The effect of municipal amalgamations on social assistance receipt
A difference-in-differences estimation
Dirk Honderd
S2581558
Date: June 8
th2020
MSc Public Administration – Economics and Governance
Leiden University
Faculty of Governance and Global Affairs
Supervisor: Prof. dr. P.W.C. Koning
Word count: 15,972
Abstract
Municipal amalgamations occur annually in the Netherlands, often supported by the argument that small local governments lack administrative capacity. In this thesis, a difference-in-differences approach is applied to estimate the effect of these amalgamations on the social assistance recipiency, inflow and outflow rates between 2004 and 2015. To measure pre-treatment and long-term pre-treatment effects, data on the social assistance receipt and the various control variables are analysed from 2001 until 2017. Two models are applied for the
estimation. First, a difference-in-differences model is used that compares the merged
municipalities with a control group consisting of all municipalities that have been unaffected during the research period. Second, a fixed effects model is applied. This model compares the municipalities that merge to a control group consisting of municipalities that will merge within the research period but did not do so yet. This method can also be referred to as “timing-of-events”. In both methods, year effects and various controls are included. I find almost no significant effects of amalgamation on the social assistance recipiency, inflow or outflow rates for both models. Estimation with a difference-in-differences model shows a small increase in outflow rates the year before consolidation. This effect disappears when using the fixed effects model. Subgroup analyses with the fixed effects model are performed to explore heterogeneity of treatment effects. One year before the merge, an increase in outflow and inflow is experienced in three subgroups: amalgamations excluding annexations, amalgamations that result in (almost) a doubling of municipalities’ population size and amalgamations involving municipalities with fewer than 25,000 inhabitants before their merger. Amalgamations involving three or more municipalities only experience an increase in the outflow rates. Overall, it can be concluded amalgamation does not result in major significant changes in the social assistance recipiency, inflow and outflow rates.
Table of contents 1. Introduction ... 5 1.1 Research question ... 7 1.2 Approach... 7 1.3 Structure... 8 2. Institutional settings... 10
2.1 The WSA and social assistance policies... 10
2.1.1 The budget ... 11
2.1.2 The instruments ... 12
2.2 Amalgamations ... 12
2.2.1 Motives behind amalgamations... 13
3. Literature review ... 14
3.1. Empirical evidence on optimal scale size ... 14
3.2 Empirical evidence on relationship size and social assistance receipt ... 16
3.3 Optimal size theory ... 17
3.3.1 Production efficiency ... 17
3.3.2 Allocative efficiency ... 18
3.4 Allocative and productive efficiency in social assistance policy ... 19
3.4.1 Moral hazard ... 21
3.4.2 Low productivity ... 22
3.4.3 Misallocation and labour market imbalance ... 23
3.4.4 Low labour demand... 24
3.4.5 Coordination / information problems ... 24
3.5 Hypotheses... 28
4. Data... 29
4.1 Descriptive sample statistics ... 31
4.2.1 Social assistance recipiency rates... 34
4.2.2 Social assistance inflow rates ... 36
4.2.3 Social assistance outflow rates ... 38
5. Models ... 40
6. Results ... 43
6.1 Social assistance recipiency rates ... 43
6.2 Social assistance inflow rates ... 45
6.3 Social assistance outflow rates ... 47
6.4 Additional analysis ... 49
6.4.1 Common trend assumption... 49
6.4.2 Heterogeneity ... 49
6.5 Hypotheses... 55
7. Conclusion ... 56
8. Discussion... 59
1. Introduction
In the Netherlands, the social assistance benefit system has experienced various reforms in the last two decades. Whereas it used to mainly serve as an income provision for those in need , social assistance policies are currently considered as instruments to re-integrate and activate people receiving benefits back to the labour market (Broersma, Edzes & Van Dijk, 2011). This transition from ‘welfare to workfare’ (Lødemel & Trickey, 2000) has been accompanied by a change in the Dutch social assistance organisation as well. Through the process of decentralisation, governmental tasks and competencies have increasingly been transferred from central to local governments (Bovens, Ten Hart & Van Twist, 2012).
The largest reform in the social assistance system took place with the introduction of the Work and Social Assistance Act (WSA) in 2004. Several years before, the discussion about the organisation of the system had ignited when various reports concluded
municipalities lacked the incentive and interest to decrease social assistance caseloads. There would be no strict supervision on the inflow into assistance, recipients were insufficiently encouraged to find a job and fraudulent activities were left undetected. Altogether, the system surrounding social assistance was ineffective and inefficient and change was deemed
necessary (The Netherlands Scientific Council for Government Policy, 1994; Committee Van der Zwan, 1993).
Since the WSA, municipalities receive lump-sum payments for social assistance benefit payments. Accordingly, they bear full financial responsibility for the recipiency within their territory. With that new responsibility, municipalities also have received more policy discretion when deciding on their local integration and activation policies (Broersma, Edzes & Van Dijk, 2011). After the introduction of the Participation Act in 2015, the WSA was
effectively expanded with two new schemes: the Social Work Provision Act (WSW) and the Work and Employment Support for Disabled Young Persons Act (Wajong). The Participation Act harmonized these acts which resulted in a framework focused on the reintegration and activation of all persons at the bottom end of the labour market (Echtelt et al., 2019).
Overall, it seems the WSA has been effective, as municipalities have reduced the number of social assistance recipients (Bosselaar, Bannink, Deursen & Trommel, 2007; Kok, Tempelman, Koning, Kroon & Berden, 2017). When given the financial responsibility and more policy discretion, municipalities can decrease the social assistance recipiency rates within their territory. At the same time, decentralisations such as the WSA, the Participation Act and others have led to more responsibilities and an increasing workload for local
governments (Boogers & Reussing, 2018). Smaller municipalities would not have sufficient government capacity to effectively and efficiently execute their new tasks and competencies. Consequently, these municipalities need to increase their capacity and are required to
amalgamate, entailing a full merger of the administrative and political organisation. This leads the so-called ‘decentralisation paradox’: tasks are increasingly being transferred to local governments as these are thought to execute these more effectively on a smaller scale. As a result of the increasing workload from decentralisations, municipalities are required to amalgamate to a larger scale (Boogers & Reussing, 2018).
Besides this seemingly contradictory process, the advantages of amalgamation are still widely debated. First of all, the theoretical academic debate does not provide clear results on consolidation effects. A larger scale would lead to scale advantages due to increased
specialisation, decreasing marginal costs and greater bargaining power (Geertsema, 2017). However, amalgamation could also lead to scale disadvantages. Larger scales hinder an accurate matching of produced services and goods to local tastes. If there are spatial differences in local preferences, smaller governments would be more efficient in matching services to these tastes (Oates, 1972). Second of all, international and national empirical studies show inconclusive results. Amalgamation would potentially lead to increased
administrative capacity, higher efficiency and better ways of coping with new regional policy issues (Fraanje, Herweijer, Van Assenbergh, Brouwer and Heins, 2008; Van den Dool & Schaap, 2011). However, quantitative research on amalgamations in the Netherlands shows consolidation does not lead to efficiency gains (Allers, 2010) or lower per capita spending (Geertsema, 2017). An international meta-analysis on case-study research also found no clear effects off amalgamation (Fox & Gurley, 2006) and an extensive literature overview on the effects of amalgamation on efficiency by Holzer, Fry, Charbonneau and Ryzin (2009) found mixed to no results.
