.
Our results, obtained by means of panel data estimates on a large sample of Italian munic-ipalities, are in line to previous results obtained on country-based data (Eyraud and Lusinyan2013).
In order to test the generality of our results, in the further empirical studies on local data ofother developed countries are necessary. In particular, since Italian equalization grants are notformula-based, we need further analyses on municipalities characterized by a stable equalizationformula.
14
In fact, in this way econometric estimates could also account for the role of expectation onfuture equalization grants.
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17
Appendix: Tables and figures
Table 5: List of variable included in the econometric model - Years 2002-2010
Category Variable N Mean SD Min Max
Y Local fees burden (no waste) % of income 41463 1.68 1.31 0 21.89Y Local tax burden % of income 41463 3.44 1.26 0.33 20.64Y Borrowing/income % 41463 1.27 2.31 0 29.8B Administrative expenditure/total exp % 41463 40.42 9.96 0 95.74B Culture expenditure/total exp % 41463 1.98 2.02 0 33.52B Sport expenditure/total exp % 41463 1.54 1.45 0 28.16B Tourism expenditure/total exp % 41463 0.62 1.31 0 32.34B Education expenditure/total exp % 41463 10.18 4.61 0 34.76B Local police expenditure/total exp % 41463 4.6 2.98 0 42.12B Traffic man. expenditure/total exp % 41463 9.36 4.43 0 43.41B Landing expenditure/total exp % 41463 20.01 7.07 0 67.92B Social expenditure/total exp % 41463 9.76 7.31 0 68.51B Ec. planning expenditure/total exp % 41462 1.4 4.04 0 62.87B Inhabitant with main residence % 41457 82.06 5.12 40.28 96.77C Unitary estate income - Euro PC 41463 1260.93 543.51 217.56 12000.96C Unitary total income - Euro PC 41463 15359.11 3358.63 5605.7 61590.84D Commercial estate value - Euro/msq 35987 1264.41 568.91 187.66 16493.15D Residential estate value - Euro/msq 40112 1128.42 514.09 257.3 12347.88E Population 31 Dec 41463 7668.02 45913.76 59 2761477E Population 0-14 % 41461 13.55 3.11 1.32 29.39E Population over 65 % 41461 20.87 6.26 4.1 63.33E Foreingner population % 41236 4.88 3.76 0 29.41E Cancelled/Population % 41463 2.91 1.26 0 55.56E New registered/Population % 41463 3.75 1.81 0 20.35E Cohousing/population*1000 36802 0.5 2.34 0 416.39F CL % votes - regional government ballots 41460 45.06 14.65 5.14 94.39F Others % votes - regional government ballots 41460 3.72 3.75 0 55.33G TOTAL grants current exp - Euro PC 41463 254.66 158.75 1.83 1975.98G TOTAL grants cap exp - Euro PC 41463 340.26 424.81 0 5202.06
Other Capital expenditure - Euro PC 41463 453.01 476.51 0 5755.57Other Current expenditure - Euro PC 41463 755.13 231 426.25 2738.44Other Revenues Total taxes - Euro PC 41463 375.65 151.58 19.59 1299.98Other Revenues Total non taxes - Euro PC 41463 178.73 135.77 0 2410.58Other Total grants - Euro PC 41463 594.92 500.71 14.86 5565.59Other Income tax sharing with CG - Euro PC 41463 52.95 52.65 0 615.72Other Revenues Total taxes - Euro PC 41463 375.65 151.58 19.59 1299.98Other Revenues Total non taxes - Euro PC 41463 178.73 135.77 0 2410.58
18
Tab
le6:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
tax
bu
rden
.A
rell
an
o-
Bon
dD
yn
am
icP
an
elG
MM
Est
imato
r.F
ull
mod
el.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
LA
G1
Local
tax
burd
en
0.3
95830***
0.2
73916***
0.2
78325***
0.4
17388***
0.3
00390***
0.3
04772***
0.3
66406***
0.1
98869***
0.2
03271***
0.3
93545***
0.2
55303***
0.2
57147***
(0.0
67)
(0.0
61)
(0.0
61)
(0.0
64)
(0.0
76)
(0.0
75)
(0.0
69)
(0.0
55)
(0.0
54)
(0.0
68)
(0.0
64)
(0.0
64)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%-0
.010372**
-0.0
28380***
-0.0
27930***
(0.0
05)
(0.0
05)
(0.0
05)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.016423**
-0.0
22800***
-0.0
22249***
(0.0
08)
(0.0
08)
(0.0
08)
VF
I3-
Gra
nts
/O
wn
Revenues
%-0
.009460*
-0.0
39294***
-0.0
38896***
(0.0
05)
(0.0
05)
(0.0
05)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%-0
.018290**
-0.0
43420***
-0.0
43759***
(0.0
08)
(0.0
08)
(0.0
08)
VF
I1xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00004***
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00004***
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000*
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00003**
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00003**
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00006***
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00006***
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00006***
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00006***
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e0.0
00014***
0.0
00013**
0.0
00017***
0.0
00015***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e-0
.000022
0.0
00365
0.0
00200
0.0
00425
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e-0
.000943
0.0
01393
-0.0
00105
0.0
01169
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Adm
inis
trati
ve
exp
endit
ure
/to
tal
exp
%0.0
86629
-0.0
32476
-0.0
35071
0.0
84893
0.0
07660
0.0
05392
0.0
71795
-0.0
05061
-0.0
07924
0.0
44261
-0.0
08070
-0.0
08576
(0.0
98)
(0.0
50)
(0.0
50)
(0.0
97)
(0.0
65)
(0.0
64)
(0.0
81)
(0.0
44)
(0.0
45)
(0.0
63)
(0.0
49)
(0.0
49)
Cult
ure
exp
endit
ure
/to
tal
exp
%0.1
00823
0.0
01051
0.0
00794
0.0
94484
0.0
16080
0.0
16437
0.0
56877
0.0
63122
0.0
63233
0.0
57365
0.0
94003
0.1
00338
(0.1
27)
(0.0
98)
(0.0
97)
(0.1
29)
(0.1
12)
(0.1
12)
(0.1
08)
(0.0
85)
(0.0
85)
(0.0
99)
(0.0
95)
(0.0
96)
Sp
ort
exp
endit
ure
/to
tal
exp
%0.1
10455
-0.0
09597
-0.0
12045
0.1
17502
-0.0
23768
-0.0
28835
0.1
17785
-0.1
62465
-0.1
59754
0.1
15200
-0.1
44345
-0.1
47267
(0.1
67)
(0.1
29)
(0.1
28)
(0.1
68)
(0.1
51)
(0.1
50)
(0.1
55)
(0.1
13)
(0.1
13)
(0.1
39)
(0.1
25)
(0.1
26)
Touri
smexp
endit
ure
/to
tal
exp
%-0
.103594
-0.0
20746
-0.0
24779
-0.0
43866
0.0
61195
0.0
55915
-0.1
75815
-0.0
03362
-0.0
00890
-0.1
88545
0.0
06323
0.0
15569
(0.1
47)
(0.1
21)
(0.1
21)
(0.1
47)
(0.1
34)
(0.1
33)
(0.1
33)
(0.1
14)
(0.1
14)
(0.1
24)
(0.1
19)
(0.1
20)
Educati
on
exp
endit
ure
/to
tal
exp
%0.1
79442
0.0
34899
0.0
34411
0.1
81023
0.0
49788
0.0
48764
0.1
34494
0.0
28077
0.0
26821
0.1
09746
0.0
19066
0.0
17293
(0.1
14)
(0.0
70)
(0.0
70)
(0.1
13)
(0.0
87)
(0.0
87)
(0.0
99)
(0.0
61)
(0.0
61)
(0.0
81)
(0.0
68)
(0.0
69)
Local
police
exp
endit
ure
/to
tal
exp
%-0
.068839
-0.1
87322***
-0.1
91570***
-0.0
88686
-0.2
27690***
-0.2
30126***
-0.0
62075
-0.1
36577**
-0.1
39794**
-0.1
03893
-0.1
89343***
-0.1
87375***
(0.1
13)
(0.0
72)
(0.0
72)
(0.1
13)
(0.0
85)
(0.0
84)
(0.1
02)
(0.0
67)
(0.0
68)
(0.0
88)
(0.0
71)
(0.0
72)
Tra
ffic
man.
exp
endit
ure
/to
tal
exp
%0.1
15238
0.0
06236
0.0
06087
0.1
01108
0.0
31986
0.0
32294
0.1
25393
0.0
13514
0.0
12582
0.0
57903
-0.0
28726
-0.0
28129
(0.1
03)
(0.0
66)
(0.0
66)
(0.1
03)
(0.0
79)
(0.0
78)
(0.0
91)
(0.0
59)
(0.0
59)
(0.0
73)
(0.0
64)
(0.0
64)
Landin
gexp
endit
ure
/to
tal
exp
%0.1
03519
0.0
69137
0.0
65354
0.1
02527
0.1
09295*
0.1
06932*
0.0
74999
0.0
63960
0.0
59783
0.0
33127
0.0
51061
0.0
50242
(0.0
99)
(0.0
48)
(0.0
48)
(0.0
98)
(0.0
63)
(0.0
62)
(0.0
84)
(0.0
41)
(0.0
41)
(0.0
65)
(0.0
45)
(0.0
46)
Socia
lexp
endit
ure
/to
tal
exp
%0.0
50658
0.0
42022
0.0
38941
0.0
51016
0.1
07792
0.1
05854
0.0
27629
0.0
27389
0.0
25530
-0.0
01598
0.0
53010
0.0
54320
(0.1
02)
(0.0
55)
(0.0
55)
(0.1
02)
(0.0
72)
(0.0
71)
(0.0
85)
(0.0
49)
(0.0
49)
(0.0
68)
(0.0
53)
(0.0
54)
Ec.
