Fiscal resilience, fiscal sustainability and social infrastructure expenditure: the impact of social spending on fiscal health in Austrian local governments Open Access

Amidst multiple crises over the past decades, the stability of public finances has become a priority for governments. In this context, two key concepts have gained prominence: financial resilience and fiscal resilience of government budgets. Financial resilience focuses on broader financial health and management strategies to mitigate and respond to pressures during times of crises (Barbera et al., 2017). In contrast, fiscal resilience involves ensuring a balanced relationship between revenues and expenditures while adapting to changing fiscal conditions, such as fluctuations in tax revenues or shifts in intergovernmental funding (Getzner and Bröthaler, 2021; OECD and The World Bank, 2019).

Although fiscal resilience is crucial for managing short-term shocks, it represents only one dimension of a government’s overall fiscal health. A thorough fiscal framework also relies on long-term fiscal planning, efficient revenue generation and debt management (Bröthaler et al., 2015). While fiscal resilience refers to the short-term capacity to withstand economic shocks, fiscal sustainability relates to the “(…) long-run capability of a government to consistently meet its financial responsibilities” (Chapman, 2008, p. 115). Although fiscal resilience and fiscal sustainability differ in terms of their temporal dimensions, they are inherently linked (ibid.). Fiscal resilience allows governments to absorb and adapt to economic shocks without compromising essential services. If governments fail to manage short-term crises effectively, they may resort to unsustainable practices, such as excessive borrowing or severe austerity measures, which can undermine longer-term fiscal sustainability.

The fiscal resilience of local governments directly affects residents’ access to essential public goods and services, especially during crises (Narbón-Perpiñá et al., 2019). Local investments in areas such as healthcare, education and social services not only support inhabitants during crises but also contribute to long-term economic stability and well-being (Gumede et al., 2024) and, therefore, may reduce pressures on public budgets. Furthermore, fiscal resilience is shaped not only by local conditions but also by spatial dependencies and interactions between neighboring municipalities (Brueckner, 2003). Public investments often generate spillover effects that benefit surrounding areas (Getzner, 2022; López et al., 2017), potentially strengthening regional capacities to manage crises. These interdependencies add a spatial dimension to fiscal resilience and emphasize the importance of considering the broader regional context when evaluating the fiscal health of local governments. Yet the role of social infrastructure expenditure and spatial dependencies remains underexplored in the literature. This gap limits understanding of how public social investments and regional contexts, rather than administrative boundaries, shape local governments’ vulnerability during crises and their post-crisis stability.

This study examines the relationship between the fiscal resilience of Austrian local governments during the 2007/2008 financial crisis and their subsequent fiscal sustainability, together referred to as fiscal health. While existing literature recognizes the connection between short-term fiscal resilience and longer-term fiscal sustainability (Honadle et al., 2003), the specific impact of resilience during the 2007/2008 crisis on post-crisis sustainability remains insufficiently explored. Additionally, while the drivers of fiscal resilience and sustainability are well-established, this study highlights two critical yet underexplored factors: social infrastructure expenditure (i.e. expenditure on education, health and social protection) and spatial dependencies. These factors are fundamental in exploring the extent to which fiscal health is shaped by influences beyond direct fiscal policies and decisions.

In short, this paper aims to answer the following research questions:

1. To what extent did social infrastructure expenditure and spatial dependencies among municipalities influence fiscal resilience during the financial crisis of 2007/2008?

2. What is the relationship between fiscal resilience during the financial crisis of 2007/2008 and fiscal sustainability in its aftermath, and how did spatial dependencies and social infrastructure expenditure influence fiscal sustainability?

The remainder of the paper is structured as follows: The next section provides a brief literature review regarding the definition and measurement of fiscal resilience and fiscal sustainability. Empirical studies of the determinants of local government fiscal resilience are reviewed in Section 3. Section 4 gives a short overview of Austria’s institutional fiscal framework. The dataset and several descriptives are presented in Section 5. The methodological framework is described in Section 6, while the results of the econometric analyses are given and discussed in Section 7. The results are summarized, and conclusions are drawn in Section 8.

Resilience has become a growing research area in many academic fields. The term resilience originates from physics but was soon applied in ecology, where resilience is often seen as “the capacity to respond to stresses […] from external (including human) sources” (Perrings et al., 1997). As resilience approaches have gained prominence, the resilience of government budgets, encompassing both financial and fiscal aspects, has received increasing research attention (Ahrens and Ferry, 2020).

While financial and fiscal resilience are interrelated and often used interchangeably in the literature, they tend to focus on different aspects of local governments’ resilience. Financial resilience is seen as the broader capability of governments to implement various strategies for maintaining financial stability, whereas fiscal resilience focuses primarily on preserving fiscal balance and ensuring expenditure flexibility. In this regard, fiscal resilience can be understood as “[…] the ability of a local entity to demonstrate quick recovery from economic shocks with minimal disruption to core service commitments” (Rao et al., 2023, p. 1). However, Papenfuß et al. (2017) note that financial resilience “encompasses both the anticipatory capacity to set early counter-measures, as well as the rapidity of returning to a stable or even a more favorable point” (p. 117). A forward-thinking and proactive approach is equally crucial for fiscal resilience, as it strengthens a government’s ability to recover swiftly, prevent long-term fiscal instability and protect public welfare (Hochrainer-Stigler et al., 2023).

