Financialisation of everyday life: exploring socio economic behaviour in Southern European Countries

Financiarización de la vida cotidiana: Un análisis del comportamiento económico en los países del Sur de Europa

Nazaret Abalde nazaret.bastero@udc.es

., España

Pedro López-Roldán Pedro.Lopez.Roldan@uab.cat

., España

Matilde Massó m.masso@udc.es

., España

Financialisation is a process of change in the economic structure of contemporary societies, which reflects the growing importance of financial actors, markets and values in economic and social life. Specialized literature on financialization traditionally contemplates three levels of analysis: macro, meso and micro. In this article we will focus on the micro level, that is, on what is called the financialisation of everyday life. (Chiapello, 2015; Lai, 2018; Langley, 2008; Martin 2002). This concept refers to the process by which individuals develop practices, attitudes and subjectivities that connect them with the functioning of global financial markets to face various needs and risks in their daily life, through the management of their income, savings and forms of investment (see Chiapello, 2015; Langley and Leyshon, 2012). The financialisation of everyday life is associated with the individualization and privatization of the risks associated with different phases and aspects of individual’s life cycles. Thus, the responsibility for protection against risks of different nature is transferred from the State or community to the individual subject, through a complex of practices, values, discourses and economic attitudes that reproduce the characteristic principles of the functioning of financial markets.

The aim of this paper is to discuss some of the difficulties involved in measuring the financialization of daily life in Southern Europe, and to propose a multivariate modelling approach for estimating the importance of attributive variables to explain financialization. We use data from the second wave of the Household Finance and Consumption Survey (HFCS, 2016), conducted by the European Central Bank in the euro area.

More specifically, the article proposes an operational definition of the financialisation of everyday life as a process that is manifested in the following economic behaviors (see Abalde Bastero, 2022): a) willingness to assume financial risks and request credit for investments (Aalbers, 2008 ; Davis and Kim, 2015; Langley, 2008; Mulcahy, 2017); b) constant search for investment opportunities (Martin, 2002); c) individual management of risks and financial well-being (Langley, 2008; Watson, 2009); d) rational financial calculations in both economic and non-economic decisions (Aalbers, 2008; Davis, 2009; Martin, 2002); e) exercise of self-discipline and self-responsibility (Aalbers, 2008; Lazzarato, 2013); and f) permissive morality towards debt (Martin, 2002).

As we propose to analyse the process of financialisation in a quantitative and statistical framework, we have delimited the different dimensions of the concept to those observable facts that have been operationalised in the form of variables measuring attitudes towards economic risk. The article discusses various aspects related to the conceptualisation and operationalisation of the so-called financialization of everyday life, a non-systematic phenomenon that takes different forms in different cultures and political traditions. Additionally, we have analysed the degree of correspondence between Spain, Italy, Greece, and Portugal to determine how homogeneous the results between these countries are, and to what extent individuals’ financial behaviour shows similar patterns in the European periphery. We have carried out typological analysis combining Multiple Correspondence Analysis (MCA), in order to establish the social space in which to identify the main factors that structure socio-economic behaviour, and Cluster Analysis (CLA) where the four countries will be compared for this purpose and a general typology of the financialization of everyday life will be constructed, particularly for southern European countries.

The main contributions of this analysis are theoretical and empirical in nature. At the theoretical level, this paper provides crucial yet hitherto unavailable evidence for measuring financialization in four countries on the basis of the HFCS variables. In addition, the financialization of individual behaviour is operationalised and a comparative analysis is undertaken using survey data for the first time in the literature. A new theoretical and methodological research agenda is also proposed for analysing financialization, using individual-level and country data, from both a qualitative and quantitative approach.

The article is organised as follows: the second section develops the theoretical concepts that frame the study; the third section proposes a model of analysis for the study of the financialization of daily life in Southern Europe; the fourth section presents the results of the factor and typological analysis; and the fifth section summarises the conclusions of the research.