Even though studies show mixed evidence on the effects of amalgamations, the number of municipalities has decreased considerably the last years. Since the introduction of the WSA in 2004, the number of municipalities has decreased from 483 to 355 in 2020 (Statistics Netherlands, 2020a). So far, there has been no research on the effect of amalgamation on social assistance development in municipalities. One study gives some indirect evidence on the effects of amalgamation – or municipality size in general - on social assistance receipt in the Netherlands. Edzes (2010) investigates the effect iveness and
efficiency of labour market strategies aimed at decreasing social assistance dependency. Using a Stochastic Frontier Analysis, he concludes that larger municipalities are more
efficient, as their social assistance costs are relatively lower to smaller municipalities.
However, his analysis only looks at the expenditures and not at the actual recipiency, inflow or outflow rates. Furthermore, amalgamations are not included in his analysis. This research aims to provide the first evidence of amalgamation effects on the social assistance receipt.
1.1 Research question
There seems to be no academic consensus on the effects of municipal amalgamation on administrative capacity and the relating efficiency. Both theoretical arguments and empirical evidence show mixed effects. Furthermore, no research has been done on the effects of amalgamation on social assistance receipt. Therefore, it is relevant to study the effect of municipal consolidations on the efficiency in the execution of the municipality’s social assistance tasks and competencies.
This has led to the formulation of the following research question: “What is the effect of municipal amalgamation on the social assistance recipiency, inflow and outflow rates of municipalities?”
Currently, there is still academic dissensus on consolidation effects. With the ongoing amalgamations in the Netherlands, this study aims to provide more clarity on the effects of amalgamation in the context of continuing decentralisations of the Dutch social security system. Results of this thesis could add to the ongoing political and academic debate on the value of municipal mergers.
1.2 Approach
The effect of amalgamation of the social assistance development was analysed using a difference-in-differences (DID) approach. This is a common research method to analyse amalgamation effects (Tavares, 2018). This approach compares a control group that is not affected by a reform with a treatment group that is affected. An important assumption is that that the treatment group would have followed the same trend over time as the control group if it would have been unaffected, the so-called ‘common trend assumption’. If this holds, the control groups trend can be used as a counterfactual to the trend of the treatment group. Instead of requiring randomization where treatment and control group are equal besides the absence or presence of treatment, DID removes the bias that would be the consequence of
time-invariant differences between the treatment and control group (Angrist & Pischke, 2015).
For this research, two models were used. First, a difference-in-differences model was estimated with OLS. This model takes all the municipalities that have not amalgamated during the research period of 2004 until 2015 as a control group and compares it to all municipalities that have amalgamated. Secondly, the effects were estimated using a fixed effects model. This model compares the municipalities that consolidate to a control group consisting of municipalities that will merge within the research period but did not do so yet. This can also be referred to as “timing-of-events”. In both models, I included year effects and various controls, such as population size and household types, reducing the risk of omitted variable bias. Furthermore, assuming the sample is heterogeneous, amalgamations will have different effects on different municipalities and these different effects should be distinguished. Therefore, subgroup analyses were performed to explore heterogeneity of treatment effects.
Three different outcome variables were used to measure the effect on social assistance receipt. Firstly, the number of social assistance recipients as a share of the total municipal population was used to estimate the recipiency rates. Secondly, the inflow as a share of the total municipality population was used to calculate the inflow rates. Lastly, the outflow out of assistance as a share of the total number of recipients was used to measure the outflow rates.
Almost all estimations resulted in small and insignificant effects for the recipiency, inflow and outflow rates. One year before amalgamation, a small increase in outflow rates was found. Subgroup analyses found a small increase in the outflow rates the year before the merger in the different groups as well. Furthermore, an increase in inflow rates was found the year before the merger for all subgroups besides amalgamations including three or more municipalities. Overall, the results in this thesis indicate that municipalities that amalgamate do not experience changes in the number of social assistance recipients, or in the social assistance inflow and outflow rates. A merger, therefore, does not seem to improve the performance of municipalities in lowering the social assistance receipt.
1.3 Structure
The thesis is written in the following order. Fist, the institutional setting of amalgamations in the Netherlands and the Dutch social assistance regulation is described in chapter 2. Hereafter, the theory on amalgamations and its application on social assistance regulation are presented in chapter 3. Chapter 4 explains how the data were collected, which variables were included and provides the descriptive statistics. Chapter 5 presents the models that were applied to
estimate the results, after which these results are described in chapter 6. The conclusion and policy recommendations of the thesis can be found in chapter 7 and the discussion including the study’s limitations in chapter 8.
2. Institutional settings
2.1 The WSA and social assistance policies
The last decades the reasoning behind social assistance policy in the Netherlands has changed dramatically. Whereas previously the local government’s task was to judge the legality of welfare applications and to ensure the inhabitants received their entitled benefit, social assistance policies are now considered as providing ways of re-integrating and activating people on social welfare back to work (Inspectie Werk en Inkomen, 2005). The change to a more activating perspective on welfare, which can be found on an international level as well, is described as the transition from ‘welfare to workfare’, where responsibility is attributed to the individuals themselves, requiring them to (find) work in exchange for receiving social assistance (Lødemel & Trickey, 2000).
In the ’90s, municipalities were regarded to be able to exert little influence on the inflow and outflow rates within their territory. Local differences in the costs of social assistance would be caused by demographic differences and would not have been the result of different policies. Therefore, they did not bear the financial risk for social assistance receipt: 90% of the ex-post social assistance benefit costs of municipalities were reimbursed and only 10% was paid as a lump-sum. Several reports concluded that municipalities could lower the receipt, but lacked the financial incentive and interest. The system, therefore, needed to be reformed (Committee Etty, 1996; Committee Van der Zwan, 1993). With the introduction of the WSA, municipalities became financially responsible for the inflow and outflow from welfare, for preventing illegitimate welfare allocations and ensuring the welfare recipients received their entitled income (Edzes, 2010). Without the ability to change the eligibility conditions for assistance, the only way municipalities could ensure minimal social assistance receipt is now through policies aimed at decreasing the number of recipients (Kok,
Tempelman, Koning, Kroon & Berden). Bosselaar, Bannkink, Van Beursen and Trommelen (2007) identified three general methods through which the WSA ensured that these goals could be achieved: decentralisation, deregulation and less reporting obligations.