pla
nnin
gexp
endit
ure
/to
tal
exp
%0.2
16075*
0.2
30945**
0.2
26833**
0.1
93565*
0.2
73527**
0.2
69785**
0.1
80292*
0.1
93960**
0.1
93459**
0.1
19779
0.2
09693**
0.2
11579**
(0.1
18)
(0.0
97)
(0.0
97)
(0.1
13)
(0.1
12)
(0.1
11)
(0.1
03)
(0.0
88)
(0.0
88)
(0.0
80)
(0.0
97)
(0.0
97)
Unit
ary
est
ate
incom
e-
Euro
PC
-0.0
01921**
-0.0
00509
-0.0
00586
-0.0
01871**
-0.0
00904
-0.0
00929
-0.0
01370
-0.0
00580
-0.0
00667
-0.0
01000
-0.0
00734
-0.0
00757
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Unit
ary
tota
lin
com
e-
Euro
PC
0.0
00013
-0.0
00263
-0.0
01187
-0.0
00072
0.0
00218
0.0
01242
0.0
00093
-0.0
00196
-0.0
00506
0.0
00028
0.0
00130
0.0
00860
(0.0
00)
(0.0
01)
(0.0
04)
(0.0
00)
(0.0
01)
(0.0
05)
(0.0
00)
(0.0
01)
(0.0
04)
(0.0
00)
(0.0
01)
(0.0
04)
19
Com
merc
ial
est
ate
valu
e-
Euro
/m
sq-0
.001082*
-0.0
00257
-0.0
00244
-0.0
00993*
-0.0
00070
-0.0
00046
-0.0
00951*
-0.0
00238
-0.0
00225
-0.0
00889*
-0.0
00087
-0.0
00085
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
Resi
denti
al
est
ate
valu
e-
Euro
/m
sq0.0
00572
-0.0
00184
-0.0
00168
0.0
00557
-0.0
00298
-0.0
00299
0.0
00210
-0.0
00027
-0.0
00011
0.0
00046
-0.0
00409
-0.0
00416
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
Popula
tion
31
Dec
-0.0
00164
-0.0
00030
-0.0
00031
-0.0
00153
-0.0
00041
-0.0
00040
-0.0
00229
-0.0
00021
-0.0
00024
-0.0
00202
-0.0
00010
-0.0
00012
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
0-1
4%
0.0
32536
-0.0
06290
-0.0
07899
0.0
31859
-0.0
03179
-0.0
05515
0.0
34512
0.0
19019
0.0
16672
0.0
24746
0.0
22128
0.0
20221
(0.0
29)
(0.0
26)
(0.0
26)
(0.0
29)
(0.0
30)
(0.0
30)
(0.0
32)
(0.0
24)
(0.0
24)
(0.0
29)
(0.0
27)
(0.0
27)
Popula
tion
over
65
%-0
.055027*
-0.0
08454
-0.0
09260
-0.0
58438*
-0.0
02975
-0.0
03953
-0.0
55554
-0.0
15738
-0.0
17294
-0.0
68666**
-0.0
17451
-0.0
20503
(0.0
33)
(0.0
23)
(0.0
23)
(0.0
35)
(0.0
25)
(0.0
26)
(0.0
36)
(0.0
21)
(0.0
21)
(0.0
34)
(0.0
24)
(0.0
25)
Fore
ingner
popula
tion
%-0
.074070
0.0
01460
0.0
01658
-0.0
93126*
-0.0
08278
-0.0
07361
-0.0
62833
0.0
05971
0.0
06115
-0.0
74692
-0.0
15685
-0.0
16138
(0.0
54)
(0.0
42)
(0.0
42)
(0.0
54)
(0.0
47)
(0.0
47)
(0.0
51)
(0.0
36)
(0.0
36)
(0.0
51)
(0.0
38)
(0.0
39)
Cancelled/P
opula
tion
%-0
.130371
-0.0
42968
-0.0
43512
-0.1
14391
-0.0
75868
-0.0
77060
-0.1
10181
-0.0
21045
-0.0
21527
-0.0
78889
-0.0
28251
-0.0
25894
(0.0
86)
(0.0
76)
(0.0
76)
(0.0
89)
(0.0
83)
(0.0
83)
(0.0
85)
(0.0
72)
(0.0
72)
(0.0
86)
(0.0
77)
(0.0
78)
New
regis
tere
d/P
opula
tion
%0.0
29150
-0.0
85792
-0.0
80093
0.0
12519
-0.1
01054
-0.0
95625
0.0
06101
-0.0
49369
-0.0
43291
-0.0
31845
-0.1
03814*
-0.0
98832*
(0.0
63)
(0.0
62)
(0.0
62)
(0.0
66)
(0.0
68)
(0.0
67)
(0.0
62)
(0.0
55)
(0.0
55)
(0.0
61)
(0.0
57)
(0.0
57)
Borr
ow
ing
-E
uro
PC
-0.0
00164
-0.0
00601
-0.0
00602
-0.0
00456
-0.0
00455
-0.0
00461
0.0
00584
0.0
00240
0.0
00234
0.0
00575
0.0
00055
0.0
00039
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Curr
ent
gra
nts
/T
ota
lgra
nts
%-0
.014337***
-0.0
17707***
-0.0
17828***
-0.0
17615***
-0.0
16131***
-0.0
16141***
-0.0
14547***
-0.0
21101***
-0.0
21303***
-0.0
16908***
-0.0
20799***
-0.0
21220***
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
CL
%vote
s-
regio
nal
govern
ment
ballots
0.0
13277**
0.0
05453
0.0
05948
0.0
14911**
0.0
10393
0.0
10728
0.0
11861*
0.0
02203
0.0
02861
0.0
11515
0.0
04442
0.0
04852
(0.0
07)
(0.0
06)
(0.0
06)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
05)
(0.0
05)
(0.0
07)
(0.0
06)
(0.0
06)
Oth
ers
%vote
s-
regio
nal
govern
ment
ballots
0.0
15538
-0.0
02561
-0.0
01990
0.0
18307
-0.0
03694
-0.0
03214
0.0
10276
-0.0
09243
-0.0
08221
0.0
17021
-0.0
08520
-0.0
08640
(0.0
14)
(0.0
14)
(0.0
14)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
13)
(0.0
12)
(0.0
12)
(0.0
14)
(0.0
14)
(0.0
14)
RM
I1.4
61266***
0.6
03536
0.5
91773
1.6
07816***
0.7
52183*
0.7
36738*
1.3
40353***
0.3
23209
0.2
84801
1.4
80155***
0.5
56465
0.5
01539
(0.4
49)
(0.3
72)
(0.3
72)
(0.4
51)
(0.4
15)
(0.4
17)
(0.4
65)
(0.3
34)
(0.3
34)
(0.4
48)
(0.3
57)
(0.3
62)
Dum
my
inc1
1.2
44668
1.7
31718***
1.7
30391***
1.2
07485
1.5
50131**
1.5
69244**
1.6
40399**
1.9
50528***
1.9
54796***
1.6
06057**
1.7
51296***
1.7
56923***
(0.8
10)
(0.6
28)
(0.6
28)
(0.8
54)
(0.7
17)
(0.7
19)
(0.8
15)
(0.5
34)
(0.5
36)
(0.7
88)
(0.6
26)
(0.6
38)
Dum
my
inc2
0.6
71964
0.9
64571**
0.9
74768***
0.5
94809
1.1
72467**
1.1
83283**
0.8
84775
0.6
81183**
0.6
84071**
0.8
57742
1.0
87966***
1.0
77540***
(0.5
83)
(0.3
77)
(0.3
77)
(0.6
36)
(0.4
66)
(0.4
66)
(0.5
85)
(0.3
01)
(0.3
03)
(0.5
67)
(0.3
93)
(0.4
02)
Dum
my
inc3
0.6
14716
0.4
70854
0.4
86357
0.7
51462*
0.5
55789
0.5
66032
0.6
54835*
0.3
94940
0.4
20324
0.8
39161**
0.4
44858
0.4
48460
(0.4
06)
(0.3
31)
(0.3
31)
(0.4
43)
(0.4
01)
(0.4
01)
(0.3
82)
(0.2
85)
(0.2
86)
(0.3
96)
(0.3
68)
(0.3
75)
Cohousi
ng/p
opula
tion*1000
0.0
22788
0.0
00096
-0.0
00857
0.0
34391
0.0
08751
0.0
07611
0.0
04967
-0.0
04785
-0.0
05832
0.0
03604
-0.0
14281
-0.0
16833
(0.0
34)
(0.0
28)
(0.0
29)
(0.0
43)
(0.0
36)
(0.0
35)
(0.0
26)
(0.0
26)
(0.0
26)
(0.0
23)
(0.0
31)
(0.0
33)
Year
2003
-0.0
16514
0.1
58920
-0.6
84146
-0.0
49334
0.6
61640
1.5
79786
0.0
76703
0.1
24238
-0.1
67866
0.0
24978
0.4
65445
1.1
08016
(0.2
08)
(0.5
29)
(3.5
69)
(0.2
10)
(0.5
90)
(3.9
38)
(0.2
08)
(0.4
68)
(3.1
33)
(0.2
11)
(0.5
11)
(3.4
39)
Year
2004
-0.0
84789
0.1
26779
-0.6
41922
-0.1
13871
0.6
29090
1.4
64286
-0.0
35008
0.0
48997
-0.2
20012
-0.0
94199
0.3
46293
0.9
26794
(0.1
97)
(0.5
19)
(3.2
90)
(0.1
99)
(0.5
77)
(3.6
25)
(0.1
91)
(0.4
61)
(2.8
90)
(0.2
02)
(0.5
02)
(3.1
71)
Year
2005
-0.1
10857
0.1
20583
-0.5
74832
-0.1
56385
0.5
46309
1.3
02391
-0.0
69387
0.0
25708
-0.2
16197
-0.1
26671
0.2
77660
0.8
00722
(0.1
67)
(0.4
05)
(2.9
09)
(0.1
67)
(0.4
51)
(3.2
06)
(0.1
58)
(0.3
61)
(2.5
56)
(0.1
65)
(0.3
92)
(2.8
04)
Year
2006
-0.0
25888
0.2
