Government retrenchment and citizen participation in volunteering: A cross-national analysis of OECD countries

Abstract

In most industrialized countries, politicians and policy makers face unprecedented levels of fiscal pressure. Such pressure has compelled governments to conduct substantial cuts in government spending and services. While policy makers have attempted to build a strong civil society to compensate for the declining government role, previous studies have not examined the link between government retrenchment and citizen involvement in volunteering. This study examines such a relationship by conducting a cross-national study of OECD countries. After controlling for individual- and country-level factors, the findings show that government retrenchment is positively associated with citizen volunteering.

Keywords

Austerity spending cuts crowd-in crowd-out policy feedback volunteering

Introduction

Politicians and policy makers in most industrialized countries face unprecedented levels of fiscal pressure. Especially, the recent financial crisis hit public finances in many developed countries (Bailey et al., 2014; OECD, 2011; Raudla et al., 2015a). Deficits and debt ratios of governments have reached unsustainable levels, which forces governments to implement consolidation plans (OECD, 2011). Conventional austerity measures include revenue increases and expenditure cuts (OECD, 2011; Scorsone and Plerhoples, 2010). In particular, significant cuts in government spending and programs were pursued by most governments as a means to reduce their growing deficits and to achieve fiscal consolidation (OECD, 2011; Raudla et al., 2017). Conventional austerity measures include short-term measures (e.g., pay freezes for public employees, cuts in capital expenditure, and small cuts to all service cuts) as well as medium-term measures (e.g., contracting out of public services, restructuring management units, cuts in discretionary public services, and public sector pay limits) and long-term measures (e.g., restructuring of front-line services, public sector workers’ pension reform, municipal mergers) (Bailey, 2016).

Although it is not typically considered as an austerity or cutback measure (Bailey, 2016; OECD, 2011; Raudla et al., 2015b; Scorsone and Plerhoples, 2010), governments in some countries, particularly in the EU and other Organisation for Economic Co-operation and Development (OECD) countries, pursue strategic devolution of responsibility for public spending and services to state and local governments and local actors including voluntary organizations and local communities while working on expenditure cuts (Bailey, 2016; Cabinet Office of Japan, 2010; Fotaki, 2015; Fyfe, 2005; Lodge and Hood, 2012; Martinelli, 2017; Prime Minister of Japan and his Cabinet, 2010; Suzuki, 2017). While some recent research and governments report the emergence of or increase in citizen volunteering or empowerment of citizens for public goods and services in response to declining roles of the state (Ministry of Land Infrastructure Transport and Tourism, 2009; Sabatinelli and Semprebon, 2017; Sotiropoulos and Bourikos, 2014), there have also been critiques of such government devolution strategies (Daly, 2011). Due to voluntary organizations’ large reliance on the donation of money and time by individuals, the success of such devolution efforts hinges on the existence of strong local communities with active citizen participation (Bartels et al., 2013). The important question to ask is whether decreased public spending leads to increased volunteering. However, surprisingly, public management and policy researchers have paid scant attention to the relationship between government retrenchment and citizen participation in volunteering. This study aims to examine this understudied association. In particular, our first goal in this article is to test how reduction in government spending is associated with citizen volunteering.

We formulate and test two contrasting hypotheses based on the literature on crowding-out/crowding-in theories on the one hand and policy feedback on the other. Our first hypothesis is that government spending cuts are positively correlated to volunteering. Alternatively, the second hypothesis is that spending cuts are negatively associated with citizen volunteering. Furthermore, policy feedback theory has shown that public behavior can be affected by how well or little the government publicizes particular policy characteristics (Campbell, 2012; Mettler, 2002, 2007; Mettler and Soss, 2004; Soss and Schram, 2007). Governments often try to mask or downplay reductions in public expenditures or services in order to avoid angering the voting public (Pierson, 1994, 1996). For instance, they may extend cuts over many years rather than dramatically cut spending all at once in order to prevent citizens from noticing the reduction in services. Therefore, the second goal in this article is to test whether or not the amount of government spending change is associated with citizen participation in voluntary service provision. Our third hypothesis is that citizen volunteering is associated with only large-scale changes, not small changes, in government expenditures.

We test the above three hypotheses by using two waves of cross-national mass opinion survey datasets: (1) the integrated dataset of the third wave of the European Values Survey and the fourth wave of the World Values Survey (1999–2001) (European Values Study Group and World Values Survey Association, 2006); and (2) the fourth wave of the European Values Survey (2008–2009) (EVS, 2015). Individual participation in voluntary activities is operationalized by individual membership in voluntary organizations and individual engagement in unpaid voluntary work. Government retrenchment is measured by general government final consumption expenditure as percentage of GDP. After controlling for potential individual- and country-level confounding factors, the findings provide empirical support for the first hypothesis: there is a positive link between government retrenchment and individual participation in voluntary work. The empirical result also supports the third hypothesis, showing that a larger expansion in government spending is negatively correlated to individual volunteering.

This study contributes to the existing research in several ways. First, this study examines the understudied association between government retrenchment and citizen volunteering. The extant literature on crowding-in and crowding-out effects mainly focus on levels of government spending. This study looks at an empirical link between retrenchment and citizen volunteering rather than spending levels. Secondly, this study brings together two strands of the extant literature that have developed rather separately: crowding-out/in theories of citizen volunteering and policy feedback theory. In particular, this study focuses on the visibility of government spending cuts, which is one significant policy characteristic in the policy feedback literature (Campbell, 2012), and examines how visibility is associated with the retrenchment-voluntarism relationship. Third, by testing our propositions in OECD member countries which have experienced unprecedented levels of fiscal pressure, this research assesses the impacts of retrenchment on citizen behavior in an industrialized setting.