2.1. The Financialisation of Households

The concept of financialisation is very often used, but it lacks a definition that has been widely accepted by the academic community (van der Zwan, 2014). Financialisation can be defined as a complex and multi-dimensional relationship of interdependence between socio-economic actors -individuals, non-financial firms, and the state-, with financial markets (see Massó, Davis and Abalde, 2020).

Van der Zwan (2014) identified three uses of the term financialisation: financialisation at the macro level of the economy, financialisation at the meso level of firms, and financialisation at the micro level of households. All of them have in common a conception of finance whereby its primary function is no longer providing capital for the production economy, but the creation of money as an end in itself, through purely speculative exchanges that materialise from generating public and private debt (see Lazzarato, 2013). Financialisation refers therefore to the existence of an increasingly autonomous financial system that is growing more and more separate from the production economy (Aalbers, 2008). The expansion of this system has changed the centrality of analytical structures based on the capital-labour relationship (see Alonso and Fernández-Rodríguez, 2012) and even the functioning of democratic societies either partly or totally (see Harvey, 2007; Duménil and Lévy, 2014).

In this paper the focus will be on the micro meaning of the term, known as the financialisation of ‘everyday life’ (van der Zwan, 2014). Financialisation will therefore be understood as a process linked to the ‘emergence of new values related to the perception of risk’ (Massó and Pérez-Yruela, 2017: 107). These values are shaped by a new culture that socialises people into the world of finance (Chiapello, 2015), both through their participation in financial markets and through their continued exposure to images, values, metrics and messages related to consumption, investment, indebtedness, risk valuation, and other concepts characteristics of the financial sphere (Langley and Leyshon, 2012; Martin, 2002).

Household motivations and aspirations, have often been understood as a residual expression of structural changes in the global financial system. Nonetheless, researchers of everyday life are committed to this new approach that appreciates the various ways in which financial logic is integrated into the everyday life of citizens through pension plans, health insurance policies, life insurance policies, credit cards, personal loans, as well as home purchases in the mortgage market (Abalde, 2020; Chiapello, 2015; Martin, 2002; Sandel, 2013). The process of financialisation implies a ‘colonisation’ of everyday life, stimulating the entrenchment of financial values into the private sphere of the household (Chiapello, 2015) and the life cycle of individuals (Langley and Leyshon, 2012). This field of research not only analyses the financial situation and economic behaviour of individuals, but also seeks to understand the various representations of financial normativity through the symbols, perceptions, attitudes, and discourses that permeate the intimate space of the household (Bowsher, 2019; Lai, 2018).

For Aalbers (2008; 2017), the financialisation of households refers to how financial motivations are increasingly dominant, both in the way individuals and households are evaluated and in the way they make everyday decisions. As a result of the financialised economy, financial logic seeps into everyday life, and economic security is increasingly subject to the performance of global financial markets (Aalbers, 2008; Chiapello, 2015; Davis and Kim, 2015; Hacker, 2006). In a scenario of shrinking social protection spending, individuals are encouraged to participate in financial markets in search of security and protection against risks (Cutler and Waine, 2001). A growing process of individualisation of risk can be identified (Abalde, 2020) through the establishment of policies that reconfigure individuals as entrepreneurs who anticipate eventualities and manage their needs (Arthur, 2012; Brown, 2006, 2015; Hacker, 2006). It therefore involves them participating in markets in the same way as a company that manages its capital (Feher, 2009), and this capital is their health, old age, education, housing, leisure, and consumption. The following section analyses this process through individual attitudes towards risk.

2.2. Attitudes towards Financial Risk: Saving, Investment and Financial Literacy

In financialised societies, the risks faced by households are undergoing a gradual process of individualisation (Abalde, 2020). In the face of reduced socialised coverage of health and old-age expenditure, the risks involved in people’s life cycles are progressively becoming individual responsibilities (Dardot and Laval, 2015). Financialisation is not only related to the financial activities associated with global markets; it is also regarded as a new mode of subjectification through the individual assumption of risk as a dimension of existence (Dardot and Laval, 2015; Martin, 2002).