46252**
0.0
64562
-0.0
29865
0.4
22497***
0.6
09913
0.0
02616
0.0
80617
0.0
10835
-0.0
49761
0.1
60834
0.2
75864
(0.1
47)
(0.1
08)
(0.6
48)
(0.1
47)
(0.1
24)
(0.7
15)
(0.1
39)
(0.0
98)
(0.5
73)
(0.1
47)
(0.1
08)
(0.6
28)
Year
2007
-0.1
08893
0.1
91380
0.2
49505
-0.1
56070
0.0
80711
-0.0
08222
-0.0
33162
0.1
03616
0.1
08347
-0.0
83603
-0.0
24393
-0.1
07096
(0.1
46)
(0.2
11)
(0.4
60)
(0.1
39)
(0.2
32)
(0.5
05)
(0.1
41)
(0.1
83)
(0.4
00)
(0.1
43)
(0.2
01)
(0.4
40)
Year
2008
-0.3
37534***
-0.0
35723
-0.1
36915
-0.3
88775***
-0.0
54925
0.0
40832
-0.2
79992**
-0.0
89129
-0.1
32928
-0.3
20845***
-0.1
36424
-0.0
81680
(0.1
22)
(0.1
08)
(0.2
98)
(0.1
17)
(0.1
16)
(0.3
31)
(0.1
16)
(0.0
96)
(0.2
67)
(0.1
15)
(0.1
06)
(0.2
92)
Obse
rvati
ons
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
Munic
ipaliti
es
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
AR
(1)
test
stati
stic
-7.5
06
-10.2
7-1
0.2
8-8
.386
-10.1
2-1
0.0
8-7
.167
-9.6
32
-9.5
80
-7.3
49
-9.7
23
-9.6
05
p-v
alu
eof
AR
(1)
stati
stic
00
00
00
00
00
00
AR
(2)
test
stati
stic
0.6
99
-0.2
34
-0.2
28
0.3
57
-0.8
66
-0.8
57
1.2
23
-1.1
77
-1.1
41
0.6
27
-0.7
29
-0.7
10
p-v
alu
eof
AR
(2)
stati
stic
0.4
84
0.8
15
0.8
19
0.7
21
0.3
86
0.3
91
0.2
21
0.2
39
0.2
54
0.5
31
0.4
66
0.4
78
Hanse
nJ
stati
stic
63.8
484.7
084.2
666.9
892.2
791.7
567.1
778.9
977.6
065.6
388.7
986.8
5D
egre
es
of
freedom
for
Hanse
nst
ati
stic
73
73
73
73
73
73
73
73
73
73
73
73
p-v
alu
eof
Hanse
nJ
stati
stic
0.7
69
0.1
65
0.1
73
0.6
76
0.0
634
0.0
682
0.6
70
0.2
95
0.3
34
0.7
18
0.1
01
0.1
28
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
20
Tab
le7:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
fees
bu
rden
.A
rell
an
o-
Bon
dD
yn
am
icP
an
elG
MM
Est
imato
r.F
ull
mod
el.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
LA
G1
Local
fees
burd
en
0.2
08170***
0.2
20444***
0.2
20721***
0.2
00950***
0.1
99821***
0.2
00281***
0.2
14666***
0.2
25462***
0.2
25884***
0.2
06891***
0.2
13706***
0.2
14118***
(0.0
74)
(0.0
77)
(0.0
77)
(0.0
72)
(0.0
72)
(0.0
72)
(0.0
76)
(0.0
77)
(0.0
77)
(0.0
74)
(0.0
73)
(0.0
73)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%0.0
02288
-0.0
03115
-0.0
02838
(0.0
04)
(0.0
05)
(0.0
05)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.002081
-0.0
06362
-0.0
06052
(0.0
07)
(0.0
08)
(0.0
08)
VF
I3-
Gra
nts
/O
wn
Revenues
%0.0
03340
-0.0
00051
0.0
00247
(0.0
04)
(0.0
06)
(0.0
06)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%0.0
00961
-0.0
01440
-0.0
01035
(0.0
07)
(0.0
08)
(0.0
08)
VF
I1xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00002*
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00002*
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00002
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00002
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00001
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00001
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00001
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00001
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e0.0
00006
0.0
00005
0.0
00008
0.0
00007
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e0.0
01597**
0.0
01441*
0.0
01666**
0.0
01442*
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e0.0
09098*
0.0
08080*
0.0
09683**
0.0
08305*
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
Adm
inis
trati
ve
exp
endit
ure
/to
tal
exp
%-0
.029398
-0.0
33803
-0.0
34405
-0.0
30144
-0.0
44818
-0.0
43742
-0.0
00890
-0.0
26057
-0.0
26597
0.0
00423
-0.0
42137
-0.0
42310
(0.0
79)
(0.0
61)
(0.0
61)
(0.0
73)
(0.0
68)
(0.0
68)
(0.0
74)
(0.0
55)
(0.0
56)
(0.0
70)
(0.0
60)
(0.0
60)
Cult
ure
exp
endit
ure
/to
tal
exp
%-0
.232426*
-0.1
87492*
-0.1
88993*
-0.2
34496**
-0.2
22889**
-0.2
22938**
-0.1
67631
-0.1
62955
-0.1
64308
-0.1
64115
-0.2
06524*
-0.2
08175*
(0.1
23)
(0.1
11)
(0.1
12)
(0.1
19)
(0.1
10)
(0.1
10)
(0.1
21)
(0.1
13)
(0.1
13)
(0.1
24)
(0.1
17)
(0.1
17)
Sp
ort
exp
endit
ure
/to
tal
exp
%-0
.164309
-0.1
02054
-0.0
99535
-0.2
01324
-0.0
65255
-0.0
61664
-0.0
87422
0.0
05848
0.0
09310
-0.1
42763
-0.0
02420
0.0
02692
(0.1
58)
(0.1
64)
(0.1
64)
(0.1
72)
(0.1
69)
(0.1
68)
(0.1
53)
(0.1
72)
(0.1
72)
(0.1
58)
(0.1
75)
(0.1
75)
Touri
smexp
endit
ure
/to
tal
exp
%-0
.148934
-0.0
89498
-0.0
88295
-0.1
64779
-0.0
90213
-0.0
86767
-0.0
92773
-0.0
39992
-0.0
39440
-0.0
99380
-0.0
57767
-0.0
56633
(0.1
44)
(0.1
40)
(0.1
40)
(0.1
46)
(0.1
39)
(0.1
39)
(0.1
41)
(0.1
43)
(0.1
43)
(0.1
45)
(0.1
46)
(0.1
46)
Educati
on
exp
endit
ure
/to
tal
exp
%-0
.064595
-0.0
23548
-0.0
23441
-0.0
69523
-0.0
77540
-0.0
75532
-0.0
18532
0.0
18793
0.0
19806
-0.0
33409
-0.0
27716
-0.0
27078
(0.0
91)
(0.0
88)
(0.0
88)
(0.0
89)
(0.0
85)
(0.0
85)
(0.0
83)
(0.0
91)
(0.0
92)
(0.0
78)
(0.0
84)
(0.0
85)
Local
police
exp
endit
ure
/to
tal
exp
%0.1
47443
0.1
10397
0.1
10352
0.1
73437**
0.1
17242
0.1
19213
0.1
85554**
0.1
34337
0.1
33833
0.1
96894**
0.1
31061
0.1
31781
(0.0
92)
(0.0
85)
(0.0
85)
(0.0
87)
(0.0
87)
(0.0
87)
(0.0
87)
(0.0
88)
(0.0
88)
(0.0
82)
(0.0
86)
(0.0
86)
Tra
ffic
man.
exp
endit
ure
/to
tal
exp
%0.0
03029
0.0
42728
0.0
42940
-0.0
08441
0.0
19397
0.0
20762
0.0
03001
0.0
47796
0.0
48762
-0.0
08500
0.0
26845
0.0
28266
(0.0
87)
(0.0
78)
(0.0
78)
(0.0
80)
(0.0
81)
(0.0
81)
(0.0
81)
(0.0
72)
(0.0
72)
(0.0
75)
(0.0
75)
(0.0
76)
Landin
gexp
endit
ure
/to
tal
exp
%0.0
23182
0.0
19041
0.0
17469
0.0
26567
0.0
02041
0.0
01868
0.0
50922
0.0
32536
0.0
31857
0.0
57415
0.0
09701
0.0
09123
(0.0
77)
(0.0
59)
(0.0
60)
(0.0
70)
(0.0
64)
(0.0
64)
(0.0
72)
(0.0
51)
(0.0
51)
(0.0
69)
(0.0
57)
(0.0
57)
Socia
lexp
endit
ure
/to
tal
exp
%-0
.002379
0.0
06042
0.0
05357
0.0
02370
0.0
01129
0.0
02145
0.0
24008
0.0
04230
0.0
04400
0.0
30212
-0.0
20045
-0.0
19664
(0.0
83)
(0.0
74)
(0.0
74)
(0.0
79)
(0.0
78)
(0.0
78)
(0.0
76)
(0.0
68)
(0.0
68)
(0.0
76)
(0.0
71)
(0.0
71)
Ec.