The operationalization of fiscal resilience is challenging, partly due to its varied definitions, leading to a variety of measures and indicators used to study similar phenomena under different terms. Wόjtowicz and Hodžić (2022), for example, use the debt-to-revenue ratio as a measure of financial resilience, which, given its focus on fiscal indicators, could also be considered a proxy for fiscal resilience. Lee and Chen (2022) study fiscal sensitivity, where the lagged value of expenditure of a local authority in a given year is normalized using the average lagged value expenditure of all local authorities in that same year. Based on an indicator used by the Indonesian government, Desdiani et al. (2022) calculate a fiscal capacity index using the total revenue and deduct mandatory as well as allocated spending. Klimanov et al. (2020) compute a fiscal resilience index for Russia’s regions by combining various factors, including per capita gross regional product, regional unemployment rates and the proportion of individuals earning below the living wage. Tests of fiscal resilience also include the estimation of reaction functions of policymakers, for instance, whether the primary surplus reacts to increased debt levels (Neck and Getzner, 2001).

A concept closely related to fiscal resilience is fiscal sustainability. While the former refers to the ability of a government to mitigate and adapt to sudden financial shocks, the latter defines a more long-term stability of government budgets (Chapman, 2008). Fiscal sustainability is therefore concerned with intergenerational equity (Rodríguez Bolívar et al., 2016). This perspective is central since intergenerational equity ensures that the fiscal obligations or pressures of the present do not disproportionately burden future generations. Although fiscal resilience and fiscal sustainability are closely connected, understanding their relationship remains essential for several reasons. Not all governments that demonstrate high fiscal resilience during a crisis necessarily achieve fiscal sustainability in the aftermath (see, e.g. Alessi et al., 2020). Studying fiscal resilience during the financial crisis and fiscal sustainability afterward is particularly important because the longer-term impacts of short-term resilience strategies can sometimes be counterintuitive. For instance, municipalities that demonstrated high fiscal resilience during the crisis by drawing heavily on reserves or increasing debt to maintain services may have faced greater fiscal challenges in the aftermath, as their strained resources or heightened financial obligations undermined their longer-term fiscal sustainability (Cepiku et al., 2016; Korac, 2017). Empirically testing the relationship between these two dimensions is therefore critical. It allows to assess which resilience strategies support, and not compromise, fiscal health over time and helps identify approaches that balance the need for immediate stability with the principles of intergenerational equity.

To measure fiscal sustainability, the “adjusted income” approach has been suggested, where financial income is adjusted according to income and expenditure for extraordinary activities (Rodríguez Bolívar et al., 2016). Others use a set of variables (e.g. financial liabilities, debt and surplus) to construct an indicator measuring fiscal sustainability (Dollery and Crase, 2006). In a similar vein, the European Commission (2022) has suggested three indicators comprising fiscal and socioeconomic variables to measure the short-term, mid-term and long-term sustainability of public finances.

In this study, we utilize the operational revenue-to-expenditure ratio ^[1] as a proxy for fiscal resilience. We use this ratio for two main reasons. First, covering both the revenue and expenditure sides of fiscal capacity, the revenue-expenditure ratio serves as a proxy for municipalities’ ability to maintain service provision and fiscal flexibility in the short term. Second, a higher ratio before a crisis can be a vital tool in enhancing a government’s ability to combat unexpected financial pressures, reducing its vulnerability to sudden changes in expenditure or revenue levels. This is important, as effective provision of goods and services is essential for meeting the needs of residents during times of economic decline. Following this, fiscal resilience is defined as the capability of a municipality to achieve or exceed pre-crisis levels of its operational revenue–expenditure ratio, whereas fiscal sustainability is operationalized as the three-year moving average ^[2] of the operational revenue–expenditure ratio, emphasizing longer-term fiscal health.

Recent crises have exerted immense fiscal pressure on governments. However, research shows that depending on institutional arrangements as well as existing resources and capabilities, governments differ in their scope and leeway to deal with the consequences of these crises. Examining the different ways in which governments are able to maintain sound public finances has therefore become a much-studied area of academic research (e.g. Barbera et al., 2020; Medir et al., 2017). This review briefly examines more general determinants of fiscal resilience and sustainability, with a stronger focus on the role of social infrastructure expenditure.

A substantial portion of the literature concentrates on the broader concept of financial resilience. Accordingly, many studies analyze local governments’ adaption behavior and strategies to deal with external shocks (Barbera et al., 2016, 2020; Mitchell et al., 2021; Papenfuß et al., 2017). Barbera et al. (2016), for instance, highlight that depending on past policies and strategies, municipalities adopt different coping mechanisms in times of budgetary constraints. This is also echoed in a study by Korac (2017), who finds that Austrian municipalities’ financial resilience is threatened by low fiscal autonomy. In a Dutch case study, Overmans (2017) reaches a similar conclusion, emphasizing the importance of autonomous financial decision-making of local authorities and higher freedom regarding their own income generation.