Numerous research studies have focused on the field of household finance and on individuals’ attitudes towards risk. A thorough review of the academic literature in this field has identified three main areas of research: one explores the relationship between financial literacy and attitudes towards investment (Campbell, 2006; Hilgert et al., 2003; Muñoz-Murillo et al., 2020); another one focuses on household money management and financial well-being (Antonides et al., 2011; Mitrut and Wolff, 2009; Porter and Garman, 1993); and the third strand analyses the socio-demographic and institutional determinants of attitudes towards economic risk (Baker et al., 2019; Bover et al., 2016; Eckel and Grossman, 2002; Farrar et al., 2019; Greig et al., 2019; Lin et al., 2019; Vale and Camões, 2015; van Rooij et al., 2007).

2.2.1. Financial Literacy and Risk Management

In the context of the financialised economy, the complexity of financial decisions made by households has reached a historically unprecedented level. The literature on the impact of financial literacy on household economic decisions shows that the degree of financial literacy is related to the socio-economic behaviour adopted (Muñoz-Murillo et al., 2020). Some studies have shown that people with sophisticated financial literacy tend to manage household money efficiently (Hilgert et al., 2003; Ward and Lynch, 2019). Other studies have reported that a lower level of financial literacy leads to conservative investment behaviour, including avoidance of financial risk (Christelis et al., 2010). Research has also suggested that cognitive ability, understood as the ability to process information in pursuit of an end result, is one of the key factors in explaining the level of financial literacy (Muñoz-Murillo et al., 2020).

The relationship between financial literacy and financial planning for retirement has been examined with particular attention. Lusardi and Mitchell (2010; 2017) showed that, in the context of US society, those who are financially literate are more likely to financially plan and manage their retirement. However, the authors also pointed to the respondents’ ability to save as being a factor. In a political era in which individuals and households are expected to take increasing responsibility for their own retirement, it is noticeable that many citizens do not have an adequate savings fund as they approach retirement (Lusardi and Mitchell, 2010; 2017). Van Rooij et al. (2011) have also analysed the relationship between financial literacy and financial planning for retirement. Their findings revealed that most of the members of the households surveyed did not understand fundamental financial concepts. In addition, large differences in financial literacy were found according to the socio-demographic characteristics of the respondents. Research by van Rooij et al. (2007) also suggested that respondents lack the necessary skills to make investments taking their retirement into account. The average respondent describes themselves as having an unsophisticated level of financial knowledge and is reluctant to take control of the investment of their retirement savings.

2.2.2. Household Money and Savings

Money is used to assess the magnitude of the value of a good or service. As such, it establishes a numerical price that condenses and summarises its value (Simmel, 2013). But money is also similar to language: money speaks, it has its own lexicon and meaning (Carruthers and Ariovich, 2010). As a medium of exchange, it establishes a two-way relationship in the context in which it operates. By embedding the money mechanism into a given structure, social imperatives shape how money is used, and the meanings attached to each use (Carruthers and Ariovich, 2010). ‘People employ money as a means of creating, transforming and differentiating their social relations’ (Zelizer, 2015: 126). The meaning given to money is transmuted in every relation and activity, establishing different categories of money. Their origin has an impact on their meaning and therefore also on the purpose for which it is used. Individuals categorise and divide household income, assigning a specific purpose and label to each spending category. In this way, they manage money according to mental budgets (Heath and Soll, 1996), as a strategy for saving and self-control.

Research by Antonides et al. (2011) showed that a household’s financial situation is related to the use of mental budgets. Setting savings targets induces the allocation of mental account labels as a tool to economise and control spending. Respondents from lower-income households and lower savings capacity engage in mental budgeting more frequently than those with higher incomes.

Household money management is also linked to financial well-being. Porter and Garman (1993) conceived of financial well-being as the conjunction of respondents’ socio-economic characteristics and household-related financial problems. Financial well-being is made up of objective attributes, perceived attributes, and evaluated attributes. Objective attributes are empirical indicators of the socio-economic and demographic situation of individuals, such as marital status, number of children, income, or home ownership. Perceived attributes are operationalised as managing the balance between household income and expenditure. In relation to the evaluated attributes, respondents compare their economic situation with that of their reference group, assessing their past financial experiences and expectations (Porter and Garman, 1993). This gives rise to an understanding of financial well-being as the interaction between individual and contextual variables.