This study is organized into five sections. The first section provides an overview of government service retrenchment and cross-national variation in citizen participation in voluntary service provision. The second section reviews what has been studied about the relationship between government retrenchment and citizen participation and introduces attributes of citizen participation in voluntary service provision, and derives the testable hypotheses. The third section describes the research design and variable operationalization, followed by a fourth section containing results and analysis. The fifth section presents conclusions, limitations, and suggestions for future research.

Public expenditure cuts and devolution of service provision responsibility to voluntary organizations

Accumulated debt and the recent recession have placed unprecedented fiscal challenges to most advanced countries (Bailey et al., 2014; Kitson et al., 2011; OECD, 2011; Peck, 2014). This has led to significant austerity measures to confront growing budget deficits (Kitson et al., 2011; OECD, 2011; Raudla et al., 2017). These cuts include both short- and medium-term measures such as personnel cuts, reduction in service provision, and limits on capital investment. These measures can be generally made by engaging the supply side of public services (i.e., government) without asking for actions on the demand side of services (i.e., citizens). However, some cutback measures, especially long-term ones, seek for transformative change in behavior and attitudes on the side of citizens, service-users, and their communities (Bailey, 2016). Devolution of decision making and responsibility for service provision to citizens and local communities is one example of transformative austerity. In fact, governments in some advanced countries have embarked on such strategic devolution as part of their cutback strategies (Bailey, 2016; Cabinet Office of Japan, 2010; Fotaki, 2015; Fyfe, 2005; Lodge and Hood, 2012; Martinelli, 2017; Prime Minister of Japan and his Cabinet, 2010; Suzuki, 2017). In consequence, expectations for voluntary organizations and local communities have been growing among policy makers in many developed countries. Such expectations are high especially in rural and small town areas where the declining number of residents have made public services especially uneconomical (Farmer et al., 2012; Northern Periphery Programme, 2013; OECD, 2010).

To give a few examples, in the UK and Japan, governments have started to emphasize the voluntary sector as a service provider. In the UK, the labor government under Prime Minister Blair promoted devolution of service provision responsibility from government to voluntary organizations. His political philosophy, the so-called “Third Way,” aimed at reinvigorating civil society and shifting its role in service provision in national policy making (Fyfe, 2005). The coalition government between the Conservatives and Liberal Democrats after the 2010 election took a more explicit approach, called “Big Society,” which promoted the redistribution of power to local communities and away from the central government (Woodhouse, 2011). The underlying belief of “Big Society” is that heavy dependence on the state leads to a decline in personal responsibility of the individual, enhances bureaucracy, and results in the breakdown of community. Therefore, the shift from “Big Government to a Big Society” should be encouraged (Lowndes and Pratchett, 2012: 30). In Japan, the Japanese Ministry of Land, Infrastructure, Transport, and Tourism (hereafter, MLIT) developed a national spatial strategy (2008) when the Liberal Democratic Party of Japan (LDP) was in power. The strategy promoted a national land plan, with the voluntary sector as the main actor for land development. A similar idea can be found in Democratic Party of Japan’s (DPJ) policy. The DPJ’s first Prime Minister Hatoyama uses the phrase, “New Public Commons,” which describes the power of people who are working actively to “resolve everyday issues like those relating to education, child-rearing, community-building, nursing care and social welfare” (Prime Minister of Japan and his Cabinet, 2010). Following his remarks, the Japanese government launched new policies to develop voluntary or nonprofit organizations such as the expansion of tax incentives, opening up the public service market to these organizations, and financial supports. The LDP-Komei coalition government endorsed a new national spatial strategy in August 2015. The roles of nonprofit and community actors in local community development under fiscal constraints are especially emphasized in the strategy (MLIT, 2015; Suzuki, 2017).

Two contrasting views of government expenditure cuts and volunteering

Success of devolution efforts largely depends on active citizen participation in local service provisions. However, much of the existing literature focuses on how cross-national differences in government spending levels are associated with cross-national variations in citizens’ attitudes and behaviors. Previous studies suggest two competing ideas: crowding-out and crowding-in views. The crowding-out view envisages an inverse relationship between government and civil society. Larger government size leads to a smaller civil society, and governmental efforts to provide public service crowd out civil society’s efforts for the same. This view is based on the premise that a zero-sum game exists between state and nonstate actors since there is a certain number of tasks that need to be done by one or the other (Gundelach et al., 2010). Voluntary action, such as providing collective goods and services, “emerges to satisfy the unsatisfied demand for collective goods” (Salamon and Sokolowski, 2003: 78; Stadelmann-Steffen, 2011). On this theory, extensive provision of governmental goods takes away the chance for citizens’ efforts to address needs to arise. Moreover, if governments take responsibility for providing collective goods and services that are better left to local civil society, such substitution of citizens’ roles damages “the long term ability of citizens to deal with similar issues themselves” (Finsveen and van Oorschot, 2007: 6; Fukuyama, 2001), as the ability to cooperate and self-organize is acquired through habit and practice.

