Social Policy and Political Trust: Long-Term Effects of Welfare Generosity in Europe

Abstract

While some argue that diminishing welfare policies erode political trust, others contend they do not significantly influence support for political institutions. Despite pressures on social spending, a comprehensive examination of the relationship between welfare policies and political trust is lacking. This research analyzes trends in political trust across Europe using Bayesian dynamic latent variable modeling and investigates the impact of within-country changes and enduring between-country differences in social policies on national-level trust. It focuses on cash benefit transfer policies, particularly those addressing for life-course risks and labor market insurance. Results show that structurally generous social policies correlate with higher political trust, but short-term changes in policy generosity do not. Furthermore, the generosity of specific policies does not exhibit a clear direct relationship with national-level trust. Overall, these findings support the skeptical view that more generous welfare policies do not easily foster increased political trust in the short term.

Keywords

political trust welfare state politics social policy Bayesian latent variable modeling random effects within-between analysis

Political Trust and Retrenching Welfare States

Citizens’ trust is crucial for the effectiveness of electoral democracies, acting as the linchpin that holds the system together (Zmerli and Van der Meer, 2017). While discussions about a “political trust crisis” are not new, scholarly work on political trust has exploded in the twenty-first century due to increasing political and economic turmoil (Van der Meer, 2017). This body of research highlights the risks associated with a declining political trust mood, as it reflects widespread doubt about whether political institutions and actors genuinely serve the public interest, uphold good governance, and safeguard citizens’ welfare. In this vein, numerous studies have linked lower levels of national-level political trust to poor economic and political performance, with rising unemployment and corruption diminishing trust (Friedrichsen and Zahn, 2014; Van Erkel and Van der Meer, 2016). Amid debates on mitigating declining trust due to increased socio-economic turmoil, attention has been drawn to the state’s ability to provide social protection to its citizens, particularly through social welfare policies (Kumlin, 2004; Lühiste, 2014).

Despite extensive research on political trust, its connection with welfare state performance has received limited attention (Haugsgjerd, 2018; Kumlin and Haugsgjerd, 2017). Past studies suggest that welfare retrenchment, especially by left-wing parties, can lead to electoral punishment (Horn, 2021) or increased support for protest movements (Bermeo and Bartels, 2014). In that regard, it has often been suggested that a decline in welfare spending also leads to decreasing trust in political institutions (Kumlin and Haugsgjerd, 2017). “Welfare efforts,” as reflected by the spending and generosity of social policies, facilitate the provision of higher levels of socio-economic security, signaling the state’s attempt to reconcile economic grievances, which in turn could bolster trust (Kumlin, 2004; Lühiste, 2014). Though insightful, the existing literature lacks a comprehensive understanding of how changing social welfare policies affect political trust. Accordingly, it remains unclear how these mechanisms function among the broader population, as people can feel burdened via greater taxation caused by more spending (Lim and Moon, 2022; Rudolph and Evans, 2005) or have different normative preferences regarding which groups’ welfare is ensured (Laenen and Gugushvili, 2021; Van Oorschot et al., 2017). Consequently, it remains unclear whether the generosity of social policies, understood in terms of their comprehensiveness and equity of social protection, can foster citizens’ trust in political institutions.

This article seeks to address three key shortcomings of the current literature. First, studies have tended to focus on individual subjective perceptions of the welfare state and their interlinkages with trust (de Blok et al., 2019; Kumlin, 2004; Lühiste, 2014). Second, studies that do examine the impact of welfare policies on trust focus on economic crises, where the effects of welfare policies are conditioned on economic setbacks (Haugsgjerd, 2018). Moreover, these studies are limited in their geographical scope, focusing on single-country case studies (e.g. de Blok and Kumlin, 2022), or in their temporal scope, focusing on cross-sectional data (Haugsgjerd, 2018; Kumlin and Haugsgjerd, 2017). This has led to omitting an objective country-based, contextual, and over-time perspective on the impact of welfare policies on political trust. Third, it is not well understood if certain types of social policies are more salient for citizens (Ahrens and Bandau, 2023; Kumlin and Haugsgjerd, 2017). Most studies with a country-level focus examine the consequences of income inequality (e.g. Goubin and Hooghe, 2020), or economic performance more in general (e.g. Van Erkel and Van der Meer, 2016). Moreover, studies that do examine normative perceptions of welfare policies and perceived reform pressures focus on individual perceptions of deservingness (Goerres et al., 2020; Kumlin and Goerres, 2022), leaving it unclear whether these mechanisms translate to the national-aggregate level. This leaves the question of how short- and long-term objective country welfare efforts influence political trust unanswered.

To overcome these limitations, high-quality macro-level data on political trust and changing welfare policies is required. In that regard, this article makes three key contributions. First, this study addresses the challenge of limited longitudinal macro-level data on political trust due to the uneven distribution of cross-national surveys over time, space, and construct operationalization. Despite an abundance of micro-level data on trust in different political institutions, research on aggregate public opinion often relies on subsets of single survey projects to mitigate imbalances in their data. To overcome this limitation, we employ Bayesian dynamic latent trait modeling (Claassen, 2019, 2022, 2024) through integrating data from various international survey projects on trust in political institutions. This approach allows us to generate smooth, balanced, and high-quality data on national-level political trust, conceptualized as a country’s political trust mood, which deepens our understanding of the public’s trust in political institutions.

Second, given the broad temporal scope of the article, spanning several decades of trends in trust, we make an empirical contribution by unraveling effects caused by long- and short-term differences in welfare states. This is done by using within-between random effect models that disentangle the impact of systemic country characteristics from year-to-year changes occurring within countries. Third, we investigate if certain social policies are of more relevance or whether an overall combined package of generous social policies fosters political trust at the national-aggregate level. Specifically, leveraging data from the Comparative Welfare Entitlements Project (CWEP) (Scruggs, 2023), we make a distinction between life course risk insurance policies (i.e. pension benefits) that all citizens are effectively guaranteed to benefit from, labor market risk insurance policies (i.e. unemployment benefits) that are more politically contested, and a country’s combined package of risk-insurance policies (i.e. pension, sick pay, and unemployment in-cash benefit policies), to theorize different mechanisms linking a state’s welfare efforts to its national political trust mood. As social policy spending can be confounded by the size of welfare target populations and the structuring of insurance policies, we particularly focus on the impact of insurance policy generosity (i.e. the replacement rate, benefit duration, benefit access and coverage) on political trust.