• Decentralisation: through decentralisation, tasks and competencies are transferred to lower governments from higher governments (Boogers, Schaap, Karsten & Van den Munckhof, 2008). With full financial responsibility, municipalities get to keep the allocated budget if there is a surplus and spend it according to their preference. However, if the costs are higher than the allocated budget, they are expected to compensate for the deficit with their resources. As a consequence, local
governments are encouraged to operate as efficiently as possible as this would prevent a budgetary deficit and could result in a surplus (Bosselaar et al., 2007).
• Deregulation and less reporting obligations: with the transfer of the financial risks and the decreasing need for the national government to control the municipalities, local governments have more discretionary freedom in reviewing welfare applications and implementing local policies. Furthermore, less information has to be reported to national governments (Bosselaar et al., 2007).
2.1.1 The budget
From 2004 onwards, municipalities receive a lump sum budget for social assistance annually. This budget consists of an “income part” that is meant to finance the benefits and a “work part” that finances the reintegration instruments. The income part is based on the macro budget for social assistance that the national government calculates annually. This budget is divided amongst the municipalities with two models: the objective and the historical
distribution model. The objective distribution model determines the whole budget for municipalities with 60,000 inhabitants or more and somewhere between 0 and 100% for municipalities between 30,000 and 60,000 inhabitants. It calculates how much budget the municipality is allocated based on exogenous factors. These factors are mostly demographic characteristics such as household and sector composition and the share of lower educated inhabitants. If the costs are higher or lower than can be expected from these factors, the municipality experiences a budget deficit or surplus, respectively. This model increases yardstick competition between the local governments: because the macro budget is partly based on the average performance of the other municipalities, they need to perform at least as well as the average municipality to avoid a deficit (Edzes, 2010).
The historical model is applied fully to municipalities with 30,000 or fewer
inhabitants, or partly for municipalities that have between 30,000 and 60,000 inhabitants. This model uses historical data on the number of welfare recipients in a municipality in a base year to calculate the ratio the municipality receives from the macro budget in the current year (Bosselaar et al., 2007).
The work part is a merged collection of a series of resources that have been made available during the ’90s to increase activation and reintegrate people in the workforce. Consequently, it is based on the historical model. The national budget is divided by the number of welfare recipients and adjusted for different local employment indicators (Edzes, 2010).
2.1.2 The instruments
To achieve the goals of the WSA, local governments have various instruments at their disposal. For instance, they can implement active labour market programmes (ALMPs) (Broersma et al., 2011). These programmes are focused on increasing the chance of a recipient to find work or to enhance their productivity (OECD, 2002). According to the
municipalities themselves, the Work First instrument is the most effective (Edzes et al., 2007). Work First is a broad concept, enabling municipalities to demand various efforts from the recipients in return for their benefits. Although each local government has the policy
discretion to formulate their exact strategy, it generally consists out of a certain combination of mandatory work and productivity-increasing measures (Bunt, Grootscholte, Kemper & Van der Werf, 2008). This approach decreases inflow as it discourages people to apply for
assistance, while it increases outflow as the recipient increases their chances on the labour market. Other discouraging and activating instruments include for instance mandatory job-search, education and the control on compliance on these conditions.
Another ALMP is the usage of wage subsidies to compensate for the low productivity and low labour demand by making employment cheaper for employers. By providing the subsidy, the municipality does not have to pay the benefits as a wage is earned that provides their income (Edzes, 2010). A way to increase the job-finding rate is through mediation, where municipalities try to match labour demand and supply on the labour market. The idea here is that the recipient is not unwilling or unproductive, but is unemployed due to mismatch of demand and supply on the labour market (Broersma et al., 2011).
Besides the instrument themselves, the ‘governance’ of these ALMPs influences the social assistance receipt as well. By coordinating with external partners such as the
Employment Insurance Agency (EIA), local care facilities and employers, municipalities can increase the effectiveness of the policy. Besides the coordination with external partners, local governments can coordinate social assistance policy with other policy fields, for instance through cooperation between the education and social affairs department to improve educational re-integration facilities (Edzes, 2010).
2.2 Amalgamations
Amalgamation is the process by which two or more municipalities are being merged into one (Derksen & Schaap, 2004). During the last century, the municipal landscape has changed dramatically through this process. Over the last 100 years, over 700 municipalities have
disappeared. Whereas there were 1110 municipalities in the Netherlands in 1920 (Schaap, 2015), there are currently 355 municipalities left (Statistics Netherlands, 2020a).
2.2.1 Motives behind amalgamations
Currently, there are three general motives behind amalgamation (Fraanje et al.,2008): 1. Most importantly, amalgamations would lead to improved administrative capacity.
Throughout the years, this concept has become the main argument for amalgamations (Korsten, Abma & Schutgens, 2007). The concept of administrative capacity is very broad. Boogers and Schaap (2007, p.6) define it as “the ability to execute tasks in co-governance and autonomy and to adequality cooperate with other governments and to represent the local community”. With more tasks transferred from national to local governments through the process of decentralisation, the increase in scale as the result of amalgamation would ensure municipalities can execute the tasks adequately (Boogers & Reussing, 2018).
2. A second motive is a need for municipalities to expand their housing capacity. Often larger municipalities seek to merge with villages near their territory to have more building possibilities.
3. The last general motive is the emergence of new spatially characterized tasks t hat demand an integrated policy with other municipalities, such as the conservation of a natural park. Compared to the other motives, this argument is used less often.
3. Literature review
The motives used to argue in favour of consolidation are eventually all linked to the idea of optimal scale size. As such, amalgamations are focused on achieving economies of scale (Allers & Geertsema, 2016). The spatial need and the emergence of new spatially
characterized tasks are quite literal: the territory of the municipality is expanded to solve spatial problems. However, enlarging administrative capacity though amalgamation is also based on optimal scale. Increasing municipal size leads for instance to more specialisation within the organisation which eventually leads to a higher administrative capacity (Boogers & Schaap, 2007). To understand the possible effects of scale enlargement on municipal
performance, results of empirical studies on the optimal municipal scale will be reviewed, after which the theories supporting smaller of larger scales will be discussed.