Alternatively, the competing crowding-in view envisions a positive relationship between government and civil society. Unlike the zero-sum game assumption, the crowding-in view assumes a complementary relationship between government and civil society (Dahlberg, 2005; Stadelmann-Steffen, 2011). This idea generally envisages resource effects of government on civil society. Governmental provision of goods and services supplies individuals with the necessary resources for developing civil society. Resources provided through public policies such as payments, goods, or services can enhance individuals’ welfare, socioeconomic conditions, skills, and life opportunities (i.e., resource effects). Consequently, these resources enhance individuals’ capacity for participation (Mettler, 2002; Mettler and Welch, 2004; Stadelmann-Steffen, 2011).

Previous cross-national studies find inconsistent results for relationships between government and civil society. For instance, Hackl et al. (2012), Stadelmann-Steffen (2011), and Simmons and Emanuele (2004) all conclude that larger public expenditure size negatively affects individuals’ decisions on volunteering, supporting the crowding-out hypothesis. On the other hand, Day and Devlin (1996) find that increasing government expenditures is negatively or positively associated with the decision to volunteer, depending on the type of spending. Bartels et al. (2013) explain that larger government expenditure is correlated to increased volunteering based on their study of the United Kingdom and other European countries. Gundelach et al. (2010) find no significant effect of social expenditure on an individual’s decision to do volunteer work. Such inconsistency suggests that there is little agreement on the validity of the two competing theories.

With regard to this article, this study is especially interested in examining whether there are inverse effects of crowding-out and crowding-in when governments embark on expenditure cuts. The crowding-out view argues that citizens’ voluntary efforts are discouraged (crowded-out) by government expenditures. When government activity is reduced by spending cuts, on the other hand, voluntary activities increase. Moreover, the policy feedback literature suggests that retrenchment creates interpretive effects, namely changing citizens’ views of their “role, status and identity within the polity” (Mettler and Welch, 2004: 501), encouraging citizen service. Furthermore, reduction in government spending will reduce citizen dependence on government and boost a cooperative sensibility and the skills needed for citizens to provide services on their own. On this view, then, smaller government will ultimately encourage citizen participation.

In contrast, the crowding-in view suggests that governmental service provision and associated benefits enhance individuals’ welfare, socioeconomic conditions, skills, and life opportunities (Mettler and Soss, 2004; Mettler and Welch, 2004). Conversely, cutbacks in such benefits may cause reverse resource effects, reducing the available resources for beneficiaries, and thus harming citizen participation. Moreover, another avenue of research suggests that government retrenchment seems to cause grievances and discontent among ordinary citizens, resulting in increasing political participation (Campbell, 2002, 2003; Muñoz et al., 2014). The central factor that promotes political participation is the threat of policy change affecting self-interest. However, such short-term participation based on self-centered motivation is unlikely to motivate long-term participation for local public services (Marschall, 2004). These results are consistent with the recent empirical findings from cross-national studies by Ponticelli and Voth (2011) and Kriesi (2013), which find a strong link between fiscal retrenchment and social instability in Europe. Accordingly, we propose the following two contrasting hypotheses:

H1: All things being equal, government expenditure cuts are positively correlated to citizen participation in voluntary service provision.

H2: All things being equal, government expenditure cuts are negatively correlated to citizen participation in voluntary service provision.

However, the amount of change may matter for the government retrenchment–citizen participation relationship. Policy feedback theories show that various policy characteristics, including visibility and proximity, shape behavior of mass publics (Campbell, 2012; Soss and Schram, 2007). The present research especially looks at policy visibility. When conducting cuts in public expenditures and services, governments may not do so in apparent ways in order to avoid voter punishment in next election (Pierson, 1994, 1996). Stretching retrenchments over several years rather than drastic cuts within a short period may help to make retrenchments less visible to the public. Citizens may not be aware of small and incremental changes in government spending. However, they may react to retrenchment or expansion only above a certain evident level. Accordingly,

H3: Only large-scale changes in government expenditures are correlated to citizen participation in voluntary service provision.

Data collection and variable operationalization

The primary purpose of this study is to test whether or not government retrenchment has an empirical link with individuals’ propensity for engagement in voluntary activities. The unit of analysis is the individual. Individual data is obtained from two waves of cross-national mass opinion survey datasets: (1) the integrated dataset of the third wave of the European Values Survey and the fourth wave of the World Values Survey (1999–2001) (European Values Study Group and World Values Survey Association, 2006); and (2) the fourth wave of the European Values Survey (2008–2009) (EVS, 2015). The former dataset allows for analysis of 29 OECD member countries and the latter dataset includes 25 OECD countries. Country level data is from OECD statistics (OECD, 2015).

This study uses the following two types of dependent variables in order to capture individual involvement in volunteering: (1) membership in voluntary organizations; and (2) engagement in unpaid voluntary work. These are the dummy variables at the individual level. While the former variable is concerned with whether or not individuals belong to voluntary organizations, the latter variable looks at actual engagement in unpaid voluntary activities. The main independent variable is retrenchment of government spending, which comes from country-level data. Furthermore, the data structure has a hierarchical nature, in which individuals are nested in country-level institutional and socioeconomic contextual factors. Thus, multilevel analysis is the most appropriate method (Jones, 2008). Numerous previous studies testing the policy feedback effects in a cross-national or subnational setting successfully employ multi-level models (Gelissen et al., 2012; Giger, 2011; Giger and Nelson, 2012; Gundelach et al., 2010; MacLean, 2010; Stadelmann-Steffen, 2011). Since the dependent variable is binary, a multilevel probit regression model with robust standard errors is employed. We assume that intercepts of individual level variables can vary across countries due to the country-level factors; therefore, a random intercept model is applied.

