Rural non-profit leaders and their (in)formal role in local development

Authors: Oto Potluka1 and Petr Fanta2
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  • 1 University of Basel, , Switzerland
  • | 2 Czech Technical University, , Czech Republic
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Current interest in place-based leadership is playing a crucial role in local development. It concerns mainly politicians and public servants. The role of non-profit leaders is still an under-researched topic. Thus, we ask the following research questions: Are rural areas with local action groups (LAGs) more attractive to people than those without? Within rural areas with LAGs, are those with a higher proportion of non-profit partners more attractive to people?

On a sample of 6,262 Czech municipalities, we tested whether membership of municipalities in LAGs and non-profit leadership attributed to positive migration balance. We did it by the application of the propensity score matching method combined with the difference–indifference approach.

We found positive estimates for both LAGs’ membership and non-profit leadership on the attractiveness of municipalities. The participation of non-profit leaders makes an important difference. These results underline the importance of bottom-up approaches with voluntary engagement. Moreover, our findings demonstrate contradictory aspects of top-down imposed policies.

Abstract

Current interest in place-based leadership is playing a crucial role in local development. It concerns mainly politicians and public servants. The role of non-profit leaders is still an under-researched topic. Thus, we ask the following research questions: Are rural areas with local action groups (LAGs) more attractive to people than those without? Within rural areas with LAGs, are those with a higher proportion of non-profit partners more attractive to people?

On a sample of 6,262 Czech municipalities, we tested whether membership of municipalities in LAGs and non-profit leadership attributed to positive migration balance. We did it by the application of the propensity score matching method combined with the difference–indifference approach.

We found positive estimates for both LAGs’ membership and non-profit leadership on the attractiveness of municipalities. The participation of non-profit leaders makes an important difference. These results underline the importance of bottom-up approaches with voluntary engagement. Moreover, our findings demonstrate contradictory aspects of top-down imposed policies.

Introduction

The level of migration from rural areas to cities is striking. In Europe, the share of the urban population to the total population is projected to increase from 73% in 2014 to 82% in 2050 (UN, 2015). High levels of migration and population change impose excessive burdens on environmental and civic infrastructure in both urban and rural areas. These changes exacerbate social tensions (van den Berg et al, 2003) and make places less attractive both for living and for economic activity (Porter, 2008).

The current interest in solving these problems is related to the concept of ‘place-based leadership’. This concept refers to the improvement of living conditions through a rebalancing of local and central powers, which enables local leaders to bring forward their views on local development (improving conditions for life) and allows for effective work with local stakeholders (Hambleton, 2014). In regional and local development, the concept of place-based leadership has started playing a crucial role (Sotarauta and Beer, 2017; Sotarauta et al, 2017). However, despite this emphasis, the role of civil society leaders and non-profit organisations (NPOs) active in local development has remained an under-researched topic, with most research instead continuing to focus on the leadership of politicians and members of business and the public sector.

Such a situation appears even though the theoretical approach to the parallel existence of the provision of public goods by all sectors – for-profit, public and non-profit – has existed for decades. This theoretical approach is based on works by Weisbrod (1975) and Hansmann (1980) concerning market and government failures. Both types of failure underline the importance of NPOs in delivering public goods where under-provision of public goods and over-exclusion of consumers appear. In such cases, NPOs are able to deliver quality public goods in sufficient quantity to clients with specific preferences. As a result, the issue of NPOs and their presence (or lack thereof) also impacts people’s quality of life in both urban and rural areas.

Not only do cities have higher population densities and political and social activities, but they also have a higher number of registered NPOs (Franek, 2005; Potluka et al, 2017b). Moreover, urban NPOs are more professionalised (Guasti, 2016). If more people live in cities, and the non-profit sector is stronger in cities, does this mean there are fewer non-profit leaders in rural areas? What is happening there? These questions remain unanswered. The ambition of our research is to fill this gap in our knowledge of non-profit leaders in rural areas and their respective influence on rural development.

European Union (EU) policies underline the importance of non-profit leadership in rural development by constituting local partnerships – local action groups (LAGs) –represented by local leaders from all sectors, including NPOs. This approach applies a bottom-up principle for creating multi-sectoral partnerships of various types of organisation. They form LAGs composed of the public sector, business and NPOs. Thus, we ask the following research questions: Are rural municipalities with LAGs more attractive to people than those without? Within rural municipalities with LAGs, are those with a higher proportion of non-profit partners more attractive to people?

Institutional settings specific to a respective place are essential factors for local development (Rodríguez-Pose, 2013). LAGs give us an excellent opportunity to research the role of NPOs and non-profit leaders in local development as their role varies among municipalities. The participation of NPOs in rural development within LAGs supported by EU funding allows us to compare local development in those rural areas. We can compare rural areas where NPOs take part only formally, with those where NPOs and (informal) non-profit leadership play an important role. We apply our analysis to the case of the Czech Republic, where LAGs cover more than 94% of all municipalities. Thus, it provides us with a sufficient dataset to compare both groups of cases.

This article is organised as follows. After this introduction, the second section provides an overview of the current discussion on place-based leadership, with a connection to non-profit leadership. The third section specifies the data used in the analysis, the process of its collection and the methodologies applied. The fourth section presents descriptive statistics about LAGs. The results point to the importance of informal networks over formal participation in partnerships. The estimated effects provide us with the conclusion that the participation of voluntary-based NPOs brings innovative approaches and makes rural places more attractive to new inhabitants. The final section concludes the article.