3.1. Empirical evidence on optimal scale size
An extensive case study literature overview by Holzer et al. (2009) on efficiency and optimal local government size provides evidence for an “inverted U-shaped relationship between size and efficiency” (p.1). Smaller governments produce economies of scale if they increase until a certain size and produce diseconomies of scale once they become larger than a certain size. The thresholds for these effects, however, seems to differ in various studies: some studies find that municipalities do not become more efficient when exceeding 20,000 inhabitants
(Katsuyama, 2003) and others conclude that no relationship exists at all (Boyne, 2003). Nevertheless, from all these studies, Holzer et al. (2009) conclude that small governments could increase efficiency by increasing in size if they have less than 25,000 inhabitants, while large municipalities become inefficient with more than 250,000 inhabitants. Consequently, the optimal scale lies somewhere between 25,000 and 250,000 inhabitants. In this research, it can be expected that municipalities with less than 25,000 inhabitants experience a lower social assistance receipt when merging, while amalgamations involving municipalities with over 250,000 experience an increasing receipt. Furthermore, the inverted U-shaped
relationship implies that an aggregated analysis involving both small and large municipality consolidations produces economies and diseconomies of scale, respectively. Consequently, these positive amalgamation effects could cancel out negative effects (Allers & Geertsema, 2016). To account for this, the effects of consolidations will be estimated for different groups, such as amalgamations where all municipalities experience (almost) a doubling in population size, or amalgamations where all municipalities have less than 25,000 inhabitants before the
merger. This might provide insight into the different effects of size on (dis)economies of scale.
Various studies that compare size and efficiency focus on per capita spending. If the costs would decrease, more resources would become available, which could result in better and more services. These studies present mixed results however, with researchers finding per capita spending to be either lower, higher or unchanged after a municipal merger (Allers & Geertsema, 2016; Geertsema, 2017). Furthermore, Allers and Geertsema (2016) point out that lower spending does not automatically mean municipalities have become more cost -efficient as it could also be the result of decreasing service production.
Whereas these previous studies mostly find amalgamation effects on aggregate municipality performance or general spending, others look into changes in specific services. A case study review by Fox and Gurley (2006) finds that the relationship between size and efficiency is dependent on many factors that are municipality and service-specific. Whereas economies of scale might appear for services such as waste processing, these effects are less likely to be perceived in services produced by various organisations and close to the
municipal inhabitants, such as education. As social assistance is provided close to the
recipient and its service provided by many organisations and persons (caseworkers, EIA, care facilities, educational and Work First facilities et cetera) these scale economies could be less visible there as well. Interestingly, Steiner and Kaiser (2017) find, using a difference-in-differences method on amalgamated local governments in Switzerland, that amalgamation leads to improved performance in their social service delivery. They do not find this effect in many other services from the same municipalities, but cannot explain the reasoning behind these different findings.
Another possible explanation for the findings of mixed results for different services is given by Holzer et al. (2009). They conclude that large scale local governments are generally more efficient in producing capital intensive services, such as waste processing and sewerage. However, smaller-scale governments would be more efficient in labour-intensive services. As social assistance delivery is mostly a labour-intensive service, smaller municipalities might be more efficient. It could also be the case that within services, some tasks would benefit more from small scale and others from large scale governments. Bish (2001) shows in his study on police departments, that standardized tasks are executed more efficiently in small
municipalities, while specialized services benefit from larger-scale governments.
A final interesting effect found specifically for municipal amalgamations is the so-called ‘common pool’ effect. Municipalities have shown to increase their expenses and their
debt in anticipation of a merger. Before amalgamation, municipalities can decide to increase their deficits and debts as these will spread over a larger future tax base, while the advantages will be for the municipality before the merger (Blom-Hansen, 2010). This behaviour has been found to exist in various studies (Allers & Geertsema, 2016). In case of social assistance, the common pool effect can cause municipalities to be less efficient in executing their social assistance tasks before the amalgamation, as they can benefit from a larger future tax base to bear the costs in the near future. It could be expected that in the years before amalgamation, the recipiency and inflow rates would be higher and the outflow rates lower due to this common pool effect.
3.2 Empirical evidence on relationship size and social assistance receipt
Qualitative and quantitative research on the relationship between municipality size and service delivery efficiency does not provide conclusive answers on general amalgamation effects. Furthermore, Steiner and Kaiser (2017) seem to be the only one to look at the effect of a merger specifically on social services. However, there have been some Dutch studies that find a relationship between municipality size and the execution of the social assistance tasks. Their results might provide some implications.
Edzes (2010) concludes that large municipalities implement different social assistance policies compared to small municipalities. They monitor fraudulent activities to a greater extent, cooperate more intensely with external parties and focus more on the coordination of social assistance with other policy fields. Furthermore, he finds that smaller municipalities have relatively higher social assistance costs than larger municipalities, suggesting they are less efficient. This could imply that amalgamation leads to increased efficiency in the form of lower recipiency and inflow rates, and higher outflow rates. A study by Edzes, Gardenier, Vrieze and Horsten (2006) finds that larger municipalities coordinate their social assistance policy to a greater extent with other policy areas. Furthermore, they conclude large
municipalities cooperate more with external actors involved in the social assistance policy. These findings are in line with Edzes’ (2010). Marlet, Ponds, Woerkens and Zwart (2016) show that municipalities with a larger budget are less incentivized to introduce drastic policy changes to lower the costs. Smaller municipalities might, therefore, be more incentivized to introduce policy changes than larger ones. Although Allers, Ed zes, De Ruijter and Engelen (2014) confirm this, they also show that a budgetary surplus leads to higher social assistance costs the next year, while a budgetary deficit leads to lower costs afterwards. Consequently,
the possible budgetary room felt by larger municipalities would not lead to inefficiencies in the long-term.
Altogether, there are some indications that larger municipalities are generally more efficient, coordinate their social assistance to a greater extent with other policy areas and cooperate more with external parties. From these studies, however, no causal inferences can be made about the possible amalgamation effect on social assistance receipt yet.
This short overview of studies on the optimal scale and amalgamation effects do not provide a clear answer to the optimal municipality size regarding social assistance. To better understand the effects of amalgamation on the effectiveness of social assistance policy, theories about the optimal scale will be discussed in more detail. The appliance of these theories on the Dutch social assistance system might lead to clearer anticipated effects of amalgamation. These effects will then be formulated into hypotheses, which will be tested later on.
3.3 Optimal size theory
Theories on the optimal municipality size differ in whether they argue in favour of smaller or larger jurisdictions (Blom-Hansen, Houlberg, Serritzlew & Treisman, 2016). The arguments in favour of either one are generally based on two types of efficiency crit eria (Geertsema, 2017). Productive efficiency states that efficiency is attained when the output of one good or service cannot be increased without the reduction of output of another good or service, given society’s available technology and inputs. Allocative efficiency states that goods and services are allocated efficiently if reallocation would make at least one consumer worse off (Nas, 2016). If both criteria are satisfied , there is a Pareto optimum leading to a maximization of utility functions (Geertsema, 2017). The question thus arises whether a larger scale through amalgamation would 1) lead to a more efficient ‘production’ of social assistance services and 2) an optimal distribution of those goods and services amongst the consumers, in this case, the local community.