Overall, our results support the argument that contrasting mechanisms relate short- and long-term welfare efforts to political trust, with the implication that there is no direct uniform short-term impact. We find that enduringly high combined welfare generosity—a comprehensive set of policies protecting citizens against risks to ensure a decent living standard when in need—does foster greater political trust. In contrast, our results show that short-term increases in generosity are prone to decrease political trust or have no direct impact, likely relating to opinion polarization, diffused accountability structures, welfare deservingness, and stealthy welfare policy reforms. In short, this study underscores that improving the generosity of some welfare policies will not translate quickly into more political trust at the aggregate-national level, but an enduringly generous welfare regime does foster more trust. More broadly, this study speaks to debates on the stability and change of political attitudes. We conclude that long-term institutional socialization processes function independently from short-term institutional performance, and that it is crucial to distinguish between the salience of policies at a given moment, from the overall relative stability of public moods.

Welfare Efforts and Political Trust Moods

Political Trust Mood Changes

Citizens’ trust in political institutions, or political trust, reflects the support individuals harbor for their political system and decision-making processes (Easton, 1975). Fundamentally, trust is rooted in the belief that political institutions and actors will adhere to expectations of positive behavior, even in the absence of monitoring by citizens (OECD, 2017). Traditionally, political support measures are categorized as “diffuse” or “specific,” where specific support pertains to day-to-day political management (covering concrete decisions, actors, or events), while diffuse support takes an expansive view (covering political regimes and communities) (Easton, 1975). Political trust, occupying a middle ground between these two ends, remains independent of daily politics but is contingent on ongoing evaluations. Within this framework, political trust encapsulates a fundamental belief that political entities will uphold principles of “good” governance.

National levels of political trust are shaped by citizens’ evaluations of how political institutions have performed, their perceptions of procedural effectiveness, and the ethical conduct of political entities. Therefore, a country may experience higher levels of trust when citizens believe in the competence, reliability, responsiveness, and/or openness of political actors (Fiske, 2002; OECD, 2017). At the aggregate level, despite citizens’ varied perceptions, this trust-as-evaluation approach thus argues that the quality of policies should to some extent matter for a country’s trust “mood,” that is, the country’s average level of trust (Bussi et al., 2022; Kumlin and Haugsgjerd, 2017).

Conceptually, a “mood” reflects a broad and relatively stable inclination of people, in this case, of citizens of a given country, to trust political institutions. Originating from research on public opinion (Stimson, 1991), a policy mood refers to the general disposition or shared feelings of the public toward policies over time and across different circumstances. Policy mood studies emphasize that aggregated attitudes represent broad and shifting sentiments, influenced by short- and long-term political and policy developments, which in turn shape how publics perceive policies and political institutions. For instance, the policy mood can shift to a greater demand for government intervention in response to periods of economic downturn, only to swing back toward preferences for market-driven solutions during times of economic stability. Yet, such shifts occur within existing ideological and institutional boundaries, as long-standing political and economic developments shape the range of viable policy sentiments of the public. Accordingly, a mood refers to the overarching tendency, or unobserved underlying climate, rather than the mere sum of isolated individual opinions at a given moment (Claassen, 2019, 2022, 2024; Stimson, 1991).

Past studies have highlighted how a country’s national level of political trust is influenced by the short- and long-term output of economic policies, such as the unemployment rate and growth of the economy, as well as short- and long-term changes in the quality of political decision-making processes, such as (control over) corruption (Friedrichsen and Zahn, 2014; Goubin and Hooghe, 2020; Ruelens et al., 2018; Van Erkel and Van der Meer, 2016; Van der Meer and Hakhverdian, 2017). Citizens use these factors to assess the performance of their political institutions. Hence, a country’s trust mood should evolve in response to long-term political, economic, and policy developments, while fluctuating due to momentary shocks, events, and shifts in opinion. Though these relationships are well established in the literature, there are limited studies simultaneously estimating the impact of both short- and long-term economic and political performance over an extended period of time across multiple countries. Hence:

Hypothesis 1a (Economic Performance): Better economic performance (1) over an extended period of time, and (2) on a yearly basis, is related to higher political trust moods.

Hypothesis 1b (Political Performance): Better political performance (1) over an extended period of time, and (2) on a yearly basis, is related to higher political trust moods.

In evaluating the performance of political institutions, the output of social welfare policies, aiming to provide crucial social rights and services to citizens, can be a key criterion to evaluate the performance of political institutions (Kumlin, 2004; Kumlin and Haugsgjerd, 2017). Welfare generosity refers to the extent to which the social policies of a given country provide comprehensive and equitable social protection, aiming to safeguard citizens against economic risks, meet their basic needs, and ensure access to opportunities. Such policies include ensuring replacement incomes in times of unemployment or sickness, poverty relief measures, pensions in old age, and promoting childcare to facilitate work (Esping-Andersen, 1990; Nicaise and Lehweß-Litzmann, 2018). While the trust-as-evaluation literature emphasizes the impact of performance evaluations for policy processes and outputs (Van der Meer and Hakhverdian, 2017), previous research has primarily explored the output of economic policies and the procedural fairness of political decision-making processes. Consequently, it remains unclear whether the generosity of social welfare policies in providing social protection, which we conceive of as a “policy output” in the Eastonian sense (Easton, 1965), is used as a performance evaluation that shapes the public’s tendency to trust political institutions.

Studies have shown how governments that implemented austerity measures in social spending usually lost votes in the election following implementation (Armingeon et al., 2016; Horn, 2021). Research indicates that citizens are more likely to support incumbent governments when satisfied with social policies at various levels of government (Giger, 2010), which also positively influences satisfaction with democracy and political trust (Lühiste, 2014). Although these relationships have been documented both between countries and over time within countries (Haugsgjerd, 2018; Kumlin and Haugsgjerd, 2017), the relationship between welfare efforts and political trust has remained relatively unexplored and undertheorized. To address this, we theorize three mechanisms that link a country’s welfare effort to its political trust mood.

