What elements of financial stress affect contracting out and intermunicipal cooperation in the provision of local public services? The impact of the great recession

Author

José Luis Zafra Gómez – (University of Granada)

Juan Sánchez Fernández – (University of Granada)

Ana María Plata Díaz – (University of Granada)

Gemma Pérez López – (University of Granada)

Abstract

The current financial crisis is one of the main factors underlying proposals made for change delivery form of municipal services. However, this situation is affected by a wide variety of financial indicators, and it is necessary to determine which of these indicators have greatest influence on decisions regarding outsourcing or long-term inter-municipal cooperation. Furthermore, the Great Recession could have modified these financial indicators, and so we must identify which of them impacted on public-service outsourcing and/or cooperation both before and during the crisis. This paper evaluates these factors with respect to a sample of Spanish municipalities, for the periods 2002-2007 and 2008-2010, via a discriminant analysis. The results obtained show that the financial indicators that affect outsourcing and cooperation are different, specifically, we find that the variables which are related to spending on transfers, budget sustainability and the flexibility of the entity, measured by its outstanding debt have the greatest impact on the outsourcing process, while the cooperation processes are influenced, in addition to the latter factors, by the short-term solvency of the entity. The elements of short term solvency, flexibility and sustainability led municipalities to outsource their public services in the pre-crisis period, while only debt and financial independence influenced the cooperation decisions during the crisis period.

Keywords

  • Financial stress
  • Contracting out
  • Intermunicipal cooperation
  • Great recession
  • Local government

1.      Introduction

Fiscal stress is one of the explanatory factors most commonly referred to in studies of outsourcing and inter-municipal cooperation (Bel and Fageda, 2007). The reasoning used to relate the two concepts is based on the idea that municipalities in this situation are faced with falling revenues (transfers and/or taxes) and, not wishing to increase the local tax burden (Tiebout, 1956; Bel and Fageda, 2007), may choose to privatise public services that present a high degree of complexity and represent a significant cost to the local authority (Savas, 2000; Greene, 2002). Moreover, this situation has been aggravated by the current economic and financial crisis (Zafra-Gómez et al., 2009a, 2009b; Zullo, 2009). The effects of this crisis on public administration are reflected in a stricter control of budgets and deficits (López-Hernández et al., 2012) and this situation has prompted a search for solutions to fiscal stress, based primarily on recentralising the decision-making process and even on the use of new models of governance (Peters, 2011).

Among the options open to municipalities for alleviating situations of fiscal stress, one of the most common is to search for new forms of service delivery, such as privatisation (Moore, 1987; Hood, 1995). However, in recent years various alternatives to outsourcing – for example, inter-municipal cooperation – have arisen as a means of restructuring the delivery of public services (Mohr et al., 2010).

Nevertheless, empirical evidence is unclear as to whether situations of fiscal stress leading to outsourcing or inter-municipal cooperation are responsible for provoking changes in management attitudes (Levin and Tadelis, 2005; Bel and Fageda, 2007; Zullo, 2009). This may be due to the fact that most studies in this respect have been of a cross-sectional nature, aiming to evaluate the performance of municipalities over an extended period of time (Bel et al., 2010). Moreover, as observed by Boyne (1998), the measures used to assess whether the municipality is undergoing fiscal stress are very poor and may not reflect the true situation (Brudney et al., 2005).

The use of long periods of analysis means that the circumstances characterising these periods must be taken into account. We are currently experiencing a period of global financial crisis, known as the Great Recession (GR), which is having a major impact on economic activity in both the private and the public sectors. Accordingly, the fiscal stress/outsourcing (or inter-municipal cooperation) relationship may have changed during this period. Authors such as James and Wooten (2006) and Maitlis and Sonenshein (2010) have reported that when an international crisis occurs, the structure and development of any organisation may be affected and undergo considerable change, and therefore action should be taken to overcome the problems faced (Christensen et al., 2011).

In view of this situation, it is necessary to identify the indicators that reflect the municipal financial situation, especially those with most impact on changes made in the provision of public services, and to determine whether these indicators are exerting the same influence during the GR.

Accordingly, the aim of this study is to establish whether the decisions taken by local public managers regarding outsourcing or inter-municipal cooperation are related to the presence of financial problems, specifically, when the municipality is undergoing a state of fiscal stress. This concept is distinguished from that of global financial crisis, known as the Great Recession (GR), which refers to the present global economic and financial crisis. The results obtained will clarify whether the financial variables were affected by the GR, thus impacting on how local public services are delivered, in terms of decisions to outsource or to enter into inter-municipal cooperation for this purpose. Furthermore, we consider a broad concept of fiscal stress, defining it in the framework of financial condition. In other words, we are not considering just the level of transfers or an indicator of local authority borrowing (Bel and Fageda, 2007), but also take into consideration variables related to transfers received, the fiscal capacity of the municipality, its cash position, level of debt and budget sustainability.

