**Risk-Intolerant but Risk-Taking—Towards a Better Understanding of Inconsistent Survey Responses of the Euro Area Households**

**Katarzyna Kochaniak 1,\* and Paweł Ulman <sup>2</sup>**


Received: 30 June 2020; Accepted: 16 August 2020; Published: 25 August 2020

**Abstract:** The sustainable development of the EU internal market for retail financial services is based on the rules of 'suitability', 'know your client', and 'know your product'. The rules ensure that financial institutions (including banks) offer retail clients only products and services that are adequate to their purposes and preferences, including risk tolerance. Our study, however, concerns households for which the above rules are not valid, since they declare risk aversion and possess risky assets. According to the European Union Markets in Financial Instruments Directive and Regulation (MiFID II and MiFIR), the inconsistent information they provide within survey questions should classify them to more compound suitability assessment procedures. In the study, we use nationally representative data for 16 euro area countries from the second wave of the Eurosystem Household Finance and Consumption Survey. Using logit regression, we identify sets of socio-demographic and socio-economic characteristics conducive to the possession of risky assets by risk-averse households in individual countries. To assess their similarity, we use the hierarchical taxonomic method with Ward's formula. The results of the study showed that risky assets were primarily possessed by risk-averse households that were characterised by high income, including from self-employment, and reference persons having a university degree and at least 55 years of age. The significance of their other characteristics was mainly shaped at the national level. The clear similarity of sets of the characteristics was confirmed only for a few pairs of countries. The information inconsistency that may result from erroneous self-assessments of being risk-averse was recognised in all countries and most often concerned high-income households with reference persons being males with a university degree. In 11 countries, the reason for this inconsistency could also be the inadequacy of assets held, also among senior households. The results provide insights for practitioners and policy. Identification of households providing inconsistent information to financial institutions, with the recognition of its reasons based on easily verifiable characteristics, may prove helpful in suitability assessments. The results confirming the similarity of household profiles requiring special attention between countries may be useful for entities operating cross-border. Due to the collection of information on risk aversion based on the single question self-classification method, conclusions regarding the restrictions of its use should also be considered relevant. In turn, policy implications may relate to consumer protection, since significant fractions of risk-averse households indeed participate in risky assets. Moreover, in selected countries, the risk-averse senior households were recognised as susceptible to making wrong investment decisions.

**Keywords:** risk tolerance; risk aversion; risk-taking; MiFID II; MiFIR; suitability assessment; households; risky financial assets; financial institutions; financial advisory; portfolio management

#### **1. Introduction**

Risk tolerance influences a wide range of households' financial decisions. Its significance for portfolio choices has been emphasised in Article 25 of Directive 2014/65/EU (MiFID II) and Articles 54 and 55 of Commission Delegated Regulation 2017/565 (MiFIR), which promote the 'suitability', 'know your client' and 'know your product' rules within the EU [1,2]. The rules emphasise the need for an in-depth assessment of retail clients' risk tolerance and ensure that they are provided only with products meeting their investment objectives and preferences. Risk tolerance and portfolio choices are the focus of interest of practitioners and researchers. In financial institutions, including personal advisory and portfolio management entities, they relate to individual cases [3–5], while in research studies they relate to entire populations [6,7] or specified subsets of individuals or households [8,9]. In all cases, information about self-assessed risk attitudes and asset participation is often collected within survey instruments, which are expected to provide up-to-date, accurate, and complete data.

Aiming at the uniform and consistent application of the MiFID II in the EU member countries, the European Securities and Markets Authority (ESMA) draws attention to the limited reliability of information derived from survey questions and the need for its re-examination [10]. It recognises the constraints of self-assessed risk tolerance, if not counterbalanced by objective criteria, as well as questions in batteries regarding portfolio components. Moreover, the ESMA signalises the inconsistency of survey information provided by particular types of respondents, e.g., those who are unwilling to take any risk but have ambitious investment objectives. This may occur if a self-assessed risk attitude is untrue or asset selection incorrect due to the respondent's narrowed understanding of characteristics and risks related to financial products and a shortage of investment experience. According to the ESMA guidelines, knowledge of the socio-economic and socio-demographic features of retail clients, such as, for instance, their marital status, family situation, age, employment situation, or liquidity needs may help recognise information inconsistency under the suitability assessment.