Combined Welfare Efforts Foster Political Trust in the Long Run

The first mechanism relates to the long-term enduring impact of sustained welfare efforts. This association between trust and social policies is related to performance of the government to ensure its citizens’ welfare (Bussi et al., 2022; Pierson, 1993). Social security policies aim to guarantee the quality of life for all citizens, as they serve to protect and maintain the quality of life for citizens in times of need. If governments have invested in programs that provide healthcare, education, and social security over an extended period of time, they show that they care about the well-being of citizens and seek to improve their lives. Over time, such efforts can have the ability to foster the feeling among all citizens that their welfare is protected by their government from any risks, be that illness, old age, or unemployment (Kumlin and Haugsgjerd, 2017). In consequence, when governments have invested in a generous welfare state, they create a sense of solidarity between citizens and the state, hence improving the political trust mood.

Shifting perspectives from the benefits of resources for individuals to the nation as a collective provides an explanation as to why economically well-off citizens too would become more trusting because of greater welfare efforts (Esping-Andersen, 1990; Kumlin and Haugsgjerd, 2017; Van Kersbergen, 2006; Wilkinson and Pickett, 2011). Importantly for contemporary times, social policies can further serve to mitigate the effects of economic inequality (Shore, 2019). When governments provide support for low-income households via social welfare policies, particularly in times of need, it can reduce the impact of disparities between the rich and poor (Lühiste, 2014; Wilkinson and Pickett, 2011). Such efforts can be interpreted as welfare efforts to create a level playing field, which can boost trust (Goubin and Hooghe, 2020; Shore, 2019). This level playing field, in turn, facilitates social cohesion and greater horizontal solidarity between citizens within a country (Goubin, 2018). Hence, greater welfare efforts also relate to higher political trust among citizens who do not end up needing these efforts.

Yet importantly, such an impact is not likely to manifest as a result of short-term changes, or per say as a result of a single enduringly generous social policy domain. Rather, fostering the belief that the state ensures citizens’ welfare—that is, fostering the belief in “good” governance—requires sustained effort across policy domains to show that the state will protect citizens whenever the need arises. Hence, it is expected that the sustained and enduring combined welfare efforts of the state is what develops higher political trust moods. This leads to:

Hypothesis 2 (Long-Term Combined Welfare State Performance): Countries with more generous policies across welfare domains have higher political trust moods.

Polarized Public Opinion and (Un)Deserving Short-Term Welfare Efforts

Although this long-term perspective of state welfare efforts can foster a positive political trust mood, the short-term challenges of achieving enduringly generous social policies can be more contested (Kumlin and Haugsgjerd, 2017; Kumlin and Stadelmann-Steffen, 2014). Welfare policies have heterogeneous impacts on different population segments, which makes it difficult to discern average effects on political trust across a national population with varying and fluctuating conditions of need. For instance, though some welfare policies are essential for the well-being of socio-economically vulnerable citizens, such as the unemployed, those who are economically well-off might see these same policies as burdensome on the state’s budgetary deficit and causing unnecessarily high taxes (Lim and Moon, 2022; Rudolph and Evans, 2005). Additionally, policymakers often incorporate blame avoidance strategies when enacting austerity policies, and can implement changes incrementally or stealthily (Jensen et al., 2014; Soss and Schramm, 2007). Consequently, within-country changes in welfare efforts are not likely to be noticed by all citizens and likely to be interpreted differently by various citizens from differing socio-economic positions.

Accountability and saliency diffusion are further exacerbated by the normative frames through which citizens view welfare policies. Most citizens agree on the necessity of actions aimed at reducing inequality (Dallinger, 2022). However, within this consensus, there are significant variations due to the contention over who qualifies as “deserving” of welfare benefits. These normative disagreements influence the reception of policies designed to aid contentious groups, such as the unemployed, and less contentious groups, such as the elderly (Laenen and Gugushvili, 2021; Van Oorschot et al., 2017).

Beyond diffused accountability and normative desirability, the fiscal pressures on maintaining a mature welfare state have become a growing cause of concern in the face of aging populations, spikes in unemployment, continued migration, and economic globalization (Kumlin and Nemčok, 2024). Although the discussion of decades past assumed that welfare states would be resilient, the sustainability, affordability, and deservingness of generous social welfare policies is today a central point of discussion. Confronted with reform pressures, this shapes perceptions of deservingness as to which risks the state is and is not responsible for (Goerres et al., 2020; Kumlin and Goerres, 2022; Pierson, 1996, 2001). Concretely, in most European countries, the state has become largely uncontested in its responsibility to protect against life-course risks, such as old age, that are effectively guaranteed for all, but is contested in its responsibility to protect against labor-market risks, such as unemployment insurance. Indeed, research indicates that the welfare reform pressures can be exaggerated depending on its association to (un)deservingness (Jensen, 2012; Laenen and Gugushvili, 2021; Van Oorschot et al., 2017).

Based on these arguments, one might expect that greater welfare efforts to ensure life-course risk insurance are less contentious and more meaningful to all citizens, as all citizens are effectively guaranteed to experience them. This would imply that nationally aggregate levels of political trust should be more sensitive to changes in the generosity of such policies. In contrast, expanding labor market insurance policies is likely to be more contested, and unpopular across most citizens. This clash in desirability is likely to itself cause a decrease in a country’s political trust mood due to increasing the salience of polarization around social policy issues. Hence:

Hypothesis 3a (Short-Term Uncontested Welfare Performance): Yearly within-country increases to life course risk insurance policies are related to higher political trust moods.

Hypothesis 3b (Short-Term Contested Welfare Performance): Yearly within-country increases in labor-market risk insurance policies are related to lower political trust moods.

Data and Methods

Dependent Variable: Capturing Political Trust Moods

This study builds on a novel statistical method developed by Claassen (2019, 2022) to construct a dataset with a broader spatial-temporal scope compared to most previous studies on nationally aggregate political trust levels. Building upon the tradition of “mood” measures that address the need for high-quality aggregate public opinion data over large time spans (Jackman, 2005; Stimson, 1991), we pooled data on trust and confidence in various political institutions from six different survey projects¹ spanning from 1981 to 2022 and covering 31 European countries.² With the proliferation of international surveys, multiple studies have sought to pool data (e.g. Van Erkel and Van der Meer, 2016), but were confronted with fragmentation of national time-series data and discrepancies in political trust item wording and scale both across and within surveys. This method is innovative as it overcomes such data restrictions by leveraging Bayesian latent variable modeling techniques that smooth over gaps in time series while accounting for item bias and time-invariant cross-national non-equivalence as well as random error (Claassen, 2019, 2022), with recent findings indicating that it can be applied to political trust measures too (Claassen, 2024; Kołczynska et al., 2024; Valgarðsson et al, 2024).