pla
nnin
gexp
endit
ure
/to
tal
exp
%0.0
85766
0.0
73262
0.0
73122
0.0
86494
0.0
62740
0.0
64213
0.1
06911
0.0
84289
0.0
84103
0.1
10402*
0.0
68934
0.0
69177
(0.0
77)
(0.0
66)
(0.0
66)
(0.0
72)
(0.0
69)
(0.0
68)
(0.0
68)
(0.0
63)
(0.0
63)
(0.0
64)
(0.0
63)
(0.0
63)
Unit
ary
est
ate
incom
e-
Euro
PC
-0.0
01045
-0.0
00898
-0.0
00952
-0.0
01334
-0.0
00858
-0.0
00916
-0.0
01409
-0.0
01810
-0.0
01858
-0.0
01634
-0.0
01665
-0.0
01706
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Unit
ary
tota
lin
com
e-
Euro
PC
-0.0
00016
0.0
01499*
0.0
09004*
-0.0
00009
0.0
01345
0.0
07989*
0.0
00047
0.0
01608**
0.0
09628**
0.0
00039
0.0
01367*
0.0
08236*
(0.0
00)
(0.0
01)
(0.0
05)
(0.0
00)
(0.0
01)
(0.0
05)
(0.0
00)
(0.0
01)
(0.0
05)
(0.0
00)
(0.0
01)
(0.0
05)
21
Com
merc
ial
est
ate
valu
e-
Euro
/m
sq0.0
00567
0.0
00680
0.0
00680
0.0
00206
0.0
00773*
0.0
00780*
0.0
00600
0.0
00774
0.0
00771
0.0
00341
0.0
00847*
0.0
00850*
(0.0
01)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
Resi
denti
al
est
ate
valu
e-
Euro
/m
sq-0
.000299
-0.0
00618
-0.0
00601
-0.0
00216
-0.0
00986**
-0.0
00960**
-0.0
00188
-0.0
00393
-0.0
00388
-0.0
00171
-0.0
00555
-0.0
00543
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
Popula
tion
31
Dec
-0.0
00069
-0.0
00075
-0.0
00076
-0.0
00016
-0.0
00032
-0.0
00032
-0.0
00102
-0.0
00100
-0.0
00104
-0.0
00038
-0.0
00020
-0.0
00022
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
0-1
4%
0.0
13138
0.0
38481
0.0
37731
0.0
09264
0.0
27750
0.0
26958
0.0
21552
0.0
57005*
0.0
56559*
0.0
19075
0.0
48534
0.0
47748
(0.0
31)
(0.0
29)
(0.0
29)
(0.0
31)
(0.0
27)
(0.0
27)
(0.0
30)
(0.0
31)
(0.0
31)
(0.0
30)
(0.0
30)
(0.0
30)
Popula
tion
over
65
%-0
.012744
-0.0
06016
-0.0
05711
-0.0
19328
-0.0
10995
-0.0
10055
-0.0
23999
-0.0
16714
-0.0
16508
-0.0
28231
-0.0
19811
-0.0
19107
(0.0
35)
(0.0
25)
(0.0
25)
(0.0
38)
(0.0
25)
(0.0
25)
(0.0
35)
(0.0
27)
(0.0
27)
(0.0
37)
(0.0
28)
(0.0
28)
Fore
ingner
popula
tion
%0.0
39239
-0.0
19146
-0.0
18536
0.0
38199
-0.0
16769
-0.0
15088
0.0
27134
-0.0
09964
-0.0
10367
0.0
30748
-0.0
03316
-0.0
03111
(0.0
62)
(0.0
48)
(0.0
48)
(0.0
60)
(0.0
47)
(0.0
47)
(0.0
60)
(0.0
47)
(0.0
47)
(0.0
62)
(0.0
45)
(0.0
45)
Cancelled/P
opula
tion
%-0
.096568
-0.0
91618
-0.0
93690
-0.1
38217
-0.0
85682
-0.0
89026
-0.0
83486
-0.1
22477
-0.1
24652
-0.1
19295
-0.1
12427
-0.1
15051
(0.1
08)
(0.0
87)
(0.0
87)
(0.1
11)
(0.0
89)
(0.0
89)
(0.1
13)
(0.0
94)
(0.0
94)
(0.1
21)
(0.0
91)
(0.0
92)
New
regis
tere
d/P
opula
tion
%0.0
27596
0.0
55456
0.0
57169
0.0
16758
0.0
21705
0.0
24292
0.0
34109
0.0
86968
0.0
88564
0.0
30606
0.0
68061
0.0
70105
(0.0
63)
(0.0
78)
(0.0
78)
(0.0
63)
(0.0
77)
(0.0
76)
(0.0
69)
(0.0
79)
(0.0
79)
(0.0
65)
(0.0
77)
(0.0
77)
Borr
ow
ing
-E
uro
PC
0.0
00161
0.0
00258
0.0
00268
0.0
00109
0.0
00325
0.0
00334
-0.0
00015
0.0
00342
0.0
00348
-0.0
00105
0.0
00453
0.0
00454
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Curr
ent
gra
nts
/T
ota
lgra
nts
%0.0
00899
-0.0
02269
-0.0
02143
0.0
00569
-0.0
00499
-0.0
00355
0.0
00747
-0.0
01455
-0.0
01288
0.0
00956
-0.0
00673
-0.0
00495
(0.0
03)
(0.0
04)
(0.0
04)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
04)
(0.0
04)
(0.0
03)
(0.0
03)
(0.0
03)
CL
%vote
s-
regio
nal
govern
ment
ballots
0.0
11404
0.0
13456*
0.0
13804*
0.0
08801
0.0
11759
0.0
12066
0.0
14599*
0.0
17440**
0.0
17718**
0.0
11386
0.0
15940*
0.0
16253**
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
Oth
ers
%vote
s-
regio
nal
govern
ment
ballots
-0.0
09011
-0.0
19744
-0.0
19301
-0.0
10783
-0.0
20554
-0.0
19881
-0.0
06678
-0.0
14866
-0.0
14614
-0.0
09253
-0.0
13138
-0.0
12600
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
14)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
16)
(0.0
16)
(0.0
15)
(0.0
16)
(0.0
16)
RM
I0.0
67607
-0.0
02496
-0.0
11446
0.0
73952
-0.2
29271
-0.2
35947
0.4
47876
0.0
74199
0.0
67689
0.3
02641
-0.0
96874
-0.1
00769
(0.4
70)
(0.3
87)
(0.3
88)
(0.4
69)
(0.3
93)
(0.3
96)
(0.4
91)
(0.3
82)
(0.3
83)
(0.4
71)
(0.3
90)
(0.3
95)
Dum
my
inc1
-1.2
10730
-0.7
98052
-0.8
34611
-1.0
48027
-0.6
92968
-0.7
21785
-0.4
11664
-0.9
14182
-0.9
43139
-0.5
58153
-1.0
06813
-1.0
31709
(1.0
24)
(0.7
54)
(0.7
60)
(0.9
82)
(0.7
49)
(0.7
52)
(1.0
22)
(0.6
97)
(0.7
05)
(0.9
86)
(0.6
98)
(0.7
04)
Dum
my
inc2
-0.8
56787
-0.1
75456
-0.1
78254
-0.7
39623
-0.0
10467
-0.0
15064
-0.3
78644
-0.2
29516
-0.2
34135
-0.4
78918
-0.1
45199
-0.1
47003
(0.6
63)
(0.3
91)
(0.3
92)
(0.6
38)
(0.4
31)
(0.4
31)
(0.6
65)
(0.4
00)
(0.4
03)
(0.6
64)
(0.4
31)
(0.4
33)
Dum
my
inc3
-0.4
22775
-0.4
85807
-0.4
92009
-0.4
02939
-0.3
44517
-0.3
44234
-0.2
11608
-0.5
36813
-0.5
45138
-0.3
01171
-0.4
99554
-0.4
99762
(0.4
38)
(0.3
90)
(0.3
93)
(0.4
49)
(0.4
20)
(0.4
22)
(0.4
50)
(0.4
03)
(0.4
06)
(0.4
61)
(0.4
38)
(0.4
42)
Cohousi
ng/p
opula
tion*1000
-0.0
24420
-0.0
13572
-0.0
13752
-0.0
31059
-0.0
19775
-0.0
19613
-0.0
34180
-0.0
14035
-0.0
14064
-0.0
33174
-0.0
07651
-0.0
07711
(0.0
40)
(0.0
37)
(0.0
37)
(0.0
46)
(0.0
40)
(0.0
40)
(0.0
45)
(0.0
36)
(0.0
36)
(0.0
45)
(0.0
34)
(0.0
34)
Year
2003
0.3
60747
1.2
61241**
8.0
37866*
0.2
73164
1.1
73944*
7.1
76824*
0.2
95627
1.2
85873**
8.5
25267**
0.2
32961
1.1
43151*
7.3
45463*
(0.2
31)
(0.6
18)
(4.1
12)
(0.2
43)
(0.6
15)
(4.1
34)
(0.2
22)
(0.5
95)
(4.0
86)
(0.2
35)
(0.6
00)
(4.1
37)
Year
2004
0.3
09183
1.2
61489**
7.4
33174**
0.2
57096
1.1
52370*
6.6
19726*
0.2
62948
1.3
07876**
7.9
02404**
0.2
22899
1.1
42268*
6.7
92372*
(0.2
15)
(0.5
99)
(3.7
84)
(0.2
25)
(0.6
00)
(3.8
08)
(0.2
08)
(0.5
76)
(3.7
59)
(0.2
26)
(0.5
85)
(3.8
08)
Year
2005
0.1
77008
0.9
49115**
6.5
29049*
0.1
46439
0.8
84602*
5.8
28705*
0.1
03320
0.9
82627**
6.9
45333**
0.0
94961
0.8
61468*
5.9
70323*
(0.1
85)
(0.4
74)
(3.3
55)
(0.1
87)
(0.4
75)
(3.3
77)
(0.1
78)
(0.4
54)
(3.3
33)
(0.1
89)
(0.4
63)
(3.3
79)
Year
2006
0.1
15515
0.0
39162
1.4
44317*
0.0
74783
0.0
55296
1.3
02825*
0.0