Theoretical background

Place-based leadership

Local development has become a multidimensional approach covering economic, social, environmental, political and cultural dimensions (Pike et al, 2007). For local and regional development, the concept of ‘place-based leadership’ has recently gained attention among researchers because of its versatile application to various geographical levels and social relationships (Collinge and Gibney, 2010a; Beer et al, 2018). This is due to the interpersonal connections that exist between individuals engaged in activities in their municipality or place of residence (Collinge and Gibney, 2010b; Sotarauta and Mustikkamäki, 2012), including civil society. Thanks to local bonds, local leaders can induce significant changes that are able to improve local living conditions (Collinge and Gibney, 2010b; Sotarauta and Mustikkamäki, 2012). We use this approach to investigate how non-profit leadership, represented by people voluntarily engaging in local affairs, influences local development in rural areas. In the case of voluntarily engaged people in NPOs, we assume that these bonds will be stronger than in the case of other leaders and thus their contribution to local development is stronger.

According to current knowledge, successful place-based leadership requires four main factors to succeed in local development. First, the share of power between relevant parties and the participation of stakeholders in local development assist in gathering public support for actions taken in development projects (van den Berg et al, 2003; Stimson et al, 2009). Second, communication of a vision among stakeholders is an essential factor (van den Berg et al, 2003; Stough, 2010; Horlings and Padt, 2013). Both of the above-mentioned factors are crucial, as a vision alone is not a sufficient condition for success nor is the public support of local stakeholders relevant without a unifying vision (Beer, 2014). The third aspect concerns public policies together with funding. The fourth factor concerns the functioning of networks (Johnson and Osborne, 2003; Stough, 2010; Horlings and Padt, 2013) as well as information sharing within the network, including among non-profit stakeholders (Koliba et al, 2016). These strategic networks relate to all stakeholders – the non-profit sector, governmental authorities, private companies and individuals (van den Berg et al, 2003; Stough, 2010; Horlings and Padt, 2013). This article concentrates primarily on non-profit leadership due to the fact that, not only is this a voluntary engagement that is brought to local partnerships, but it is also a contribution that is able to bring with it social innovations as well.

Non-profit leadership

European regions are characterised by their strong local civil societies and democratic participation in many cultural, social and political processes (Cassiers and Kesteloot, 2012; Luria et al, 2015). When conflicts occur, however, the political decisions taken may disadvantage some groups of the public due to asymmetric information. Therefore, NPOs could exercise an important role by including the public in processes from which they would otherwise be excluded as well as by disseminating information to the public. In this role, NPOs could act as mediators between individuals and municipalities because they represent a broad spectrum of opinions and are able to communicate these to the public sector. In order to do this, NPOs need experienced leaders.

Civic engagement in NPOs or as individual activists plays an important role as it is often the first activity people can participate in to help improve the place they live. This is due to the fact that the economic solutions for regional development often seem unsuited to resolving the problems of local communities (Wirth et al, 2016). As social capital theory (Putnam, 1993) shows, regions with tight social contacts and trust among people have better chances for development. Strong social engagement along with civic-minded citizens are among the important factors that make a respective municipality more attractive to others (Lekwa et al, 2007; Fertner et al, 2015).

On the other hand, public participation does not automatically increase democratic legitimacy and social justice. These principles can only thrive where suitable political conditions hold, where leaders are motivated to uphold them, and where institutions are committed to promoting them (Fung, 2015). Strom (2008) discusses extending participation in the renewal of downtown areas by enlisting a wider section of the public – beyond the economic elites – to participate in the urban political economy. Although residents may participate in renewal projects, it is difficult for them to influence the final decisions because of customary rigidities – for example, see the case of Norway in Hanssen (2010). Local leadership nevertheless has the power to change the existing governance structure, even if its efforts are hampered by internal tensions caused by the different capacities among stakeholders (Eizaguirre et al, 2012; Cornforth et al, 2015).

Activating residents to participate in cultural and political life as well as in the community is an essential tool for encouraging local development (Paarlberg and Yoshioka, 2016); however, oftentimes many dwellers are non-permanent residents who do not have strong political positions (Eizaguirre et al, 2012). This means that political interests can wind up split between newcomers and established residents (Collin and Robertson, 2005). Political participation substantially helps new residents to become integrated into a society. From this perspective, we ask whether voluntary engagement in non-profit leadership helps to develop rural areas and make them more attractive for living. In our research, we define attractiveness as long-term population growth following the logic that a higher quality of life attracts people to either move to a municipality (Navarro-Azorín and Artal-Tur, 2015) or not to leave if they are satisfied with living there (Barreira et al, 2019).

Attractiveness of municipalities

An indicator of whether a municipality is perceived positively is easily observable through population size increase or decrease. Prosperous municipalities attract more inhabitants than other municipalities and, as a result, experience growth in population size, which is especially caused by an influx of new residents (Navarro-Azorín and Artal-Tur, 2015; Barreira et al, 2019). Recent data show that overall rural depopulation is not the case in the Czech Republic (Novotná et al, 2013), although the effect is not balanced across the whole country. Small municipalities in suburban areas of centres like Prague or Brno have witnessed a growing number of inhabitants, while more rural areas at the national and inter-regional periphery provide another picture (Novotná et al, 2013). What we see as important is that both urban and rural municipalities have witnessed parallel trends in changes in population caused by natural development. Large cities, for example, witnessed depopulation between the years 2010–14 mainly due to the depopulation of cities within economically deprived regions where the unemployment rates were highest. People threatened by unemployment, especially young people, left those regions because of the economic crises in 2009 and 2012–13, when their chances of getting a job were severely diminished.

Local action groups – an opportunity for non-profit leaders in rural areas

The European rural development programme LEADER1 has been providing support to rural areas for more than 25 years. One of its principles is local partnership working through LAGs. The local partnerships combine broad bottom-up participation of local citizens and decentralised top-down support with funding from regional and national programmes. They are the hub for networking among local actors and with external partners (Lukesch and Schuh, 2007). These principles fit into the concept of place-based leadership and non-profit leadership.