Wόjtowicz and Hodžić (2022) find that the total revenue as well as surplus levels, plays a central role in maintaining a low debt-to-revenue level in Croatian and Polish cities. This is also emphasized by Lee and Chen (2022), who, for example, find that own-source revenues and non-tax revenues increase the financial resilience of US states. Conversely, Ji et al. (2016) stress that intergovernmental grants positively affect a region’s fiscal sustainability, as they are less dependent on volatile own-tax incomes. In a similar vein, Klimanov et al. (2020) argue that financial independence of lower government levels on national grants might harm regional budgets in phases of economic downturn, as these regions might be more exposed to the negative consequences of economic instability.

However, public finances are not only influenced by fiscal decisions, policies or financial management practices. For instance, Barbera et al. (2017) find that local governments face an additional burden to maintain financial resilience when social and demographic pressures persist for a longer time. Accordingly, a declining population can strain local budgets as the revenue base decreases while social needs (e.g. care) might increase. In addition, municipalities facing higher unemployment rates, especially in times of crisis, may be less able to mitigate financial shocks as they may have a smaller tax base. This may be particularly the case for municipalities that generate a lot of their own revenue but have to lay off staff due to financial stress (Desdiani et al., 2022). Other socioeconomic variables that influence fiscal outcomes and may thus drive or restrict fiscal health are the number of people under 16 (Rodríguez Bolívar et al., 2016), the share of elderly people (De Widt, 2021) or the level of income of residents (Pereirinha and Pereira, 2021). Finally, human capital may be a driver of financial and fiscal resilience, as municipalities with higher human capital may be less vulnerable to economic shocks and able to recover more quickly from them (Wang and Li, 2022).

Given the potential adverse impacts of socioeconomic pressures on public budgets, social infrastructure expenditure has been identified as a possible mediator (Deléchat et al., 2018; Lahiani et al., 2022; Wang et al., 2023). Social infrastructure encompasses the services and institutions that sustain and enhance human development and societal well-being (Renner et al., 2024). In this paper, social infrastructure is more narrowly defined to include only education, health and social protection because these sectors represent the most substantial components of social expenditure in local government budgets. Respectively, expenditure on these types of social infrastructure strengthens individuals’ capacities by improving access to essential services, reducing inequalities and fostering social cohesion (Klinenberg, 2018). For instance, access to education enhances workforce productivity and long-term economic output (Coronel and Díaz-Roldán, 2024; Mercan and Sezer, 2014), while effective healthcare systems improve public health and reduce associated costs (Linden and Ray, 2017; Raeesi et al., 2018). By reducing the severity of social and economic disruptions, social infrastructure expenditure could enhance fiscal resilience by alleviating short-term fiscal pressures and support fiscal sustainability by preserving a government’s long-term fiscal capacity. This also promotes intergenerational equity, central to fiscal sustainability, by ensuring that future generations are not burdened with excessive fiscal strain.

Moreover, the literature to date mostly lacks a spatial perspective on fiscal health, even though it has been highlighted that public finances exhibit spatial dependencies (e.g. Case et al., 1993; Rios et al., 2017). Spatial dependencies may occur due to several reasons. First, decision-makers in one municipality (i.e. municipality 1) may encounter multiple incentives to decrease or increase their spending. On the one hand, a neighboring municipality (i.e. municipality j) could offer infrastructures and public services to the whole region as a “central place” or due to the economies of scale and scope of certain infrastructural systems (Bel and Warner, 2015). As a result, municipality i might be able to reduce its spending and free-ride (López et al., 2017). On the other hand, the residents of municipality i may compare the delivery of public services (quality and quantity) with that of municipality j. Consequently, decision-makers in municipality i may face competition and have an incentive to adjust spending (Di Liddo and Giuranno, 2016). Second, municipality i could face fiscal shocks similar to those of municipality j due to potential similarities in their economic and fiscal circumstances. Third, local governments might make their fiscal decisions based on decisions made in neighboring municipalities (Guo and Wang, 2017) or draw insights from similar experiences (Mitchell et al., 2021).

Reviewing the literature highlights three key gaps. First, there is a limited body of research examining the role of social infrastructure expenditure in enhancing both short-term fiscal resilience and longer-term fiscal sustainability. Second, most studies fail to account for spatial dependencies in understanding fiscal outcomes, potentially missing and biasing results. Third, most studies examine either short-term resilience or long-term sustainability in isolation, overlooking the dynamic interplay between the two. To address the gaps in the literature based on this theoretical framework, two separate spatial models are employed to analyze the role of social infrastructure expenditure in enhancing both fiscal resilience and sustainability, with particular emphasis on their interconnections.