Dependent variables

This research utilizes two types of dependent variable for the individual involvement in voluntary activities: (1) membership in voluntary organizations and activities and (2) engagement in unpaid voluntary work. Previous studies often distinguish membership (Howard and Gilbert, 2008; Schofer and Fourcade-Gourinchas, 2001) from actual volunteering activity (Bartels et al., 2013; Gundelach et al., 2010; Howard and Gilbert, 2008; Stadelmann-Steffen, 2011; Wemlinger and Berlan, 2016) as indicators for citizen volunteerism. While actual voluntary work is considered as active participation because it requires a high level of involvement and commitment, membership in voluntary organization is regarded as passive participation because it may simply ask for a monetary or symbolic contribution (Howard and Gilbert, 2008; Wemlinger and Berlan, 2016). Therefore, these two measures differ in terms of levels of involvement in volunteering, voluntary work requiring a higher level of involvement than membership. The purpose of using these two different measurements is to determine whether spending cuts are related only to increased/decreased membership in voluntary organization or to actual voluntary work, or to both measures, allowing researchers to analyze the impacts of cuts on volunteering in detail.

Besides the levels of involvement, we also distinguish areas of volunteering. The World Values Survey and the European Values Survey ask whether or not respondents are involved in different types of voluntary organizations and activities, and whether or not they are currently doing unpaid volunteer work.¹ In order to test the effects of retrenchment on various areas of civic activities, the following three variables were created: membership in (or volunteering for) (1) any organization; (2) a service provision organization; and (3) a social service provision organization. The first variable indicates whether or not an individual holds membership in or did unpaid volunteer work for any of the above 15 organizations (0: no, 1: yes). This is the most comprehensive variable, capturing volunteering in the widest range of volunteer areas. The second variable focuses more specifically on volunteering in areas of service provision organizations.² The third variable, social service provision organization, is the most restrictive variable, limited only to social service organizations. It only considers social welfare service for elderly, handicapped or deprived people; local political action groups on issues like poverty, employment housing, and racial equality; and organizations concerned with health, following Stadelmann-Steffen (2011). We use three different variables depending on volunteering areas covered. We cannot assume that general public spending is equally associated with voluntary work in all areas of volunteering (Stadelmann-Steffen, 2011).³ Cuts may affect volunteering only in certain areas. The purpose of using different volunteering area variables is to examine if general government spending cuts are associated with volunteering only in some specific areas of volunteering or with volunteering broadly construed.

Independent Variables

Levels of government service provisions are measured by general government final consumption expenditure as percentage of GDP.⁴ Previous cross-national studies mostly rely on aggregated-level spending data as an indicator for levels of government size and activities; therefore, it is justifiable to use the aggregated-level data. Two types of independent variables are created to indicate retrenchment and expansion of government services. The variable, government retrenchment, is the averaged yearly percent change of government spending over 10 years. Then, the percentage change is multiplied by −1. Thus, positive numbers indicate reductions in government spending and negative numbers indicate expansion.⁵ In order to reduce fluctuations in spending size, a 3-year moving average of spending data is used in calculating annual percentage changes. Finally, the second independent variable, large change in government spending, is a categorical variable which classifies spending changes into (1) small change, (2) large-scale retrenchment, and (3) large-scale expansion. This variable is created to test the third hypothesis that only large-scale spending changes affect citizen participation in service provision. Countries whose government retrenchment variable falls into the range between 25th and 75th percentile of the entire population are given a value of zero (0: small change). Countries whose government retrenchment variable falls above the 75th percentile of the population receive a value of 1 for large-scale retrenchment. Countries with lower than the 25th percentile of the entire government retrenchment variable are given a value of 2 for large-scale expansion.⁶

Control variables

Since the data has a hierarchical structure, both individual and country level factors should be controlled in the analysis. Based on previous studies, the following individual-level variables are included in the analysis: age, age-squared, gender, full-time employment, income, education, and marital status (Bartels et al., 2013; Finsveen and van Oorschot, 2007; Hackl et al., 2012; Stadelmann-Steffen, 2011; Van Oorschot and Arts, 2005). Number of children is not included because it is highly correlated to marital status. The following two country-level controls are included: current spending size and GDP per capita. Although it is ideal to include more country-level controls, the small sample size at the country level makes one cautious about adding more variables in a multilevel analysis. Moreover, several country-level variables tend to be correlated to GDP per capita, which leads to multicollinearity. Current spending size is widely used in previous cross-national studies examining the relationship between spending size and levels of volunteerism and social capital (Bartels et al., 2013; Hackl et al., 2012; Stadelmann-Steffen, 2011). It captures a 3-year moving average of spending size for each country before the survey year. Current spending size is measured by general government consumption expenditure as a percentage of GDP. Summary statistics of all variables in the EVS3/WVS4 analysis are shown in online Table A1, and those in the EVS analysis are in online Table A2. Online Tables A3 and A4 report the correlation matrix of all variables for both analyses. As seen from the tables, there is no high correlation among independent and control variables.