The LEADER approach began with the aim of improving the development potential of rural areas (Granberg et al, 2015). This development would be achieved by drawing on local initiative and skills, promoting the acquisition of knowledge on local integrated development, and disseminating this knowledge to other rural areas (European Communities, 2006). Information from evaluations and rural stakeholders indicate that the LEADER approach is a tool that works well in entirely different situations and area types, thus adapting rural policy making to the extreme diversity of a respective rural area’s needs (European Communities, 2006). This seems to be very close to the concept of place-based leadership.

Not only is LEADER an approach to rural development supported by European Structural and Investment Funds, but it is also a new view on participatory democracy, compared with traditional representative democracy (Peters and Pierre, 2004; Geissel, 2009). For example, Granberg et al (2015) point out the role of LAGs as being a real change from government to governance because members are recruited from the territory where LAGs reside. The shift from government to governance reflects the move of decision making to multi-stakeholder platforms and networks as well as decentralisation to levels and areas where knowledge and implementation resources are located (Sotarauta and Mustikkamäki, 2012; Thuesen and Derkzen, 2015). This enhances the relevance and sustainability of decisions made by involving local stakeholders (OECD, 2001). It also complies with the financial support for place-based leadership and local development (Johnson and Osborne, 2003; Stough, 2010; Horlings and Padt, 2013). While decisions about general types of interventions within LEADER are taken at a central level, the selection process and adjustments to local needs are made at the local level. Local people and communities do not necessarily have the particular expertise and skills that the central government provides (Andreassen et al, 2014), but they are equipped with a knowledge of local problems and a willingness to help develop the community.

The share of NPOs within LAGs presents a proxy for local voluntary initiative. Municipalities with low social capital (Putnam, 1993) and inactive inhabitants often do not have such NPOs in their LAGs. In such cases, they need to find other NPOs to fill the requirements, usually inviting NPOs set up by the public sector.

LAGs gradually won popularity among Czech rural municipalities. Initially, 16 LAGs were financially supported to realise their development plans from EU and Czech national budgets in the year 2004. This number had grown to 63 by the year 2008 (Dhv Cr and Ministerstvo Zemědělství ČR, 2009). Later, plans were made for supporting up to 80 LAGs requiring financing of their Strategic Plan Leader (SPL, the plans for local development). However, high interest combined with the readiness of LAGs to finance their SPLs led to a decision for support of an additional 32.

In the period 2014–20, LAGs realised local development by using community-led local development (CLLD) strategies prepared in cooperation with local actors (European Commission, 2014). In 2018, there were 180 LAGs active in the Czech Republic, receiving financial support for realising 178 CLLD strategies.2

There were 6,209 municipalities with fewer than 25,000 inhabitants in the Czech Republic in 2013. Of those municipalities eligible to be part of a LAG, only 322 (5.7%) of them were not (see the distribution of the population in Table 1). The process of forming a LAG area is open and the only reason for a municipality not to be covered by LAG activity is because of its own decision not to participate. The 322 municipalities voluntarily decided not to be part of any LAG. Reasons behind this decision may be a low interest in LAG activities from local inhabitants. As Kull (2016) shows, 53% of the public in Finland were not very interested or not interested at all in LAG membership. In Germany the number was even higher, reaching 61% of the public not interested in membership. Those attitudes may be reflected in the decisions of the elected representatives of municipalities.

Table 1:

Structure of municipalities in the Czech Republic and their coverage by LAGs

Population size (inhabitants)Under 500500 – 2,0002,001 – 5,0005,001 – 25,000More than 25,001Rural areasTotal
N3,4732,098411227446,2096,253
Covered by LAGs3,2532,02339221905,8875,887
Total population838,8111,984,7831,246,8952,340,6504,104,9866,411,13910,516,125
Population in LAGs789,5251,913,8571,190,6752,243,97406,138,0316,138,031
Share of municipalities in LAGs (%)93.7%96.4%95.4%96.5%0%94.8%94.2%
Share of rural population in LAGs (%)94.1%96.4%95.5%95.9%0%95.7%58.4%

Source: Own calculation based on data from the Czech Statistical Office (2018a; 2018b); population size as of the year 2013. The number of municipalities varies across years (6,262 municipalities is the highest number of Czech municipalities since 2004)

Despite the condition that more than 50% of members in LAG decision-making bodies must be from the private sector, it is evident that there is still a dominant position of the public sector within Czech LAGs. Many official representatives of LAGs are also active mayors of the participating municipalities. The dominant role of municipalities is underlined by the fact that they realised 58.4% of all projects financed within the LEADER programme in the Czech Republic during the 2007–13 programming period (Dhv Cr et al, 2010).

Based on the discussion above, we developed the following hypotheses:

Rural municipalities that are members of LAGs witness positive migration balance than municipalities outside of LAGs.

Recent research (Barreira et al, 2019) shows that residential attractiveness relates to place-based preconditions concerning a prospective inhabitant’s desire to move to a certain municipality. Moreover, such a move is connected with costs. Therefore, the expected increase in quality of life has to exceed these costs, otherwise people will not move (Navarro-Azorín and Artal-Tur, 2015) (for a similar research design see, for example, Lekwa et al, 2007; Fertner et al, 2015; Navarro-Azorín and Artal-Tur, 2015; Barreira et al, 2019). High social trust and social capital make places better for living and regions with tight social contacts and trust among people have better chances for development (Putnam, 1993). Strong social engagement provided, among others, by NPOs and civic-minded citizens helps to make a municipality more attractive for living (Lekwa et al, 2007; Fertner et al, 2015). Simultaneously, the size of social trust and social capital correlates with the number of active NPOs in place. Thus, it is assumed that a higher share of NPOs within LAGs represents higher social capital and better life conditions. We transform this logic into hypothesis Hypothesis 2:

A higher participation of NPOs within LAGs positively correlates with positive migration balance within these municipalities.

Data and methodology

Data collection

The data for analysis comprises three main parts. The first concerns data of the Czech Statistical Office. This dataset is composed of information on all municipalities between the years 2008 and 2018 (Czech Statistical Office, 2018a). It relates to:

  • demographic information on population size, the average age of the population, migration and the unemployment rate;

  • public infrastructure provided – kindergartens, schools, ambulances, hotels and pensions;

  • other information about municipalities – total area, arable land area and number and type of legal persons registered.