The rest of this paper is structured as follows. In the next section, the concept of financial condition is discussed, as a valuable element for measuring whether a municipality is undergoing financial stress. We then examine, from a theoretical standpoint, the relationship between fiscal stress and outsourcing or inter-municipal cooperation. Section four introduces the concept of crisis management to address the implications of the impact of the GR on the relationship being studied. In section five, we explain the methodology used, the data analysed and the results obtained, for a sample of Spanish municipalities for the period 2002-2010. In the final section, we discuss these results and draw appropriate conclusions.

2.      Using financial condition to measure fiscal stress in local government

The primary objective of financial information in the context of local government is to represent its economic and financial position, thus facilitating decision-taking by individuals, rating agencies, managers and the community in general, providing an instrument for effective action to be taken when financial circumstances are adverse, and a measure for determining rewards when circumstances are favourable. One of the main lines of research currently being addressed in the area of local government finance is the construction and development of indicators to measure how local authorities are managing their resources and their finances.

Studies related to the financial position of an entity have referred to the concept of financial position, i.e., the entity’s ability to meet its obligations from the resources at its disposal (Lorig, 1941; Berne, 1992; Zafra-Gómez et al., 2009c). Measurement of this concept provides information about the entity’s solvency or liquidity, that is, its ability to meet its obligations in the long term and the short term, respectively. Accordingly, the present financial analysis aims to determine the financial risks associated with local authorities’ economic activities, by analysing their solvency.

Unlike financial position, the concept of financial condition addresses not only this facet of economic-financial information, but also others that influence the development of service delivery in municipalities, and which, even if they are not reflected in the analysis of financial position, have a tangible impact on the financial health of the local authority. However, the terms financial position and financial condition have sometimes been used in a confusing way, despite the Governmental Accounting Standards Board having clarified the broader nature of the concept of financial condition (paragraph 34 of Concept Statement 1), and different terms have been used to refer to the concept of financial condition, including fiscal crisis, fiscal stress, fiscal distress, fiscal emergency or financial condition (Honadle, 2003). Thus, the US State of Rhode Island uses the term “crisis”, while Ohio speaks of “fiscal emergency’”, and Michigan and Pennsylvania, “fiscal distress”.

In this context, the analysis of financial condition has been widely discussed (Hendrick, 1989; Greenberg and Hillier, 1995; Groves et al., 2003; Hendrick, 2004; Kloha et al., 2005a, 2005b; Wang et al., 2007; Zafra-Gómez et al., 2009a, 2009b, 2009c; Cohen et al., 2012) and the determinants of financial condition or fiscal distress have been studied from various perspectives, with different systems being proposed for measuring and evaluating the financial health of local authorities.

Among the different possibilities offered to measure this concept, for the purposes of the present study, we start with two that seem most appropriate. On the one hand, the proposal made by Groves et al. (2003), who pointed out that financial condition can be measured in terms of four inter-related factors: cash solvency, budgetary solvency, long-term solvency and service-level solvency. These authors defined cash solvency as the entity’s ability to generate sufficient liquidity to meet its short-term obligations; budgetary solvency is its ability to obtain sufficient budget revenues, without provoking a budget deficit; long-term solvency concerns the government’s ability to meet all its long-term liabilities; and service-level solvency is its ability to provide the level and quality of services necessary for the welfare of the community in question.

The second contribution considered was that of Greenberg and Hillier (1995) and CICA (1997), for whom financial condition can be measured through various indicators related to sustainability, flexibility and vulnerability. Sustainability is viewed as the ability of the entity to maintain, foster and preserve the social welfare of its citizens using the resources at its disposal. Flexibility is the entity’s capacity to respond to changing economic and financial circumstances within the limits of its fiscal capacity; and vulnerability is its level of dependence on external funding to enable public spending levels to be maintained.