Figure 1 shows the theoretical framework built on the literature review and areas where empirical evidence remains limited. Accordingly, we understand fiscal health as two interlinked components: fiscal resilience, defined as the ability of local governments to absorb and adapt to fiscal shocks with minimal short-term disruption and fiscal sustainability, understood as the capacity to maintain balanced fiscal operations after a crisis. We hypothesize that fiscal resilience is a necessary precondition for sustainability: municipalities which recover more quickly from fiscal shocks are more likely to sustain a stable fiscal performance over time. However, short-term recovery strategies can create long-term risks. Accordingly, measures that stabilize finances during crises, such as reserve depletion, deferred investments or debt accumulation, may undermine long-term fiscal health (see, e.g. Burriel et al., 2020; Calcagno, 2012; Jacques, 2021).

While these strategies represent immediate fiscal responses (see, e.g. Kim and Warner, 2021; Ladner and Soguel, 2015), we extend the analysis by examining how two other factors shape both short-term fiscal resilience and long-term sustainability: social infrastructure expenditure and spatial dependencies. Social infrastructure expenditure reflects investments in core welfare services (e.g. education, healthcare and social protection). While these expenditures may constrain immediate fiscal flexibility during a crisis, they can also enhance resilience by reducing social pressures and ensuring service continuity. In the longer term, these investments can boost human capital, lower individuals’ exposure to economic risks and reduce future demands on public budgets (see, e.g. Chzhen, 2017; Ötker-Robe and Podpiera, 2013; Prasad and Gerecke, 2010). Spatial dependencies capture how local governments are influenced by neighboring jurisdictions (i.e. through economic linkages, shared policy environments or mimetic behavior). In the short term, these interdependencies can increase or buffer crisis impacts depending on regional dynamics. In the long term, they may affect fiscal sustainability by shaping collective policy norms, competitive pressures or access to shared resources and administrative capacity (see, e.g. (Ferraresi et al., 2018; Piedra-Peña et al., 2024; Ter-Minassian and Fedelino, 2010)).

Fiscal health not only entails maintaining an equilibrium between revenue and expenditure but also extends to the structure of revenue generation and fund allocation as well as the autonomy of local governments to make fiscal decisions (Barbera et al., 2017; Rao et al., 2023). Austrian municipalities assume different responsibilities regarding local goods and service provision. These responsibilities can be broadly categorized into three domains. First, municipalities are entrusted with mandatory tasks encompassing essential services. Second, discretionary tasks allow municipalities some leeway in decision-making. Last, expenditures often align with the preferences of local citizens, resulting in significant variations in spending priorities among municipalities (Mitterer et al., 2016). Within this framework, the funding of municipalities is composed of three primary revenue streams:

1. Obligatory functions are financed through a share of federal taxes, allocated basically on a per capita basis.

2. For specialized tasks or financial pressures, additional funds are allocated to municipalities to alleviate specific fiscal stresses and fund specific projects.

3. Autonomous revenue generation occurs through local taxes, such as payroll and property taxes, along with utility fees for municipal services like water and wastewater management.

However, the operational reality exceeds this legal framework. On the one hand, Austria’s institutional structure may affect fiscal resilience by restricting decision-making flexibility, as municipalities are often dependent on higher levels of government for funding and policy direction. This constraint could influence the ability of municipalities to respond promptly to unforeseen economic shocks. On the other hand, some municipalities might be able to cope better with financial distress, as their financial leeway is higher due to higher local tax revenues. Moreover, empirical evidence suggests that spending behaviors of neighboring municipalities can interdependently shape financial strategies (Rios et al., 2017), underlining the significance of spatial influences on fiscal health. Thus, despite the legal regulations regarding local government revenue and expenditure, fiscal health might vary vastly in Austria due to demographic, socioeconomic and fiscal-political factors.

To estimate the fiscal resilience and fiscal sustainability of Austrian municipalities, a comprehensive dataset spanning from 2004 to 2022, encompassing fiscal, economic and social variables for 2,093 municipalities, is utilized. The data are obtained from Statistics Austria. More details on the variables can be found in Table 1.

To examine regional differences in fiscal resilience, the annual change in the mean revenue-expenditure ratios for the eight provinces ^[3] spanning from 2004 to 2022 is shown in Figure 1. A pronounced decline in the ratios is observable starting in 2007 across all provinces, coinciding with the start of the financial crisis. The decrease observed from 2007 to 2008 showed variability across provinces, ranging from −1.6% for Lower Austria to over −4 percent for Burgenland and Carinthia. Notably, Upper Austria and Salzburg were exceptions, as they did not undergo a decline during this period. However, all provinces experienced a decrease in their revenue-expenditure ratio from 2008 to 2009, with the extent ranging from −5.6% for Tyrol to −9.7% for Carinthia. Following the crisis years, although there was an overall upward trend in the mean ratio for all provinces, the degree of increase varied among them. Accordingly, only two provinces surpassed a ratio above zero until 2011. Upper Austria was the only province sustaining a ratio higher than zero for an extended period before experiencing a decline in 2020, along with all other provinces, which marked the start of the COVID-19 pandemic.