A single question self-classification is one of the methods of estimating individuals' and households' risk attitudes. It is based on the following question with four possible answer variants: 'Which of the following statements comes closest to describing the amount of financial risk that you (and your husband/wife/partner) are willing to take when you save or make investments?


The question has been widely applied in nationally representative surveys, which allow concluding about general or particular subjective risk attitudes within a specific population, with outcomes discussed in the literature related to consumer finance. This method has been used by both researchers and practitioners [11–17].

Our study is devoted to particular households residing in 16 euro area countries that assess themselves as unwilling to take any risk (risk-averse) but hold risky financial assets in their portfolios. The inconsistent information they provide within survey questions should classify them to more compound suitability assessment procedures under MiFID II and MiFIR. Our study aims to profile these households according to their socio-demographics and socio-economics, i.e., to describe the primary providers of information for the purposes of re-examination in individual countries. The problem we analyse can be referred as to a gap between a subjective and objective risk attitude of a household, since the response to the single question is based on self-assessment, and risky asset participation discloses existing risk exposure [12,18–20]. We are particularly interested in recognising the possible causes of the information inaccuracy, which can be declaring untrue risk aversion or holding inadequate financial assets, as well as in the profiles of households to which they can be assigned. As the single question self-classification was commonly used, this study also aims to recognise its limitations when applied to specified types of respondents. The paper seeks to answer the following research questions:


The discussed information inconsistency can be identified in most of the euro area countries. According to the second wave data of the Eurosystem Household Finance and Consumption Survey (HFCS), in domestic populations, up to 35% of households which declare unwillingness to take any financial risk hold risky financial assets.

Our study extends the existing research line of inquiry regarding risk tolerance and risk behaviour, particularly their incoherence, including its causes and consequences. In contrast to previous studies which examine the gap between the subjective risk tolerance and objective risk tolerance within their whole ranges, we focus solely on the risk-averse households holding risky financial assets in portfolios, for which the consequences of the aforementioned gap might be the most severe. It should be noted that current knowledge about the causes and consequences of the gap is modest. The same can be concluded about the socio-demographic and socio-economic profiles of households which undervalue their own risk tolerance and overexpose to financial risk. Moreover, few studies relate to the EU populations, but if they do so, they rely on data for specific groups of retail investors, like the clients of selected financial institutions [12,18]. The data we use are nationally representative, thus giving an insight into the euro area populations, and allowing to draw conclusions about their similarities and dissimilarities regarding the issues analysed. Such an approach is currently desired due to the re-regulation of the markets for retail financial services, not only in the EU but globally.

The results of our study have implications for practice and policy. The knowledge about households which provide inconsistent information and should be treated with utmost caution may aid professionals to remain compliant with MiFID II and MiFIR. Since the new regulatory environment has been implemented, they are obliged to recognise the constraints of retail clients prior to offering them financial products and services. Our findings seem to be useful for entities operating internationally since we identify the countries regarding which a suitability assessment can be based on similar procedures. The policy implications refer to the issues of consumer protection as a significant part of households are self-reliant, i.e., they make financial decisions on their own and are excluded from the suitability assessment [21]. The prevalence of such households which are overexposed to financial risk (risk-averse but prone to making wrong choices) may lead to social problems under financial market stress. Thus, it is essential to know if the self-classification approach offers, in fact, an accurate gauge of risk-taking propensities that helps in decision making.

The remainder of the paper is organised as follows: Section 2 contains an overview of the theory and literature related to households' financial risk tolerance and behaviour. Section 3 presents the methodology. Section 4 describes the HFCS data applied in the study. Section 5 contains the results of empirical analysis and discussion. Section 6 contains conclusions.