3.3.1 Production efficiency
Geertsema (2017) identifies multiple ways in which municipality size affects production efficiency positively. First, larger municipalities have more employees working on the same set of tasks. Labour can be divided amongst more people, resulting in fewer tasks per person and more time per task per employee. This enables specialisation, contributing to the higher
efficiency of the employee and the aggregated department and municipality. Secondly, economies of size can increase when municipalities get larger. Because they experience the same fixed costs for certain services as smaller municipalities but can distribute these costs over a larger output, the marginal costs decline. Likewise, the number of employees and politicians does not grow proportionally to the population size. Consequently, the mean costs per inhabitant decrease. Lastly, larger municipalities have more bargaining power when contracting private companies. This may lead to lower prices and/or a higher quality of services and goods.
However, larger organisations can also experience scale disadvantages due to
diseconomies of scale. Larger organisations require more internal coordination, as there are more civil servants that each fulfil their tasks. The administrative costs that are made to coordinate their efforts and the increased noise that occurs, lead to inefficiencies (Geertsema, 2017). Furthermore, growing organisations typically have more hierarchical relations,
resulting in more information flows and higher informational costs. The information
asymmetries and noises that occur, decrease the efficiency of organisations (Blom-Hansen et al., 2016). A second negative consequence of increasing jurisdictions is the decrease in competition between the jurisdictions, as there are simply fewer local governments. This argument is particularly relevant for the administration of social assistance benefits.
‘Yardstick competition’ can result in higher efficiency as local politicians are responsive to voters that compare local performances on their performances. If there are fewer jurisdictions, there is less competition between municipalities on the base of efficiency (Allers, 2012). In the case of the social assistance system, this means that smaller municipalities would
experience more competition from others to keep their receipt low. Interestingly, because the objective distribution model mostly applies to larger municipalities, amalgamation could lead to an increase in yardstick competition (Edzes, 2010).
3.3.2 Allocative efficiency
Most arguments regarding allocative efficiency are in favour of smaller governmental units. The main argument in favour of allocative efficiency states that larger municipalities become more responsive to inhabitants that would otherwise not live within their jurisdiction. When formulating and implementing public policy, the municipality is less responsive to the welfare effects on persons outside of their jurisdiction. However, this would lead to inefficient
outcomes as these people are still be affected by the decisions of those municipalities, through so-called externalities. By increasing jurisdiction size, more inhabitants are included in their
decision making and thus spillover effects are reduced as these externalities are internalized (Geertsema, 2017; Oates, 1972).
An advantage of smaller governments is their ability to match their public services to their inhabitants’ preferences. As local governments would be closer to the citizens than centralized governments due to their knowledge of local preferences, tastes and conditions (Oates, 1972), the same can be applied to smaller and larger municipal jurisdictions (Blom-Hansen et al., 2016). The ability of smaller governments to better match policy with local preferences is the result of three mechanisms. First of all, small groups of voters have relatively more influence in smaller municipalities, increasing their ability to consciously affect local policy. Second, it is easier for an organisation that needs to formulate one policy for all local inhabitants that matches their preferences, if there are less divergent preferences to be included. Third, by increasing municipality size, the number of local jurisdictions decreases. Fewer municipalities leave fewer possibilities for diversity in local policies, leaving people with decreasing options to choose from (Geertsema, 2017).
3.4 Allocative and productive efficiency in social assistance policy
With the introduction of the WSA, local governments were expected to be able to directly influence the inflow and outflow into assistance to make municipalities more efficient. Research by Broersma et al. (2012) concluded that, with the new instruments, municipalities have become more cost-efficient. There are also factors on which the municipalities have no influence. However, these factors do determine the assistance receipt. To understand how scale effects can influence the municipalities ability to influence social assistance receipt within their territory, the determinants for the receipt should be made clear. Figure 1 illustrates these determinants (Allers et al. (2013, p.20) The main determinant of the receipt are exogenous factors on which the government has no direct influence. These are also the factors that are included in calculating the local budget with the objective distribution model. Examples are household types, population density, the share of inhabitants with a migration background and the share of the lower educated inhabitants (Edzes, 2010). The other two determinants are the organisational efficiency and the local policy, that together form the potential policy discretion. These are the determinants on which a municipality does have influence. The local policy element consists of strategies aimed at achieving the purpose of the WSA: lower the inflow and increase the outflow from welfare, preventing illegitimate welfare allocations and ensuring the welfare recipients receiving their income. The available
strategies for these policies will be discussed later. Furthermore, municipalities can lower costs by improving efficiency. The organisation of the internal municipal processes would result in minimal social assistance costs (Allers et al., 2013).
Figure 1
Determinants of social assistance development.
Note: Adapted from “De doorwerking van de financiële prikkel van de WWB binnen gemeenten”, by Allers, M.A., Edzes, A., Engelen, M., Geertsema, J.B., , de Visser, S. and Wolf, E., 2013, p.20, Groningen: COELO.
I argue that productive efficiency mostly affects the organisational efficiency and allocative efficiency mostly affects local policymaking. As argued, amalgamation can result in lower or higher efficiency of the service production, and an increasing or decreasing convergence of the produced services and the local tastes and conditions. The same applies to this research context, where amalgamation can lead to more efficient or inefficient production of social assistance services and a decreasing or increasing convergence of these services and the local community’s preferences. Using the five possible strategies and their respective instruments identified by Edzes (2010), I show how scale advantages and disadvantages can occur in the social assistance tasks as a consequence of increasing or decreasing productive and allocative efficiency. Scale advantages would then lead to lower recipiency and inflow rates and higher outflow rates. Scale disadvantages would lead to higher recipiency and inflow rates and lower outflow rates. This reasoning is illustrated in Figure 2.
Figure 2
Underlying mechanisms of consequences amalgamation on the social assistance receipt
Edzes (2010) identifies five problems which municipalities face in their efforts to minimize the social assistance receipt and shows which strategies are available to solve each of these. The effects of amalgamation on productive and allocative efficiency will be related to these problems and solutions to understand the possible consolidation effects. A summary of the problem, the available instruments and the scale advantages and disadvantages are be presented in table 1.
3.4.1 Moral hazard
First of all, municipalities face moral hazard problems. When assessing the legality of the application and providing the benefits there exists an information asymmetry between the recipient and the municipality. Because the recipient has more information about his job search effort, he or she can put in less effort, time and/or money than is expected to return to work. However, as the municipality pays for the recipient’s social assistance benefits, they want the recipient to return to work as soon as possible. Consequently, the municipality has to take action to ensure the recipient puts in the effort to flow out of assistance, for instance through a Work First programme and to check if the recipient complies with the conditions.
• Production efficiency. Specialisation enables larger municipalities to have employees specifically look for fraudulent activities and to check whether recipients comply with the conditions. Furthermore, Work First facilities, where recipients work in return for their benefits, can be organised with lower marginal costs and companies facilitating this can
be contracted with greater bargaining power. However, it also requires more coordination in larger municipalities as all these employees and external partners need to coordinate their efforts.