Analysis and results

We conducted separate analyses for two different samples: EVS3/WVS4 and EVS4. We used multilevel probit regression models given that the dependent variables are binary. We performed two robustness checks to further demonstrate the validity of the findings. First, we ran multilevel logistic regression models with robust standard errors to see if we would obtain similar results. Second, we pooled the two datasets and performed multilevel analysis with survey wave and year dummies to test whether a specific effect of survey wave and year would affect the validity of results. We estimated two models. Model 1 uses the government retrenchment variable as an independent variable in order to assess the impacts of spending cuts on voluntary activities. Model 2 uses the large change in government spending variable. This model was tested to analyze how large changes in spending are associated with citizens’ volunteering. Online Table A5 reports contextual variance of the EVS3/WVS4 analysis and online Table A6 shows the variance of EVS4 analysis. Calculations of the intraclass correlation coefficient (ICC) range from 0.11 to 0.34 for the EVS3/WVS4 analysis and range from 0.31 to 0.57 for the EVS4 analysis, providing further empirical justification for the use of multilevel model.

Tables 1 and 2 report the results of model 1 for the EVS3/WVS4 analysis and the EVS4 analysis, respectively. Regarding individual-level covariates, overall, both results support the findings of previous studies (Bartels et al., 2013; Finsveen and van Oorschot, 2007; Hackl et al., 2012; Stadelmann-Steffen, 2011; Van Oorschot and Arts, 2005). Age is positive and its quadratic term is negative in all results except one model that has membership in service provision organizations as a dependent variable (EVS3/WVS4 and EVS4) and one with participation in volunteering for service provision organizations (EVS4). The results suggest that age carries a positive correlation with the probability of being a member of a voluntary group and doing unpaid voluntary activities, up to a certain age. Interestingly, being female is negatively associated with involvement in any voluntary organization or service provision organization (membership and volunteering). However, it is positively linked with holding membership in and volunteering for the organizations that provide social services. Being employed full time generally has negative link with membership and volunteering, which is consistent with previous studies. Income levels are generally associated with the likelihood of having membership and volunteering except for social service organizations. Higher levels of income are correlated with one’s propensity for voluntary activities. Education levels are strongly correlated to the higher likelihood of individual membership in and volunteering for voluntary organizations. Across all dependent variables, having higher education positively increases one’s chance for being involved in voluntary activities. Marital status only partially affects voluntary activity participation. There is no statistically significant correlation between marital status and the dependent variables except volunteering for voluntary organizations (p-value <0.1) in the EVS3/WVS4 analysis and volunteering for voluntary organizations and service provision organizations (p < 0.05) in the EVS4 analysis.

Table 1.

EVS3/WVS4: Multilevel probit models estimating the association between government retrenchment and membership and volunteering in voluntary organizations

	Membership			Volunteering
Variables	Voluntary organization	Service provision organization	Social service organization	Voluntary organization	Service provision organization	Social service organization
Country-level variables
Government	0.07	0.09	0.07	0.11**	0.12**	0.10**
retrenchment	(0.07)	(0.08)	(0.06)	(0.06)	(0.06)	(0.05)
Current spending	−0.56**	−0.60**	−0.32**	−0.45**	−0.46**	−0.15
size (ref = first quarter) Second quarter	(0.28)	(0.28)	(0.16)	(0.21)	(0.21)	(0.15)
Third quarter	−0.16	−0.25	−0.28*	−0.42**	−0.43**	−0.42***
	(0.27)	(0.27)	(0.16)	(0.20)	(0.21)	(0.16)
Fourth quarter	0.28	0.14	−0.13	−0.25	−0.25	−0.21
	(0.32)	(0.30)	(0.16)	(0.20)	(0.20)	(0.14)
GDP per capita (ln)	0.91***	0.91***	0.49***	0.34*	0.38**	0.28**
	(0.23)	(0.23)	(0.14)	(0.18)	(0.18)	(0.13)
Individual-level variables
Age (centered)	0.00***	0.00	0.01***	0.00***	0.00***	0.01***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
Age squared	−0.00***	0.00	−0.00***	−0.00***	−0.00***	−0.00***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
Gender	−0.13***	−0.07***	0.13***	−0.11***	−0.08***	0.13***
	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.02)
Full-time	0.04*	−0.09***	−0.09***	−0.06***	−0.10***	−0.12***
employment	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
Income
Medium	0.17***	0.13***	0.00	0.12***	0.11***	0.01
(ref. = low)	(0.03)	(0.03)	(0.03)	(0.02)	(0.02)	(0.03)
High	0.29***	0.23***	0.05**	0.22***	0.19***	0.06*
	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)
Education
Medium	0.24***	0.23***	0.17***	0.22***	0.22***	0.14***
(ref. = low)	(0.03)	(0.03)	(0.04)	(0.03)	(0.03)	(0.03)
High	0.55***	0.52***	0.34***	0.46***	0.44***	0.32***
	(0.05)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)
Marital status	0.01	0.00	−0.01	0.05*	0.04	−0.03
	(0.02)	(0.02)	(0.03)	(0.03)	(0.03)	(0.03)
Constant	−8.85***	−8.94***	−5.89***	−3.68**	−4.12**	−3.95***
	(2.24)	(2.23)	(1.42)	(1.78)	(1.81)	(1.31)
Country-level	0.23***	0.21***	0.08***	0.11***	0.11***	0.08***
variance	(0.05)	(0.04)	(0.03)	(0.02)	(0.02)	(0.02)
Observations	31,861	31,861	31,861	31,861	31,861	31,861
Number of countries	29	29	29	29	29	29

Note: Robust standard errors in parentheses.

***

p < 0.01, **p < 0.05, *p < 0.1.

Table 2.

