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LEX LOCALIS - JOURNAL OF LOCAL SELF-GOVERNMENT
Vol. 13, No. 2, pp. 161 - 184, April 2015
Drivers for the Financial Condition of Local
Government: A Comparative Study Between
Italy and Spain
ISABEL BRUSCA, FRANCESCA MANES R OSSI & NATALIA AVERSANO 2
ABSTRACT This paper aims to analyse the influence of socio-
economic, political and financial factors on the financial conditionof Italian and Spanish local governments in a comparative approach.
The research is also aimed at understanding to what extent a modelfor the analysis of the financial condition can be generalized to
different contexts. We assume that the financial condition is a
multidimensional concept, with the results highlighting that while in
Spain there is a high correlation between the long term financial and
short term economic situations and an indicator can combine both
dimensions, in Italy both dimensions are differentiated. There arealso differences in the drivers of financial sustainability in both
countries.
K EYWORDS: • financial condition • financial sustainability •
financial health • financial indicators • local government • Spain •
Italy
CORRESPONDENCE ADDRESS: Isabel Brusca, University of Zaragoza, Department ofAccounting and Finance, Gran Ví, 50005 Zaragoza, Spain, email: [email protected] Manes Rossi, University of Salerno, Department of Management and
Information Technology, Via Giovanni Paolo II, 84084 Fisciano SA, Italy,[email protected]. Natalia Aversano, University of Salerno, Department ofManagement and Information Technology, Via Giovanni Paolo II, 84084 Fisciano SA,
Italy, [email protected].
DOI 10.4335/13.2.161-184(2015)
ISSN 1581-5374 Print/1855-363X Online © 2015 Lex localis (Maribor, Graz, Trieste, Split)Available online at http://journal.lex-localis.info.
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162 LEX LOCALIS - JOURNAL OF LOCAL SELF-GOVERNMENT
I. Brusca, F. Manes Rossi & N. Aversano: Drivers for the Financial Condition of Local Government: A Comparative Study Between Italy and Spain
1 Introduction
One of the effects of the recent financial crisis has been to force local governments
(LG) to deal with financial difficulties. In fact, while the resources available have
decreased, citizens continue to ask for an increasing amount and better quality of
public services.
Scholars have discussed at length, the factors that can determine or contribute tocreating financial distress or financial crisis (Groves and Valente, 2003, Klein et
al., 2003, Carmeli, 2007, Jones and Walkers, 2007) and – especially in recent
years under the incumbent financial crisis – many models have been proposed
both by practitioners and standard setters (CICA, 1997, ICMA, 2003; UK Audit
Commission, 2007) as well as scholars (Zafra-Gómez et al., 2009; Cohen et al.,2012, Manes Rossi, 2011; García-Sánchez et al., 2012) to prevent financial
distress. In addition, the IPSASB recently released a Recommended Practice
Guideline (RGS, 2013) “Reporting on the Long-Term Sustainability of an Entity’s
Finances”, highlighting the need to monitor the ability of public ent ities to sustain
their projects in the long-term.
This study aims to discuss the interesting research theme in a comparative
approach, by analysing the situation of all the Italian and Spanish local
governments with more than 60.000 inhabitants and relating their financial
conditions to some economic and social factors. Italy and Spain have been chosen
because they are two Southern European countries characterised by a Napoleonic
administrative tradition (Peter, 2008). In addition, their financial situation iscontrolled by the European Union.
The research is also aimed at understanding to what extent the use of financial
indicators to monitor the financial health of a local government can be generalized
to different contexts and whether a model can have or not an international
application to support both managers and politicians in assuming timely decisionsto avoid financial distress.
A set of indicators has been identified in accordance with previous literature and
its relevance has been evaluated with principal component analysis. The results
highlight that in Spain there is a high correlation between the long term and shortterm economic situations, with an indicator combining both dimensions. However,
in Italy two different indicators are necessary to measure both dimensions.
Furthermore, the number of inhabitants and density of the population are two
drivers for fiscal stress in Italy, while in Spain only the number of inhabitants is
significant.
The paper is organized in five sections, excluding the present introduction. First,
the literature review discusses the definitions of financial condition elaborated by
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scholars as well as the environmental, organizational and financial determinants
that can affect it. The third section describes the Italian and Spanish context, along
with the tools that have already been adopted to prevent financial distress. The
fourth section defines the objectives of the empirical research as well as theresearch design, while the fifth presents the results collected and discusses them in
accordance with the objectives. In the conclusion, the results achieved are
summarized, along with the limitations of the study and any possible future
developments.
2 The analysis of financial condition in local goverments: A literature
review
Since the first financial crisis experienced by large cities in the USA in the 1970-
80s, like New York and Cleveland, scholars have discussed the conditions andeffects of the so-called financial distress or financial crisis or fiscal strain(Honadle et al., 2004). As reported by Dollery and Crase (2006), there are
numerous definitions but no consensus about the concept of financial health and
financial condition. Rivenbark et al. (2010) revise the different concepts used and
define financial condition as “a local government’s ability to meet its ongoing
financial, service and capital obligations based on the status of resource flow and
stock as interpreted from annual financial statements”.