In the present study, the concept of financial condition is used to determine whether a municipality is in a position of financial stress, and the financial condition is assumed to include the following aspects: cash solvency, defined as the organisation’s ability to generate sufficient liquidity to pay its short-term debts (Groves et al., 2003); flexibility, the organisation’s capability to respond to changes in the economy or in its financial circumstances, via modifications to public debt (Greenberg and Hillier, 1995; CICA, 1997); budgetary sustainability (or service-level solvency), the organisation’s ability to maintain, promote and protect the social welfare of the population, employing the resources at its disposal (Greenberg and Hillier, 1995; CICA, 1997; Groves et al., 2003; Hendrick, 2011); financial independence, the level of dependence on external funding received via transfers and grants (Berne, 1992; ICMA, 2003; Honadle, 2003; Zafra-Gómez et al., 2009a). Finally, we consider long-run solvency, using a broad time horizon for this study. All of these measures are set out in Table 1 and are evaluated using the set of indicators derived from budgetary and balance sheet information.

Elements of the Financial Condition

Indicators

Definition

Short-run solvency

Cash Surplus Index (CSI)

Difference between net short-term receivables, liquidity and net short-term liabilities

Liquidity Index (LI)

Liquidity divided by net short-term liabilities

Budgetary solvency

Flexibility

Net Savings Index (NSI)

Difference between the receivables from current budget resources and the budget obligations from non-financial current expenditures, reduced by annual amortisation payment –including interest and principal

Taxable value divided by Financial Charge Index (TVFCI)

Taxable budgetary receivables divided by annual amortisation payment – interest and principal –

 

Weight of Budgetary Receivables (TVCR)

Taxable budgetary receivables divided by annual current budgetary receivables

 

Sustainability of Budgetary Receivables (CETV)

Current budgetary payables divided by taxable budgetary receivables

 

Debt

Outstanding debt of the local authority and its autonomous organisations, consortia and associations

Independence

Index of Financial Independence (ITRANSF)

Grants budgetary payables divided by total budgetary payables.

Weight Payables/Transfers

(TE/G)

Total budgetary payables divided by grants

Sustainability

Non-Financial Budgetary Result Index (NFBRI)

Current budgetary payables, non-financial capital budgetary payables divided by non-financial current budgetary receivables, non-financial capital budgetary receivables.

Table 1. Elements of the financial condition

3.      Cooperate or outsource in response to fiscal stress?

Outsourcing can be defined as a form of privatisation in which a private company obtains residual gains from service delivery (Vickers and Yarrow, 1988; Warner and Bel, 2008) and in this field it is the most important of the alternatives available (Pallesen, 2004). One of the economic factors promoting outsourcing is the impact of fiscal stress (tax burden, legal limitations on local tax levels and the size of transfers from central to local government) on local government. Bel and Fageda (2007) observed that one of the hypotheses most commonly analysed and empirically tested is that of the relationship between fiscal stress and outsourcing (Ferris, 1986; Miranda, 1994; Kodrzycki, 1998; Brown et al., 2008; Hebdon and Jalette, 2008) and various studies have concluded that local officials respond to fiscal problems by this means (Touche-Ross Company, 1987; Mouritzen and Nielsen, 1988; ICMA, 1989; Morgan and Hirlinger, 1991).

Outsourcing is most commonly resorted to by larger municipalities, because smaller ones will often not have access to providers of the services required (Kodrzycki, 1998; Warner and Hefetz, 2003). As an alternative, municipalities can choose to join forces, via inter-municipal cooperation, to provide services that would be too costly for each one alone. Inter-municipal cooperation can reduce public sector spending, as the services provided under this form of management are consolidated via a single entity, whereas there may previously have been a larger number of entities and a higher level of total expenditure (Parks and Oakerson, 1993). In other words, it is hypothesised that small local authorities could employ inter-municipal cooperation to exploit economies of scale (Warner and Hefetz, 2003; Dijkgraaf et al., 2003; Warner, 2006a; Zullo, 2009). In addition, they would retain control of the service provided, which is not the case with outsourcing (Warner, 2006b). For these reasons, assuming that greater cooperation leads to lower spending and thus reduces fiscal stress for local government, there is a high probability that municipalities faced with fiscal stress will opt for the service to be provided in the form of inter-municipal cooperation.

4.      The effect of the great recession on the relationships between fiscal stress and outsourcing or inter-municipal cooperation

As discussed in Section 2, numerous concepts have been proposed for evaluating the financial condition of public entities. However, events of the last decade may have changed how these concepts are viewed. As a result of the globalisation of the economy, events in localised areas can affect economic activity worldwide. This situation has given rise to the concept of crisis management. This concept was first developed in the private sector but in the present context can be readily transferred to the public sector. Crisis management can be clearly differentiated from the concepts of fiscal crisis, fiscal distress and financial condition. These latter are all part of what may be considered the economic and financial problems of a single entity, but crisis management refers to factors and events that influence the business activity of production units and which can also provoke major changes in organisational life (James and Wooten, 2010). These changes may be substantial and structural, and require public managers to adopt strategic responses to adapt the entity to the new circumstances.