88510
0.0
26074
1.5
28878**
0.0
49076
0.0
21198
1.3
09959*
(0.1
50)
(0.1
24)
(0.7
38)
(0.1
49)
(0.1
17)
(0.7
47)
(0.1
38)
(0.1
30)
(0.7
24)
(0.1
53)
(0.1
31)
(0.7
40)
Year
2007
0.0
49587
-0.4
37626*
-1.0
29673*
0.0
40412
-0.3
82520
-0.9
04088*
0.0
32697
-0.5
24277**
-1.1
56234**
0.0
03575
-0.4
48091*
-0.9
87902*
(0.1
47)
(0.2
54)
(0.5
41)
(0.1
42)
(0.2
46)
(0.5
35)
(0.1
43)
(0.2
62)
(0.5
49)
(0.1
52)
(0.2
60)
(0.5
48)
Year
2008
0.0
84243
-0.0
57596
0.6
79509**
0.0
77036
-0.0
53831
0.6
01904*
0.0
30334
-0.1
05818
0.6
81587**
0.0
29286
-0.0
88410
0.5
87535*
(0.1
39)
(0.1
25)
(0.3
34)
(0.1
35)
(0.1
19)
(0.3
40)
(0.1
36)
(0.1
31)
(0.3
34)
(0.1
39)
(0.1
34)
(0.3
42)
Obse
rvati
ons
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
19,1
16
Munic
ipaliti
es
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
4,7
44
AR
(1)
test
stati
stic
-5.7
65
-6.0
80
-6.0
89
-5.9
86
-6.3
24
-6.3
20
-5.7
49
-5.8
41
-5.8
60
-5.8
88
-5.6
13
-5.6
25
p-v
alu
eof
AR
(1)
stati
stic
8.1
4e-0
91.2
0e-0
91.1
4e-0
92.1
5e-0
92.5
5e-1
02.6
1e-1
08.9
5e-0
95.1
8e-0
94.6
3e-0
93.9
1e-0
91.9
9e-0
81.8
6e-0
8A
R(2
)te
stst
ati
stic
1.2
05
1.2
98
1.2
66
0.4
94
0.9
73
0.9
43
1.6
69
1.1
29
1.1
21
0.9
67
0.4
42
0.4
23
p-v
alu
eof
AR
(2)
stati
stic
0.2
28
0.1
94
0.2
05
0.6
21
0.3
31
0.3
46
0.0
952
0.2
59
0.2
62
0.3
34
0.6
58
0.6
72
Hanse
nJ
stati
stic
64.3
862.0
561.9
261.7
260.6
460.8
467.6
059.1
558.6
464.9
957.5
957.2
2D
egre
es
of
freedom
for
Hanse
nst
ati
stic
73
73
73
73
73
73
73
73
73
73
73
73
p-v
alu
eof
Hanse
nJ
stati
stic
0.7
54
0.8
16
0.8
19
0.8
24
0.8
49
0.8
44
0.6
57
0.8
79
0.8
89
0.7
37
0.9
07
0.9
13
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
22
Tab
le8:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
tax
bu
rden
.F
ixed
effec
tF
GL
Ses
tim
ato
r.F
ull
mod
el.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%-0
.014763***
-0.0
14927***
-0.0
14918***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.010286***
-0.0
10782***
-0.0
10772***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I3-
Gra
nts
/O
wn
Revenues
%-0
.021774***
-0.0
26480***
-0.0
26442***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%-0
.026755***
-0.0
29990***
-0.0
29946***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I1xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00000
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00000
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00000***
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00000***
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00002***
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00002***
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00001***
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00001***
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e-0
.000022***
-0.0
00023***
-0.0
00014***
-0.0
00018***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e-0
.000671***
-0.0
00743***
-0.0
00559***
-0.0
00694***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e-0
.000652***
-0.0
00721***
-0.0
00541***
-0.0
00672***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
RM
I-0
.107726**
-0.1
05156**
-0.1
05433**
-0.0
80945
-0.0
80374
-0.0
80536
-0.1
61816***
-0.1
19250***
-0.1
20424***
-0.1
17791**
-0.1
03389**
-0.1
04419**
(0.0
49)
(0.0
49)
(0.0
49)
(0.0
52)
(0.0
51)
(0.0
51)
(0.0
43)
(0.0
42)
(0.0
41)
(0.0
47)
(0.0
44)
(0.0
44)
LA
Gta
xburd
en
%0.2
77178***
0.2
77205***
0.2
77213***
0.3
10308***
0.3
09711***
0.3
09773***
0.2
34375***
0.2
29097***
0.2
29359***
0.2
57060***
0.2
52772***
0.2
53060***
(0.0
27)
(0.0
26)
(0.0
26)
(0.0
28)
(0.0
27)
(0.0
27)
(0.0
25)
(0.0
24)
(0.0
24)
(0.0
26)
(0.0
25)
(0.0
25)
Adm
inis
trati
ve
exp
endit
ure
/to
tal
exp
%-0
.001309
-0.0
01322
-0.0
01321
-0.0
01521
-0.0
01566
-0.0
01565
-0.0
01702
-0.0
02032
-0.0
02032
-0.0
01277
-0.0
01638
-0.0
01637
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Cult
ure
exp
endit
ure
/to
tal
exp
%0.0
01020
0.0
01008
0.0
01011
0.0
00516
0.0
00469
0.0
00475
0.0
04716
0.0
04519
0.0
04547
0.0
05655
0.0
05324
0.0
05351
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Sp
ort
exp
endit
ure
/to
tal
exp
%0.0
08743
0.0
08675
0.0
08679
0.0
08842
0.0
08591
0.0
08594
0.0
06598
0.0
05321
0.0
05330
0.0
07412
0.0
06408
0.0
06416
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
05)
(0.0
05)
(0.0
06)
(0.0
06)
(0.0
06)
Touri
smexp
endit
ure
/to
tal
exp
%-0
.004088
-0.0
04027
-0.0
04033
-0.0
04660
-0.0
04574
-0.0
04579
0.0
01048
0.0
02393
0.0
02392
0.0
00836
0.0
01801
0.0
01795
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
Educati
on
exp
endit
ure
/to
tal
exp
%-0
.010039***
-0.0
10015***
-0.0
10018***
-0.0
10251***
-0.0
10240***
-0.0
10242***
-0.0
10910***
-0.0
10610***
-0.0
10621***
-0.0
09500***
-0.0
09488***
-0.0
09497***
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
Local
police
exp
endit
ure
/to
tal
exp
%-0
.017516***
-0.0
17536***
-0.0
17536***
-0.0
16942***
-0.0
16990***
-0.0
16993***
-0.0
20518***
-0.0
21025***
-0.0
21051***
-0.0
21541***
-0.0
22092***
-0.0
22112***
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
Tra
ffic
man.
exp
endit
ure
/to
tal
exp
%-0
.000051
-0.0
00031
-0.0
00033
-0.0
00670
-0.0
00651
-0.0
00653
-0.0
00431
-0.0
00829
-0.0
00826
0.0
00059
-0.0
00370
-0.0
00365
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
04)
(0.0
04)
(0.0
04)
Landin
gexp
endit
ure
/to
tal
exp
%0.0
15141***
0.0
15170***
0.0
15168***
0.0
16170***
0.0
16223***
0.0
16221***
0.0
12311***
0.0
12356***
0.0
12350***
0.0
12880***
0.0
12827***
0.0
12824***
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Socia
lexp
endit
ure
/to
tal
exp
%0.0
02714
0.0
02776
0.0
02771
0.0
01398
0.0
01483
0.0
01481
0.0
04399*
0.0
05008**
0.0
05017**
0.0
05423**
0.0
05743**
0.0
05748**
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
03)
(0.0
03)
(0.0
03)
23
Ec.