In some countries, the term ‘financial sustainability’ has become fashionable and
even several standard setters seem to prefer this expression. ThePriceWaterhouseCoopers (2006, 96) report states that “the financial sustainability
of a council is determined by its ability to manage expected financial requirementsand financial risks and shocks over the long term without the use of disruptive
revenue or expenditure measures”. Along the same lines, the RGS of the IPSASB
(2013) highlights the need to monitor the ability of public entities to sustain their
projects in the long-term. The RGS depicts three intertwined dimensions of long-
term financial sustainability: service dimension, revenue dimension and debit
dimension.
Assuming that there is a large variety of nuance inside the concept of financialsustainability, we consider that this can be analysed with reference to the financial
condition or financial health, which represents the ability to comply with current
and future obligations through a proper inflows by tax, transfers and services as
well as to sustain a certain service level, coherent with the citizens’ needs(Honadle et al., 2004). According to Groves and Valente (2003), from an internal
perspective, the financial condition can be synthesised in cash, budgetary, long run
and service solvency of the entity.
Several models have been developed with the aim of assessing the financial
condition, while preventing financial distress. The first group focuses on
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analysing the financial equilibrium of a LG every year in order to assess if a
condition of distress occurred or not (i.e. Jones and Walkers, 2007). The secondgroup, which is larger, aims at forecasting the future ability of the LG in
maintaining a financial equilibrium (Kleine et al., 2003; Zafra-Gómez et al., 2009;
Cohen et al., 2012; García-Sánchez et al., 2012; Manes Rossi et al., 2012). These
models adopt a large variety of techniques, ranging from basic approaches such as
accounting information and financial reporting analysis (e.g. Kleine et al., 2003;
Manes Rossi, 2011), to more sophisticated statistical modelling approaches, evenwith the aim of discriminating a financial healthy LG from a distressed one (e.g.
Zafra-Gómez et al., 2009; Cohen et al., 2012; García-Sánchez et al., 2012; Manes
Rossi et al., 2012).
In addition, standard setters and regulators all over the word have developedseveral models to assess financial condition. It is well-known that central
governments need to monitor the financial health of a LG. In several countries, the
control agencies have defined some predictive models. For example, in France, the
Direction Générale des Collectivités Locales (1997) has provided an alert system
composed of 7 indicators, while in Australia and the UK, models have been
prepared by control agencies to discriminate a healthy LG from non-healthy ones.Similarly, in USA, the 10-point scale proposed by Brown (1993) or the model
proposed by the ICMA as developed by Groves and Valente (2003) have been
largely adopted (Zafra-Gómez et al., 2009).
In the European context, some studies focused on a LG credit ratings and
solvability assessment (Manes Rossi, 2011) for the analysis of the financialcondition. In fact, financial equilibrium is an essential prerequisite in order to gain
access to the capital market, by obtaining a good rating (Caperchione and
Salvatori, 2012).
Simultaneously, there is an increasing amount of literature on identifying the
determinants that can provoke or accelerate some detrimental financial conditions.Some scholars consider environment factors, such as socioeconomic forces
(Peterson 1976; Capalbo and Grossi, 2014), as the principal external determinants
that can affect the financial situation of a LG, assuming that they affect both the
citizens’ need and demand of public services as well as productive costs (Andrews
et al., 2005; Boyne et al., 2001). Empirical research has tried to analyse the effectsof population, density of the population or gross domestic product (Bahl and
Duncombe, 1993; Zafra-Gómez et al., 2009; Guillamón et al., 2011; García-
Sánchez et al., 2012; Vicente et. al., 2013).
Political factors have also been another issue considered in current literature as
influencing the financial condition of local governments, considering thatconservative parties have a lower level of debt (Kiewiet and Szalky, 1996),
although many studies have not found a relationship between political ideologies
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and the level of debt (Vicente et. al., 2013). Furthermore, the incidence of political
budget cycles on debt has also been studied (Benito et al. , 2012).
In addition, organizational factors such as human resources and capabilities thatthe organization has acquired or developed, have been considered as pivotal for
the LG to have the ability to cope with the need of changes, which in turn support
the possibility of maintaining a financial equilibrium (Carmeli and Cohen, 2001;
Carmeli, 2007). Considering current literature, the study aims to contribute to this
field by creating a model for the analysis of the financial condition of Italian andSpanish LG, that combines all the above dimensions and tests to what extent
environment factors can influence the financial condition.
3 The Italian and Spanish scenario
3.1 The control of financial health in Italy
Italy belongs to those European countries characterized by a bureaucratic
approach in Public administration, where any reforms are mainly implemented
through the law and with a highly legalistic governance culture (Ongaro and
Vallotti, 2008). Italian Local Governments (ILG) manage most of the public
services and in the last decades, there has been an increasing use of partnershipswith other public or private operators to run services like transportation, waste,
water as well as many others. ILG obtain resources only partially by transfers and
grants from Central and Regional governments, while they have the power to bothincrease local taxes as well as manage their own assets.