To illustrate the exact operationalization of the trust mood measure, it is helpful to discuss concrete survey items. Sporadically since 1981, the European Values Study included the following item: “Please look at this card and tell me, for each item listed [National Parliament and Civil Services], how much confidence you have in them, is it a great deal (4), quite a lot (3), not very much (2) or none at all (1)?” In contrast, items included in the European Social Survey on a bi-annual basis since 2002 ask, “Using this card, please tell me on a score of 0-10 how much you personally trust each of the institutions I read out [politicians, political parties, and the national parliament]. 0 means you do not trust an institution at all, and 10 means you have complete trust.” Despite both survey questions asking explicitly about trust and confidence in political institutions, the two items differ in wording, response scales, and institutional focus, while also having differing country samples and time frames, each of which introduces some type of bias in measuring political trust. For the purposes of this study, we excluded items that attempt to capture political trust implicitly to limit bias introduced by question wording, meaning item batteries needed to explicitly ask about trust or confidence. Moreover, to sufficiently account for bias introduced by survey projects, items from surveys with less than three waves were excluded. Last, we only included survey items fielded in multiple European countries across multiple waves, in turn reducing bias introduced by country-specific question interpretations. Table A.1 in Appendix A shows the list of items that were used for the computations of political trust mood scores.

In the simplest terms, to account for these item variations, responses are first recoded into affirmative (1) and dissenting (0) responses to ensure comparability (more information about the statistical principles and equations applied can be found in Appendix A). Biases introduced by survey-item differences are accounted for by using a survey-item loading score in the measurement model of political trust, ensuring variation due to wording or format does not distort the estimates. As items can function differently across countries, a country-item parameter is used to ensure that variation is not driven by country variations in the interpretation of questions. To smooth over time gaps, estimates for each year are informed by their prior level, producing consistent estimates of the political trust mood across Europe over time. This approach yields scores for country-years that reflect fluctuations in the overarching tendency of publics to trust their political institutions. As is common in latent measurement models, these scores are standardized around a grand mean of zero with a standard deviation of one, allowing for direct comparisons across time and countries.

Scores are estimated using Bayesian Markov-Chain Monte Carlo methods via the R package CmdStanModel (Carpenter et al., 2017; Češnovar et al., 2021). Four parallel chains were run with 1000 samples, where the first 500 samples are used as warm-up and the remaining samples analyzed for the posterior distribution. Models converged with $\hat{R} s$ between 0.95 and 1.05. This resulted in 1066 country-years as based on 3335 nationally aggregated public opinion measures on political trust. This allows for one of the most comprehensive analyses of trends in trust in Europe to date (Claassen, 2024; Kołczynska et al., 2024; Norris, 2011, 2022; Valgarðsson et al, 2024).

The remainder of this article will focus on the latent country-year estimates of political trust, also known as political trust mood scores. To give insight into what the scores imply, Figure 1 visualizes all the country-years for which the method was applied. The political trust “mood” scores reflect the extent to which a given country-year is trusting of their political institutions relative to the grand mean fixed at 0. Accordingly, scores reflect specifically when and which European countries had more or less political trust during the last four decades relative to each other as opposed to being based on an item scale or percentage of affirmative responses. From these average trends, and as can be expected from past research (Haugsgjerd, 2018), we can see that European countries experienced a particularly turbulent period following the 2008 recession. While the average level of trust in 2020 was slightly above the grand mean (x̄ = 0.12), the average across Europe from 2009 to 2017 hovered around −0.20. Beyond the average trend across countries, Figure 1 orders countries with higher scores in 2020 toward the top and lower scores to the bottom of the Figure.

Figure 1.

Political Trust Mood Scores Across Europe over the Last Four Decades.

As this ordering clearly shows, and as can be expected from past findings (Norris, 2011, 2022; Zmerli and Van der Meer, 2017), there is group of high trust countries with positive scores, mainly in northern Europe (e.g. Switzerland, Sweden, and Germany), and low-trust countries with negative scores, mainly in southern and eastern Europe (e.g. Poland, Slovakia, and Greece). This highlights how there are both enduring differences between countries and yearly fluctuations that overlap with established causes of political trust, hence providing quality data on how much a country was trusting of their political institutions.

Established Causes of Trust: Economic and Political Performance

To examine whether the descriptive trends are indeed significantly related to established causes of differences in national-level political trust, we include key economic and political performance factors (Friedrichsen and Zahn, 2014; Van Erkel and Van der Meer, 2016). To test hypothesis 1a for economic performance, we include the unemployment rate and GDP per capita. Data for this is obtained from the World Development Indicators (Armingeon et al., 2018). To test hypothesis 1b for political performance, we include control of corruption as measured in the World Governance Indicators (WGI) by the World Bank (2018). This index reflects aggregate perceptions of the extent to which there is control over the use of public power for private gains and quality of policy formulation.

Welfare State Generosity

To examine how welfare efforts are associated with a country’s political trust mood, we use data from the Comparative Welfare Entitlement Project (Scruggs, 2023). The CWEP indices focus on citizens’ rights to social insurance, considering aspects beyond expenditure, such as how the money is spent, and policies are structured. The indices account for qualification and waiting periods, expected duration of benefits, standard replacement rates, contribution proportions, and coverage rates. Scores are determined by summing these characteristics and classifying countries as less generous, averagely generous, or more generous, based on their deviation from the mean score in the CWEP dataset. These classifications are combined so that higher values indicate the risk insurance policies are more generous. At the time of producing this study, the CWEP is yet to incorporate data on Eastern European countries, leading to a reduction of the total country-year sample (Scruggs and Ramalho Tafoya, 2022).

The CWEP contains data on three public insurance policy programs that take up large portions of in-cash benefit transfers of social policies across countries: Pension, Unemployment, and Sickpay. Additionally, the CWEP provides a combined generosity score that is based on the sum of scores for the three respective programs. For hypothesis 2, we use the combined generosity index to test whether enduringly high combined welfare efforts foster positive political trust moods. For hypotheses 3a and 3b, we use the pension³ and unemployment⁴ generosity indices to test whether short-term changes with differing degrees of contentiousness have diverging associations to political trust moods.