pla
nnin
gexp
endit
ure
/to
tal
exp
%-0
.001033
-0.0
01023
-0.0
01023
-0.0
00462
-0.0
00439
-0.0
00437
-0.0
03655
-0.0
04229
-0.0
04212
-0.0
04893
-0.0
05363
-0.0
05342
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
04)
(0.0
03)
(0.0
03)
Pro
pert
yta
x-
ord
inary
taxra
te%
0.9
10096***
0.9
09549***
0.9
09571***
0.8
63946***
0.8
64800***
0.8
64690***
0.8
82026***
0.8
68696***
0.8
68442***
0.8
12231***
0.8
06326***
0.8
06093***
(0.0
80)
(0.0
80)
(0.0
80)
(0.0
83)
(0.0
83)
(0.0
83)
(0.0
74)
(0.0
73)
(0.0
73)
(0.0
76)
(0.0
76)
(0.0
76)
Pro
pert
yta
x-
taxra
tem
ain
resi
dence
%0.2
27532***
0.2
27356***
0.2
27392***
0.2
49496***
0.2
46674***
0.2
46845***
0.1
74774**
0.1
62824**
0.1
63374**
0.2
04172**
0.1
89576**
0.1
90167**
(0.0
82)
(0.0
82)
(0.0
82)
(0.0
83)
(0.0
83)
(0.0
83)
(0.0
81)
(0.0
80)
(0.0
80)
(0.0
82)
(0.0
81)
(0.0
81)
Dum
my
inc1
0.0
91170**
0.0
91194**
0.0
91194**
0.0
72716*
0.0
76629**
0.0
76483**
0.1
20270***
0.1
15474***
0.1
15381***
0.1
13343***
0.1
20584***
0.1
20450***
(0.0
37)
(0.0
37)
(0.0
37)
(0.0
38)
(0.0
38)
(0.0
38)
(0.0
35)
(0.0
34)
(0.0
34)
(0.0
36)
(0.0
34)
(0.0
34)
Dum
my
inc2
0.0
84912***
0.0
84487***
0.0
84548***
0.0
92915***
0.0
93642***
0.0
93651***
0.0
71566***
0.0
59867***
0.0
60097***
0.0
90774***
0.0
85688***
0.0
85901***
(0.0
25)
(0.0
25)
(0.0
25)
(0.0
26)
(0.0
26)
(0.0
26)
(0.0
24)
(0.0
23)
(0.0
23)
(0.0
25)
(0.0
23)
(0.0
23)
Dum
my
inc3
0.0
65820***
0.0
65714***
0.0
65741***
0.0
81854***
0.0
81647***
0.0
81681***
0.0
39053***
0.0
34754**
0.0
34891**
0.0
61256***
0.0
57137***
0.0
57272***
(0.0
16)
(0.0
16)
(0.0
16)
(0.0
16)
(0.0
16)
(0.0
16)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
Unit
ary
est
ate
incom
e-
Euro
PC
-0.0
00149***
-0.0
00149***
-0.0
00149***
-0.0
00121**
-0.0
00121**
-0.0
00122**
-0.0
00175***
-0.0
00169***
-0.0
00170***
-0.0
00156***
-0.0
00155***
-0.0
00155***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Unit
ary
tota
lin
com
e-
Euro
PC
-0.0
00122***
-0.0
00777***
-0.0
00757***
-0.0
00124***
-0.0
00860***
-0.0
00837***
-0.0
00107***
-0.0
00729***
-0.0
00711***
-0.0
00115***
-0.0
00866***
-0.0
00843***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Com
merc
ial
est
ate
valu
e-
Euro
/m
sq0.0
00091**
0.0
00091**
0.0
00091**
0.0
00101***
0.0
00101***
0.0
00101***
0.0
00087**
0.0
00086**
0.0
00086**
0.0
00089**
0.0
00089**
0.0
00089**
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Resi
denti
al
est
ate
valu
e-
Euro
/m
sq-0
.000092**
-0.0
00092**
-0.0
00092**
-0.0
00082**
-0.0
00083**
-0.0
00083**
-0.0
00127***
-0.0
00130***
-0.0
00131***
-0.0
00112***
-0.0
00116***
-0.0
00116***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
31
Dec
-0.0
00004***
-0.0
00004***
-0.0
00004***
-0.0
00005***
-0.0
00005***
-0.0
00005***
-0.0
00003***
-0.0
00004***
-0.0
00004***
-0.0
00004***
-0.0
00004***
-0.0
00004***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
0-1
4%
-0.0
01125
-0.0
01228
-0.0
01223
-0.0
05228**
-0.0
05248**
-0.0
05263**
0.0
04537**
0.0
05225**
0.0
05124**
0.0
01832
0.0
02631
0.0
02527
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Popula
tion
over
65
%-0
.000109
-0.0
00215
-0.0
00207
-0.0
01613
-0.0
01764
-0.0
01763
0.0
01744
0.0
01194
0.0
01166
0.0
00552
0.0
00287
0.0
00259
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Fore
ingner
popula
tion
%0.0
00094
0.0
00136
0.0
00132
-0.0
00273
-0.0
00184
-0.0
00189
0.0
00018
0.0
00701
0.0
00685
-0.0
00039
0.0
00387
0.0
00371
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Cancelled/P
opula
tion
%0.0
07212*
0.0
07230*
0.0
07230*
0.0
07571**
0.0
07546**
0.0
07551**
0.0
07062**
0.0
07375**
0.0
07385**
0.0
07002**
0.0
06994**
0.0
07008**
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
04)
(0.0
04)
(0.0
04)
New
regis
tere
d/P
opula
tion
%-0
.008001***
-0.0
07898***
-0.0
07906***
-0.0
05827**
-0.0
05735*
-0.0
05733*
-0.0
09192***
-0.0
08099***
-0.0
08073***
-0.0
08878***
-0.0
08347***
-0.0
08321***
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
Cohousi
ng/p
opula
tion*1000
0.0
00404**
0.0
00407**
0.0
00406**
0.0
00431**
0.0
00430**
0.0
00429**
0.0
00945***
0.0
00946***
0.0
00947***
0.0
00908***
0.0
00929***
0.0
00929***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
LA
G1
Borr
ow
ing
-E
uro
PC
0.0
00077***
0.0
00077***
0.0
00077***
0.0
00065***
0.0
00066***
0.0
00066***
0.0
00029
0.0
00025
0.0
00026
0.0
00020
0.0
00018
0.0
00018
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Curr
ent
gra
nts
/T
ota
lgra
nts
%-0
.007634***
-0.0
07706***
-0.0
07700***
-0.0
06281***
-0.0
06344***
-0.0
06344***
-0.0
11520***
-0.0
12609***
-0.0
12623***
-0.0
13022***
-0.0
13644***
-0.0
13653***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
CL
%vote
s-
regio
nal
govern
ment
ballots
-0.0
01987***
-0.0
02001***
-0.0
01999***
-0.0
02378***
-0.0
02377***
-0.0
02377***
-0.0
01435***
-0.0
01359**
-0.0
01364**
-0.0
01858***
-0.0
01767***
-0.0
01770***
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Oth
ers
%vote
s-
regio
nal
govern
ment
ballots
0.0
06638***
0.0
06655***
0.0
06654***
0.0
07590***
0.0
07605***
0.0
07605***
0.0
04375***
0.0
04381***
0.0
04382***
0.0
05382***
0.0
05273***
0.0
05275***
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Year
2004
0.0
34066**
-0.2
23636***
-0.1
86672***
0.0
63686***
-0.2
20738***
-0.1
79235***
-0.0
28614**
-0.2
51501***
-0.2
17560***
-0.0
01684
-0.2
66420***
-0.2
24569***
(0.0
17)
(0.0
12)
(0.0
12)
(0.0
18)
(0.0
13)
(0.0
12)
(0.0
14)
(0.0
11)
(0.0
10)
(0.0
15)
(0.0
11)
(0.0
11)
Year
2005
0.0
90274***
-0.1
41505***
-0.1
14557***
0.1
36879***
-0.1
17419***
-0.0
87158***
-0.0
02602
-0.2
02168***
-0.1
77339***
0.0
30439**
-0.2
01330***
-0.1
70744***
(0.0
15)
(0.0
12)
(0.0
11)
(0.0
17)
(0.0
12)
(0.0
11)
(0.0
13)
(0.0
11)
(0.0
11)
(0.0
13)
(0.0
12)
(0.0
11)
Year
2006
-0.3
12938***
0.1
05950***
0.1
24046***
-0.2
82131***
0.1
89733***
0.2
10044***
-0.4
07454***
-0.0
09898
0.0
06737
-0.4
08367***
0.0
75628***
0.0
96090***
(0.0
19)
(0.0
09)
(0.0
09)
(0.0
19)
(0.0
09)
(0.0
09)
(0.0
18)
(0.0
10)
(0.0
10)
(0.0
19)
(0.0
09)
(0.0
09)
Year
2007
-0.5
90672***
-0.6
65329***
-0.5
74933***
-0.6
86280***
(0.0
23)
(0.0
23)
(0.0
21)
(0.0
22)
Year
2008
-0.4
76310***
-0.2
78769***
-0.2
57714***
-0.5
16360***
-0.2
89328***
-0.2
65678***
-0.4
37558***
-0.2
37646***
-0.2
17685***
-0.4
96322***
-0.2
42700***
-0.2
18482***
(0.0
13)
(0.0
16)
(0.0
16)
(0.0
13)
(0.0
17)
(0.0
17)
(0.0
12)
(0.0
13)
(0.0
13)
(0.0
12)
(0.0
13)
(0.0
13)
Year
2009
-0.3
96701***
-0.1
70900***
-0.0
72933***
-0.4
38190***
-0.1
80884***
-0.0
70890***
-0.3
71150***
-0.1
45855***
-0.0
53535**
-0.4
17417***
-0.1
36443***
-0.0
24463
(0.0
19)
(0.0
25)
(0.0
25)
(0.0
20)
(0.0
26)
(0.0
26)
(0.0
16)
(0.0
21)
(0.0
21)
(0.0
18)
(0.0
22)
(0.0
22)
Year
2010
-0.1
19202***
-0.0
73055***
-0.1
22968***
-0.0
71140**
-0.0
92386***
-0.0
48722**
-0.0
74398***
-0.0
21461
(0.0
27)
(0.0
27)
(0.0
28)
(0.0
29)
(0.0
23)
(0.0
23)
(0.0
23)
(0.0
23)
Const
ant
5.1
30354***
14.5
17003***
14.2
10494***
4.9
79291***
15.5
41250***
15.1
97568***
5.6
61644***
14.9
22373***
14.6
40548***
6.2
43890***
17.2
96528***
16.9
46861***
(0.3
91)
(0.3
61)
(0.3
56)
(0.4
11)
(0.3
95)
(0.3
90)
(0.3
67)
(0.3
31)
(0.3
27)
(0.4
18)
(0.4
02)
(0.3
97)
Obse
rvati
ons
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
R-s
quare
d0.6
93
0.6
93
0.6
93
0.6
74
0.6
74
0.6
74
0.7
30
0.7
34
0.7
34
0.7
18
0.7
21
0.7
21
Munic
ipaliti
es
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
24
Tab
le9:
Coeffi
cien
tsp
oin
tes
tim
ate
s.D
epen
den
tvari
ab
le:
fees
bu
rden
.F
ixed
effec
tF
GL
Ses
tim
ato
r.F
ull
mod
el.