The law, which also provides a complete set of rules for accounting, describes the
conditions of financial health and sets out ten parameters as indicators of distress
(Manes Rossi, 2011). According to D. Lgs. 267 (art.244) financial distress occurs
when the entity, municipality or province is no longer able to perform its essential
functions and deliver due services, or when it is no longer able to meet debt with
third parties through the ordinary means of restoring the fiscal balance or debtinstrument with an off balance-sheet. The accounting systems requires both the
preparation of a budget and reporting as well as a budgetary modified cash- andcommitment-based accounting systems for both, even if the reporting is integrated
by financial and income statements prepared in accordance with accrual principles
(Nasi and Steccolini, 2008). Three different institutions play the role of watchdogs
regarding the financial condition of ILG: the Ministry of Interior, the NationalAudit Court and the State General Accounting Department (which is a part of the
Ministry of Economy). In the case financial distress is declared by the mayor, an
Extraordinary Board is appointed by the central government, upon the suggestion
of the Ministry of the Interior, with the duty to prepare and manage a plan to
extinguish all the expired debts. Meanwhile, the city council has to reorganize the
whole activity, with the aim of removing what has provoked the financial
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disequilibrium. The declaration of distress has a significant impact on the citizens:
local-tax increases, services are reduced to the mere essential and no personnelcan be hired until the financial equilibrium is restored.
In order to avoid this condition, since 2012 a new regime has been introduced –
the so-called financial re-equilibrium procedure – where the city council, with the
aim of facing an incumbent distress, prepares a plan (no longer than 10 years) to
cope with the financial equilibrium condition.
3.2 The control of financial sustainability in Spain
Spanish local governments have increased the services delivered since the
decentralisation process in force since the 1990s. The increase in services and theimportant expenditures in infrastructures and equipment have led to a continuous
increase in the level of debt of governments. With the financial crisis, the situation
has been aggravated, with the control of public expenditure and debt having
become one of the main objectives for public policies.
In this framework, Spanish Central Governments have always tried to control theincrease of debt of local governments and different laws limit the use of debt for
financing local government expenditures.
These controls have been highlighted by the Spanish financial crisis and different
initiatives have been carried out under the Stability and Growth Pact of the
Member States of the European Union.
With the aim of fulfilling the Treaty, the Spanish Law of Budgetary Stability and
Financial sustainability prohibits public entities from obtaining deficit, increasing
the expenditure over the increase in the Gross Domestic Product (GDP) and limits
public sector administrations debt to 60% of the GDP (44% for Central
Government, 13% Autonomous Communities or States and 3% for localgovernment). Those entities that do not fulfill the objectives of budgetary stability
must prepare an economic-financial plan that within a year will allow the entity to
fulfill these objectives. The entities that do not achieve the limit of debt must also
elaborate a plan to balance the situation.
In this framework, financial sustainability studies are particularly timely and
relevant both in Spain and Italy, where the control of financial health is currently a
priority of the Government.
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4 Research design
4.1 Objectives and Methodology
In order to carry out the analysis, all the Italian and Spanish Local Governments
with more than 60,000 inhabitants were selected.
The analysis has two main objectives:
a) The construction of a model for the analysis of the financial condition thatidentifies what dimensions must be considered. Several studies (i.e. Groves and
Valente, 2003; Klein et al., 2003; Jones and Walkers, 2007; Zafra-Gómez et al.,
2009; Cohen et al., 2012; García-Sánchez et al., 2012; Manes Rossi et al., 2012)
have proposed a methodology for analysing the financial condition of a local
government but it does not coincide with what indicators must be used and how itmust be propounded in order to obtain a score determining the financial condition ofa local government. Furthermore, current literature argues that different indicators
can be suitable for different legal and economic environments (Carmeli, 2007) but
there is no empirical research that proves it.
In this framework, we have tried to obtain a model for the financial analysis of local
governments using both financial and economic indicators. Considering that theanalysis of the financial health of a government requires taking into account
different perspectives, we have used a principal component analysis to identify what
the most relevant indicators are. The variables included in the analysis are based onthe level of debt of the government, along with variables representing the economic
capacity of the entity.
The analysis was carried out in both Spain and Italy, with the aim of not only
comparing the two countries but also to study to what extent the same determinants
can affect the financial condition of Italian and Spanish LG. As previously
suggested by some scholars, the heterogeneity of legal structures and socioeconomic
framework must be controlled (Blejer and Cheasty, 1991). Thus, we intend to verifyto what extent this can influence the analysis of financial condition and whether it is
possible to apply the model on an international level.
The methodology used for this part is principal component analysis (PCA). This
method allows to reduce a data set based on observations of variables into a set of
values of new variables called principal components (PC), characterized by the factthat they are interrelated. The components are built as a linear combination of the
original variables and collect most of the information contained in the original
variables (Lattin et al. 2003). The first PC explains the maximum percentage of the
total variance of the data, the second the maximum percentage of the remaining
variance, and so on.