2.2.3. The Determinants of Attitudes towards Financial Risk

Regarding the assessment of financial risk, multiple studies have focused on investigating the determinants of household financial risk (Bover et al. 2016; Del-Rio and Young, 2005; Farinha, 2004; Kempson and Atkinson, 2006; Rahman et al. 2020; Vale and Camões, 2015). These studies have mainly analysed the relationship between financial vulnerability, indebtedness and two categories of variables: socio-demographic variables and institutional variables. The first group includes the socio-demographic characteristics of the household and its financial behaviour; the second group contains normative aspects of the institutional context. Anderloni and Vandone (2008) underlined how difficult it is to measure the impact of the institutional context on the level of household indebtedness. Institutional variables are defined by public policies, historical legacies and regulatory frameworks that shape households’ economic decisions (van Gunten and Navot, 2018). However, their measurement is affected by the level of transparency and legal restrictions of each country (Anderloni and Vandone, 2008).

The variables traditionally considered in research on the socio-economic behaviour of households are age, income, gender, occupation, and educational attainment. Generally speaking, people are exposed to greater financial risk in their thirties. As age moves beyond 40, the demand for loans decreases, either because respondents have a stable income level or because they exhibit more conservative risk-taking behaviour (Anderloni and Vandone, 2008).

Vale and Camões (2015) suggested that age and household income are important determinants of household indebtedness in the OECD. Household income has a major impact on indebtedness decisions and is a determining factor in the study of the risk of financial vulnerability. Numerous studies have provided evidence that there is a strong association between income and the likelihood of over-indebtedness (Terraneo, 2018).

Other studies have supported a gender difference in attitudes towards financial risk. On average, women are found to have less risky asset portfolios than men and they are less willing to accept financial risks (Barsky et al., 1997; Harris et al., 2006). However, more recent studies (Lin et al. 2019) have shown that men are no more favourable to indebtedness than women.

Occupation is also a determinant of household over-indebtedness. Unemployment generally promotes the acceptance of unfavourable credit conditions given the economic solvency scenario it entails (Anderloni and Vandone, 2008). With regard to the level of education attained, it has been suggested that those with higher education have greater opportunities to assess their financial situation and easily manage the information provided by the financial system (Anderloni and Vandone, 2008). The lower the level of education attained, the higher the willingness to take on debt (Greig et al., 2019).

2.3. Analysis Model and Methodology

2.3.1. Case study. A Semi-peripheral model of capitalism: the status of southern European countries

Our analysis focuses on the cases of Portugal, Italy, Greece and Spain. These southern European countries do not constitute a homogeneous model in economic, cultural, or institutional terms. However, they share the same peripheral position within the European Union (Rodrigues et al., 2020). The varieties-ofcapitalism approach (see Hall and Soskice, 2001) offers interesting insights into differences among the developed economies, but it can hardly address the specificity of Southern Europe. Following Rodrigues et at., (2016), the term semi-periphery takes on a dual meaning. On the one hand, it accounts for the particular combination of characteristics of developed and developing countries such as a late industrialization and backward economic development compared to core European countries from continental Europe. On the other hand, the financial systems of southern European countries share similar characteristics. They are mainly based on bank credit, with underdeveloped securities markets, and are still characterized, in large part, by speculative investments (Gambarotto et al., 2019).

As Molina and Rhodes (2007) pointed out, the production system of southern European market economies is more fragmented than either liberal or coordinated market economies along large-firm/small-firm, public-private, and territorial divides. The internal heterogeneity of the production regimes and welfare systems in the south of Europe makes it difficult to address one production model with a single form of comparative advantage (Molina and Rhodes, 2007). This heterogeneity is precisely a characteristic of the Mediterranean model of capitalism affected by an unequal form of regional growth and an absence of economic convergence (Gambarotto et al., 2019).