The second source (Czech Statistical Office, 2018b) provides data on LAGs, especially information on municipality membership within LAGs. The third source concerns a survey among LAGs, which provides us with additional data on the composition of partnerships within LAGs. For our research, information on the legal status of members was especially important. The time series for the different variables do not cover the same time period. A list of all variables with their definitions is available in Appendix 4.

The net migration present within a municipality was chosen as a measurement as it can reflect the long-term satisfaction of people as well as other related factors (see the explanation in the theoretical discussion above).

To get relevant information on LAG composition, we used a questionnaire survey among LAGs as well as their annual reports. The survey was realised in March and April 2018 using a web form. All 179 LAGs preparing CLLD strategies were asked by email to participate in the survey during April 2018. In the first round, we received 36 responses representing a response rate of around 20%. LAGs not filling in the questionnaire were asked again to participate in the survey. After the reminder, the number of respondents increased to 99 responses, representing the final response rate of more than 55%. Moreover, some LAG responses were checked randomly by us to verify the quality of the answers provided in accordance with the respective annual reports. Where possible, we also added data about partnership based on the annual reports of the LAGs. In the case of 11 LAGs, there was no information available on the composition of the LAG, neither in an annual report nor on the internet.

Methodology applied

The size of the sample enabled us to apply a quasi-experimental approach. To estimate the effects of a municipality’s participation in a LAG and the effect of NPO activity within LAGs on relative net migration, we applied a propensity score matching approach (for an explanation of this method, see for example Khandker et al, 2010; Gertler et al, 2011). This method compares treated and comparison groups in order to get an estimation of the impact on the treated group (average treatment effect on treated group – ATET). In our case, the treated group represented municipalities active in LAGs, while municipalities with no activity in any LAG comprised the comparison group. This approach was chosen since, in the case of panel data analysis, some data are missing for some periods, especially newer datasets (see Appendix 4). The variables missing are mainly: the number of legal persons registered, the total area of a municipality, the arable land size, the number of hotels and the number of pensions (all available only until the year 2016). Some variables are only available until the year 2015, such as the number of kindergarten classes, the number of school classes and the number of ambulance facilities.

We carried out our analysis in the following four steps. First, we used the following 13 observable variables to count the propensity score (the probability of obtaining support from EU funding for the LAG) for the year 2012 at the municipality level:

  • (1) unemployment rate (2011) to distinguish among municipalities with low employment and low economic strength due to lower taxes paid;

  • (2) arable land (in hectares) as we expect that larger municipalities have lower population densities as well as lower intensity of social contacts (we have also factored in the population size of the municipality);

  • (3) number of registered legal persons as this variable represents job opportunities and business initiatives in a municipality and thus also an expected higher active participation in a LAG;

  • civic infrastructure within a municipality: (4) number of classes in childcare centres; (5) number of classes in schools; (6) number of ambulant facilities to distinguish between municipalities from which people commute to work and municipalities providing support for their inhabitants;

  • (7) number of hotels and motels and (8) number of pensions, as proxy variables for supporting tourism;

  • (9) number of inhabitants (two-year average for 2011 and 2012);

  • (10) average age of inhabitants to demographically distinguish between municipalities with intense social contacts and those without;

  • (11–13) region in which a LAG is active to cover the geographical differences among municipalities (three regions covering the Czech Republic – Moravia, Central Bohemia and other parts of Bohemia – were created by merging 13 self-governing regions into three geographically homogeneous regions).

These variables enabled us to also involve economic activity and supply and demand (number of registered legal persons and unemployment rate) in terms of the labour market. We have used logistic regression to get the propensity score, a score which expresses the probability that a municipality will be a member of a LAG based on observable socioeconomic and demographic indicators.

Second, we paired municipalities into two groups (with and without membership of a LAG). We did so by an approach of nearest neighbour matching without replacement (cases already paired are not available to be paired again). This was applied using an IBM SPSS 24 package, with a calliper threshold (the maximum tolerated difference between matched subjects) of 0.2 of the standard deviation of the logit of the propensity score (for more details, see for example Khandker et al, 2010). Municipalities with similar propensity scores from both groups were paired based on propensity score.

We followed the recommendation of Abadie et al (2004) to use four matches per unit whenever there were more options for matching (more options for matching within the calliper tolerance). This procedure provided us with a sample of 322 municipalities that were not members of a LAG and 1,088 municipalities that were part of a LAG. To check the robustness of the estimates, we also estimated one-to-one matching (322 municipalities in each of the groups). The estimates for both approaches provided us with similar estimates. Thus, we primarily present the estimates on the larger sample.

Third, to check whether the two groups of municipalities were statistically different or not, we ran t-tests and chi-square tests for each variable, thus counting the propensity score (for more details concerning the tests, see Appendices 1–3). There were no significant differences for all of the variables included. Thus, we can treat both groups as statistically similar. If this were not the case, we would have to apply propensity score matching combined with a difference-in-difference approach.