Before discussing the findings of the econometric exercise, it is advantageous to examine temporal differences in the duration municipalities took to attain or surpass pre-crisis levels of their operational revenue-expenditure ratio. Table 2 shows that nearly 20% of municipalities achieved recovery within two years following the onset of the crisis, with approximately half achieving this within four years. Interestingly, close to 20% of municipalities only attained recovery by 2021, marking the first year after the COVID-19 pandemic outbreak. An additional 1.4% either recovered after 15 years or failed to do so by 2022. Consequently, these municipalities did not reach their pre-crisis levels by 2022. These figures, however, do not provide insights into whether municipalities maintained pre-crisis levels over an extended period. It remains plausible that after recovery, municipalities experienced a decline in their revenue-expenditure ratio in subsequent years.

To account for unobserved spatial dependencies, this paper employs a spatial approach in the econometric exercise. The methodological approach comprises three sequential steps: (1) First, an analysis is conducted to examine the determinants influencing municipalities’ hazard concerning the effects of the financial crisis, employing a Bayesian Cox Proportional-Hazards Model. (2) Following this, the risk factor and survival probabilities for each year during the financial crisis (2008–2010) are predicted based on the Cox-Proportional Hazards Model outcomes. (3) These predicted values are then incorporated into a Spatial Durbin Model ^[4].

To estimate the ability of municipalities to bounce back or forward concerning their operational revenue-expenditure ratio (i.e. fiscal resilience), we use a Bayesian Cox Proportional-Hazards Model. The model estimates the effect of independent variables on the hazard function (i.e. the probability of “surviving”). More specifically, the Cox-Proportional Hazards Model focuses on event time modeling, analyzing the duration until a particular event occurs. In this paper, the time to an event is the time it takes for municipalities to recover to pre-crisis levels (bounce back) or the time it takes for municipalities to reach a higher revenue-expenditure ratio than before the crisis (bounce forward). To this end, the hazard function of the Cox Proportional-Hazards Model can be written as follows:

where $hi(t)$ is the hazard function for municipality i and $i={1,…,n}$ with n being the total number of municipalities, $h0(t)$ is the baseline hazard function, $β$ is a vector of regression coefficients associated with covariates and $Xi(t)$ is the vector of covariates for the i-th municipality at time t, with $Xi={Xi1,…,Xik}$ for the $k={1,…,K}$ covariates.

However, the model in Equation (1) assumes that the fiscal resilience of municipality i is independent of unobserved spatial characteristics. To account for the potential effects of space, we use a Spatial Bayesian Cox-Proportional Hazards Model. This is done by introducing $υi$ into the model, which indicates the spatial frailties for all municipalities. To estimate $υi$⁠, an adjacency matrix $E=[eij]$ is created where $eij=1$ if municipality i and j share a common border and $eij=0$ otherwise. Municipalities are not assumed to be a neighbor to themselves, and thus $eii=0$⁠. The spatial frailty is then estimated using an intrinsic conditional autoregressive prior, which is frequently used to model spatial dependencies (Held and Rue, 2010). Equation (1) can then be rewritten as

with the prior for $υi$⁠:

where $ei+$ is the number of all neighbors of municipality i, and $τ2$ is the variance parameter.

For the estimation process, we follow the approach outlined by Zhou and Hanson (2018), who utilize a Markov Chain Monte Carlo (MCMC) algorithm to estimate the posterior density of the coefficients ^[5]. For details on the estimation, see Zhou and Hanson (2018).

To examine the relationship between fiscal resilience and fiscal sustainability, the results from the Spatial Bayesian Cox-Proportional Hazards Model are utilized to estimate the level of fiscal resilience exhibited by each municipality during the crisis (2008–2010). By forecasting survival probabilities and risk factors during the financial crisis, valuable insights into the potential vulnerability of municipalities after the crisis can be gained. These predicted values may represent the ability of municipalities to better anticipate or manage fiscal crises. First, the survival probability for each municipality is calculated for the years 2008–2010, which represents the likelihood that a municipality will recover from the impact of the financial crisis during these years:

Second, risk scores (RS) for all municipalities for the years during the crisis are predicted. A higher risk score suggests a greater vulnerability to the financial crisis based on the characteristics of the municipality:

where the risk factor is the exponentiated sum of the linear predictor. Following this, municipalities are categorized into risk terciles: the top third of municipalities based on their mean risk factor for the years 2008–2010 are labeled as the “high risk” group, the bottom third as the “low risk” group and the remaining municipalities fall into the “medium risk” group.

In the third step, we analyze the link between fiscal resilience and fiscal sustainability as well as other drivers of fiscal sustainability. To address the potential presence of spatial spillovers, we employ a Spatial Durbin Model. The primary objective of the model is to examine whether municipalities that demonstrated greater fiscal resilience during the financial crisis are able to maintain better fiscal health in the aftermath of the crisis. To this end, we first calculate the three-year moving average of the percentage change of the revenue-expenditure ratio, which is then used as the dependent variable (fiscal sustainability) in the Spatial Durbin Model. The model is defined as

where $yit$ is the three-year moving average of the percentage change of the revenue-expenditure ratio for municipality i at time t, $ρ$ is the spatial autoregressive parameter and W is the row-standardized spatial weights matrix based on the queen contiguity concept. $Xit$ is a vector containing the exogenous variables for municipality i at time t and $β$ is a vector of the respective coefficients and $θ$ refers to the indirect spillover effects. $εit$ is the normally distributed error term for municipality i at time t.