The process of European integration forced these countries to address important structural transformations in a short time spam in numerous and varied institutional fields. Since the 1980s, southern European countries experienced an intense process of privatization, liberalization, and deregulation in different sectors of activity, including finance (Gambarotto and Solari, 2015; Rodrigues et al., 2020). The creation of the single European market and the adoption of the Maastricht convergence criteria, in force since 1993, imposed strict fiscal and monetary discipline on these countries. In turn, this resulted in important restructuring costs and weaknesses in the production system (Pataccini, 2017).

European integration involuntarily induced a further phase of peripheralization in southern countries (Gambarotto and Solari, 2015). This was further accentuated by a process of deindustrialization and speculative foreign investment in real state that was accompanied, more recently, by a boom in the tourism sector (Rodrigues et at., 2020).

The Economic and Monetary Union (EMU) created a favourable context for the process of financialization that assumed a subordinated or peripheral form in southern European countries (Gambarotto and Solari, 2015; Gambarottto et al., 2019; Lapavitsas and Powell, 2013; Rodrigues et al., 2016, 2020). Contrary to core European countries, southern European countries are import oriented and centered on their domestic markets (Gambarotto and Solari, 2015). They lack the services of financial innovation that core countries benefit from, are more dependent on foreign capital investment and advanced credit-based finance, and have a stronger tendency towards deindustrialization (Perez and Matsaganis, 2018; Stockhammer, 2016). These characteristics increase the fragility of growth regimes in southern European countries, reinforcing their consideration as part of the periphery.

In sum, structural similarities of southern European countries, together with heterogeneous work regimes, and fiscal and macroeconomic situations pose the question of how subordinated financialization actually works in individuals’ everyday life of these countries.

2.3.2. Objectives and Assumptions

The objectives and working hypotheses are set out below. This section bridges the theoretical and empirical phases by breaking down the general objective of the article into two specific objectives and two working hypotheses.

The first specific objective is to analyse the process of financialisation through socio-economic behaviour and attitudes related to the financial management of life risks. The first defined scenario concerns the individual management of life risks. Previous studies (Abalde, 2020) have described the shaping of a slightly financialised daily life space, in which public welfare coverage predominates, and where the financial markets play a secondary role.

Specific Objective 1: Analyse individual socio-economic behaviour with respect to financial risk taking and management of funds.

Hypothesis 1. Individual socio-economic behaviour oriented towards life risk management shows a low degree of financialisation in Spain, Italy, Greece, and Portugal.

The research also requires a second analytical stage, focusing on the interrelation of the characteristics across the four countries. This gives rise to the second specific objective, to examine the degree of convergence of the results obtained from the data for Spain, Italy, Greece, and Portugal. According to the hypothesis as defined, differentiated socio-economic behaviour is to be expected according to income level and country. This means that internally, socio-economic status determines the financial behaviour of individuals. At the same time, however, it also entails that there are differences between the countries analysed, as high-, middle-, and low-income households do not have identical behaviour in the four countries under study.

Specific Objective 2: Determine the main differentiation factors in socioeconomic behaviour between Spain, Italy, Greece, and Portugal.

Hypothesis 2. The socio-economic behaviour of individuals in Southern Europe has differentiated patterns according to the socio-economic level and the country in question.

2.3.3. The Database and the Study Variables

This research used the database from the second wave of the Household Finance and Consumption Survey (HFCS), conducted by the European Central Bank in the euro area for 2016. The HFCS collects information on individual demographic and socio-economic characteristics, and from the entire household of which respondents are part: real assets, liabilities, financing methods, financial assets, credit constraints, household money management, and consumption (HFCS, 2016). Given the structure of the HFCS questionnaire and the objectives of the study, the unit of analysis in this research is the individual.

Table 1 shows the variables used in the research. The methodological objective was to determine the differentiation factors between the four countries analysed in order to characterise a model for the financialisation of daily life in southern Europe, specifically differentiating the behaviour of respondents on an individual basis and by country in a subsequent cluster analysis (López-Roldán, 1996; López-Roldán and Fachelli, 2015). For this purpose, an analysis design has been developed where the interrelationships among four initial dimensions have been established, resulting in the joint treatment of 17 original variables. The first three dimensions consist of 7 variables each and operationalise attitudes towards economic risk, whereas the fourth dimension, made up of 9 variables, incorporates individual socio-demographic characteristics. All variables have been treated as categorical, so the age variable has been recoded into ranges, and the household income variable into quintiles.