Fourth, we applied a difference-in-difference approach (using ordinary least squares) to control for changes in key socioeconomic and demographic variables with a potential effect on net migration because of a longer timespan in our analysis. In our analysis, we estimated whether membership of a LAG (values 1/0) and a non-profit leadership (share of NPOs as partners in LAGs) had an effect on the sum of net migration between the years 2012 and 2018 (see Table 3 for variables used in the models) in the following form:
M1
M2
Table 2:

Descriptive statistics for municipalities

The whole sampleNMeanMedianStandard deviationMinimumMaximum
Share of the public sector as partner5,4540.360.370.140.101.00
Share of NPOs as partner5,4540.260.270.130.000.62
PSM sample
Membership in a LAG1,4100.771.000.420.001.00
Share of the public sector as partner1,0040.380.380.140.101.00
Share of NPOs as partner1,0040.270.290.130.000.62

Source: Own calculations based on data from the Czech Statistical Office (2018a; 2018b)

Table 3:

Models estimating the impact of membership in a LAG and share of NPOs in LAGs on relative net migration

M1 – Log of net migration 2012–18M2 – Log of net migration 2012–18
BSig.BSig.
Constant‒2.364.00‒1.231.00
Membership in a LAG.410.02
Share of NPOs1.046.00
Change in number of economically active subjects (2012–16)2.297.041.453.00
Change in arable land (2012–16)‒2.054.79.464.907
Change in number of classes in childcare providers (2012–15).317.28.395.04
Change in number of classes in schools (2012–15).306.36.122.61
Change in number of hotels (2012–15)‒.293.06‒.189.04
Change in age structure of the population (2012–18)‒6.438.09‒12.347.00
Log population size 20121.222.00.898.00
Karlovarsky region.411.08
Moravian-Silesian region.144.25
Ustecky region-.001.99.389.01
Adj. R-Square.746.533

Source: Czech Statistical Office (2018a; 2018b), own calculations. Model 1 involves a dummy variable of membership in a LAG (N = 322 (control group), N = 1,088 (treated group)), while model 2 tests the shares of NPOs only in LAGs (N = 1,004). The change in the number of ambulances was dropped from the model due to its low variability. The missing information about LAG composition for 84 municipalities (difference of 1,004 to 1,088) causes the lower sample size in model 2

In these models, the variable membership in a LAG and the share of NPOs are variables of our interest. A positive change in the number of economically active subjects can cause rising job opportunities in a municipality. Thus, it can have a positive effect on migration (people arriving because of job opportunities within a municipality). The size of a municipality depicts that larger municipalities have a lower population density as well as a lower intensity of social contacts. As we presume that people need contact with others, we also control for this variable. Infrastructure variables (number of classes in all types of schools, existence of outpatient facilities and so on) should have a positive effect on the attractiveness of a municipality. Demographic characteristics (age of a population, the size of a municipality) are variables which we expect to influence attractiveness for people to arrive as well as the structure of social services. The regional variables were selected according to the unemployment size within the regions. We have selected three regions with the highest unemployment rates in the Czech Republic. The logic is that higher unemployment relates to a tendency to leave a municipality.

Results

Descriptive statistics – composition of LAGs

From the data, it is evident that many LAGs have met the required proportion of the majority of partners outside of the public sector by including quasi-NPOs as partners. These are legally NPOs, but with a strong link to the public sector, or have been established by the municipalities (for example, micro-regions or associations of municipalities being officially one public body but gathering in fact several municipalities – it counts as one public sector partner, though all other municipalities take part). As Andreotti et al (2012) point out in such cases, there is a problematic issue of defining the mandate of such NPOs. There are some LAGs which are represented solely by organisations belonging to the public sector (including NPOs set up by this sector), while there are other LAGs where the public sector plays a minor role (for both extreme cases, see the distribution in Figure 1 on the right side and Table 2). As of 2017, the mean share of partners from the public sector was 38.5%. The variability among LAGs is large enough to test whether the share of non-public sector NPOs has an impact on rural development measured by the relative net migration in municipalities supported by LAGs.

Figure 1:
Figure 1:

Change of population according to share of NPOs and public sector in LAGs

Citation: Voluntary Sector Review 12, 1; 10.1332/204080520X15874664170938

Source: Czech Statistical Office (2018a; 2018b), own calculations, each dot represents a municipality

Visual inspection reveals that, even within LAGs, it is evident that municipalities are not homogeneous as the change in population differs among municipalities (see Figure 1 and the table in Appendix 5). Each box plot of data in Figure 1 represents a particular group of municipalities within LAGs. Moreover, there is not a clear visual relationship between the composition of the partnership within a LAG and the change of population for the share of public partners in LAGs. It is partially visible for the share of NPOs, but such visibility does not constitute a statistical test. Among public sector partners, we count not only municipalities and micro-regions but also all partners set up by the public sector, even if they have non-profit legal status. This approach was chosen to get the actual share of NPOs within the LAGs.

The variance among municipalities in the involvement of NPOs in designing (see Figure 1) and implementing local development strategies underlies the importance of place-based leadership and institutional framework tailored to local needs (Rodríguez-Pose, 2013). Despite the rule that less than half of all partners must be from the public sector, the differences show how LAGs tackle this requirement. In some cases, the LAGs meet the requirement only formally, but the actual participation of other partners besides the public sector is very low.

Results of the propensity score matching combined with the difference-in-difference approach

To estimate the impact of a municipality’s involvement in a LAG on relative net migration between 2012 and 2018, we applied propensity score matching in combination with the difference-in-difference approach (see the details in the methodological section). The selection of timing depicts both the pre-intervention period (combined population average for years 2011 and 2012) and the period when LAG support is entirely under way (2018). Using a two-year average as a baseline enables us to avoid sudden changes in population size. As described in the methodological part of the research, we worked with a sample of 1,410 municipalities. After matching municipalities, we estimated the impact on the variable of our interest – relative net migration.

The test of whether being in a LAG affected the net migration change in municipality population difference between 2012 and 2018 shows that municipalities in a LAG witness a statistically significant increase in population of 0.401% (p value = .02) (see Table 3). This supports hypothesis Hypothesis 1. This coefficient represents about 100 people coming to a municipality with 25,000 inhabitants. For municipalities in our sample, the mean population size is 1,041 (municipalities with LAGs) and 845 (municipalities without LAGs) inhabitants, respectively. The possible change related to the LAG would be very minimal (about four people of growth due to migration).