EVS4: Multilevel probit models estimating the association between government retrenchment and membership and volunteering in voluntary organizations

	Membership			Volunteering
	Voluntary organization	Service provision organization	Social service organization	Voluntary organization	Service provision organization	Social service organization
Country-level variables
Government	0.07	0.09*	0.03	0.07***	0.09***	0.02
retrenchment	(0.06)	(0.05)	(0.04)	(0.02)	(0.02)	(0.02)
Current spending	−0.04	−0.10	−0.10	−0.22*	−0.18	−0.20
size (ref = first quarter) Second quarter	(0.18)	(0.16)	(0.11)	(0.13)	(0.13)	(0.12)
Third quarter	0.04	0.06	0.04	0.07	0.13	0.06
	(0.18)	(0.15)	(0.08)	(0.19)	(0.19)	(0.13)
Fourth quarter	0.60**	0.57**	0.25*	−0.03	0.03	0.04
	(0.27)	(0.25)	(0.13)	(0.13)	(0.14)	(0.11)
GDP per capita (ln)	1.17***	1.14***	0.73***	0.74***	0.79***	0.60***
	(0.19)	(0.17)	(0.09)	(0.10)	(0.10)	(0.10)
Individual-level variables
Age (centered)	0.00***	0.00	0.01***	0.00**	0.00	0.01***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
Age squared	−0.00**	0.00	−0.00***	−0.00***	−0.00***	−0.00***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
Gender	−0.13***	−0.07***	0.16***	−0.11***	−0.07***	0.14***
	(0.03)	(0.02)	(0.03)	(0.02)	(0.02)	(0.03)
Full-time	0.04	−0.07**	−0.06**	−0.04*	−0.07***	−0.12***
employment	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.04)
Income
Medium	0.13***	0.10***	0.04	0.07***	0.06*	0.04
(ref. = low)	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)
High	0.24***	0.23***	0.01	0.15***	0.15***	0.02
	(0.04)	(0.04)	(0.03)	(0.04)	(0.04)	(0.04)
Education
Medium	0.26***	0.27***	0.18***	0.23***	0.22***	0.18***
(ref. = low)	(0.04)	(0.03)	(0.04)	(0.03)	(0.03)	(0.03)
High	0.55***	0.55***	0.36***	0.45***	0.43***	0.32***
	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)
Marital status	0.02	0.03	0.02	0.07**	0.08**	0.04
	(0.02)	(0.02)	(0.03)	(0.03)	(0.03)	(0.04)
Constant	−12.51***	−12.42***	−9.09***	−8.37***	−9.08***	−7.88***
	(1.96)	(1.73)	(0.99)	(0.97)	(0.98)	(0.98)
Country-level	0.16***	0.13***	0.04***	0.07***	0.07***	0.05***
variance	(0.04)	(0.03)	(0.01)	(0.03)	(0.02)	(0.01)
Observations	27,815	27,815	27,815	26,817	26,817	26,817
Number of countries	25	25	25	25	25	25

Note: Robust standard errors in parentheses.

***

p < 0.01, **p < 0.05, *p < 0.1.

Regarding country-level variables, GDP per capita (logged) is correlated to membership in and volunteering for voluntary organizations across all dependent variables (p < 0.01 or 0.05) except one model with volunteering for any voluntary organizations as a dependent variable (p < 0.1) in the EVS3/WVS4 analysis. All other things being equal, higher GDP leads to the higher likelihood of individual membership in and volunteering for voluntary organizations. Interestingly, current spending size is generally associated with lower likelihood of having membership in and volunteering for voluntary organizations in the EVS3/WVS4 analysis, which is in line with the crowding-out theory. Note that the baseline category for the current spending size is the first quarter of the population in the spending size. The spending size is operationalized by general government consumption expenditure as a percentage of GDP. Compared to citizens living in the lowest-spending country group, citizens in the countries in the higher spending group (second quarter and third quarter) are less likely to be engaged in volunteering at any voluntary organization and service provision organizations in the EVS3/WVS4 analysis. However, the same results do not hold in the EVS4 analysis.

The main interest of this research is to find how government retrenchment affects levels of voluntary activity. Recall that the variable, government retrenchment, is the averaged yearly percent change of government spending over 10 years. The percentage change is then multiplied by −1. In the analysis of the EVS3/WVS4, government retrenchment is positively associated with individual volunteering in all three types of dependent variables (any type of voluntary organizations, service provision organizations, and social service provision organizations) (p < 0.05) (Table 1). This means that reduction in government spending has a positive link with citizen engagement in volunteering, which provides an empirical support for H1. However, models with membership in voluntary organizations do not produce statistically significant results. Thus, the results suggest that government retrenchment has an association only with active volunteering for voluntary organizations, not simply holding membership. The analysis of EVS4 finds similar results (Table 2). Government retrenchment is positively associated with individual propensity for volunteering in any type of voluntary organization and in a service provision voluntary organization (p < 0.01), all other things being equal. When encountering a decline in government spending, citizens are more likely to dedicate their time and energy to volunteering, supporting H1. Table A7 in the online appendix reports estimation results using multilevel logistic models with robust standard errors. Coefficients of government retrenchment are statistically significant across three dependent variables, but only with p < 0.1. Online Table A8 shows estimation results with multilevel logistic models for the EVS4 analysis. Government retrenchment is positively associated with one’s propensity for volunteering in any type of voluntary organizations and service provision organizations (p < 0.01), holding other variables at means. This shows robustness of the findings from multilevel probit model estimations. Online Table A9 reports results of multilevel probit models using the pooled datasets. This is to demonstrate robustness after controlling for effects of survey waves and sources. Online Table A9 shows that government retrenchment is positively associated with voluntary work at any type of voluntary organizations (p < 0.1) and at service provision organizations (p < 0.05). That is consistent with results in the main models using EVS3/WVS4 (Table 1) and EVS4 (Table 2).