Table 1
Variables used in the analysis

We have not included personal loans, lending for consumption and mortgage indebtedness, as we differentiate, according to Lazzarus and Luzzi (2015), bankarisation, that is, the basic access to banking services, from financialization, as the later refers to the individual propensity to take and manage the protection against economic risks, connecting individuals with financial markets through a wide range of subjective, cognitive and factual dimensions (Chiapello, 2015). The literature review shows that financialised behaviour of individuals is often identified with the acquisition of a broad categories of products that share the characteristic of being “risky”. A risk product in finance is defined, standardly, as an asset that provides an uncertain nominal cash flow (Schooley and Worden, 1996). In this article we focus on products related to the process of individualization of risks: stocks, mutual funds and private pension plans.

2.3.4. Analysis Techniques

The aim was, first, to identify the main differentiation factors that latently underlie the set of variables used to define the social space of attributes of the financialisation of everyday life in the four countries under study. The multivariate analysis technique chosen was Multiple Correspondence Analysis, formulated in its version of conditional analysis taking the country as a conditional variable in order to compare the data of individuals from the four countries. This is a type of correspondence analysis (Escoffier, 1990), which also combines the original variables and reduces the information to the main factors, but where the purpose is to establish the most significant structure of interrelationships between various categorical variables, while also introducing an external conditioning variable (which was the country variable in this case). This can lead to provide a common picture for the four countries studied with regard to attitudes towards risk.

The 17 variables used were divided into four sub-clouds corresponding to each country. Each country may behave more or less differently from the others. Using this technique, the four sub-clouds were re-centred with respect to the overall centre of gravity (G) of the four countries as a whole (Figure 1), i.e., their barycentric coordinates were moved to the global origin. The overall inertia of the point cloud was decomposed, as well as the sum of the ‘intra’ inertia in each sub-cloud and the ‘inter’ inertia of each barycentre with respect to the global centre. The effect of re-centring involved eliminating the ‘inter’ dispersion and performing an ‘intra’ analysis only. The conditional MCA therefore involved a unified analysis of the different territories. The interest lies in a joint comparative study of Spain, Italy, Greece, and Portugal on a common basis¹.

Figure 1
Recentring of point clouds in Conditional Multiple Correspondence Analysis

Once the main differentiating factors of the financialisation of daily life in the four countries had been determined, the specific position that each country occupies can be seen. Then a general typology could be developed that identified the main types of behaviours and attitudes towards financialisation. Technically, a hierarchical cluster analysis was applied, using Ward’s method, based on a minimal loss of inertia between groups².

3.1. Conditional Multiple Correspondence Analysis

This section details the results obtained from the conditional MCA. This technique assigns three different roles to variables: conditioning, active, and supplementary. The conditioning variable represents the country, which allowed for not only a global analysis of Southern Europe, but also the specific study of the cases in each territory. The active variables represent financial behaviour, household money management and perceptions of risk and investment. The supplementary variables, which contained the socio-demographic characteristics, complement the characterisation of the profiles extracted from the analysis, as descriptive “independent variables”.

3.1.1. The main Dimensions of the Financialisation of Daily Life

Conditional MCA retains two main factors with almost all the variance explained, corrected using the Benzécri formula. The first axis absorbed most of the information with 94.5% of the inertia, yielding an essentially unidimensional analysis. The second axis only contributed 5.5% of the inertia.

The first and foremost dimension was made up of the variables that captured attitudes towards economic risk and ownership of financial assets (‘household investments in mutual funds’, ‘household owns bonds’, ‘household owns publicly traded shares’ and ‘investment attitudes’). According to the contributions of the categories of the active variables (see Table 2 and Figure 2), this factor outlines a profile that holds cautious and moderate behaviour towards financial risk-taking and pension plan provision in opposition to investment in risky financial assets, such as bonds or listed shares.