Given that the level of social expenditure can influence the interpretation of changes in welfare efforts, we control for the total social expenditure as a percentage of a country’s GDP (Scruggs and Ramalho Tafoya, 2022). To capture differences in social policy expenditure, this study uses data from the OECD (2019). Social expenditure refers to the public and mandatory, as well as voluntary private, expenditure within government social policies. Importantly, expenditure itself can be confounded by other factors that do not reflect the extent to which citizens are ensured welfare and protected against risks. For example, expenditure can be higher due to the increased “objective” demand for specific policies (e.g. a growing population of elderly and higher unemployment rates) or not be reflective of generosity given the manner in which policies are structured (e.g. high benefit duration for low replacement rates). Nonetheless, as citizens can relate changes to cash benefit welfare policies with state budgetary deficits, we control for the total level of social policy expenditure to isolate the impact of welfare efforts, and with expenditure for the elderly and unemployment specifically.

Modeling and Sampling Strategy: Enduring and Transient Efforts Across Europe

To disentangle the impact of short- and long-term welfare efforts, this study leverages hierarchical random-effect within-between (REWB) models, wherein observations at year t are nested within countries i. Specifically, for all variables, an across time mean variable (x̄_i) is created to gauge long-term differences between countries. Furthermore, this across time mean is subtracted from the original value (x_ti − x̄_i), capturing the year’s difference to the country’s mean over time, and hence reflecting short-term changes occurring within countries. To account for spurious effects, a time trend control β₀(t) is added to the model. Moreover, to isolate the short- and long-term estimates for welfare efforts, controls (v_i) are added with similar within-between transformations (for a detailed discussion on the advantages of REWB models, see Bell et al., 2018; Fairbrother, 2014). The advantage of this method is that we can disentangle the impact of persistent disparities between countries on political trust from unfolding internal dynamics within countries. Moreover, past studies showcase that utilizing REWB models is fruitful in understanding how macro-level dynamics over time and across countries impact political trust (e.g. de Blok et al., 2022; Goubin and Hooghe, 2020).

The equation is as follows:

y_{it} = β_{0} (t) + β_{1} (x_{ti} - {\bar{x}}_{i}) + β_{2} ({\bar{x}}_{i}) + v_{i} + ε_{it}

Because of data availability across the various data sources, there is a notable reduction in the total country sample when including the CWEP indices, and a further reduction in the total year sample when including the WGI indices. This results in a total balanced sample of 15 countries (Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and the United Kingdom) across two decades (1998, 2000, and yearly since 2002 until 2018 before the onset of Covid-19). Though smaller than desired, this 285 country-year sample does provide a variety of changing economic conditions, political performance, and welfare regimes, while remaining largely within a comparable geographic-historical scope of (Western) European countries in the early twenty-first century. Nonetheless, given lower power, we keep our models parsimonious. An overview of the descriptive statistics for the original factor scales, as well as their within-between transformation for this sample of country-years is provided in Table 1. In section “Robustness Analysis,” as part of the robustness analyses, we first run the main analysis models using robust standard errors. Additionally, we run models that exclude political performance, allowing tests with a wider time span (annual observations from 1991 to 2018).⁵ All robustness analyses are found in Appendix B.

Table 1.

Descriptive Statistics of Within-Between Transformations.

Variables (and within-between transformation)	Min	Max	Mean	SD
Economic & Political Performance
Unemployment Rate (% Working Population)	2.49	27.69	8.21	4.64
. . . between	3.65	16.40	8.21	3.59
. . . within	-8.17	12.01	0.00	2.95
GDP per Capita (divided by 1000)	11.53	103.55	42.13	18.02
. . . between	19.71	75.07	42.13	14.79
. . . within	-40.27	28.48	0.00	10.29
Control Corruption (multiply by 10)	-1.90	24.54	15.20	6.49
. . . between	1.46	22.69	15.20	6.31
. . . within	-5.39	6.09	0.00	1.54
Welfare Efforts
Combined Generosity	21.78	45.46	34.71	5.22
. . . between	24.69	44.31	34.71	5.07
. . . within	-3.23	5.44	0.00	1.23
Pension Generosity	8.79	15.80	12.74	1.58
. . . between	8.96	14.54	12.74	1.48
. . . within	-1.65	2.62	0.00	0.56
Unemployment Generosity	3.75	15.21	10.50	2.84
. . . between	5.10	14.57	10.50	2.76
. . . within	-2.11	2.49	0.00	0.65
Total Social Policy Expenditure (% GDP)	13.14	32.65	24.63	3.79
. . . between	17.70	30.23	24.63	3.11
. . . within	-5.56	6.43	0.00	2.17
Old Age Expenditure (% GDP)	2.39	14.79	8.84	2.72
. . . between	3.58	13.22	8.84	2.46
. . . within	-3.61	3.24	0.00	1.17
Unemployment Expenditure (% GDP)	0.13	3.58	1.24	0.78
. . . between	0.26	3.00	1.24	0.70
. . . within	-1.29	1.35	0.00	0.36

Main Results: Long- and Short-Term Correlates of Political Trust Moods

Table 2 shows the results of the REWB models. Starting with the null model (0), we find an intraclass correlation (ICC) of 70%, indicating that much variation in political trust mood scores in (western) Europe during the last two decades is explained by enduring between country differences as opposed to transient fluctuations. This aligns with what we see in Figure 1, where the fluctuations in how much citizens in a country trust their political institutions largely hover slightly above, slight below, or on the average level of trust, while the ultimate country rankings do not change substantially.

Table 2.

REWB Models on the Short- and Long-term Impact of Welfare Performance on Political Trust Moods.