To estimate Equation (6), we adopt the methodology introduced by Leorato and Mezzetti (2016), which presents a hierarchical Bayesian model designed for spatial panel data analysis. In their study, the authors propose an approach to decompose the covariance matrix of the dependent variable into separate matrices representing temporal and spatial dependence. Specifically, they utilize a Kronecker product of the temporal and spatial covariance matrices, thereby effectively capturing both spatial and temporal dependencies present in the data. Equation (6) is transformed into a hierarchical linear model with the following specifications:

where $μ=(μ1′,…,μT′)′$ is a vector including spatial and time random effects, $Ψ$ refers to the temporal and $Φ$ to the spatial covariance matrix.

MCMC techniques and Gibbs sampling are employed to iteratively draw samples from the joint posterior distribution of model parameters. For details regarding the estimation procedure, readers are referred to Leorato and Mezzetti (2016).

The first part of the analysis concentrates on the determinants of fiscal resilience (i.e. the capability of municipalities to reach or exceed pre-crisis revenue-expenditure ratios). Table 3 presents the results from the Bayesian Cox Proportional Hazards Model.

So far, a broader perspective on the role of social infrastructure expenditure remains largely overlooked. Consequently, this analysis primarily focuses on socioeconomic drivers and social infrastructure expenditure, with other determinants discussed more briefly. Table 3 suggests that municipalities with diversified revenue sources, particularly higher self-generated income like property taxes, exhibit stronger fiscal resilience and recover more effectively from financial crises. While intergovernmental transfers help absorb economic shocks (Fabbrini, 2013), reliance on them can weaken recovery post-crisis, as funding often declines (Scharff, 2020). Interestingly, greater financial leeway appears to reduce resilience, potentially because municipalities with larger surpluses adopt risk-averse strategies, prioritizing reserves over proactive investments. As Barbera et al. (2017) argue, financial resilience depends not just on surplus levels but on how resources are allocated to address vulnerabilities and enhance long-term stability.

In this regard, Table 3 indicates that social infrastructure expenditure may be a mitigator of such vulnerabilities. This may be attributed to education and healthcare leading to a more skilled and healthier workforce, which in turn enhances productivity and drives economic and social resilience (see, e.g. Beylik et al., 2022; Yardimcioglu et al., 2014). Furthermore, social assistance programs provide a safety net for vulnerable groups, which may mitigate the adverse effects of economic downturns (Kiendrebeogo et al., 2017). This, in turn, may help to prevent fiscal strain resulting from, for example, increased demand for public services.

Moreover, these findings suggest that social infrastructure expenditure can increase fiscal resilience, even if higher investments result in a decline in reserves. In this regard, Barbera et al. (2017) emphasize the crucial role of local governments’ ability to self-regulate in fostering financial resilience, particularly when budgetary positions remain low over time. This self-regulation is linked to the development of strong anticipatory and coping capacities, allowing governments to effectively adapt to fiscal shocks despite limited fiscal flexibility. In this context, the positive relationship between fiscal resilience and social infrastructure expenditure suggests that investments in areas such as education, healthcare and social protection can help mitigate vulnerabilities. These investments may enhance local governments’ adaptability, acting as a stabilizing force even in municipalities with constrained fiscal leeway.

The importance of the mediating effects of social infrastructure expenditure is also evident in the impact of various socioeconomic factors on fiscal resilience. For instance, a municipality’s unemployment rate reduces the capability required for municipalities to bounce back or forward, as can be seen by the negative mean coefficient in Table 3. As unemployment rates rise, individuals increasingly depend on public assistance and infrastructure while also being excluded from the labor market. This dual impact not only diminishes the tax revenue base but also potentially undermines the longer-term fiscal recovery of municipalities. Although unemployment benefits are provided by the public unemployment insurance system and are, hence, a national transfer, the results suggest that unemployment also affects the financial burden carried by municipalities. In contrast, a higher average income of residents in a municipality increases municipalities’ fiscal resilience, as indicated by the mean coefficient for average income being significantly different from zero in Table 3. As individuals have higher incomes, they might be more likely to allocate financial resources for economic downturns. This can be crucial when local governments face an economic shock and, hence, for example, cut back on public goods and services (Bufe et al., 2022).

Furthermore, Table 3 shows that both the population size and population change positively affect fiscal resilience. This can be an indication of the fiscal strength of larger and growing municipalities. As municipalities mostly receive their revenue based on their population within the fiscal equalization system, which allocates money generated by taxes from the national to subnational level, municipalities that have more inhabitants might have a stronger revenue base. While population growth also increases the spending for municipal infrastructures, it often brings economic benefits in terms of economies of scale, scope and density (Prieto et al., 2015). This mechanism might pose a challenge to smaller municipalities or municipalities that experience a population decline, which may receive proportionally less funding based on their smaller populations.