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168 LEX LOCALIS - JOURNAL OF LOCAL SELF-GOVERNMENT
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b) The identification of factors and drivers that can determine or at least affect the
financial condition. Most of the previous studies (Carmeli, 2007; Zafra-Gómez etal., 2009; Manes Rossi et al. 2012; Vicente et. al., 2013) focus on the analysis of
debt per capita to analyse what factors determine debt level. Our study focuses on
the financial indicators identified in the first part of the analysis.
The objective is to understand what variables affect or can be used to predict a
detrimental change of the financial condition in local governments in Italy andSpain. We use a linear regression approach to model the relationship between the
financial condition and the explanatory variables.
First, we carried out a simple linear regression analysis with the aim of analysing
whether there is or not the influence of each variable on the financial condition. Thedependent variable is the financial indicator obtained and the independent variables
are the different dimensions. We then considered the dimensions that affect the local
fiscal health according to Hendrick (2004) and grouped the variables into four
classes: size, socio-economic, political and financial structure.
FS= f (size, socioeconomic, political and financial factors).
Simple linear regression analysis allows to select the variables that are significant in
order to construct a model to determine the financial condition that includes the
independent variables through multiple linear regressions. We have used the
stepwise model in which the choice of predictive variables is carried out by an
automatic procedure.
4.2 Sample and Variables
The sample used for the analysis includes all the Italian and Spanish local
governments with more than 60,000 inhabitants: 102 Italian and 123 Spanish local
governments. In order to analyse the financial condition, the budgetary data for2012 and 2011 were collected, along with other information about the
socioeconomic and political variables used in the analysis, which refer to 2012.
We focus only on the largest cities since they have a high percentage of the total
debt of the local government of both countries, while the debt of the smaller citieshas relatively less importance and is also lower. Bigger cities also have a higher
percentage of the population in both countries, thus representing a higher percentage
of local government expenditure (Hulten and Peterson, 1984; Rivers and Yates,
1997; Vicente et. al., 2013). Furthermore, the data are more reliable for the bigger
entities and sometimes are not available for smaller entities.
Table 1 shows the variables used for the principal component analysis and how they
are defined as well as the descriptive statistics for Italy and Spain.
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Table 1: Variables for the analysis of Principal Components
The variables expressing the long term situation, in accordance with some previousstudies (Carmeli, 2007; García-Sánchez et al., 2012; Vicente et. al., 2013) focus on
the level of debt and the capacity of the entity to repay that debt.
Whereas, the variables expressing the short term stability focus on the operating
revenues surplus (Brown, 1993; Cohen et al., 2012; Manes Rossi et al. 2012;
Vicente et. al., 2013).
VARIABLE Definition Country
Mean
Std.
Deviation
L O N
G T E R M F
I N A N C I A L
S I T U A T I O N
Debt per capita Total debt/Number ofinhabitants
ItalySpain
719.24765.23
471.60516.27
Debt over GDP Total debt/GDP Italy
Spain
4.65
3.71
3.70
2.82
Debt overOperative
revenues
Total debt/operativerevenues
ItalySpain
74.5985.30
45.7756.42
Variation of debtin the year per
capita
Debt 2012-debt2011/Number of
inhabitants
ItalySpain
-58.18210.03
102.41357.41
Debt service Payments fordebt+Payments for
interest of
debts/operatingrevenues
ItalySpain
10.6510.92
7.896.60
S H O R T T E R M S
T A B I L I T Y
Operative Surplus per capita
(Operative revenues-Operative
expenditures)/number
of inhabitants.
ItalySpain
115.00171.262
87.98423.81
Operative Surplus
over operative
revenues
(Operative revenues-
Operative
expenditures)/operative revenues.
Italy
Spain
9.74
10.55
5.08
12.29
Operative
expenditurecoverage
Operative
expenditure/operativerevenues
Italy
Spain
90.26
89.45
5.08
12.29
Debt Payments
coverage
(Operative revenues-
operativeexpenditure)/payments for
debt
Italy
Spain
2.25
22.08
2.56
222.34
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The mean of the debt per capita of local governments is greater for Spanish LG than
for Italian LG, where the standard deviation is also higher. The percentage of debtover operative revenues is also higher for Spain, with it reaching 85.30. However,
the debt represents a higher percentage of GDP in Italy than in Spain. During 2012,
the data show that while in Italy the mean of the debt per capita decreased to €58.18
per capita, in Spain it increased to €210.03.
Using the indicators constructed with the principal component analysis as dependentvariables, in line with some previous studies, we tried to analyse the effect of size
(García-Sánchez et al., 2012; Vicente et. al., 2013), socio-economic (Zafra-Gómez
et al., 2009; Vicente et. al., 2013), financial (Skidmore and Scorsone, 2011; Zafra-
Gómez et al., 2009) and political characteristics (Vicente et. al., 2013). Furthermore,
we carried out the same analysis using the variable debt per capita, studied innumerous papers as a determinant of financial health in local government (Carmeli,
2007; Zafra-Gómez et al., 2009; Guillamón et al., 2011; Manes Rossi et al. 2012;
Vicente et. al., 2013).
Table 2 shows the independent variables used for the analysis of the factors that
influence the financial condition as well as the descriptive statistics for Italy andSpain.