• Allocative efficiency. It is easier to formulate a policy for all local inhabitants that match individual preferences and local conditions if there are fewer inhabitants whose needs and conditions need to be taken into account. Larger municipalities experience larger
information asymmetries with the recipient. Therefore, it is more difficult for them to have a detailed picture of all recipients, their preferences and their efforts in job-seeking.
Consequently, control afterwards and a ‘strategy of threat’ is more important in larger municipalities. Smaller municipalities might have less need for that, or would be even more efficient, as they would know their social assistance recipients better.
3.4.2 Low productivity
Individuals receiving social assistance are often not sufficiently productive to receive wage earnings above the income provided by the benefit. This so-called ‘productivity trap’ can be caused by insufficient experience, skills or education or a disability (Nelissen, Fontein & Van Soest, 2005). The municipality can use the ‘work part’ of its budget for active labour market policies (ALMP), which include a range of measures such as schooling and subsidized jobs to increase their productivity, so they may find work with wage above the benefit level in the future. Another instrument can be the usage of wage subsidies (Edzes, 2011).
• Production efficiency. Larger municipalities have the possibility of letting (more) employees specialise in reintegration strategies. Furthermore, larger municipalities also have greater bargaining power when contracting private companies (Geertsema, 2017). In this case, it could be companies focused on reintegration through experience and/or offering education to the social assistance recipients. With their bargaining power, larger municipalities might be able to contract better-performing reintegration companies or educational institutions than smaller municipalities. Moreover, if these measures include fixed costs, larger municipalities can spread these costs over more recipients, leading to lower average costs for every beneficiary. A possible disadvantage can be the
inefficiencies caused by a lack of coordination between the employees working on
specialised tasks and the noise created as information has to flow through more layers. For example, a local employer that is familiar with the municipality’s social service and employs persons receiving wage subsidies could get this organised more efficiently in a
smaller municipality. In a larger social service, this ‘direct’ line becomes less convenient due to all sorts of congestions and coordination and communication issues.
• Allocative efficiency. Smaller municipalities are better at matching the local preferences of their inhabitants. It might be more difficult for merged municipalities to offer the facilities aimed at raising recipients’ productivity that match the needs, preferences and conditions for the individual recipient. For example, a person experiencing language barriers
preventing him or her from finding work requires different kinds of services than a person who has not got the necessary job skills. If a municipality provides a person with language problems specific job-trainings, while the other receives language classes, these measures will be inefficient. Knowledge about the recipients is thus an important aspect of
increasing the efficiency of the policy.
3.4.3 Misallocation and labour market imbalance
Demand and supply of labour do not always meet each other naturally. Municipalities can take measures that facilitate the match of supply and demand on the labour market (the Ministry of Social Affairs and Employment, 2011). Municipalities can do this for instance through mediation or informing unemployed individuals about the job vacancies and the employer about the persons searching for a job (Broersma et al., 2011).
• Production efficiency. Larger municipalities can employ people specifically focused on increasing the match between labour demand and supply, for example through regional or local vacancy database. Or they can contract private companies to do so at lower costs than smaller municipalities can. However, larger municipalities might experience
increased coordination and control costs that cause inefficiencies within the organisational processes.
• Allocative efficiency. An advantage of larger municipalities is the size of their labour markets. As illustrated by De Vetten and Koning (2008), municipalities are incentivized to find employment for social assistance recipients living within their jurisdiction, but not for recipients in other municipalities. Finding employment for recipients outside of their territory leads to fewer vacancies for their own recipients. Consequently, municipalities are not actively sharing their local labour markets with each other. If municipalities increase in size however, the local labour market increases in size and so does the
possibility of matching demand and supply. As the labour market has a more regional than local nature (Edzes, 2010), an increase in labour market scale further helps social
reducing the spillover effects. When a municipality merges, the welfare externalities of decisions that would normally spill over outside of their borders are now internalized. Therefore, municipalities have a greater incentive to include these effects in their decision-making process, leading to an increase in allocative efficiency.
A disadvantage is that larger municipalities have less information on the individual preferences of employers and job-seekers, making it more difficult to match demand and supply of labour. Greater knowledge about the skills and knowledge local employers require and the skills job seekers have, would lead to more matches of demand and supply.
3.4.4 Low labour demand
Unemployment and social assistance dependency can arise when there is more supply of than demand for labour. Municipalities can encourage local job creation to a certain extent by investing in their infrastructure and industrial sites (Boersma et al., 2011). The few studies on the actual influence of municipalities on local labour market demand , however, suggest this influence is limited (Denters & Van Dam, 1993; Elhorst, Broersma, Zeilstra & Oosterhaven, 2007).
• Productive efficiency. Larger municipalities can employ people that focus on increasing the general labour demand. This, however, requires more coordination within the municipality and possibly leads to more managerial layers, which can both lead to inefficiencies. Moreover, the increase of larger jurisdictions reduces yardstick competition between municipalities on attracting companies. This leads to possible inefficiencies in job creation opportunities. However, as explained in Section 2.1.2, larger municipalities compete against one another due to the objective distribution model. This is a form of yardstick competition that would then increase due to amalgamation.
• Allocative inefficiency. As it is easier for smaller municipalities to adjust the policy to local preferences and conditions, it also might be easier to invest in job creation projects that match the local needs.
3.4.5 Coordination / information problems
The problem of coordination manifests itself in two general ways. First, strategies for decreasing the number of people receiving social assistance requires coordination within the municipal organisation itself. For example, intra-municipal coordination between the
education and social affairs departments may be useful when the aim is to reintegrate people using education (Broersma et al., 2011). Furthermore, external coordination can also prove to be useful. For instance, coordination with the Employment Insurance Agency to increase labour matches, or inter-municipal coordination and cooperation may be useful in tackling regional issues, as increasing labour demand with labour market policies might be more efficient on a regional level (Edzes, 2010).
• Productive efficiency. Larger local governments can have employees specifically
focused on increasing coordination with other departments and cooperation with external parties. However, larger municipalities require more internal coordination between and within all the departments. As a result, more communication and control is
necessary. As more organisational layers are introduced to coordinate these new needs, bureaucratic congestion can occur that further lead to inefficiencies (Blom-Hansen et al., 2016). The only research on the relationship between municipality size and internal coordination of social assistance policy in the Netherlands was done by Edzes et al. (2006). They find that larger municipalities are actually better at coordinating the social assistance tasks with other policies.
• Allocative efficiency. Municipalities are required to coordinate with external actors, such as educational facilities, EIA and care facilities. If there are more external partners to coordinate with, as could be the case in larger municipalities, inefficiencies may arise. Edzes et al. (2006) find, contrary to the argument made above, that larger municipalities are better at cooperating and coordinating with external partners than smaller municipalities.
Table 1 summarizes the problems municipalities experience in reducing social assistance dependency, the available instruments and the possible scale advantages and disadvantages as a consequence of amalgamation.