More interesting results from the perspective of non-profit leadership and changes in population concern the share of NPOs in relation to population change. Not only are the results statistically significant (p value = .00), but they also show a 1.046% population increase between the years 2012 and 2018 for every 1% increase in total NPO partnership share. These results support Hypothesis 2. This also shows a very small increase of about 10.9 people per each 1% increase in the share of NPO participation within a LAG in an average-sized municipality. The mean share of NPOs among all LAGs is 26.7%, which would make for a mean difference of 27.9 people per municipality. The coefficient for share of NPOs is 2.5 higher than the coefficient for a simple membership of a LAG. Although both of these changes are small, comparison between these two results shows how important are the volunteered activities in NPOs for local development and attractiveness of municipalities.

Both models reveal positive estimations of attraction for a municipality relating to two variables in both tested models – participation in a LAG and share of NPOs in a partnership (see Table 3). First, the change in the number of economic subjects and initial population size in a municipality shows that the growing number of economic subjects represents a proxy for growth potential of employers to attract more people to come due to job opportunities. The estimated difference due to the rising number of economic subjects is on average 2.3 people in the model with LAG membership and 1.5 in the model with NPO share, respectively. Second, the estimates for the initial size (Log population size 2012) of a municipality show that people tend to come to larger municipalities (approximately 1% for each 1% size of a municipality).

The estimates for the change in age structure of the population and the change in number of hotels show negative trends. This relates to the long-term trend of ageing and the depopulation of peripheral regions similar to all Central and Eastern European countries (Novotná et al, 2013; Flaga and Wesołowska, 2018).

The number of classes in childcare centres and schools has a positive, but non-significant relationship. The recent research of Sipple et al (2019) confirms a positive relationship between school proximity and economic status, thus supporting the assumption that attractive municipalities also provide a sufficient number of places for children either in childcare centres or in schools.

Discussion

Comparing these results, we can say that voluntarily involved non-profit leaders in LAGs have the potential for success in local development, even if this alone is not a factor in stopping the depopulation of rural areas. Our results confirm the three main conclusions found in previous studies. First, the sharing of political power among stakeholders helps to increase the relevance of public policies (van den Berg et al, 2003; Stimson et al, 2009), as the stakeholders help to define the political objectives according to the actual local needs. In this case, there is a possibility for non-profit organisations to help define the objectives of local strategies. Participation in such NPOs is also the first step for many individuals when deciding to engage in local social life and, later, in political decision making. In this case, there is a possibility for non-profit leaders to take part in decisions concerningthe investment policies of LAGs. Second, setting up communication platforms in the form of LAGs helps to share relevant visions and communicate their place-based relevance (van den Berg et al, 2003; Stough, 2010; Horlings and Padt, 2013; Beer, 2014). The participation of non-profit leaders also represents a situation where local policy makers hear other stakeholders’ voices. Third, the estimated impact especially grows when in combination with public policy support from the EU. This supports the necessity of financial resources to implement the visions developed via local consent among relevant stakeholders. Thus, our results confirm the importance of a combined effort between agents of public policies and networks represented by the LAGs and NPOs associated with them (Johnson and Osborne, 2003; van den Berg et al, 2003; Stough, 2010; Horlings and Padt, 2013).

Although the estimates are quite small, these results suggest that local initiatives play a more important role than public expenditure programmes imposed from national or supranational levels without a bottom-up initiative. At the same time, the results also confirm the importance of local social capital (Putnam, 1993). Policies aimed at increasing the attractiveness of life in rural areas may be less effective in their aims if they do not take into account local specifics (Niedomysl, 2007; Solana-Solana, 2010). Similarly, our analysis reveals significant and higher estimates of the participation of NPO leaders in solving local problems when compared with simple membership of a municipality in a LAG on the attractiveness of municipalities in the form of a positive net migration. This result shows discouraging consequences of participatory and co-productive practices if they are imposed from the top down, even if the policy achieves its intended effects. Voluntarily implemented bottom-up strategies have higher chances for success in place-based policies. As Pestoff (2014) points out, while the voluntary sector helps to overcome barriers and enables people to participate in co-creation, it needs to go hand in hand with the capabilities of these stakeholders (Sancino, 2016).

Our results also point out how significant the interaction among stakeholders, social capital and mutual learning is (Putnam, 1993; Horlings et al, 2018) in comparison with top-down imposed public policies. Grassroots organisations such as NPOs are capable of bringing a variety of innovative concepts. Such innovation is missing if the involvement of an NPO is taken only in order to get EU funding and not in actual practice. Higher trust among people leads to a higher participation rate among members of an NPO as well as higher overall participation of the NPO in public life (Putnam, 1993). This creates a mix of formal and informal relationships in partnership. Informal institutions stay beyond the official control of the system run by the central government, while local leadership is provided with higher autonomy (Bentley et al, 2017), especially when stakeholders trust each other. This brings power-sharing, collaboration and flexibility to LAGs and, thus, the ability to deal with specific local issues (Horlings et al, 2018) by highlighting local approaches and local initiative (Diamond, 2010).

As Diamond (2010) concludes, NPOs working in networks can provide innovations for local development. Our results show the importance of cooperation among the involved partners. As far as only a formal form of partnership is concerned (represented by politically dependent NPOs as partners in LAGs set up by the public sector), non-profit leaders from the usual local NPOs could have a feeling of frustration and disempowerment (O’Hare, 2010, Potluka et al, 2017a). In such a situation, the potential and ambitions of a partnership are not yet fulfilled, and only the implementation of top-down policies prevails in such circumstances.

We can explain the lower estimated effects of imposed participation in terms of two reasons. First, it is caused by the dominance of political parties in policy making and second, the low willingness of political elites to enable other stakeholders to take part in the political decision-making process in the Czech Republic (Potuček, 1999). In such cases, politicians tend to involve only those stakeholders who are under their control. The second issue concerns the generally low social capital that exists in post-communist countries in comparison with long-term democracies (Potluka et al, 2019), causing low general participation in public affairs and the need to find any available partners who are able to meet the formal requirements of EU programmes.