Along with the role of social infrastructure expenditure, this study focuses on the potential spatial dependencies of fiscal health. Figure 2 displays the posterior mean frailties across all municipalities. Spatial frailties introduce random effects into the analysis, capturing unobservable variations in the data. In this context, greater frailties indicate areas, where municipalities are slower to recover. This underscores the pronounced clustering of fiscal resilience, notably evident in the northern and western regions where municipalities exhibit low fiscal resilience, possibly due to underlying regional attributes or budgetary decisions. Consequently, regions marked by higher frailties may necessitate targeted assistance or tailored policies to accelerate the recovery trajectory and encourage fiscal resilience. This finding emphasizes the importance of contextual approaches to public sector risk management (see, e.g. Bracci et al., 2021). The identified spatial frailties further illustrate how localized vulnerabilities can amplify fiscal risks in ways that may not be fully captured by conventional fiscal metrics. This underscores the need for risk assessment frameworks that incorporate spatial and contextual factors to enhance the resilience of public finances (see Figure 3).

The subsequent part of the analysis delves into the fiscal sustainability of local governments after the financial crisis. This involves examining the determinants that impact fiscal sustainability (the three-year moving average of the percentage change in the revenue-expenditure ratio) using a Spatial Durbin Model. In addition to the covariates already integrated into the Cox-Proportional Hazards Model, three additional factors are incorporated into the Spatial Durbin Model: (1) the mean survival probabilities for the years 2008–2010, (2) the risk group (derived from the risk scores of each municipality) and (3) the duration (in years) it took municipalities to restore pre-crisis revenue-expenditure ratios. Table 4 presents the results of the Spatial Durbin Model.

The analysis highlights the critical relationship between fiscal resilience during crises and the longer-term fiscal sustainability of municipalities. As demonstrated in Table 4, municipalities that exhibited stronger fiscal resilience were significantly more capable of maintaining fiscal sustainability in the aftermath of economic shocks. This underscores that resilience is not only merely about short-term recovery but also about establishing the foundation for sustained fiscal health (Gorina et al., 2018). Municipalities with higher risk scores, indicating greater vulnerability to economic downturns, tend to struggle more with restoring fiscal health. In contrast, those with higher survival probabilities and shorter recovery times demonstrate greater adaptive capacity, allowing them to rebound efficiently. This highlights that the ability of governments to respond to immediate shocks forms the basis for long-term fiscal sustainability, as adaptive responses can help creating the flexibility and institutional capacity needed to manage future pressures (Afonso et al., 2023; Afonso and Coelho, 2024). Ultimately, these patterns demonstrate that resilience is not merely a reactive mechanism but a strategic investment in long-term fiscal health. Recognizing the interconnected nature of resilience and sustainability is essential for identifying factors that can reduce municipal vulnerability both before and after crises, fostering a more proactive approach to fiscal governance (Forni et al., 2018).

Beyond fiscal resilience during the crisis, post-crisis fiscal conditions play a crucial role in longer-term sustainability. Table 4 shows that higher debt levels weaken fiscal sustainability, while greater fiscal reserves enhance it (e.g. by enabling proactive investments (Leeper et al., 2010)). This financial stability may create opportunities for strategic spending. In this regard, our findings indicate that municipalities with higher social infrastructure expenditure post-crisis tend to show greater fiscal sustainability, potentially highlighting the role of perceived vulnerability and a municipality’s preparedness for economic shocks (see, e.g. Agyemang et al., 2023; Barbera et al., 2017, 2020). Our results suggest that while social infrastructure spending reduces immediate fiscal flexibility, it may enhance longer-term sustainability by preparing governments for future crises, minimizing the need for costly emergency measures. In this context, the concept of path dependency plays a significant role (see, e.g. Padovani et al., 2024). Accordingly, governments with a history of underinvesting in social infrastructure may be trapped in persistent vulnerabilities, facing rigid expenditure patterns and systemic constraints.

Furthermore, various demographic and socioeconomic factors affect fiscal sustainability. For example, local unemployment exerts a negative influence on a municipality’s fiscal sustainability, as reflected by the negative mean coefficient for the unemployment rate in Table 4. As already argued, unemployment often coincides with increased demand for social welfare programs (Saunders, 2002). Additionally, the dependency ratio poses a challenge to fiscal sustainability. This stands somewhat in contrast with Prescott and Gjerde’s (2022) findings that a higher proportion of working-age individuals increases the risk of prolonged economic crises for local governments. In Austria, the strong welfare state may mitigate some of these risks, with national interventions such as short-time work programs absorbing immediate economic pressures. However, our findings suggest that unemployment and the proportion of dependents, rather than just the working-age population, are key factors affecting fiscal sustainability. A higher dependency ratio may decrease economic output and increase demands on social services, especially in the aftermath of a crisis (Auerbach, 2016; Gist, 2011).

Finally, fiscal sustainability demonstrates spatial dependencies, as demonstrated by the parameter $ρ$ in Table 4. This presence of spatial spillovers in fiscal sustainability highlights the interdependent nature of municipal fiscal sustainability, where fiscal conditions in one jurisdiction influence those in neighboring municipalities. Of particular relevance to this study are the spillover effects of social infrastructure expenditure and fiscal resilience variables. Table 5 presents the direct, indirect and total effects of these variables.