Figure 1 shows the predicted probabilities of someone—a person who is female, full-time employed, married, and with medium income and education—volunteering for social service organizations. As seen from the figure, probabilities of an individual volunteering increase as governments conduct more spending cuts, holding other things at constant.

Figure 1.

Probability of volunteering for service provision organization. Data: EVS4. Probabilities correspond to a female, full-time employed, medium income level, medium education level, and married. Other variables are held at means.

Tables 3 and 4 report the results of model 2 which utilizes the second independent variable, large change in government spending, as an independent variable. Recall that it is a categorical variable which classifies spending changes into (1) small change, (2) large-scale retrenchment, and (3) large-scale expansion. This variable is created to test the third hypothesis that only large-scale spending changes affect citizen participation in voluntary service provision. The results of the EVS3/WVS4 and the EVS4 analyses suggest that experiencing higher levels of government retrenchment is not associated with the dependent variables. However, very interestingly, experiencing large government expansion is significantly correlated to individuals’ likelihood for participating in voluntary activities compared to the baseline category (small change in government spending) (p < 0.1, p < 0.05, p < 0.01). This result holds for all variables except membership outcome for three types of organization in the EVS4 analysis. Online Table A10 in the appendix reports results of model 2 when using the pooled samples. Results show that large-scale expansion is negatively associated with volunteering in three types of organizations (p < 0.01), which is identical to the result in the EVS/WVS4 sample (Table 3) and EVS4 sample (Table 4). These results show robustness of the main results when controlling for survey waves and sources. Online Tables A11 and Table A12 report the estimation results using multilevel logistic regression models for the EVS3/WVS4 and EVS4, respectively. Both tables support findings from the multilevel probit models. Figure 2 compares probabilities of individual participation in volunteering for service provision organizations in the EVS4 analysis. As seen from the figure, government expansion clearly reduces the chance of being involved in voluntary work for service provision organizations, providing empirical support for H3.

Table 3.

EVS3/WVS4: Multilevel probit models estimating the association between large change in government spending and membership and volunteering in voluntary organizations

	Membership			Volunteering
Variables	Voluntary organization	Service provision organization	Social service organization	Voluntary organization	Service provision organization	Social service organization
Country-level variables
Large change in government spending
Large-scale	0.02	0.06	−0.08	−0.09	−0.08	−0.13
retrenchment (ref. = small change)	(0.20)	(0.20)	(0.12)	(0.15)	(0.14)	(0.12)
Large-scale	−0.42**	−0.42*	−0.34*	−0.54***	−0.55***	−0.49***
expansion	(0.20)	(0.23)	(0.18)	(0.17)	(0.19)	(0.17)
Current spending	−0.48*	−0.51*	−0.25	−0.34	−0.34	−0.06
size (ref = first quarter) Second quarter	(0.28)	(0.28)	(0.19)	(0.21)	(0.23)	(0.18)
Third quarter	−0.15	−0.22	−0.23	−0.35	−0.35	−0.35*
	(0.26)	(0.27)	(0.18)	(0.22)	(0.23)	(0.18)
Fourth quarter	0.25	0.13	−0.13	−0.26	−0.25	−0.22
	(0.30)	(0.29)	(0.17)	(0.21)	(0.22)	(0.16)
GDP per capita (ln)	0.84***	0.85***	0.44***	0.26	0.30*	0.20
	(0.22)	(0.22)	(0.13)	(0.18)	(0.17)	(0.13)
Constant	−8.15***	−8.37***	−5.36***	−2.85*	−3.34**	−3.17**
	(2.09)	(2.08)	(1.33)	(1.68)	(1.68)	(1.25)
Country-level	0.22***	0.20***	0.08***	0.10***	0.10***	0.07***
variance	(0.05)	(0.04)	(0.03)	(0.02)	(0.03)	(0.02)
Observations	31,861	31,861	31,861	31,861	31,861	31,861
Number of countries	29	29	29	29	29	29

Note: Individual level control variables are not reported in the table. Robust standard errors in parentheses.

***

p < 0.01, **p < 0.05, *p < 0.1.

Figure 2.

Table 4.

EVS4: Multilevel probit models estimating the association between large change in government spending and membership and volunteering in voluntary organizations