Table 2: Independent Variables
VARIABLE Definition Country MeanStd.
Deviation
S I Z E
Population (INH.)
Number of
inhabitantsItalySpain
176.023190.464
306.928332.177
Density of population(DP)
Number ofinhabitants/Km2
ItalySpain
1,486.5
42,696.7
26
1,642.733,323.74
S O C I O E C O N O M
I C
Unemployment (U)% of unemployment
people.
Italy
Spain
11.83
15.29
5.40
3.79
Gross Domestic Product
(GDP)
Total GrossDomestic Product/n.inhabitants.
Italy
Spain
16,605.19
22,166.60
3,870.51
5,561.65
P O L Í T I C A L Political party in
government (PP)
Conservative party=0Progressive party=1
Italy
Spain
0.81
0.33
0.39
0.470
Gender of theMayor(G)
Man=0Woman=1
ItalySpain
0.060.23
0.240.421
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F I N A N C I A L S T R U C T U R E
Capital
expenditure(KE)
Total capitalexpenditure/n.
inhabitants
Italy
Spain
187.25
84.76
230.58
61.60
Personalexpenditure(PE)
Personalexpenditure/n.
operative revenues
ItalySpain
27.5836.44
8.426.80
Fiscal pressure(FP)Fiscal revenues/n.inhabitants
ItalySpain
691.00613.26
232.52183.90
Fiscal revenues over
GDP (FR)
Fiscal
revenues/GDP
Italy
Spain
0.043
0.029
0. 0174
0.012
Financial
independence(FI)
Fiscal
revenues/operativerevenues
Italy
Spain
62.71
66.45
14.72
9.92
Operative grants (OG)
Grants for current
expenditure/operative revenues
Italy
Spain
17.02
31.21
15.39
9.84
We have constructed three multiple linear regressions, one for each dependent
variable, as follows:Y= α + β 1 INH + β 2 DP + β 3 U + β 4 GDP+ β 5 PP+ + β 6 G + β 7 KE + β 8 PE+ β 9 FP + β 10 FR+β 11 FI + β 12 OG+ ε
Regarding the data, it is worth noting that the personal expenditure index is a little
higher in Spain. The fiscal pressure per capita is however higher in Italy, where it
reaches €691 in Italy and €613 in Spain, representing 4.3% of the GDP in Italy and2.09% in Spain. Nevertheless, the financial independence ratio of Italian local
governments reaches 62.71% compared to 66.45% in Spain. Whereas, relating to
the size, the mean of the number of inhabitants - as well as the density of
population - is slightly higher for Spain. There are also differences in the GDP per
capita, higher in Spain than in Italy but also with more variability. Nevertheless, the
unemployment index is also higher in Spain, with a mean of 15.29%, while in Italy,it is 11.83%. Regarding the political variables, in most of the Italian LG, there is a
mayor from a progressive party (only in 19% of the cities does a conservative party
govern) and in 94% of the cases, the mayor is a man. In Spain, 67.5% of the mayors
are from a conservative party and the percentage of women increases to 22.8%.
5 Analysis of the results
5.1 Principal Component Analysis
In order to carry out the PCA, first all the variables included in table 1 were
considered. However, considering both the problems of communality and
redundancy, some of them were removed, as highlighted in table 4. Tables 3 and 4show the results and Graph 1 compares the components for Italy and Spain.
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Table 3: Matrix of the Principal Component
Country ComponentInitial Eigen values
Total % of Variance % Cumulative
Italy1 2.752 45.871 45.871
2 2.156 35.939 81.811
Spain1 3.860 64.342 64.342
2 1.045 17.409 81.750
Table 4: Extraction Method: Principal Component Analysis with two componentextracts
Italy SpainComponents Components
1 2 1 2
Debt per capita .943 .173 .900 .250
Debt/ GDP .913 .200 .884 .226
Debt/Op. revenues .863 .089 .948 .122
Op. Surplus/ Percapita -.062 .911 -.801 .409Op. Surplus /op. revenues -.050 .939 -.837 .404
Debt-payment -.527 .604 -.164 -.766
Graph 1: Principal components
The PCA shows that there are some differences in the dimensions for the analysis
of the financial condition in Italian and Spanish local governments.
In Italy, the results show that a first component includes the variables representing
the level of debt which is called long term financial situation. The first componentexplains a 45.87% of the variance.
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Long term financial situation = 0.943*Debt Per capita+0.913*Debt/GDP+
0.863*Debt/operative revenues-0.062*Operative surplus percapita-
0.050*Operative surplus/operative revenues-0.527Debt payment.
The second component explains 35.94% of the variance and includes all the
variables representing a short term economic perspective (Table 3). It reveals that
in Italy there is no correlation between the variables representing the long term
financial situation (level of debt) and short term economic situation (operative
surplus). In fact, the correlation coefficients between both types of variable is verylow.
In Spain, the first component explains 64.34% of the variance but includes both
the long term debt as well as the short term economic dimension in the same
component, but with a negative sign. Those entities with a higher level of debt andlower surplus will have more financial problems. There is a high correlation
between both dimensions. Those entities with a higher level of debt also have less
operative surplus.