For such a crisis to be present, there must exist a set of elements clearly differentiating it from other types of problems. First, a severe threat must be detected (Hermann, 1963), one that could significantly affect the aims of the organisation. The latter author noted that the concept of crisis also incorporates a certain element of surprise. But the entity must react appropriately both to the surprise and to the threat. This is what Hermann terms the short-term decision. Thus, a management crisis should present both these elements, although subsequently both the same author and Brady (1974) downplayed the importance of the element of surprise and of rapid decision taking. This concept of crisis could very well encompass the present Great Recession (GR). The GR has been characterised by its progressive appearance in different settings and the progressive decisions taken in response by different governments. The level of intensity of the crisis has varied among different countries, and the responses made by their governments have also differed. At present, and for the specific case of Europe, countries such as Portugal, Greece, Italy, Ireland and Spain are engaged in a whirlwind dismantling of the public sector, aimed at achieving total control of the public deficit.

This climate of change is also apparent at the local level, which is the object of most studies of financial condition, and thus any research in this field with an international focus, carried out since 2008, must take account of this situation characterising public sector finances in general and those of municipalities in particular. The first references to the situation of municipalities and their financial condition are the studies by López-Hernández et al. (2012) and Pérez-López et al. (2013), analysing the financial condition at the start of the period of crisis management. These studies have reported that the crisis affects different elements of the financial condition of local governments, to varying degrees. The element of financial condition that has undergone the most severe deterioration is that of budgetary sustainability, i.e., the control of the public deficit, which in turn has negatively impacted on budgetary stability. Secondly, the indicators of flexibility, that is, of government debt, have worsened. This latter element has been examined by the second group of authors (Pérez-López et al., 2013), who found that the variables which determine the level of debt, in the period from 2008 to 2011, presented certain differences from those identified in studies conducted during periods of economic stability.

These first studies in the Spanish context corroborate the need to consider the effects of crisis management in evaluating the financial condition of public bodies, particularly at the local level, and its relationship with the emergence of phenomena such as outsourcing and inter-municipal cooperation. The current economic and financial crisis may have altered the elements comprising financial condition and have pushed municipalities into outsourcing services or entering into processes of inter-municipal cooperation. Therefore, we propose the following hypotheses:

H1: The elements of the financial condition affecting the outsourcing of public services differ between the pre-crisis period and during the Great Recession.

H2: The elements of the financial condition affecting processes of inter-municipal cooperation for the provision of public services differ between the pre-crisis period and during the Great Recession.

5.      A study of local governments in Spain

5.1.    Methodology and data

In view of the characteristics of the data and the particular aims of this study, we decided to conduct a stepwise discriminant analysis (Sánchez-Fernández and Luque-Martínez, 2012). This analysis technique was applied for the following reasons:

  • First, because the fundamental purpose of the study was to determine the relationship between behaviour (assessed by a dichotomous variable) and a set of financial indicators (expressed in terms of ten measurement metrics), under the assumption that these indicators may influence the behaviour. This configuration of variables makes the technique especially suitable and also enables us to evaluate the relative weight or importance of each value in characterising the behaviour.
  • Second, having ten independent metrics makes it especially necessary to reduce the dimension of the problem and to develop a model containing the fewest possible independent variables. In this respect, the stepwise procedure for estimating discriminant functions allows us to obtain a model comprised exclusively of the independent variables that offer the greatest discrimination and prediction capacity, while removing potential redundancies among them.

The study sample was constituted of 1,572 local authorities in Spain, each with over 1,000 inhabitants, of the total of 3,106 such Spanish local authorities, for the period 2002-2010. Fiscal stress and economic, financial and budgetary data were obtained from the Directorate General for Financial Coordination with Regional and Local Authorities (DGCFCAEL). The number of inter-municipal cooperation processes was ascertained by consulting the general database of local entities, maintained by DGCFCAEL Finally, a purpose-built database was constructed by incorporating the announcements published by local authorities in Spanish official provincial gazettes regarding the outsourcing of certain services. Information about the descriptive statistics is given in Table 2.