Table 1
Overview problems and instruments surrounding social assistance dependency, and possible scale (dis)advantages Unemployment
cause
Moral hazard Low productivity Misallocation Low labour demand Coordination / information problems
Instruments Work First, mandatory job-search, fraud control
Education, training, wage subsidies, subsidized jobs Mediation, increasing labour market transparency
Policy focused on job creation, wage
subsidies
Cooperation, coordination of policy with other
departments, joint implementation Scale
advantages
• Specialisation in fraud detection and compliance
• Lower marginal costs in Work First facilities
• Bargaining power with e.g. private Work First facilities
• Specialisation in reintegration strategies
• Bargaining power with e.g. education providers • Specialisation in matching supply of and demand for labour • Reduction of spillovers due to increased labour market scale • Specialisation in job creation policy • Increased yardstick competition due to objective distribution model. • Employees specifically focused on increasing coordination with other departments and external cooperation.
• Increased coordination with other municipal tasks (Edzes et al., 2006)
• Increased cooperation with external parties, such as EIA, care facilities, et cetera. (Edzes et al., 2006
Scale disadvantages • Coordination and communication costs • A mismatch between knowledge on and preferences and conditions of recipients or applicants • Coordination and communication costs • A mismatch between reintegration and activation strategy and preferences and conditions recipients • Coordination and communication costs • A mismatch between labour demand and supply • Coordination and communication costs • A mismatch between job creation and local conditions • Decreased yardstick competition • Coordination and communication costs • Increased coordination
with other municipal tasks • Increased cooperation
with external parties, such as EIA, care facilities, et cetera.
3.5 Hypotheses
From the findings of previous studies and the application of optimal scale theory on local labour market strategies, it remains unclear what the possible effects will be of consolidation on the social assistance recipiency, inflow and outflow rates. Therefore, the following
hypotheses are formulated:
1. During the years preceding amalgamation, municipalities experience an increase in the social assistance recipiency and inflow rates and a decrease in outflow rates due to a common pool effect.
2. a. After amalgamation, municipalities experience an increase in the social assistance recipiency and inflow rates and a decrease in outflow rates.
b After amalgamation, municipalities experience a decrease in the social assistance recipiency and inflow rates and an increase in outflow rates.
c. After amalgamation, municipalities experience no significant changes in their social assistance recipiency, inflow and outflow rates.
4. Data
Statistics Netherlands (2020a) publishes all municipal mergers on their website. Because the WSA was introduced in 2004 and was effectively expanded in 2015 with the introduction of the Participation Act, I focused on mergers between that period: those that occurred in 2005 until 2014. This provided a sample of a total of 526 municipalities, that either remained unaffected, were amalgamated or were newly formed. All municipalities are given an
individual code by Statistics Netherlands. However, newly formed municipalities that kept the name of one of the amalgamated municipalities were not given a new one. Therefore, I gave those specific local governments individual codes. Furthermore, six municipalities were excluded from the analysis, because these were amalgamated twice in the research period. After this selection, I had a sample of 520 municipalities in total. These consisted of 358 municipalities that did not change throughout the period, 119 municipalities that were merged into new municipalities and 43 new municipalities that were formed. Data of Statistics
Netherlands (2015) on every municipality’s annual total number of recipients and the inflow in and outflow from social assistance were integrated with data of Statistics Netherlands (2020b) on various control variables, into one dataset containing panel data. As pre- and post-treatment effects were calculated four years before up to four years after the merge, all data were collected from 2001 until 2017.
To analyse the effect of consolidation on the social assistance receipt, the annual data of municipalities before amalgamation were aggregated to the level of the municipality after the amalgamation. All the data of municipalities that would merge were hereby already aggregated into one ‘municipality’ before their merge. For example, municipalities A and B were amalgamated into municipality C in 2009. Municipality A had an inflow of 50 recipients in 2008, while municipality B had an inflow of 60 recipients in 2008. Municipality A and B were then aggregated into one municipality, summing their inflow data into a value of 110 in 2008. As a result, this value can be compared to the inflow value of municipality C in 2009. By collapsing the dataset in this way, municipalities that would merge and the formed municipality from that merger were effectively treated as a single municipality.
The distribution of amalgamations over the years is illustrated in Figure 3 and 4. Figure 3 shows the development of consolidations throughout the research period. It seems the number of amalgamations is relatively evenly distributed. After 2005 no more than ten municipalities were formed annually and no amalgamations occurred at all in 2008. Figure 4
shows the frequencies of amalgamations clustered by the number of involved municipality per merge.
Figure 3
Number of newly formed and amalgamated municipalities
Figure 4
Frequencies of the number of municipalities involved in a single amalgamation
To estimate an amalgamation effect, data on social assistance for every municipality were required. Statistics Netherlands provides several datasets on local social assistance. The primary data used in this research is the dataset that records the total number of recipients at the beginning of every year, together with the inflow, the outflow and the total number at the end of the year for every municipality from 1999-2014 (Statistics Netherlands, 2015). Separate datasets provided by Statistics Netherlands recorded the number of total recipients and the inflow and outflow in 2015, 2016 and 2017 (Statistics Netherlands, 2016; Statistics Netherlands, 2017; Statistics Netherlands, 2019). Unfortunately, in these datasets, the total
0 5 10 15 20 25 1 2 3 4 N u m b e r o f a m a lg a m a ti o n s
Number of involved municipaities per amalgamation
0 5 10 15 20 25 30 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 A m a lg a m a te d o r n e w ly fo rm e d m u n ic ip a li ti e s
number of recipients was measured somewhere during the year, with the exact dates unknown.
Control variables that were included, such as population size and household information, were also recorded by Statistics Netherlands (2020b) for the entire research period. Data on the following control variables from 2001 until 2017 were included:
• Population size: amalgamation is partly driven by the idea that small municipalities lack the administrative capacity for certain tasks, resulting in most municipalities with small population sizes that amalgamate. Therefore, population size is an important control as it influences the decision to amalgamate and is related to the administrative capacity necessary to minimize social assistance development.
• Population characteristics: all the following characteristics can have an effect on the social assistance development within the municipality. Consequently, these influence the demand on the government capacity that drives the decision to amalgamate or not. Therefore, these were all included as controls:
o Gender: according to the Ministry of Social Affairs and Employment [MSAE] (2019), relatively more women than men receive social assistance. The number of women as a share of the population was therefore included.
o Age: more than half of the social assistance recipients are older than 45 years (MSAE, 2019). Age categories as a share of the population were included to control for this.
o Migration background: relatively more persons with a migration background receive social assistance, especially those with a non-Western migration background (MSAE, 2019). The share of people with a migration and a non-Western migration background as part of the total population were included to control for this.
o Household type: relatively more social assistance recipients live in a single person household (Doove, Dill, Joosten & Rouw, 2018). To control for the household types, the two-person households with children, without children and single-person households as a share of the total number of households were included.