The equation of the first component (explains 64.34% of the variance) is the
following:
Financial situation = 0.900 * Debt Percapita + 0.884 * Debt/GDP + 0.948 *Debt/operative revenues-0,801*Operative surplus percapita-0,837*Operative
surplus/operative revenues-0,164*Debt payment.
The second component, in Spain, explains only 17.409% of the variance and the
variable with a higher weight is debt payment, since all the others have a highweight in the first component.
To summarize, while in Spain there is high correlation between long term debt and
the short term economic-financial situation and an indicator that combines both
can explain a high percentage of the variance, in Italy both dimensions have a
different behaviour. The indicators of the economic situation such as operativedeficit and the debt level are in two different components.
5.2 Drivers for financial condition
In the second part, we tried to analyse the factors that influence or can explain the
differences in the financial condition, carrying out a regression analysis with all thevariables so as to analyse whether the variables are significant or not over the
dependent variables. For the variables dummy, the T-test of the difference of means
was used.
Three alternative dependent variables were considered: component 1, component 2
and debt per capita.
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The results in Tables 5, 6 and 7 show that for Italy the variables that have a
significant influence are: population, density of population and most of the variablesrepresenting the financial structure of expenditures and revenues of local
government. However, the political and socioeconomic variables, such as the
political party in power, the gender of the mayor, unemployment and GDP are not
significant in any of the models. In Spain, the situation is very different: size is
important when measuring the number of inhabitants, with there being less
relevance when considering the density of the population. The political and socio-economic factors are significant in component 1, that in the case of Spain has a high
explicatory power, with only the gender of the mayor not being significant in any of
the models. The financial structure of the revenues and expenses is also a driver for
financial stress.
Table 5: Factors that explain component 1 in Italian and Spanish LGs
Dependent: Component 1 Italy Spain
F/T Coef. Sig. F/T Coef. Sig
Population (INH.) 2.882 -0.169 0.093 0.114 0.031 0.736
Density of population (DP)3.329 -.181 .071 2.500 -.142 .116
Unemployment (U)1.518 -.124 .221 7.613 .243 .007
Gross Domestic Product (GDP)
.465 -.069 .497 7.002 -,234 .009Political party in government (PP)
.010 1.536 .132 4.388 2.753 .007
Gender of the Mayor (G).010 .289 .764 .032 .216 .829
Capital expenditure (KE).080 .028 .779 4.341 .186 .039
Personal expenditure (PE).305 .056 .582 8.170 .251 .005
Fiscal pressure (FP)1.393 .118 .241 .230 -.044 .633
Fiscal revenues over GDP4.097 .200 .046 1.801 .121 .182
Financial independence (FI)5.213 .225 .025 .580 .069 .448
Operative grants 5.950 -.239 .017 .001 -.003 .973
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Table 6: Factors that explain component 2 in Italian and Spanish LGs
Dependent: Component 2 Italy Spain
F/T Coef. Sig. F/T Coef. Sig
Population (INH.) 1.244 0.112 0.093 2.820 0.151 0.096
Density of population (DP)7.196 .262 .009 .335 -.053 .564
Unemployment (U)2.255 .150 .136 .129 -.033 .720
Gross Domestic Product (GDP).341 -.059 .561 .420 -.059 .518
Political party in government (PP).514
-1.004 .252 .642 1.302 .195
Gender of the Mayor (G).882 .851 .248 5.171 -.158 .875
Capital expenditure (KE) .012 .011 .913 1.055 -.093 .306
Personal expenditure (PE)11.664 -.326 .001 1.383 -.106 .242
Fiscal pressure (FP)5.325 .227 .023 12.669 .308 .001
Fiscal revenues over GDP6.023 .241 .016 11.490 .294 .001
Financial independence (FI)8.962 -.289 .003 8.238 .252 .005
Operative grants1.524 .124 .220 10.079 -.277 .002
Table 7: Factors that explain debt per capita in Italian and Spanish LGs
Dependent: Debt Per capita Italy Spain
F/T Coef. Sig. F/T Coef. Sig
Population (INH.) 4.669 -.212 .033 4.669 -.212 .033
Density of population (DP) 4.953 -.218 .028 .801 -.081 .373
Unemployment (U) 1.923 -.138 .169 1.784 .121 .184
Gross Domestic Product (GDP) .433 -.066 .512 .871 -.085 .352
Political party in government (PP).370 1.118 .292 4.702 2.760 .007
Gender of the Mayor (G) .113 .393 .710 2.403 -.714 .477
Capital expenditure (KE) .570 .076 .452 7.023 .234 .009
Personal expenditure (PE) .177 -.042 .675 1.565 .113 .213
Fiscal pressure (FP) 1.611 .127 .207 4.366 .187 .039
Fiscal revenues over GDP 5.381 .227 .022 6.524 .226 .012
Financial independence (FI) 1.037 .102 .311 1.724 .119 .192
Operative grants 2.362 -.153 .128 .660 -.074 .418
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In Italy, the entities with more inhabitants have less financial stress when
considering component 1, which represents the long term financial situation. In fact,the level of debt per capita is lower for bigger entities, since the coefficient of the
variable in table 7 is negative and significant. Similarly, these entities have a better
short term economic situation, with the variable in table 6 having a positive
coefficient and being significant. The density of the population has a similar
influence: entities with a higher density of the population have fewer problems in
the long term financial situation, debt per capita and a better situation whenconsidering the second component, which represents the short term economic and
financial situation.