	(0)	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	std. Beta	std. Beta	std. Beta	std. Beta	std. Beta	std. Beta	std. Beta	std. Beta
Economic Performance
Unemployment Rate (btw)		0.060(0.116)			0.058(0.097)	0.039(0.109)	0.064(0.098)	0.137(0.113)
Unemployment Rate (btw)		0.060(0.116)			0.058(0.097)	0.039(0.109)	0.064(0.098)	0.137(0.113)
Unemployment Rate (wi)		–0.349*** (0.021)			–0.372*** (0.021)	–0.363*** (0.022)	–0.325*** (0.026)	–0.296*** (0.032)
Unemployment Rate (wi)		–0.349*** (0.021)			–0.372*** (0.021)	–0.363*** (0.022)	–0.325*** (0.026)	–0.296*** (0.032)
GDP per Capita (btw)		0.472*** (0.112)			0.418*** (0.097)	0.427*** (0.101)	0.427*** (0.100)	0.426*** (0.092)
GDP per Capita (wi)		0.091** (0.028)			0.089** (0.027)	0.097*** (0.028)	0.074** (0.027)	0.089** (0.028)
		0.091** (0.028)			0.089** (0.027)	0.097*** (0.028)	0.074** (0.027)	0.089** (0.028)
Political Performance
Control of Corruption (btw)		0.448*** (0.110)			0.398*** (0.094)	0.445*** (0.100)	0.399*** (0.094)	0.540*** (0.097)
Control of Corruption (btw)		0.448*** (0.110)			0.398*** (0.094)	0.445*** (0.100)	0.399*** (0.094)	0.540*** (0.097)
Control of Corruption (wi)		0.160*** (0.023)			0.159*** (0.022)	0.163*** (0.022)	0.154*** (0.022)	0.159*** (0.022)
Overall Welfare Performance
Combined Generosity (btw)			0.555*** (0.165)		0.175* (0.070)		0.168* (0.073)
Combined Generosity (wi)			0.046		–0.073***		–0.044*
			(0.032)		(0.019)		(0.022)
Specific Welfare Performance
Pension Generosity (btw)				–0.154(0.179)		0.088(0.075)		0.071(0.065)
Pension Generosity (wi)				–0.103** (0.038)		–0.056* (0.023)		–0.028(0.025)
Unemployment Generosity (btw)				0.456* (0.179)		0.129(0.072)		0.186* (0.081)
Unemployment Generosity (wi)				0.088** (0.033)		–0.057** (0.021)		–0.037(0.021)
Welfare Spending Controls
Total Social Expenditure (btw)							0.020(0.063)
Total Social Expenditure (wi)							–0.093** (0.032)
Old Age Expenditure (btw)								0.128* (0.063)
Old Age Expenditure (wi)								–0.047(0.040)
Unemployment Expenditure (btw)								–0.072(0.081)
Unemployment Expenditure (wi)								–0.071** (0.025)
Random Effect
σ²	0.24	0.08	0.24	0.23	0.08	0.08	0.07	0.07
τ₀₀	0.57	0.06	0.32	0.35	0.04	0.04	0.04	0.03
ICC	0.70	0.41	0.57	0.61	0.33	0.36	0.34	0.29
N	15 Countries
Observations	285
AIC	476.845	212.779	481.821	481.289	212.712	218.792	221.382	232.228

Within-country effects were abbreviated to wi and between-country effects to btw. Estimates shown are Standardized Beta Coefficients. *p < 0.05, **p < 0.01, ***p < 0.001.

To see whether the political trust mood scores are related to established causes in the literature on national-level political trust, we start by discussing the short- and long-term impact of economic and political performance factors. After including the within-between effects for economic and political performance (model 1), the ICC already drops to 41%, suggesting around 30% of between country differences in political trust moods relate to economic and political performance. Here, we hypothesized that positive economic conditions, measured by the unemployment rate and GDP per capita, and political conditions, measured by the control over corruption, are related to higher political trust moods. As Table 2 shows, there is indeed a positive impact of greater short- and long-term control over corruption. However, we find that only within-country increases in the unemployment rate are related to lower political trust moods, while there is no significant estimate for between-country differences.⁶ We do find that both higher within- and between-country GDP per Capita levels are positively related to political trust moods. Hence, these results provide support for both hypothesis 1a and 1b on the impact of economic and political performance.

Next, we turn to hypothesis 2 on the enduring impact of combined welfare efforts. For this, we hypothesized that the between-country differences in welfare generosity relate to higher political trust moods, while we did not expect this for short-term within-country changes. Indeed, as we see in Table 2, across model iterations, there is a significant positive between-country estimate for combined welfare generosity, while the within-country estimate is insignificant or negative. Although not to the same extent as economic and political performance, combined welfare efforts do explain around 23% of the ICC. The contrast in estimate direction with the amount of variance explained underscores how enduringly strong welfare efforts can facilitate more positive perceptions of the government, but that achieving this incrementally can be a contested journey. Accordingly, this finding provides support for the theoretical mechanism underlying hypothesis 2 on the long-term combined welfare efforts.

Interestingly, when examining specific welfare policies—the generosity of old age and unemployment insurance—there is no clear direct impact of short- and long-term differences on political trust. We anticipated that increased generosity in old age spending would positively correlate with political trust, while more generous unemployment benefits would be associated with a decline in trust. However, as shown in models 3, 5, and 7 of Table 2, the results for pension and unemployment benefit generosity are largely inconsistent. Pension generosity yields an insignificant between-country estimate, while the within-country estimate is negative across all three models testing hypothesis 3a. Moreover, much less variance in political trust moods between countries is explained by these specific welfare efforts, with an ICC drop of less than 10%. We speculate that this may be due to heightened discussions on reform pressures stemming from aging populations and increasing polarization around pension spending. Consequently, we reject hypothesis 3a (Short-Term Uncontested Welfare Performance). Similarly, the coefficients for unemployment benefit generosity vary in both sign and significance, offering no clear evidence of an effect from long- or short-term changes. Therefore, we also reject hypothesis 3b (Short-Term Contested Welfare Performance).

Robustness Analysis

The results of the robustness analyses are presented in Appendix B. To ensure the robustness of these analyses, models were rerun using robust standard errors (Table B.2). First, there are no substantial changes in the economic and political performance indicators.⁷ This result is in line with the literature, and they explain a substantial amount of variation in political trust mood scores, as indicated by the drop in the ICC. Second, for combined welfare generosity, although there is a decrease in the significance level, the positive between-country effect remains significant at a p < 0.10 level. Given the statistical power and the number of between-country effects in these models that substantially explain national-level political trust, this result indicates tentative robustness. Third, when using robust standard errors for the models containing pension and unemployment benefit generosity, the positive effect of between-country unemployment generosity in models 3 and 7 stays significant.