VA
RIA
BL
ES
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
VF
I1-
Gra
nts
/T
ota
lE
xp
endit
ure
%-0
.005115***
-0.0
08433***
-0.0
08408***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I2-
(Gra
nts
+T
ax
Shari
ng)/
Tota
lE
xp
endit
ure
%-0
.008947***
-0.0
10998***
-0.0
10971***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I3-
Gra
nts
/O
wn
Revenues
%-0
.007661***
-0.0
14519***
-0.0
14503***
(0.0
01)
(0.0
01)
(0.0
01)
VF
I4-
(Gra
nts
+T
ax
Shari
ng)/
Ow
nR
evenues
%-0
.018740***
-0.0
24358***
-0.0
24322***
(0.0
02)
(0.0
02)
(0.0
02)
VF
I1xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I1xH
FIl
oc2
-0.0
00001***
(0.0
00)
VF
I1xH
FIl
oc3
-0.0
00001***
(0.0
00)
VF
I2xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I2xH
FIl
oc2
-0.0
00001***
(0.0
00)
VF
I2xH
FIl
oc3
-0.0
00001***
(0.0
00)
VF
I3xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I3xH
FIl
oc2
-0.0
00002***
(0.0
00)
VF
I3xH
FIl
oc3
-0.0
00002***
(0.0
00)
VF
I4xH
FIl
oc1
-0.0
00000***
(0.0
00)
VF
I4xH
FIl
oc2
-0.0
00002***
(0.0
00)
VF
I4xH
FIl
oc3
-0.0
00002***
(0.0
00)
HF
Iloc1
-M
ax
avera
ge
incom
e-
avera
ge
incom
e0.0
00004***
0.0
00001
0.0
00009***
0.0
00009***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc2
-M
ean
avera
ge
incom
e-
avera
ge
incom
e-0
.000012
-0.0
00066**
0.0
00057**
-0.0
00014
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
HF
Iloc3
-M
edia
navera
ge
incom
e-
avera
ge
incom
e-0
.000010
-0.0
00062**
0.0
00059**
-0.0
00010
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
RM
I-0
.132211***
-0.1
05407***
-0.1
05827***
-0.1
08008***
-0.1
04402***
-0.1
04875***
-0.1
70430***
-0.1
12766***
-0.1
13690***
-0.1
59763***
-0.1
37330***
-0.1
38516***
(0.0
39)
(0.0
40)
(0.0
40)
(0.0
40)
(0.0
40)
(0.0
40)
(0.0
39)
(0.0
37)
(0.0
37)
(0.0
39)
(0.0
36)
(0.0
36)
LA
Gfe
es
burd
en
%0.2
06252***
0.2
05046***
0.2
05054***
0.2
03378***
0.2
02748***
0.2
02755***
0.2
03953***
0.2
00654***
0.2
00658***
0.1
95464***
0.1
92876***
0.1
92881***
(0.0
32)
(0.0
32)
(0.0
32)
(0.0
32)
(0.0
32)
(0.0
32)
(0.0
31)
(0.0
31)
(0.0
31)
(0.0
31)
(0.0
31)
(0.0
31)
Adm
inis
trati
ve
exp
endit
ure
/to
tal
exp
%-0
.006772**
-0.0
06851**
-0.0
06855**
-0.0
06387**
-0.0
06476**
-0.0
06480**
-0.0
06966**
-0.0
07410***
-0.0
07417***
-0.0
06368**
-0.0
06870***
-0.0
06878***
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
Cult
ure
exp
endit
ure
/to
tal
exp
%0.0
06485
0.0
06421
0.0
06432
0.0
06766
0.0
06684
0.0
06691
0.0
08512*
0.0
08198*
0.0
08237*
0.0
10835**
0.0
10306**
0.0
10339**
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
Sp
ort
exp
endit
ure
/to
tal
exp
%-0
.001789
-0.0
02661
-0.0
02668
-0.0
00425
-0.0
01152
-0.0
01163
-0.0
02741
-0.0
04640
-0.0
04636
-0.0
01994
-0.0
03714
-0.0
03713
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
Touri
smexp
endit
ure
/to
tal
exp
%0.0
16187*
0.0
16573*
0.0
16572*
0.0
15638*
0.0
15830*
0.0
15829*
0.0
19220**
0.0
21016**
0.0
21044**
0.0
20746**
0.0
22028***
0.0
22049***
(0.0
09)
(0.0
09)
(0.0
09)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
09)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
(0.0
08)
Educati
on
exp
endit
ure
/to
tal
exp
%-0
.018800***
-0.0
18363***
-0.0
18376***
-0.0
17771***
-0.0
17612***
-0.0
17624***
-0.0
19107***
-0.0
18594***
-0.0
18612***
-0.0
17376***
-0.0
17201***
-0.0
17222***
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
Local
police
exp
endit
ure
/to
tal
exp
%0.0
46256***
0.0
46281***
0.0
46258***
0.0
45821***
0.0
45807***
0.0
45789***
0.0
45047***
0.0
44601***
0.0
44548***
0.0
43028***
0.0
42515***
0.0
42461***
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
(0.0
06)
Tra
ffic
man.
exp
endit
ure
/to
tal
exp
%-0
.014430***
-0.0
14324***
-0.0
14328***
-0.0
13806***
-0.0
13759***
-0.0
13762***
-0.0
14451***
-0.0
14985***
-0.0
14987***
-0.0
13287***
-0.0
13907***
-0.0
13910***
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Landin
gexp
endit
ure
/to
tal
exp
%-0
.000598
-0.0
00282
-0.0
00281
-0.0
00283
-0.0
00141
-0.0
00142
-0.0
02215
-0.0
02171
-0.0
02178
-0.0
03228*
-0.0
03295*
-0.0
03302*
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Socia
lexp
endit
ure
/to
tal
exp
%0.0
18935***
0.0
19400***
0.0
19409***
0.0
19976***
0.0
20191***
0.0
20194***
0.0
19705***
0.0
20520***
0.0
20547***
0.0
22581***
0.0
23016***
0.0
23035***
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
07)
(0.0
06)
(0.0
06)
25
Ec.