In Spain, the results (contrasting Guillamón et al. (2011) and Vicente et al.
(2013),which found a positive relation as well as Benito and Bastida (2004) whichfound no significant relation in a sample including entities up to 50.000 inhabitants)
show that entities with more inhabitants have also a lower level of debt, since the
population variable has a negative coefficient and is significant in the regression
with the debt per capita. They show also a better situation in the short term
economic and financial situations. However, the variable is not significant in
explaining the whole financial condition (component 1) of Spanish localgovernments. In spite of the negative impact of the density of the population on the
per capita total expenditures found in Bastida et al. (2013), the results show that the
density of the population is not significant in explaining the differences in financial
health.
The political party is a significant variable in the case of Spain, showing that progressive governments have more debt per capita and that the financial condition
(component 1) is also higher, in line with the results of Guillamón et al. (2011) and
Vicente et al. (2013). The unemployment rate also has a positive impact on the
financial condition in the case of Spain, and those entities with higher
unemployment have more financial problems, which is in line with Zafra-Gomez et
al. (2009). Nevertheless, in this study, unemployment is not significant for the debt per capita, contrasting the results of Vicente et al. (2013) where it has a positive
relevance on the level of debt. On the other hand, the GDP is a good driver for
financial health and entities with a higher GDP have lower financial stress. This
confirms the results in Guillamón et al. (2011) but differs from those obtained in
Bastida et al. (2013).
With respect to the financial structure of the revenues and expenses, in Spain those
entities that have a higher capital expenditure per capita have more debt, since the
law requires that debt goes to financial long term investments. Thus, entities with a
higher capital expenditure per capita are more likely to have financial stress.
However, capital expenditure per capita is not relevant for Italian entities. The percentage of personal expenditure over operative revenues is also significant in
component 1 of Spanish local governments, which shows that the higher the
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expenses are, the higher the probability to have financial problems is. In Italy, the
last variable is significant only in the short term economic and financial situation
(component 2), but does not influence the long term situation nor the level of debt.
Regarding the revenues, the fiscal revenues over GDP is the variable that has
significant power in explaining both the long term financial stress, short term
economic and financial situation as well as debt per capita in the case of Italy.
Although focusing on operative surplus entities with a higher percentage of
revenues over GDP, they have a better short term financial situation as well as moredebt per capita and more probability of having higher long term financial stress
indicators. Fiscal pressure is also positively correlated with the short term economic
and financial situation (component 2) as well as the financial independence. This
confirms that fiscal policies can influence the level of debt of governments
(Guillamón et al., 2011).
The operative transfer and grants (for financing current expenditures) have a
positive impact on the long term financial situation for Italy, since those entities
with a higher percentage of operative transfer and grants have lower values in
component 1.
In Spain, the percentage of fiscal revenues over GDP also has a positive impact onthe debt per capita and component 2, while it is not significant for component 1.
Fiscal pressure is significant in the debt per capita as well as component 2,
highlighting how those entities with a higher level of taxes per capita also have ahigher debt per capita. Operative transfer and grants are only relevant for
component 2.
With the aim of selecting a group of indicators suitable for predicting financial
distress, all the variables that are significant in the simple regression analysis were
considered in a multiple regression, using the stepwise method of the regression.
The results are shown in Tables 8, 9 and 10.
Table 8: Multiple Regression Analysis for Component 1
Dependent: Component 1 I taly Spain
Coef. Sig. Coef. Sig
Population (INH.)
Density of population (DP)-0.230 0.020
Unemployment (U)0.254 0.003
Gross Domestic Product (GDP)
Political party in government (PP)-0.240 0.004
Gender of the Mayor (G)
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Capital expenditure (KE)0.277 0.001
Personal expenditure (PE)0.234 0.005
Fiscal pressure (FP)
Fiscal revenues over GDP
Financial independence (FI)
Operative grants-0.286 0.004
R
F
0.096
6.191
0.204
8.83
Table 9: Multiple Regression Analysis for Component 2
Dependent: Component 2 I taly Spain
Coef. Sig. Coef. Sig
Population (INH.) 0.191 0.029
Density of population (DP)0.207 0.017
Unemployment (U)
Gross Domestic Product (GDP)
Political party in government (PP)
Gender of the Mayor (G)Capital expenditure (KE)
Personal expenditure (PE)-0.212 0.20
Fiscal pressure (FP)
Fiscal revenues over GDP0.323 0.001 0.318 0.000
Financial independence (FI)-0.411 0.000
Operative grants
R 2
F
0.291
11.178
0.108
8.38
Table 10: Multiple Regression Analysis for Debt Percapita
Dependent: Debt Per capita Italy Spain
Coef. Sig. Coef. Sig
Population (INH.) -0.257 0.000
Density of population (DP)-0.330 0.000
Unemployment (U)
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Gross Domestic Product (GDP)
Political party in government (PP)
Gender of the Mayor (G)Capital expenditure (KE)
Personal expenditure (PE)
Fiscal pressure (FP)
Fiscal revenues over GDP0.167 0.006
Financial independence (FI)
Operative grants
Debt per capita t-10.739 0.000 0.726 0.000
R
F0.545
40.1290.567
80.846
For the first principal component, in the case of Italy, there are only two variables
that enter in the model (due to autocorrelation problems): the density of the
population and the operative grants index. However, the explanatory power of the
model is very low. For component 2, in addition to the density of the population, personal expenditure index, fiscal revenues over GDP and financial independence
are also significant. In this case, the explanatory power of the model increases to
29.1%.