Conclusion

Our study tries to shed light on the impact of the formal and informal participation of local leaders, especially people leading NPOs, on policy making and local development strategies. We do that by testing whether voluntary engagement in non-profit leadership helps to develop rural areas and make them attractive enough to grow the population by positive net migration. For that reason, we tested the impact of the implementation of rural development policies at the local level on population size changes in rural municipalities between the years 2012 and 2018. Moreover, we tested the impact of the participation of non-profit leaders on shaping these strategies at the local level, and their effect on population size changes during the same years.

Our analysis has provided supporting evidence for the idea that the existence of a LAG has a direct relationship with the popularity of a specific municipality. The estimated impact resulting from the implementation of a LAG on net population change is significant. On the other hand, estimates for the participation of actual non-profit leaders show even better results. Our model estimates a higher increase of population relative to the share of NPO presence in partnerships than the estimates for the existence of LAGs. The presence of non-profit leaders taking part in local intersectoral partnerships has the potential for local development and supports the attractiveness of a municipality to new residents due to higher social capital and collaboration among stakeholders.

The results also confirm the importance of a place-based leadership approach to local development. Local leaders are aware of local needs and are better prepared to react to them. They need a communication platform which gives them the possibility to exchange ideas and enable communication among stakeholders. LAGs provide such a platform. Due to effective communication among relevant stakeholders, such a platform would increase the relevance of the policies as well as responsibility among stakeholders. The visions, plans and ideas need policy and financial support, all of which can be provided by a relevant LAG.

The results also shed light on the role of non-profit leadership in rural areas of the Czech Republic as a representative of an Eastern European country. Eastern European countries are both the major recipients of EU funding and the countries that have the lowest level of social trust within the EU.

Our research did not answer all questions relating to the role of NPOs in rural development. Thus, recommendations for further research concern a deeper analysis of the structure of NPOs in local development. Our analysis did not elaborate on which type of NPOs rural non-profit leaders are most active in, but we assume that they are involved in local issues. We can assume that NPOs active in development and environmental issues have a higher impact on living conditions and, consequently, the popularity of a municipality. Moreover, while our data provided information about the role of NPOs within formal structures, such information is missing for municipalities without LAGs. Furthermore, a study from a country with a higher level of social trust could shed light on the role of non-profit leaders when their involvement is spontaneous. Though the result estimates show the positive effects resulting from the presence of NPOs in local partnerships (LAGs), each NPO differs in its approach. Thus, there can be some NPOs which opportunistically orientate themselves towards EU funding. In such cases, any non-profit leadership would disappear whenever public financial support ended.

NPOs may also play an important role in fighting natural ageing, which often leads to the depopulation of rural areas. Our models suggest that ageing and the natural depopulation of a rural area play a crucial role in diminishing its attractiveness. Young people are often the ones who leave for cities for better opportunities. Thus, another direction of future research should concern the role of NPOs in mitigating these processes.

Annex 1: Distribution of the probability of being in a LAG in municipalities with and without LAG

F2
Source: Czech Statistical Office (2018a; 2018b), own calculations, N = 322 (control group), N = 1088 (treatment group)

Annex 2: T-tests of variables describing municipalities with and without a LAG

tSig. (2-tailed)Mean differenceStd. error difference95% confidence interval of the difference
LowerUpper
Unemployment rate (2011)‒0.3610.7218‒0.1340.371‒0.8620.594
Arable land in 2012 (hectares)1.1380.265526.08022.917‒18.87671.035
Number of legal persons registered (2012)‒0.1840.854‒3.03716.542‒35.48729.413
Number of classes in childcare centres (2012)‒0.1120.911‒0.0220.198‒0.4120.367
Number of classes in schools in 2012‒0.2610.794‒0.1650.633‒1.4071.076
Ambulance facilities in 2012‒0.3520.7325‒0.0020.006‒0.0130.009
Number of hotels (2012)0.1980.8430.0120.059‒0.1040.127
Number of pensions (2012)0.5150.61070.0950.186‒0.2690.460
Mean age (2012)0.4950.6200.0930.188‒0.2760.463
Mean population (in two-year 2011–12 average)‒0.2820.778‒38.350129.005‒289.414216.713
Log population size 20120.9320.3520.0290.031‒0.0320.089

Source: Czech Statistical Office (2018a; 2018b), own calculations; N = 322 (control group), N = 1,088 (treatment group)

Annex 3: Comparison of the number of municipalities from various regions with and without a LAG

RegionMembership in a LAGChi-square
NoYes
Central BohemiaNoN2077400.224
%21.9%78.1%
YesN115348
%24.8%75.2%
Other regions in BohemiaNoN1966310.3768
%23.7%76.3%
YesN126457
%21.6%78.4%
MoraviaNoN2418050.8328
%23.0%77.0%
YesN81283
%22.3%77.7%
TotalN3221,088
%22.8%77.2%