pla
nnin
gexp
endit
ure
/to
tal
exp
%0.0
58984***
0.0
59065***
0.0
59076***
0.0
58535***
0.0
58591***
0.0
58602***
0.0
58009***
0.0
57484***
0.0
57499***
0.0
56137***
0.0
55631***
0.0
55650***
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
Pro
pert
yta
x-
ord
inary
taxra
te%
-0.1
41367
-0.1
46235
-0.1
46447
-0.1
53097
-0.1
52328
-0.1
52445
-0.1
72724*
-0.1
97266**
-0.1
97676**
-0.2
29530**
-0.2
42949**
-0.2
43250**
(0.0
96)
(0.0
96)
(0.0
96)
(0.0
95)
(0.0
95)
(0.0
95)
(0.0
97)
(0.0
97)
(0.0
97)
(0.0
95)
(0.0
95)
(0.0
95)
Pro
pert
yta
x-
taxra
tem
ain
resi
dence
%-0
.025417
-0.0
32237
-0.0
31804
-0.0
10746
-0.0
19659
-0.0
19402
-0.0
56869
-0.0
76142
-0.0
75435
-0.0
58439
-0.0
82786
-0.0
82142
(0.0
98)
(0.0
98)
(0.0
98)
(0.0
97)
(0.0
97)
(0.0
97)
(0.0
96)
(0.0
96)
(0.0
96)
(0.0
94)
(0.0
94)
(0.0
94)
Dum
my
inc1
0.0
60274
0.0
63851
0.0
63717
0.0
61665
0.0
71631
0.0
71650
0.0
72838
0.0
67134
0.0
66847
0.0
89667**
0.1
00732**
0.1
00689**
(0.0
45)
(0.0
46)
(0.0
46)
(0.0
45)
(0.0
45)
(0.0
45)
(0.0
45)
(0.0
45)
(0.0
45)
(0.0
45)
(0.0
44)
(0.0
44)
Dum
my
inc2
0.0
38908
0.0
37842
0.0
37899
0.0
49094
0.0
51285
0.0
51357
0.0
30651
0.0
15782
0.0
15811
0.0
44183
0.0
37981
0.0
38106
(0.0
34)
(0.0
34)
(0.0
34)
(0.0
34)
(0.0
34)
(0.0
34)
(0.0
33)
(0.0
33)
(0.0
33)
(0.0
33)
(0.0
32)
(0.0
32)
Dum
my
inc3
-0.0
03276
-0.0
02286
-0.0
02222
0.0
07194
0.0
07254
0.0
07279
-0.0
17841
-0.0
23021
-0.0
22969
-0.0
11981
-0.0
16931
-0.0
16892
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
(0.0
15)
Unit
ary
est
ate
incom
e-
Euro
PC
-0.0
00101*
-0.0
00097*
-0.0
00097*
-0.0
00099*
-0.0
00099*
-0.0
00099*
-0.0
00107*
-0.0
00095*
-0.0
00096*
-0.0
00111**
-0.0
00105**
-0.0
00105**
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Unit
ary
tota
lin
com
e-
Euro
PC
-0.0
00044***
-0.0
00109***
-0.0
00107***
-0.0
00050***
-0.0
00154***
-0.0
00151***
-0.0
00035***
-0.0
00091***
-0.0
00089***
-0.0
00037***
-0.0
00164***
-0.0
00160***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Com
merc
ial
est
ate
valu
e-
Euro
/m
sq-0
.000081**
-0.0
00084***
-0.0
00083***
-0.0
00085***
-0.0
00086***
-0.0
00086***
-0.0
00086***
-0.0
00089***
-0.0
00088***
-0.0
00095***
-0.0
00097***
-0.0
00097***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Resi
denti
al
est
ate
valu
e-
Euro
/m
sq-0
.000017
-0.0
00018
-0.0
00018
-0.0
00006
-0.0
00008
-0.0
00008
-0.0
00033
-0.0
00037
-0.0
00037
-0.0
00031
-0.0
00035
-0.0
00036
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
31
Dec
0.0
00004***
0.0
00003***
0.0
00003***
0.0
00004***
0.0
00004***
0.0
00004***
0.0
00004***
0.0
00004***
0.0
00004***
0.0
00005***
0.0
00005***
0.0
00005***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Popula
tion
0-1
4%
0.0
04342
0.0
04469
0.0
04380
0.0
03626
0.0
04025
0.0
03957
0.0
07487**
0.0
08781**
0.0
08630**
0.0
09443***
0.0
11165***
0.0
11006***
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Popula
tion
over
65
%0.0
01813
0.0
01240
0.0
01209
0.0
01497
0.0
01274
0.0
01251
0.0
02841
0.0
02233
0.0
02177
0.0
03351
0.0
03186
0.0
03128
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
03)
(0.0
02)
(0.0
02)
(0.0
02)
Fore
ingner
popula
tion
%0.0
01096
0.0
01622
0.0
01614
0.0
01212
0.0
01497
0.0
01490
0.0
00945
0.0
01908
0.0
01894
0.0
01128
0.0
01817
0.0
01800
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Cancelled/P
opula
tion
%0.0
04428
0.0
04590
0.0
04601
0.0
04127
0.0
04084
0.0
04093
0.0
04424
0.0
04891
0.0
04907
0.0
03974
0.0
04023
0.0
04039
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
05)
(0.0
04)
(0.0
04)
New
regis
tere
d/P
opula
tion
%-0
.003627
-0.0
03097
-0.0
03066
-0.0
04359
-0.0
04266
-0.0
04243
-0.0
04270
-0.0
02967
-0.0
02902
-0.0
06525*
-0.0
05988*
-0.0
05926*
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
(0.0
04)
Cohousi
ng/p
opula
tion*1000
-0.0
00935***
-0.0
00996***
-0.0
00995***
-0.0
01010***
-0.0
01049***
-0.0
01048***
-0.0
00612***
-0.0
00658***
-0.0
00653***
-0.0
00570***
-0.0
00618***
-0.0
00613***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
LA
G1
Borr
ow
ing
-E
uro
PC
0.0
00103***
0.0
00106***
0.0
00106***
0.0
00113***
0.0
00114***
0.0
00114***
0.0
00075***
0.0
00070***
0.0
00070***
0.0
00067***
0.0
00062**
0.0
00062**
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
Curr
ent
gra
nts
/T
ota
lgra
nts
%-0
.003784***
-0.0
04203***
-0.0
04220***
-0.0
04775***
-0.0
04872***
-0.0
04880***
-0.0
05584***
-0.0
06932***
-0.0
06980***
-0.0
09362***
-0.0
10082***
-0.0
10119***
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
CL
%vote
s-
regio
nal
govern
ment
ballots
0.0
02191**
0.0
02217**
0.0
02211**
0.0
02015*
0.0
02072*
0.0
02068*
0.0
02495**
0.0
02654**
0.0
02645**
0.0
02508**
0.0
02718***
0.0
02711***
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
01)
Oth
ers
%vote
s-
regio
nal
govern
ment
ballots
0.0
01682
0.0
01909
0.0
01910
0.0
02168
0.0
02242
0.0
02240
0.0
00470
0.0
00473
0.0
00473
0.0
00159
0.0
00034
0.0
00030
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
(0.0
02)
Year
2004
0.0
22085
0.0
12399
0.0
15392
0.0
37885**
0.0
07145
0.0
12894
-0.0
22258
-0.0
09810
-0.0
08289
-0.0
35104**
-0.0
39790***
-0.0
33461***
(0.0
15)
(0.0
14)
(0.0
14)
(0.0
15)
(0.0
14)
(0.0
14)
(0.0
15)
(0.0
14)
(0.0
13)
(0.0
14)
(0.0
13)
(0.0
13)
Year
2005
-0.0
37428**
-0.0
43396***
-0.0
41145***
-0.0
22434
-0.0
46844***
-0.0
42594***
-0.0
94229***
-0.0
79627***
-0.0
78482***
-0.1
21013***
-0.1
15210***
-0.1
10513***
(0.0
15)
(0.0
15)
(0.0
14)
(0.0
14)
(0.0
15)
(0.0
14)
(0.0
16)
(0.0
15)
(0.0
15)
(0.0
16)
(0.0
16)
(0.0
15)
Year
2006
-0.1
03407***
-0.0
54988***
-0.0
53474***
-0.1
03908***
-0.0
31367***
-0.0
28567***
-0.1
53323***
-0.1
17304***
-0.1
16721***
-0.2
06527***
-0.1
19685***
-0.1
16709***
(0.0
22)
(0.0
12)
(0.0
12)
(0.0
22)
(0.0
11)
(0.0
10)
(0.0
23)
(0.0
15)
(0.0
15)
(0.0
25)
(0.0
13)
(0.0
13)
Year
2007
-0.0
71316***
-0.1
02121***
-0.0
70983***
-0.1
28352***
(0.0
23)
(0.0
24)
(0.0
23)
(0.0
23)
Year
2008
0.0
18315
0.0
44715***
0.0
46651***
-0.0
01703
0.0
40052***
0.0
43378***
0.0
38875***
0.0
78883***
0.0
80491***
0.0
17695
0.0
97173***
0.1
01141***
(0.0
15)
(0.0
10)
(0.0
10)
(0.0
15)
(0.0
10)
(0.0
10)
(0.0
14)
(0.0
10)
(0.0
10)
(0.0
14)
(0.0
10)
(0.0
10)
Year
2009
-0.0
05990
0.0
21651
0.0
30832**
-0.0
18900
0.0
24522*
0.0
40022***
0.0
14245
0.0
55796***
0.0
62899***
0.0
11011
0.0
89630***
0.1
07712***
(0.0
17)
(0.0
15)
(0.0
15)
(0.0
16)
(0.0
15)
(0.0
15)
(0.0
17)
(0.0
15)
(0.0
15)
(0.0
16)
(0.0
15)
(0.0
16)
Year
2010
-0.0
04708
-0.0
00376
-0.0
00502
0.0
06825
0.0
30878*
0.0
34349**
0.0
70204***
0.0
78876***
(0.0
18)
(0.0
18)
(0.0
18)
(0.0
18)
(0.0
17)
(0.0
17)
(0.0
17)
(0.0
17)
Const
ant
2.7
20521***
3.8
42452***
3.8
19438***
3.0
69997***
4.6
95796***
4.6
47103***
2.8
34092***
4.1
21028***
4.1
11958***
3.6
81655***
5.9
49920***
5.8
98161***
(0.2
87)
(0.3
87)
(0.3
79)
(0.3
01)
(0.4
23)
(0.4
14)
(0.2
81)
(0.3
87)
(0.3
80)
(0.3
05)
(0.4
50)
(0.4
42)
Obse
rvati
ons
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
25,9
38
R-s
quare
d0.2
09
0.2
12
0.2
12
0.2
18
0.2
19
0.2
19
0.2
23
0.2
33
0.2
33
0.2
56
0.2
64
0.2
64
Munic
ipaliti
es
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
5,3
75
Robust
standard
err
ors
inpare
nth
ese
s***
p<
0.0
1,
**
p<
0.0
5,
*p<
0.1
26