In the case of the debt per capita, the level of debt of the previous year (lagged
variable) was also considered, taking into account that it is a variable thatmaintains a certain stability. For Italy, in addition to the debt of 2011, the
population and the density of the population are significant in the model in
explaining 73.9% of the variance of the debt per capita.
In Spain, there are four variables that enter into the multiple regression for thefinancial health indicator (component 1): unemployment, political party, capital
expenditure and personal expenditure. The R 2
of the model is 20.4%. For
component 2, the variables are population and fiscal revenues over GDP. In thedebt per capita regression, the significant variable is also the percentage of fiscal
revenues over GDP, in addition to the debt of the previous year. The model
explains 72.6% of the variance of the debt per capita.
6 Conclusions
The global financial crisis has had significant effects on the viability and financial
conditions of the public sector, including local governments. They are facing
financial difficulties, in part related to the need to increase public services
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provided with a reduction of available resources and in part connected to the
financial crisis.
In this new era, it has become extremely relevant for the on-looking agencies,
politicians and citizens to detect the financial performance of local governments
(Cohen et al., 2012) as well as a more general concept of financial condition. In
current literature, several studies (i.e. Kleine et al., 2003; Jones and Walkers,
2007; Zafra-Gómez et al., 2009; Cohen et al., 2012; García-Sánchez et al., 2012;Manes Rossi et al., 2012) along with standard setters and regulators all over the
world (CICA, 1997, ICMA, 2003; UK Audit Commission, 2007) have developed
several model to assess and prevent financial distress.
The novelty of this study is threefold: it presents a comparison between twoEuropean countries affected by the financial crisis, attempting to discover the
dimensions of the financial condition of Italian and Spanish local governments
using principal component analysis, while studying how the economic and social
conditions of the local government affect their financial health.
The analysis of the financial condition shows relevant differences between Italyand Spain. In Italy, the results highlight how the long term financial situation and
the short term economic perspective are not correlated to each other and have a
different behaviour. Thus, the analysis of the financial health should be carried out
considering both dimensions separately. On the contrary, in Spain these two
dimensions are strongly negatively correlated. In other words, entities with a
higher level of debt and lower operative surplus will have more financial problems.
Moreover, the results also highlight how the factors that can explain the results
highlight how differences in the financial health are strongly different in Italy and
Spain. The number of inhabitants is an important element in both countries,
therefore the Italian and Spanish larger local governments have a lower level ofdebt and better situation in the short term economic and financial situation.
However, the density of the population is not a significant variable for Spanish
LG, while it has a negative effect on the level of debt of Italian LG.
The socioeconomic and political variables have no impact on the financial healthof the Italian municipalities but, for the Spanish LG, the results highlight how the
progressive political party and unemployment rate have a positive impact on the
financial stress.
Differences also emerge in relation to the influence of the financial variables on
the financial health of LG.
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For example, capital expenditure per capita and the percentage of personal
expenditure over operative revenues influence the financial stress of the Spanish
municipalities, while they do not have a strong influence on the Italian ones.
On the other hand, the fiscal revenues over GDP, fiscal pressure and the operative
transfer and grants have a stronger influence on the financial health of Italian LG.
These results could support managers and politicians in understanding which
factors should be constantly monitored, with the aim of assuming timely decisions
so as to avoid financial distress.
In this framework, the law also plays an important role in the control of financial
health of the local governments. In fact, in both countries, it is expected that the
municipalities in financial difficulty have to prepare a financial rebalancing plan
in order to avoid financial distress.
This study highlights how, even if Italy and Spain have a similar economic, social
and administrative environments, the factors that have an impact on the financial
distress are different. For these reasons, it is difficult to create a single model to
prevent the financial crisis of LGs for all countries, while it is more correct to
develop a specific model that reflects the peculiarities of each country.
Nevertheless, the analysis presents several limitations. First, the data for only for
one year was analysed because we want to related the financial condition to
political variables, that can change in a three-five year period. Moreover, thesample focuses on entities with more than 60,000 inhabitants, with it being
necessary to extend the analysis to smaller entities. Further possible developmentsof the research could include the analysis and comparison with other countries
with a different socioeconomic framework, with the aim of highlighting the main
differences in the factors affecting the financial distress.
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