The second dimension, independent of the first, introduced a much less important nuance that was conceptualised on the basis of variables linked to expenditure management and respondents’ saving behaviour. The categories of the active variables that discriminated in this dimension defined a contrast between people who had higher spending and overspending (mainly people with low income and lower social position), versus those who did not change in this respect over the past year (see Table 2 and Figure 2).

Table 3 shows the coordinates of the supplementary variables introduced in the analysis for illustrative purposes to show the association with the factors obtained and the active variables. The values of the categories, which are very close to the centroid, show that most of the socio-demographic variables did not significantly discriminate between individuals in the analysis. However, the economic level of individuals was relevant. Thus, the weight of the ‘total household gross income’ variable, which indicates the association between the level of income and the financial behaviour of the individuals included in the first dimension, was particularly important: the higher the level of income, the higher the risk and the more financialised behaviour.

Table 2
Contributions of the active categories

Table 3
Coordinates of the supplementary categories

Thus, a central dimension/ axis was found that gave rise to two socio-economic behavioural profiles. One was a moderate investor profile who participates in the financial markets, taking economic risks to a greater extent. The other was a traditional profile that was averse to economic risk and whose main tactic in managing household money is the search for savings.

Figure 2
Representation of active and supplementary variables in factor and rank cluster analysis

Taking the two dimensions into account and applying the cluster analysis, a differentiated behaviour was confirmed. Firstly, cluster 2 shows the group of individuals with a ‘financialised’ profile and represented only 11% of the population. This was an investor group willing to take substantial and medium-sized financial risks. In fact, the variables with the dominant weights in the dimension, which were also furthest away from the centroid were the following: ‘household owns investments in mutual funds’, ‘household publicly traded shares’, ‘household owns bonds’ and ‘investment attitudes’. It was the grouping with the highest household income (Q5 and Q4), so the amount of expenditure does not exceed income and favours savings. With regard to the supplementary variables, the average person in this group lives with a partner, owns a house, has secondary education and is active in the workforce (ISCO-7). According to the above, this cluster reflects an investor profile with a willingness to take higher economic risks. However, although this investor profile acquires financial products and assets, this tendency is not very prominent. This type of investor is more often found in Spain and Italy. According to the literature, it seems to be confirmed that in both countries the higher the income level, the greater the propensity to participate in financial markets. However, as we will see, this does not constitute a universal behavior, since in Portugal and Greece this pattern of behavior is not identified, which points to a relevant contextual and cultural influence, which should be analyzed in future studies.

The rest of the population manifested a traditional and reluctant investment behaviour which, internally, and due to the effect of the second factor, was divided into two groups, represented in cluster 2 and cluster 3, respectively. The group in cluster 1 (26%) experienced high expenses and was susceptible to financial exclusion due to the job instability that characterised it. This group was highly averse to economic risk, mainly due to their low income (Q1 and Q2). The group had high expenses that were equal to or exceeded their annual income and was therefore financially vulnerable. In addition to not participating in the markets through the purchase of financial products, they also did not access them through housing, as their main residence was rented. This traditional, non-investing grouping is most associated with the populations of Portugal and Greece, and somewhat less with Spain. Finally, the largest group (cluster 3, with 63%) also represented a profile that lacked an investor identity, as it was a group whose members did not take financial risks and managed their needs through savings. Consequently, we are faced with a conservative profile when it comes to assuming risks. They had a medium-low level of income and, although their saving capacity was restricted, they retained surplus money to protect themselves against unexpected events. Although this was not an investment profile, this group was willing to turn to the financial markets for protection in their old age by taking out a private pension plan. The tenure status of their main residence was owned or rented, suggesting that household infrastructure is the real asset that connects this grouping to financial markets. As can be seen in Figure 2, most of the cases in Italy and Spain fall within this dimension.

The theoretical interpretation of the results points to a meagre financialisation of the household space. Individuals’ participation in financial markets is low and vital risk management manoeuvres depend solely on accumulated monetary capital. The first working hypothesis formulated is therefore confirmed, as the results of the analysis suggested low financialisation levels in the risk individualisation process.