Source: Czech Statistical Office (2018a; 2018b), own calculations

Annex 4: List of variables

VariableDefinitionAvailabilityNotice
Municipality IDUnique code for each municipality (six digits)All yearsThis code enables us to merge data from various datasets.
Municipality nameName of a municipalityAll yearsEven we have a unique code. We also used names of municipalities to check their membership of a LAG.
Population sizeNumber of inhabitants registered in a municipality2004–18We used information concerning the size of the population as of 31 December.
Net migrationNet migration measured by number of people2011–18Calculated as the number of people arriving minus the number of people leaving from a municipality.
Relative net migrationRelative size of net migration to the size of a municipality2012–18Sum of net migration in years 2012–18 divided by the population size in 2012 in a municipality.
Average age of the populationAverage age of the population measured in years of age2011–18
Number of legal persons registeredNumber of all legal persons registered in a municipality2012–16Includes public sector, businesses including freelancers and non-profit organisations.
Total area of a municipalityMeasured in ha.2012–16
Region of a municipalityThis data allows us to distinguish membership of a municipality on all levels of regional classification.All yearsWe used a classification dividing the Czech Republic into three regions – Central Bohemia, other regions in Bohemia and Moravia.
Arable land sizeMeasured in hectares2012–16
Number of hotelsNumber of hotels with at least 5 rooms and at least 10 beds2012–16
Number of pensionsNumber of pensions with at least 5 rooms and at least 10 beds2012–16
Number of kindergarten classesNumber of classes for children aged 3 to 6 years old2012–15
Number of classes in schoolsNumber of classes for children aged 6–15 years old2012–15
Number of ambulance facilitiesNumber of ambulance facilities2012–15
Unemployment rateShare of unemployed people to economically active population in a municipality, measured as %2008–11Unemployed are classified as jobseekers who can immediately start work when offered a suitable job. Measured on 31 December.
Membership in a LAGMeasured as a dummy variableAll years
Number of partners in a LAGNumber of all official partners in a LAG2004, 2008, 2013, 2017
Status of a partnerThis variable describes whether a partner represents an NPO, public sector or business entityAll yearsLegal form was adjusted according to justice.cz where annual reports and names of the founders are listed.
Share of NPOs as partners in a LAGShare of NPOs among all partners in a LAG, measured as %All yearsNumber of NPOs (proved by the variable status of a partner) divided by the number of all partners in a LAG.
Share of public sector as partners in a LAGShare of public sector among all partners in a LAG, measured as %All yearsNumber of public sector partners (proved by the variable status of a partner) divided by the number of all partners in a LAG.

Source: Czech Statistical Office (2018a; 2018b), survey

Appendix 5: Change in net migration within years 2012–18

NMinimumMaximumMeanStd. deviation
All municipalities in the Czech Republic6,277‒7,67749,68421.0657.2
Municipalities in LAGs5,887‒1,2571,76718.5102.6
Municipalities with partnership information5,454‒1,2571,76717.6102.8
In this group:
  Share of the public sector up to 20%662‒7826098.174.7
  Share of the public sector 20%–40%2,658‒1,1681,76716.1102.3
  Share of the public sector 40%–60%1,891‒1,2571,41921.5114.6
  Share of the public sector 60%–80%97‒5443655.691.9
  Share of the public sector 80%–100%146‒30014310.446.2
In this group:
  Share of NPOs up to 20%1,835‒1,0824368.973.6
  Share of NPOs 20%–40%3,151‒1,1681,41917.8104.1
  Share of NPOs 40%–60%463‒1,2571,76749.6166.6
  Share of NPOs 60%–80%5‒13622243.0157.3
  Municipalities not in LAGs322‒9111,91528.5138.2

Note: Correlation between LAG membership and change in migration is ‒0.021 (p value 0.10), correlation between share of NPOs as partners and change in migration is +0.105 (p value 0.00).

Notes

1

LEADER means Liaisons Entre Action de Développement de l’Économie Rurale in French.

2

Only one CLLD strategy remained unapproved, and one LAG decided not to prepare such a strategy.

Conflict of interest

The authors declare that there are no conflicts of interest.

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Supplementary file 1:

List of variables with the basic descriptive statistics

VariableWhole samplePSM sample
NMin.Max.MeanStd. Dev.NMin.Max.MeanStd. Dev.
Population size 20126,2072267931030.352219.6851,410224388815.152032.729
Population size 20186,2080247971044.082193.2111,409024045840.442049.188
Sum of net migration 2012–186,277‒7677.0049684.0021.039657.1791,410‒1168.001915.0028.571127.157
Relative net migration 2012–186,252‒0.370.960.0400.0901,410‒0.330.780.05200.100
Average age of the population 20126,20730.660.640.9022.7051,41030.659.340.9092.9684
Average age of the population 20186,20431.765.242.0732.6891,40531.758.842.0062.8847
Number of legal persons registered 20126,20703562128.65284.5321,41003194104.80260.660
Number of legal persons registered 20166,20803354120.70256.8421,4090284999.59239.518
Total area in a municipality 20126,20642.28833158.2201213.6311431.7371,41042.28733158.220952.1611747.530
Total area in a municipality 20166,2080.00028080.1661211.0961342.2721,40942.28728080.166925.8981373.898
Arable land size 20126,2063.3776873.708656.814598.4711,4107.8433175.418461.170361.275
Arable land size 20166,2073.3776871.450653.822595.4091,4097.8253118.866457.114353.289
The number of hotels 20126,2070560.221.3421,4100190.170.925
The number of hotels 20166,2080560.251.4381,4090200.201.050
The number of pensions 20126,2070810.342.0131,4100810.352.925
The number of pensions 20166,2080750.482.2911,4090750.433.020
The number of classes in kindergartens 20126,2070391.523.3301,4100391.133.128
The number of classes in kindergartens 20156,2090421.593.3741,4100421.203.244
The number of classes in schools 20126,20701424.2111.0471,41001282.899.972
The number of classes in schools 20156,20901364.3911.4461,41001353.0910.502
The number of ambulance facilities 20126,207010.010.0971,410010.010.088
The number of ambulance facilities 20156,209020.010.0991,410010.010.084
Unemployment rate 20116,2070.0050.0010.92895.394531,4100.0050.0010.9575.851
Membership in a LAG (programming period 2013-2020)6,209010.950.2221,410010.770.420
Number of partners in a LAG (programming period 2013-2020)2,8961814350.6225.1935551814351.7825.027
Share of NPOs as partners in a LAG5,4540.0000.6190.257010.1251961,0040.0000.6190.2660.128
Share of public sector as partners in a LAG5,4540.0961.0000.364410.1441171,0040.0961.0000.3750.144

Source: Czech Statistical Office (2018a, 2018b), survey

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  • 1 University of Basel, , Switzerland
  • | 2 Czech Technical University, , Czech Republic

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