 

N

Minimum

Maximum

Mean

Std. Deviation

NSI

14148

-3.104772859

0.89351469

0.07

0.16

TVCR

14148

0.042473713

0.964158577

0.58

0.15

NFBRI

14148

0.310360754

3.495602817

1.02

0.17

TE/G

14148

0.069991998

2.765167007

0.57

0.21

CSI

14148

-192.8107649

6564.840583

3.71

59.35

LI

14148

-90.87335352

6555.557724

2.34

58.91

TVFCI

14148

0.206163572

51853.79258

33.43

615.93

CETV

14148

0.090599958

5.330711451

0.69

0.27

Debt

14148

0.00E+00

6776856000

12798263.92

155579214.09

ITRANSF

14148

0.044581194

0.947001888

0.46

0.16

Table 2. Descriptive variables

5.2.    Results

The first variable under analysis was outsourcing, and note was taken of the differences between the two groups defined by the dependent variable in relation to the measures for the ten values ​​considered. However, not all the differences observed between the two groups were statistically significant. Thus, the last column in Table 3 shows that only 5 of the 10 variables revealed significant differences between the two groups.

Variable

Non-outsourcers:

mean value

Outsourcers:

mean value

Total

Sign.

Wilks’ Lambda

F

Sig.

NSI

0.07

0.07

0.07

0.440

1

0.596

0.440

TVCR

0.57

0.63

0.58

0.000

0.984

222.734

0.000

NFBRI

1.02

1.02

1.02

0.861

1

0.03

0.861

TE/G

0.56

0.65

0.57

0.000

0.98

295.409

0.000

CSI

3.73

3.56

3.71

0.914

1

0.012

0.914

LI

2.36

2.16

2.34

0.896

1

0.017

0.896

TVFCI

35.40

17.19

33.43

0.274

1

1.198

0.274

CETV

0.68

0.74

0.69

0.000

0.995

72.808

0.000

Debt

5433871.57

73266829.19

12798263.92

0.000

0.982

265.151

0.000

ITRANSF

0.47

0.37

0.46

0.000

0.971

427.854

0.000

Table 3. Equality of the means

More specifically, it was found that the non-outsourcing group presents values that are higher and very different from those of the group that does outsource, with respect to the TVCFI variables and the short-term solvency ratios (CSI and LI). Moreover, the mean debt level of municipalities that outsource far exceeds that of the non-outsourcers, which corroborates the findings reported by Pérez-López et al. (2013).

In general, the existence of these significant differences between the two groups regarding these variables suggests it may be possible to develop an explanatory model to predict membership of these groups from the individual valuations for these variables.

Since the dependent variable divides the sample into two groups (non-outsourcing vs. outsourcing), discriminant analysis provides a single discriminant function that forms the basis for classification and prediction.

In this case, the discriminant function has a canonical correlation of 0.22, indicating that the function has an average association with the dependent variable that it is intended to predict. However, the analyses carried out clearly reveal significant differences in the mean discriminant scores for the two groups (Wilks’ Lambda = 0.952, significance = 0.000), which shows that this function has a certain discriminant capacity between the groups defined by the dependent variable.

The stepwise inclusion procedure resulted in the inclusion in the discriminant function of only four of the ten independent variables. The following table shows the values ​​of the standardised coefficients of these variables in the discriminant function.

Variable

Coefficient

NFBRI

-0.089

CETV

0.374

Debt

-0.574

ITRANSF

0.999

Table 4. Standardised coefficients of the discriminant function

From these values, we conclude that the four variables that make up the resulting model have unequal weights in shaping the discriminant function (between -0.089 and 0.999). Furthermore, these values ​​allow us to anticipate that the discriminant function will clearly distinguish between municipalities with higher CETV, ITRANSF and NFBRI values. In other words, those with higher levels of current expenditure in relation to their tax revenues, those with higher costs of transfers to other entities and those with higher budget deficits are all more likely to outsource public services. For the debt variable, we find a similar situation. Decreases in municipal debt increase the likelihood of outsourcing taking place. This may be due to the fact that municipalities which outsource public services do not need to incur higher levels of debt, as they have already reduced spending by outsourcing their services (Pérez-López et al., 2013, 2014).

Outsourcing

Function

Pre-crisis function

GR function

1

1

1

0

0.079

0.077

0.097

1

-0.646

-0.739

-0.608

Nonstandardised canonical discriminant functions evaluated at the mean values for the groups

Table 5. Functions at the centroids of the groups

Figure 1. Correlations between the discriminant function and the independent variables (structure matrix)

Regarding the model’s predictive capabilities, the results show that the discriminant function correctly predicts 64.2% of cases. In addition, for the non-outsourcing municipalities, this prediction rate is 64.2%, very similar to the outsourcing group (64.6%) (see Table 6). In general, however, this solution achieves a considerable improvement in the classification of cases, with a hit ratio that is higher than the percentage of cases that could be classified correctly by chance (50%). Furthermore, Press’s Q statistic corroborates the predictive ability of the model (Q = 1141).