To increase the statistical power of the models, we ran additional analyses that excluded the control of corruption indicator (Table B.3), as data for this indicator is largely limited to the twenty-first century, allowing an additional decade of observations to be included in the models.⁸ Starting with economic performance, the within and between effects for the GDP per capita, and the within effect of the unemployment rate, remain significant, while the between effect of the unemployment rate remains insignificant. Turning to the estimates for the combined generosity index, countries with an enduringly more generous package of welfare policies do have significantly higher political trust moods, while within-country changes do not have a significant relation. This also holds true after applying robust standard errors (Table B.4). For specific welfare efforts, all effects become insignificant. This result aligns with our discussion on the importance of combined welfare efforts, as opposed to certain welfare domains. Nonetheless, the between-country effect for unemployment generosity does remain significant at a p < 0.10 level when accounting for economic performance, in contrast to our discussion on deservingness, though the estimates become insignificant once controlling for expenditure. Accordingly, hypothesis 1 (impact of economic and political performance) and hypothesis 2 (long-term impact of combined welfare efforts) are accepted, while hypotheses 3a and 3b are rejected.

Discussion: Do Welfare Efforts Foster a Positive Political Trust Mood?

Amid ongoing debates on declining political trust and the impact of growing economic inequality (Goubin and Hooghe, 2020; Haugsgjerd, 2018; Kumlin and Haugsgjerd, 2017), understanding how welfare efforts influence citizens’ perceptions of political institutions is vital. While numerous studies explore individual subjective perceptions of welfare states and their connection to trust (e.g. de Blok et al., 2019; Kumlin and Haugsgjerd, 2017; Lühiste, 2014), there remains a notable absence of comprehensive, country-based, and longitudinal analyses (Haugsgjerd, 2018). In this light, this study offers three significant contributions. First, it argues that social welfare policies can foster trust in the long-term, but that governments face a contested journey to expand their welfare efforts due to public opinion polarization around welfare deservingness, diffused accountability structures, and perceived welfare reform pressures. Second, it leverages a novel methodological approach to studying political trust at the national level from the public opinion mood literature, which produces scores that accurately reflect trust differences over time and countries while accounting for survey project methodological errors and smoothing over gaps in data availability. Finally, it offers empirical insights that transcend single-country cases and short-term change to welfare regimes by broadening the geographical and temporal scope of analysis using REWB models, disentangling the consequences of enduring country characteristics from yearly policy changes.

First, and in line with past studies (Zmerli and Van der Meer, 2017), our findings visually illustrate the fluctuating trends of political trust over four decades in Europe, showcasing heightened turbulence post the 2008 Great Recession while highlighting differences between high- and low-trust countries. Moreover, our analysis shows how enduring country differences and fluctuations within countries are substantially explainable by established economic and political performance indicators of political institutions (Friedrichsen and Zahn, 2014; Van Erkel and Van der Meer, 2016; Van der Meer and Hakhverdian, 2017). These findings underscore the utility of mood methods in capturing trust variations while addressing methodological constraints of past studies.

Second, our findings somewhat contrast with past studies on welfare policies and political trust. While studies have found that satisfaction with welfare policies can be associated with political trust at the individual level (e.g. de Blok et al., 2019; Kumlin, 2004), our analyses do not readily corroborate this finding at the aggregate level. Particularly, as outlined in our theoretical discussion, there are different mechanisms that explain political trust at the individual and at the national level. Our findings show that short-term improvements in the generosity of some welfare policies within countries do not have a clear direct impact on political trust moods, while countries with sustained high levels of welfare generosity across policy domains do have more positive political trust moods. This seemingly paradoxical finding relates to the increasingly contested nature of welfare politics, where short-term changes are interpreted differently across citizens and can heighten the salience of polarized public opinion over which reforms are preferred, which in turn can lower political trust moods. Yet, in the long-run, countries that have a variety of enduringly generous welfare policies are able to foster more political trust, as it boosts confidence in the belief that the state is there to ensure citizens’ welfare and maintain a decent standard of living in times of any and all needs.

Importantly, while hypothesizing that life course policies should be more popular, we observe that more spending and generosity for specific policy domains do not readily increase trust. This should not entirely come as a surprise. Citizens worry about the feasibility of public policies and their potential costs (Giger and Nelson, 2013; Kumlin and Haugsgjerd, 2017). As highlighted by Kumlin and Haugsgjerd (2017), welfare “change now seems less driven by a malicious neo-liberal attack or an exceedingly destructive race to the bottom, but more often by a quest for sustainability in the face of demographic and economic realities.” Following this line of reasoning, some citizens can accept retrenchment while others prefer achieving sustainability via other means to ensure that public policies are sustainable in the longer run. The mirror of this also holds true: some citizens will lose trust if they believe that public policies are too expansive in scope and generous to be sustainable, while others support them. In short, specific policy changes could cause worries about the sustainability or low quality of specific benefits, but not equally across all citizens. Hence, we can only conclude that there is no uniform positive impact of specific welfare entitlements on political trust.

While the present study offers valuable and novel insights into the relationship between welfare policies and political trust, it is not without limitations. First, the complex impact of welfare efforts requires distinguishing between individual-level perceptions and national-level trends. Echoing conclusions on electoral punishment (Ahrens and Bandau, 2023), it appears that political institutions and actors are not, on average, perceived as less trustworthy by citizens due to short-term welfare retrenchment. This suggests that theoretical expectations linking social welfare policies to political trust at the individual level may not translate as effectively to the aggregate level. Second, the reduction in sample size, due to data availability constraints across various sources, limits the statistical power and generalizability of the results. Notably, this issue stems from the exclusion of Eastern European countries in the models of welfare generosity, which could introduce sample bias, especially given the lower levels of trust observed in these regions compared to more mature welfare states in Northern and Western Europe. Additionally, the study’s primary focus on European countries may restrict its applicability in a broader global context. In combination with the smaller sample size, this more homogeneous group of country-years is less able to capture significant differences between countries. Hence, our results should be interpreted as being on the more parsimonious and conservative side. Finally, while the within-between transformation helps to distinguish the effects of short-term and long-term welfare generosity, it does not allow for the estimation of more precise temporal dynamics. Specifically, it remains unclear at what point short-term improvements shift from being too contested to have a widespread impact on trust across the population to being recognized as a means through which the state demonstrates solidarity with its citizens. Therefore, this study can only draw conclusions based on enduring cross-country differences over the past decades and annual within-country changes.