The results of the analysis also showed that the cases of Greece and Portugal tended to cluster socio-spatially on the right-hand side of Figure 2, ‘aversion’, and those of Italy and Spain on the left-hand side, ‘investment’. Therefore, evidence was found of heterogeneous behaviour across the four countries. Thus, the second working hypothesis was confirmed, albeit with very moderate differences that suggest a relatively shared identity within Southern European countries.

Despite the growing volume of literature on the financialisation of daily life, studies that empirically examine the various theoretical approaches used have been scarce. This article has analysed the financialisation of individuals’ socio-economic behaviour in Southern Europe using data from the HFCS (2016). Specifically, a model has been designed to analyse the financialisation of everyday life based on variables related to individual financial behaviour, household money management, and the perception of economic risk. Using this operational model as a reference, a factor analysis was conducted combined with a cluster analysis to analyse the behaviour of individuals in Spain, Italy, Greece, and Portugal.

The results confirmed the first hypothesis: socio-economic behaviour oriented towards risk management and the management of vital needs had a low level of financialisation. Recent theoretical contributions have established that the financialisation of everyday life operates through the transfer of risk from states to citizens (Culter and Waine, 2001), disincentivising public provision of social welfare, and stimulating individual responsibility through financial markets (Martin, 2002). However, the analysis here has shown a weakly financialised scenario of everyday life, as respondents’ participation in the financial sphere by purchasing risk-bearing financial assets and taking out a pension plan was found to be in the minority.

The literature reviewed suggests that financialisation disseminates a specific formulation of financial values and practices to every area of human life (Chiapello, 2015), including housing, health, old age, and consumption. These spheres and activities, hitherto governed by non-commodified value tables, have undergone a gradual process of ‘economisation’ (Caliskan and Callon, 2009). However, in the dimension of old age, the results of the analysis indicated that the financial markets were not seen as a source of protection. In the household dimension, the findings showed that home ownership was the main asset of the respondents. More research is needed on the individual and contextual motivations behind home buying in each country, especially in Southern Europe.

With regard to the second working hypothesis, the results confirmed a differentiated socio-economic behaviour, which places Greece and Portugal in stark contrast to Spain and Italy. Greece and Portugal did not have overtly financialised attitudes. However, the socio-economic behaviour identified in Spain and Italy was slightly financialised in the financial behaviour dimension. Thus, this model of financialisation in Southern Europe renders a mixed picture: Italy and Spain were found to have a ‘semi-financialised’ profile, while Greece and Portugal revealed a ‘reluctant’ profile. In conclusion, the analyses question the financialisation of individual economic action in Southern Europe and point to the characterisation of a heterogeneous pattern of socio-economic behaviour in the region, albeit with moderate differences. Literature o household financial risk has centred in the life cycle hypothesis on how spending varies over a lifetime (Modigliani and Brumberg, 1954; 1980). As we have seen in the theoretical discussion, there is abundant literature about the processes of over indebtedness and its relationship with occupation, financial literacy and income (Anderloni and Vandone, 2008; Terraneo, 2018; Vale and Camões, 2015). However, there are few studies about which variables shape greater or lesser risk propensity, and how the banking-financial culture of each territory is shaped. Furthermore, there is a gap in the literature about how variables such as income, financial literacy and life cycle are interrelated when explaining risk propensity. This analysis has a number of shortcomings attributable to the limitations of the quality of some of the variables in the database used. Nevertheless, this article opens up some promising research agendas. From a methodological point of view, the literature on financialisation could benefit from this operational model of everyday life by applying it to further surveys. From a theoretical and empirical perspective, the article outlines new areas of study. Firstly, it is necessary to analyse the interrelation of cultural and economic factors, such as income, that strongly determine individual risk management and propensity through the purchase of financial products in each country. To this end, it is essential to incorporate institution al and cultural variables into the analysis. Secondly, new Eurozone countries should be included in the research to allow a more rigorous test of the degree of homogeneity of the so-called Southern European model.

Acknowledgements

This article has received funding from the Ministry of Science and Innovation Government of Spain/AEI. Projects reference number: PID2019106273RB-100; PID2022-1393150B-100