  

0

1

 

Count

0

8091

4521

12612

1

544

992

1536

%

0

64.2

35.8

100

1

35.4

64.6

100

Table 6. Classification results

In view of the study aims, we were particularly interested in determining whether a similar explanation could be found for the behaviour of the dependent variable in the pre-crisis period (before 2008) in comparison to that for the GR (from 2008). Therefore, the discriminant analysis was repeated, obtaining the results discussed below.

With respect to the test for the equality of the means of the independent variables, the significant differences obtained previously were repeated in the same five variables as was the case for the combined sample group, for each of the two periods (see Table 7).

 

Pre-crisis

GR

Wilks’ Lambda

F

Sign.

Wilks’ Lambda

F

Sign.

NSI

1

1.169

0.280

1

0.858

0.354

TVCR

0.985

142.315

0.000

0.979

101.542

0.000

NFBRI

1

1.252

0.263

1

0.283

0.595

TE/G

0.977

220.025

0.000

0.969

150.21

0.000

CSI

1

0.001

0.978

1

1.926

0.165

LI

1

0.001

0.979

1

1.71

0.191

TVFCI

1

0.899

0.343

1

0.288

0.591

CETV

0.994

54.068

0.000

0.991

42.136

0.000

Debt

0.979

205.033

0.000

0.985

69.406

0.000

ITRANSF

0.968

308.444

0.000

0.959

202.313

0.000

Table 7. Equality of the means

Similarly, the same four variables were obtained as in the general case for the pre-crisis and GR periods, with similar weights, and with the same sign.

Variable

Pre-crisis

GR

NFBRI

-0.128

-0.161

CETV

0.370

0.354

Debt

-0.591

-0.455

ITRANSF

0.984

1.073

Table 8. Standardised coefficients of the discriminant function

For the pre-crisis period, the discriminant function presents a canonical correlation of 0.232 (Wilks’ Lambda = 0.946; significance = 0.000), whereas for the GR, it is 0.236 (Wilks’ Lambda = 0.944, significance = 0.000). Therefore, the discriminant functions are significant and their explanatory power is practically identical. In addition, the coefficients of the discriminant function are similar, and identical for the pre-crisis period and for the GR. We conclude, therefore, that the indicators which determine the fiscal stress-outsourcing relationship were not modified by the onset of the GR. This finding is corroborated by the fact that the percentage of correctly classified cases is also very similar, with 66.1% for the pre-crisis period and 63.3% for the GR.

Table 9:.

 

Total

Pre-crisis

GR

 

0

1

0

1

0

1

0

8091

4521

5641

2902

2586

1483

1

544

992

294

595

235

412

0%

64.2

35.8

66.0

34.0

63.6

36.4

1%

35.4

64.6

33.1

66.9

36.3

63.7

Hit Ratio

64.2%

66.1

63.6

Q

1141

979

347

Table 9. Summary of case classifications

The second variable analysed was that of inter-municipal cooperation. This variable takes the value 1 when the local authority enters into cooperation with another or participates in a consortium, and the value 0 if it does not. The last column of Table 10 shows that for 8 of the 10 variables, there were significant differences between the two groups.

Variable

No cooperation group

Mean value

Cooperation group

Mean value

Total mean

Sign.

Wilks’ Lambda

F

Sig.

NSI

0.073

0.078

0.074

0.272

1

1.207

0.272

TVCR

0.572

0.620

0.576

0.000

0.991

129.051

0.000

NFBRI

1.021

1.036

1.023

0.003

0.999

8.605

0.003

TE/G

0.560

0.636

0.567

0.000

0.989

154.691

0.000

CSI

2.966

11.117

3.714

0.000

0.998

22.282

0.000

LI

1.614

9.539

2.342

0.000

0.998

21.38

0.000

TVFCI

35.131

16.560

33.426

0.300

1

1.073

0.300

CETV

0.681

0.751

0.687

0.000

0.994

80.167

0.000

Debt

10862972.210

31941114.672

12798263.916

0.000

0.998

21.686

0.000

ITRANSF

0.461

0.400

0.455

0.000

0.988

166.894

0.000

Table 10. Equality of the means

The group of local authorities that entered into processes of inter-municipal cooperation presented different values from those obtained for the municipalities that outsourced public services. Our results show that the cooperating municipalities do not present worse levels of short-term solvency or of transfers and subsidies. On the other hand, they do have higher average levels of debt, although, as discussed below, this does not affect the value of the discriminant functions.