	Membership			Volunteering
Variables	Voluntary organization	Service provision organization	Social service organization	Voluntary organization	Service provision organization	Social service organization
Country-level variables
Large change in government spending
(ref. = small change)
Large-scale	−0.10	−0.07	−0.07	−0.11	−0.08	−0.16
retrenchment	(0.21)	(0.19)	(0.11)	(0.10)	(0.10)	(0.10)
Large-scale expansion	−0.06	−0.14	−0.00	−0.46***	−0.49***	−0.28***
	(0.25)	(0.24)	(0.12)	(0.14)	(0.13)	(0.10)
Current spending size	−0.04	−0.11	−0.09	−0.31**	−0.27**	−0.25**
(ref = first quarter) Second quarter	(0.23)	(0.21)	(0.13)	(0.13)	(0.14)	(0.11)
Third quarter	−0.06	−0.04	−0.01	0.08	0.13	0.04
	(0.22)	(0.21)	(0.10)	(0.17)	(0.17)	(0.11)
Fourth quarter	0.56**	0.50*	0.22	−0.10	−0.05	−0.00
	(0.28)	(0.27)	(0.14)	(0.14)	(0.14)	(0.11)
GDP per capita (ln)	1.16***	1.12***	0.73***	0.64***	0.69***	0.54***
	(0.24)	(0.23)	(0.12)	(0.13)	(0.13)	(0.13)
Constant	−12.37***	−12.07***	−9.07***	−7.22***	−7.84***	−7.15***
	(2.52)	(2.39)	(1.32)	(1.29)	(1.28)	(1.32)
Country-level	0.17***	0.14***	0.04***	0.05***	0.05***	0.04***
variance	(0.03)	(0.03)	(0.01)	(0.01)	(0.01)	(0.01)
Observations	27,815	27,815	27,815	26,817	26,817	26,817
Number of countries	25	25	25	25	25	25

Note: Individual level control variables are not reported in the table. Robust standard errors in parentheses.

***

p < 0.01, ** p < 0.05, *p < 0.1.

Discussions and limitations

This study tests how government retrenchment is associated with voluntary activities by using two waves of mass opinion surveys. Government retrenchment is operationalized by averaged yearly percent change of government spending over 10 years. Participation in voluntary activities is measured by two dependent variables: individual membership in voluntary organizations, and individual engagement in unpaid voluntary work. Unlike previous studies that look at the current size of government spending, this study examines how changes in levels of government spending are associated with citizen volunteering. Findings show that expenditure cuts are positively related to individual volunteering for voluntary organizations, supporting H1. Likewise, individuals living in the context of large-scale government expansion are less likely to do volunteering for voluntary organizations. Most results are robust across two analyses (EVS3/WVS4 and EVS4) and two estimation models, confirming H3. Results of models 1 and 2 are in line with what the crowding-out view proposes. Expenditure cuts are associated with increased citizen volunteering and increased spending is negatively associated with volunteering. Finding causal mechanisms is not the main purpose of this study, but, as the crowding-out theory proposes, reducing government activities does seem to be associated with increased citizens’ participation in volunteering. On the other hand, extending government activity reduces citizens’ willingness to participate in volunteer activities.

It is notable that government retrenchment is mostly associated with voluntary work, but not membership. These two variables differ in terms of level of involvement (Howard and Gilbert, 2008; Wemlinger and Berlan, 2016). Membership merely requires one’s belonging to a voluntary organization, while voluntary work asks for actual engagement in unpaid work. Membership can be obtained or maintained by simply paying membership without actual physical contributions. Conversely, the latter requires more active participation. This suggests that expenditure cuts may motivate active participation in volunteering, not simply passive membership. Furthermore, retrenchment may be associated with a shift from nominal membership to active participation. Further causal analysis is needed to explore this link.

Note also that retrenchment is similarly associated with voluntary work regardless of area of voluntary organization except social service organization in the EVS4 analysis. Results suggest that general public spending cuts are associated with increased active voluntary work by citizens both in specific types of organizations (i.e., service-oriented and social service organizations) and more broadly in voluntary organizations in general. We also find that large-scale expansion of government spending is negatively related to citizen volunteering in a similar way. Such similar results across different areas of volunteering may be due to the use of a comprehensive measurement of spending cuts, namely, general government final consumption expenditures. Due to data limitation in the period of EVS3/WVS4, following a previous study by Bartels et al. (2013), we used this measurement, which captures spending cuts in general, not in particular areas of spending. Future study should investigate the relationship between different kinds of government spending and kinds of volunteering as more detailed historical data becomes available.

This study is not without limitations. First, due to the lack of cross-national datasets for individual volunteering, this research relies on two cross-sectional datasets. Therefore, the results are observational, not causal. Other confounding factors may have affected the outcomes. In addition, the effects of government retrenchment/expansion are not completely consistent across different types of dependent variables. Such inconsistency may be due to time and country-specific contextual factors. Third, data unavailability impedes us from assessing the role of government devolution efforts. Perhaps the positive impact of retrenchment on volunteering may be due to governments’ efforts to foster civil society through promoting contracting-out and subsidizing nonprofit organizations. However, data unavailability impedes us from assessing the specific role of devolution efforts. Despite these limitations, this study contributes to the understudied link between government retrenchment and citizen volunteering by bringing together two strands of literature that have been separately developed. Further research should undertake the unexplored tasks as the data becomes available.

Supplemental Material

Supplemental material - Supplemental material for Government retrenchment and citizen participation in volunteering: A cross-national analysis of OECD countries

Supplemental material, Supplemental material for Government retrenchment and citizen participation in volunteering: A cross-national analysis of OECD countries by Kohei Suzuki in Public Policy and Administration

Footnotes

Acknowledgements

The original version of this article was written as one chapter of the author's dissertation at Indiana University, Bloomington, USA. I would like to thank the dissertation committee members: professors Gregory Kasza, Sergio Fernandez, Timothy T. Hellwig, Leslie Lenkowsky, and Armando Razo for their valuable and helpful comments.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research for this paper was financially supported by the research project, “Out of Control or over Controlled? Incentives, Audits and New Public Management”, and I gratefully acknowledge the financial support from Riksbankens Jubileumsfond (the Swedish Foundation for Humanities and Social Sciences).

Notes

Supplemental Material

Supplemental material for this article is available online.

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