These limitations suggest several clear directions for future research. First, the Comparative Welfare Entitlements Project plans to expand its data to include Eastern Europe and to release entitlement generosity indices for additional policy domains. This expansion would help to address potential sampling biases and allow for a more nuanced understanding of the theoretical expectations related to different welfare efforts. Accordingly, future research can seek to replicate our findings using a broader geographic and social policy scope.

Second, given trends of privatization and reduction of government budgets, it is important to underscore that social policy changes do not occur in a vacuum and are frequently open to scrutiny in public debate. As theorized, it is possible that within-country improvements have no impact, or can even have a negative impact, due to the politicalization of public opinion on welfare policies. Yet, this is contingent on the country-specific policy discourse and the accountability structures of policies.

While our study has focused on how objective (changes) in policy conditions are linked to the overall trust mood within a given country, we did not link this to the national salience of these policies in political discourses or national media. Drawing on insights from literature on immigration attitudes (Claassen and McLaren, 2022; Dennison and Geddes, 2019) or fear of crime (Wenzelburger and Schröder, 2025), there is ample evidence to suggest that short-term objective changes in crime rates or migration numbers do not readily alter public attitudes. Instead, heightened salience in public discourse is more likely to influence concerns about these issues. When a policy lacks salience, it might not trigger strong public reactions, whereas highly salient policies can cause a measurable shift in the public’s policy mood. Importantly, the “reform by stealth” literature highlights that this can even be a premeditated strategy of political actors to avoid electoral punishment and a public backlash (Jensen et al., 2014). Hence, future research should seek to study how welfare policy changes are connected to discourses around welfare efforts and the overall salience of these efforts.

More in general, this study contributes to the larger literature on the stability and volatility of citizens’ political trust (Devine and Valgarðsson, 2024; Mishler and Rose, 2001), and other types of political attitudes, such as satisfaction with democracy (Valgarðsson and Devine, 2022), redistributive preferences (O’Grady, 2019), or migration attitudes (Claassen and McLaren, 2022). Across these attitudes, it has long been debated to what extent they are dependent on the actual behavior of political agents, such as political crises, changes in incumbent governments, and policy reforms, versus to what degree they are contingent on socialization and long-term institutional determinants. With regard to political trust, the object of our study, the findings here corroborate the conclusion by Devine and Valgarðsson (2024) that trust is mainly being determined by long-term processes.

Third, different modeling techniques can be leveraged to gain a more fine-grained insight into how long is long enough for citizens to believe that the state will ensure their welfare through any and all times, leading to higher national political trust. Specifically, time-series cross-sectional analysis with multiple varying time-lagged estimates could provide greater insight into how one-time changes differ from repeated short-term efforts to improve citizens’ welfare.

Finally, future research can further harness the potential of Bayesian dynamic latent trait modeling and mood scores by applying them to a broader range of attitudinal domains beyond political trust. Numerous cross-national surveys capture public opinion on a wide array of topics, yet regularly differ in item wording, temporal coverage, and geographic scope. As this latent variable modeling approach adjusts for survey methodology differences and question wording variations, can smoothen data gaps and takes measurement error into account (Claassen, 2020), it offers a valuable way of collecting country-level panel data on public opinion by overcoming differences across international survey projects. This suggests possibilities for studying public opinion and political attitudes where cross-sectional survey data is available, such as on attitudes regarding migration, EU integration, the environment, inequality perceptions, and similar.

Overall, our findings add important depth to the ongoing debates around welfare policy. Crucially, this study highlights that simply enhancing the generosity of welfare programs is unlikely to lead to immediate gains in political trust. Instead, such changes are more likely to amplify public opinion polarization, with the public’s response being heavily influenced by perceptions of policy sustainability and notions of deservingness. However, when citizens feel assured that they are protected against a broad range of risks and can rely on robust benefits to maintain a decent standard of living during times of need, they are more likely to trust that the state will safeguard their well-being, ultimately fostering greater political trust.

Supplemental Material

sj-docx-1-psx-10.1177_00323217251340857 – Supplemental material for Social Policy and Political Trust: Long-Term Effects of Welfare Generosity in Europe

Supplemental material, sj-docx-1-psx-10.1177_00323217251340857 for Social Policy and Political Trust: Long-Term Effects of Welfare Generosity in Europe by Matthijs Gillissen, Silke Goubin and Anna Ruelens in Political Studies

Footnotes

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: This work was supported by Horizon Europe Framework Programme (3H230125) and the Flemish Research Council (FWO) (grant number 12AZH24N).

ORCID iDs

Matthijs Gillissen

Silke Goubin

Anna Ruelens

Supplemental Material

Additional supplementary information may be found with the online version of this article.

Appendix A. Operationalising Political Trust Mood Scores

Table A.1. Overview of Survey-Item-Years

Figure A.1. Overview of Survey-Country-Year

Appendix B. Robustness Analyses

Table B.1. Unstandardized Effect Estimates of Main Text Fixed Effect Models

Table B.2. Unstandardized Fixed Effect Models Using Robust Standard Errors

Table B.3. Unstandardized Fixed Effect Models Without Political Performance and With a Longer Time Frame

Table B.4. Unstandardized Fixed Effect Model for Longer Time Frame Using Robust Standard Errors

Notes

Author biographies

Matthijs Gillissen is a doctoral student at HIVA – KU Leuven. At HIVA, he is involved in projects related to economic inequality, social policies, political trust, public opinion, and political participation since January 2023. His main fields of interest include comparative politics and public opinion research, as well as the political consequences of inequality.

Silke Goubin is a postdoctoral researcher at HIVA (FWO fellow). At HIVA, she is involved in projects related to inequality, social policy, migration, and public opinion since 2021. Silke’s main fields of interest include comparative politics, public opinion research, social welfare, migration, and the political consequences of inequality. She has published in journals such as the Journal of European Public Policy, the Journal of Ethnic and Migration Studies, and Electoral Studies.

Anna Ruelens is a research manager at HIVA – KU Leuven in the research group Poverty and Social Inclusion. She is specialized in social policy, more precisely in the topics of poverty, social protection, social inclusion, migration, and political trust. She has published in journals such as the Journal of Computational Social Science, Social Science Research, and Social Indicators Research.

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