The discriminant function has a canonical correlation of 0.12, indicating that the function does not present a very high association with the dependent variable that it is intended to predict. However, the results of the analyses clearly reveal significant differences in the mean discriminant scores of the two groups (Wilks’ Lambda = 0.985, significance = 0.000), which shows that the function does have a certain capacity to discriminate between the groups defined by the dependent variable.

The stepwise inclusion procedure resulted in the inclusion in the discriminant function of only four of the ten independent variables. The following table shows the values ​​of the standardised coefficients of these variables in the discriminant function.

Variable

Coefficient

NFBRI

-0.185

CSI

-0.317

Debt

0.279

ITRANSF

0.867

Table 11. Standardised coefficients of the discriminant function

From these values, we conclude that the four variables that make up the resulting model have unequal weights in shaping the discriminant function (between -0.317 and 0.867). Furthermore, we anticipate that the discriminant function will clearly distinguish between municipalities with higher values ​​for transfers to other entities (ITRANSF) and for level of debt, on the one hand, and those which present negative values for budget deficit and cash solvency, on the other. On comparing these results with those obtained for the case of outsourcing, we see they are very similar, except for the exit of the CETV variable and the entry of CSI (short-term cash solvency) in the discriminant function. This latter aspect means that increases in short-term cash solvency make the municipality less likely to cooperate with others.

Intermunicipal Cooperation

Function

Pre-crisis function

GR

function

1

1

1

0

0.039

-0.042

-0.019

1

-0.384

0.319

0.447

Nonstandardised canonical discriminant functions evaluated at the mean values for the groups

Table 12. Functions at the centroids of the groups

Figure 2. Correlations between the discriminant function and the independent variables (structure matrix)

Regarding the model’s predictive capability, the results show that the discriminant function correctly predicts 57.9% of the cases. For the municipalities that do not cooperate, this predictive capability was 57.7%, a similar value to that for the municipalities that do ​​cooperate (59.7%). Nevertheless, in general, this model obtains some improvement in the classification of cases, since the hit ratio is higher than the percentage of cases that could be classified correctly by chance (50%). In addition, Press’s Q statistic corroborates the predictive ability of the model (Q = 356).

  

0

1

 

Count

0

7420

5429

12849

 

1

523

776

1299

%

0

57.7

42.3

100

 

1

40.3

59.7

100

Table 13. Classification results

The corresponding cluster analysis (pre-crisis vs. GR) produced the results discussed below.

With respect to the test for the equality of the means of the independent variables (see Table 14), the significant differences were not the same for the two periods in question. Indeed, there were also some differences with respect to the overall sample. Specifically, while in the pre-crisis period there were differences for all the variables except NSI, NFBRI and TVFCI, in the GR the differences in CSI and LI also ceased to be significant.

 

Pre-crisis

GR

Wilks’ Lambda

F

Sign.

Wilks’ Lambda

F

Sign.

NSI

1

0.666

0.415

1

0.133

0.715

TVCR

0.991

81.236

0.000

0.994

27.602

0.000

NFBRI

1

1.139

0.286

1

1.351

0.245

TE/G

0.993

70.422

0.000

0.994

30.16

0.000

CSI

0.998

15.977

0.000

1

0.012

0.913

LI

0.998

15.378

0.000

1

0.041

0.840

TVFCI

1

1.141

0.285

1

0.162

0.688

CETV

0.996

39.017

0.000

0.998

10.223

0.001

Debt

0.998

14.513

0.000

0.997

12.039

0.001

ITRANSF

0.991

83.192

0.000

0.994

28.589

0.000

Table 14. Equality of the means

The discriminant functions are significantly different in the two time periods, mainly because in the GR, only TE/G and Debt form part of the discriminant function, and NSI, TVCR and CSI cease to have explanatory power, which means that there was a significant change from the pre-crisis period to the GR in the indicators that determine whether municipalities cooperate with each other.