Accordingly, social infrastructure expenditure demonstrates significant direct, indirect and total effects, indicating that such investments generate benefits that extend beyond a municipality’s boundaries. If one municipality lacks sufficient social infrastructure, it may experience greater demand for social services, leading to higher fiscal strain within the whole region. However, when neighboring municipalities invest in social infrastructure, it alleviates pressure on their own resources by spreading benefits across multiple municipalities.

The spillover effects of fiscal resilience variables, including mean survival probability, risk group classifications and time until bounce back/forward, vary in magnitude and direction. Mean survival probability and risk group classifications primarily exhibit significant direct effects, suggesting that a municipality’s ability to withstand fiscal shocks influences its own sustainability but does not generate substantial spillovers to neighboring municipalities. In contrast, time until bounce back/forward exhibits significant direct, indirect and total effects, implying that the speed of fiscal recovery has broader regional consequences. Municipalities that recover more quickly not only stabilize their own finances but also contribute to regional fiscal sustainability. Conversely, municipalities experiencing prolonged fiscal distress may generate negative spillovers by, for example, increasing social service demands.

Municipalities with objectively stable financial positions may still perceive heightened fiscal risk if they are geographically close to jurisdictions with weaker fiscal health, emphasizing the impact of external conditions on local risk perception (Zhou and He, 2024). This risk is further amplified by external shocks or regional policy decisions, which can create spillover effects that directly affect their budgets (Solé-Ollé, 2006). Conversely, municipalities with limited financial flexibility or low reserves can reduce their perceived risk by engaging in regional collaboration, leveraging shared resources and benefiting from positive spillover effects (Tang and Wang, 2022). These findings highlight the need to incorporate spatial interdependencies into fiscal health and risk assessment frameworks. They also reinforce the idea that proactive fiscal policies, particularly long-term investments in social infrastructure, generate benefits that extend beyond individual municipalities, contributing to overall regional fiscal sustainability.

This study explores the factors influencing fiscal resilience and fiscal sustainability, with a specific emphasis on the influence of social infrastructure spending as a mediator in the face of economic shocks and post-crisis growth trajectories as well as the impacts of spatial dependencies. The analysis comprises two parts. First, the determinants of fiscal resilience of Austrian local governments during the financial crisis of 2007/2008 are analyzed using a Spatial Cox-Proportional Hazards Model. Second, using a Spatial Durbin Model, the drivers of fiscal sustainability after the crisis are examined. Both models focus on the mitigating effect of social infrastructure expenditure on fiscal health while accounting for the potential interconnectedness and spatial dependencies between municipalities.

The results of this study demonstrate that fiscal resilience and fiscal sustainability are inherently interconnected, shaped by both spatial and temporal dynamics. Resilience, particularly in the form of recovery speed, emerges as a critical mechanism through which short-term adaptive capacity influences longer-term fiscal health at both local and regional levels. This relationship is crucial because it challenges the notion that resilience is purely reactive and short-lived. Rather, it shows that how local governments respond to shocks can either reinforce or risk their fiscal health over time. Crucially, both fiscal resilience and sustainability are shaped by broader demographic and socioeconomic pressures as well as the social infrastructure expenditure. This extends existing research, suggesting that fiscal strength alone may not be enough to withstand economic shocks or maintain stable public finances. Instead, investing in social goods and services can reduce vulnerabilities during crises while also contributing to sustained fiscal health. Since fiscal resilience and sustainability are closely linked, these investments challenge austerity-driven approaches, which often cut social infrastructure during and after crises. Instead, social infrastructure investments play a critical role in enhancing risk management and enabling proactive adjustments before crises, which are essential for longer-term sustainability. Additionally, the observed spatial dependencies in fiscal health underline that fiscal resilience and sustainability extend beyond individual municipalities, emphasizing the broader regional context in maintaining or achieving fiscal health.

These findings have several policy implications. Firstly, policymakers should facilitate collaboration and coordination among neighboring municipalities to address mutual fiscal challenges. This entails enabling municipalities to pool resources, exchange best practices and devise joint strategies to strengthen fiscal resilience and sustainability. Local governments as well as higher government levels, must account for the spatial distribution of economic activities, infrastructure investments and resource allocation to mitigate adverse spillover effects and foster equitable fiscal outcomes. Moreover, recognizing the role of social infrastructure expenditure in enhancing fiscal outcomes, policymakers should prioritize such investments despite the associated costs, as their mitigating effects on fiscal pressures are essential for longer-term fiscal health.

Future research could examine whether the findings of this study hold true in the context of the COVID-19 pandemic, particularly by analyzing how fiscal resilience indicators influence different trajectories of fiscal sustainability. Additionally, given the spatial interdependencies of fiscal health, further studies could conduct a spatial heterogeneity analysis to assess variations in fiscal resilience and sustainability across different regions or clusters. Such an approach would help identify region-specific determinants of fiscal health, evaluate the role of localized factors and reveal potential differences in how spatial dependencies shape fiscal outcomes in diverse regional contexts.