4.1 Descriptive sample statistics
Table 1 shows the descriptive statistics for all relevant variables for the different groups: the total sample, the unaffected municipalities, the amalgamated municipalities and the newly
formed municipalities. Some interesting information can be derived from this table. Looking at the population size, the number of municipal inhabits is far lower in municipalities chosen for amalgamation than unaffected municipalities. Before amalgamation, these municipalities are almost half the size of the unaffected municipalities, whereas after the merger their average population size exceeds the non-amalgamated ones. Two things can be derived from this. First, municipalities are (partly) chosen to merge based on their small population size, which is also confirmed in the literature (Schaap, 2015). Secondly, municipalities became more similar to those unaffected after consolidation. This process is also visible in the other observed variables. Before the merge, the total number of recipients and inflow were lower, while their outflow was higher. After consolidations, these rates increased and decreased, respectively, becoming more similar to the unaffected local governments. As mergers are (partly) based on the idea of administrative capacity, it was unexpected that social assistance rates were more favourable in the former amalgamated municipalities than the unaffected and newly formed municipalities. In chapter 6, estimates of these differences will show if these differences are significant or not.
The increasing similarity is also visible for household types, migration background and certain age groups. It seems that these variables and the assistance rates are associated. An increase in one-person households, population size and people with a migration
background, as predicted above, seems to be associated with less favourable social assistance rates.
Table 1 Descriptive statistics Total sample Non-amalgamated municipalities Former amalgamated municipalities Newly formed municipalities Number of municipalities 520 (0) 358 (10.571) 119 (9.589) 43 (6.287) Average annual amalgamated or newly formed municipalities 11.9 (2.693) 4.3 (1.096) Recipiency rates 0.013 (0.000) 0.014 (0.000) 0.010 (0.000) 0.013 (0.001) Inflow rates 0.005 (0.000) 0.005 (0.000) 0.004 (0.000) 0.005 (0.000) Outflow rates 0.349 (0.001) 0.346 (0.001) 0.375 (0.004) 0.335 (0.004) Average population size 37,982
(711) 39,206 (760) 22,864 (2073) 53,013 (3791) Average number of households 16,843 (368) 17,433 (396) 9,911 (1,041) 23,309 (1,932) Female (share) 0.502 (0.000) 0.503 (0.000) 0.500 (0.000) 0.502 (0.000) 15 ≤ Age < 25 0.114 (0.000) 0.115 (0.000) 0.111 (0.000) 0.112 (0.000) 25 ≤ Age < 45 0.258 (0.000) 0.257 (0.000) 0.274 (0.001) 0.235 (0.001) 45 ≤ Age < 65 0.284 (0.000) 0.284 (0.000) 0.278 (0.001) 0.298 (0.001) Age < 15 | ≥ 65 0.345 (0.000) 0.345 (0.000) 0.337 (0.000) 0.355 (0.001) Migration background as
part of total population
0.128 (0.001) 0.132 (0.001) 0.102 (0.001) 0.129 (0.003) Non-Western migration background as part of population 0.052 (0.001) 0.055 (0.001) 0.035 (0.001) 0.052 (0.003)
One person households 0.289 (0.001) 0.294 (0.001) 0.256 (0.002) 0.292 (0.002)
Note. Standard deviations of the means are shown in parentheses.
4.2 Dependent variables
Three dependent variables are measured as an indication of the social assistance receipt: the social assistance recipiency, inflow and outflow rates. For each variable, the method of calculation is explained, after which the development of its values over the years are illustrated.
4.2.1 Social assistance recipiency rates
The social assistance recipiency rates within a given municipality were measured as the total number of recipients at the start of a specific year, divided by the total population within that municipality measured at the start of that same year. For the years 2015, 2016 and 2017 it is unsure when the number of recipients was measured during the year. Figure 5 shows the development of the share of this variable from 2001 until 2017. The figure illustrates that throughout the period, the share of recipients shows an increasing trend, particularly in the years following the Great Recession. Furthermore, the unchanged municipalities seem to have higher shares of recipients on average in all years.
Households with children 0.325 (0.000) 0.324 (0.000) 0.333 (0.001) 0.332 (0.001) Two or more person
households without children 0.386 (0.001) 0.383 (0.001) 0.411 (0.002) 0.376 (0.002)
Figure 5
Total number of social assistance recipients as a share of the total population within a municipality from 2001 until 2017
However, the primary interest lies in the consequence of amalgamations on social assistance reliance. To illustrate this, the collapsed dataset has been used to calculate the mean recipient share of the population before and after amalgamation. Figure 6 and 7 are the result of this calculation, where the means are calculated between three years before and three years after amalgamation. Figure 6 illustrates the recipiency rates within a municipality clustered by amalgamation year. For instance, “amalg2009” is based on all the municipalities that merged in 2009, thus taking 2009 as reference year ‘0’. It shows no clear changes in the social assistance recipiency rate before and after amalgamation when clustered by amalgamation years: some amalgamation year groups show a decreasing trend after their merge, whereas others show an increase. To provide a clearer picture of potential amalgamation effects, the different cohorts are aggregated in Figure 7. This graph illustrates that one year before the merge, the municipalities seem to experience an increase that lasts until one year after the merge. However, an increase of around 0.08 percentage point could be considered quite small. Moreover, without a possible comparison with the control group, no conclusions can be
drawn yet. Therefore, no amalgamation effect can be deduced from the graph.
0 0,002 0,004 0,006 0,008 0,01 0,012 0,014 0,016 0,018 0,02 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 N u m b e r o f re c ip ie n ts a s s h a re o f th e p o p u la ti o n year +2000
Amalgamated municipalities, before amalgamation Amalgamated municipalities, after amalgamation Unchanged municipalities
Figure 6
Development of total social assistance recipiency (share) before and after amalgamation for different cohorts of municipalities
Figure 7
Mean share social assistance recipients of the population three years before and after amalgamation
4.2.2 Social assistance inflow rates
The yearly inflow into social assistance within a given municipality was measured as the inflow into social assistance in a specific year, divided by the total population within that municipality measured at the start of that same year. This variable indicates the municipality’s
0 0,005 0,01 0,015 0,02 0,025 -3 -2 -1 0 1 2 3 N u m b e r o f re c ip ie n ts a s s h a re o f th e p o p u la ti o n
Years before and after amalgamation
amalg2005 amalg2006 amalg2007 amalg2009 amalg2010
amalg2011 amalg2012 amalg2013 amalg2014
0,0104 0,0106 0,0108 0,011 0,0112 0,0114 0,0116 0,0118 0,012 0,0122 -3 -2 -1 0 1 2 3 N u m b e r o f re c ip ie n ts a s s h a re o f th e p o p u la ti o n
Years before and after amalgamation