Variable

Pre-crisis

GR

NSI

-0.291

 

CETV

0.529

 

TE/G

0.440

0.838

CSI

0.347

 

Debt

0.315

0.502

Table 15. Standardised coefficients of the discriminant function

For the pre-crisis period, the discriminant function obtained has a canonical correlation of 0.115 (Wilks’ Lambda = 0.987; significance = 0.000), while for the GR it is 0.092 (Wilks’ Lambda = 0.992; significance = 0.000). Therefore, the discriminant functions are significant and their explanatory power is practically identical. However, it should be noted that when the evaluation period is separated into two sub-periods, the elements of the financial condition that affect the cooperation process change significantly, with the variable that measures the budget deficit (NFBRI) and the index of transfers to other authorities (ITRANSF) being eliminated from the model. Replacing these variables, the model for the pre-crisis period introduces a variable that reflects the flexibility and sustainability of the current budget (NSI). When NSI is negative, the municipality is more likely to cooperate with other local entities. Also introduced is the TE/G variable, which measures the dependence of the local authority on grants in order to meet its expenses; when this variable increase, there is an increased probability of cooperation with other bodies. The third aspect introduced is the variable that reflects the entity’s short-term solvency, although in this period it is positively related with inter-municipal cooperation, and so part of the fiscal stress-intermunicipal cooperation relationship is not accounted for by this variable. Finally, the outstanding debt variable for the pre-crisis period is positively related with cooperation processes, which implies that when debt rises, there is a greater likelihood of the municipality cooperating with others. This occurs because the local authority seeks to transfer debt to other instrumental entities, such as consortia or municipal associations, seeking to keep the debt value off the general account (Pérez-López et al., 2014). In other words, this mechanism is used as a means of debt avoidance1.

Regarding the GR period, it should be noted that the debt variable has a similar effect to that observed for the pre-crisis period, together with the TE/G variable, and so both indicators are associated with an increased likelihood of inter-municipal cooperation. Finally, the percentage of correctly classified cases was significantly higher for the GR period (63.6%) than for the pre-crisis period (55.7%).

 

Total

Pre-crisis

GR

 

0

1

0

1

0

1

0

7420

5429

4588

3738

2885

1638

1

523

776

437

669

77

116

0%

57.7

42.3

55.1

44.9

63.8

36.2

1%

40.3

59.7

39.5

60.5

39.9

60.1

Hit Ratio

57.9

55.7

63.3

Q

356

124

250

Table 16. Case classification summary

6.      Discussion and conclusions

Fiscal stress is one of the main variables included in models seeking to identify the factors that explain why municipalities outsource and enter into inter-municipal cooperation agreements for the provision of public services. However, no in-depth study has previously been made of this variable. According to several theories, the presence of a situation of fiscal stress may provoke changes in how municipal services are provided, in order to reduce costs and thus levels of fiscal stress. But what factors in the entity’s financial condition induce it to carry out these changes? Previous studies have only considered the possibility of outsourcing, but there are others that municipalities could adopt in order to reduce the costs of their services. For this reason, we have broadened

the analysis, examining the impact of fiscal stress on management changes, not only regarding outsourcing to a private operator, but also addressing the question of inter-municipal cooperation. The results obtained show that when a set of financial indicators present values according to which municipalities are undergoing financial stress, these authorities will conduct operations to outsource public services and/or engage in cooperation with other municipalities. For both cases, the methodology applied in this study, that of discriminant analysis, obtained discriminant functions that were sufficiently precise to enable us to predict with a high degree of probability when a municipality will outsource services or enter into inter-municipal cooperation, in reaction to a state of fiscal stress. However, the elements that lead to these two outcomes vary slightly. While the variables that have the greatest impact on the outsourcing process are related to spending on transfers, budget sustainability and the flexibility of the entity, measured by its outstanding debt, cooperation processes are influenced, in addition to the latter factors, by the short-term solvency of the entity.

The division of the period of analysis into pre-crisis (2002-2007) and crisis (2008-2010) reveals differences in the behaviour pattern. While the GR did not alter the elements of the financial condition that lead municipalities to outsource services, there were significant changes with respect to processes of inter-municipal cooperation. On the other hand, in the pre-crisis period, questions of sustainability, flexibility and short-term solvency led municipalities to outsource their services, while during the GR, only debt and financial independence had a significant influence on cooperation decisions.

Another noteworthy finding is that the debt variable presented a different behaviour for the two responses: while it was negatively associated with outsourcing, the sign for cooperation was positive, because in the accounts item of outstanding debt municipalities are obliged to include the debt of the consortia or municipal associations in which they participate.

As a future line of research, we intend to analyse other forms of management open to local authorities in their aim to become more efficient and to overcome situations of fiscal stress. These forms include the creation of autonomous organisations and the provision of services by provincial councils. Finally, more complex analytic methods will be used, highlighting the strength and direction of relationships among the variables that may account for the level of outsourcing. To this end, and in view of the strong correlations between many of the financial indicators, we propose a preliminary factor analysis to identify specific factors that, after explaining and justifying their possible relations in terms of the corresponding theory, will allow us to use structural equation models based on a path-analysis method to explain the level of outsourcing and other forms of management.

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