#### **2. Theoretical Background and Literature Review**

#### *2.1. Theory*

Financial risk tolerance can be defined as the maximum amount of uncertainty that someone is willing to accept when making a financial decision [22] or the willingness to engage in a financial behavior in which the outcomes are uncertain with a possible identifiable loss [23]. It is the inverse of an economic term of risk aversion derived from household preferences [24–26]. Risk aversion refers to a hesitancy to accept a choice that has an uncertain payoff when an alternative choice with a more certain outcome is available [26]. The concept of risk aversion was developed by Pratt [27] and Arrow [28] with the use of normative models of rational choice describing how people ought to make decisions under uncertainty.

The first economic theory which we should recall is the expected utility theory which relates to links between risk aversion and risk behaviour. It assumes in its basic form that consumers are rational, and their risk preferences remain constant under uncertainty [29]. For this reason, consumers are expected to make the same choices regardless of the situation or event which has occurred [30,31]. Optimal behaviour under uncertainty is possible only under the assumption that risk-averse individuals should maximise expected utility, which is a function of outcomes related to the wealth or income levels [32]. Pratt [27] and Arrow [28], providing the measures of risk aversion with the coefficients of absolute and relative risk aversion. The first one can be used for global comparisons of risk aversion, e.g., among individuals, with the assumption that a person with higher absolute risk aversion for every prospect may be assessed as more risk-averse. This measure may also be considered as local under the assumption that an individual with a higher absolute risk aversion will always have a higher risk premium for small bets. A relative risk aversion is, in some sense, independent of wealth levels, since the coefficient measures the willingness to accept bets being a proportion of the current wealth [32].

The expected utility theory was extended within the modern portfolio theory [33], which relates to the optimality of portfolios consisted solely of risky assets. This approach of mean-variance assumes that risk-averse investors with diversified portfolios maximise their satisfaction (referred to as utility) by maximising their portfolios' returns for a given risk level. Thus, they should take the additional risk only if returns associated with the risk are high. With the increasing significance of liquidity needs, theorists began to draw attention to portfolios consisting of both risky and risk-free assets. Tobin [34] identified an investor's risk attitude as a determinant of the optimal portfolio choice from the set of efficient portfolios consisting of both asset categories. Thus, self-assessed risk attitudes became essential for proper allocational decisions between risk-free and risky assets. In this approach, greater risk tolerance results in the choice of higher volatility, which is compensated for by a higher expected return [35]. This paradigm can be, in some sense, visible in MiFID II and MiFIR, as the recognition of clients' risk attitudes conditions further financial asset recommendations.

However, as an increasing number of studies were signalling the incompatibility between what consumers should do and what they actually do, the rationality of investors' choices was being questioned, as well as the ability of normative models to explain actual investment choices [29,36–43].

The new approach to risk attitudes was enhanced with behavioural finance and psychosocial aspects. The descriptive prospect theory incorporated risk-seeking in the domain of losses in the analyses. According to Kahneman and Tversky [41], the carriers of value or utility were changes of wealth, rather than final asset positions that included current wealth. Within this theory, the utility function was defined over gains and losses separately, and a probability weighting function converted the underlying probabilities of the lottery into subjective probabilities [44]. The significance of perceptions and judgments for decision making became expressed in the assumption of the dependence of a person's risk tolerance on how a situation or event is framed. Della Vigna [45] found that consumers demonstrate risk aversion when they are asked to make a choice in which the outcome is framed as a gain, and risk-seeking when the choice is framed as a loss. More orientation toward behavioural finance, psychology and sociology can be recognised in theory assuming the significance of feelings triggered

by the situation and risky choice for the decision-making process. In Loewenstein, Weber, Hsee and Welch's risk-as-feelings hypothesis, emotional reactions to risky situations often differ from reasoned assessments and directly influence investment behavior [46,47].

As we have presented, knowledge about the links between financial risk tolerance and financial risk behaviour has a broad theoretical framework, related not only to the economy and finance, bus also psychology and sociology. Regarding our study, the significance of prospect theory with its subjective input may be recognised, however, only when considered jointly with a sociological theory of family development. The similarity of the concepts of a household and a family should be noted here [48]. Two aspects of the theory of family development make the prospect theory useful for understanding how the family (household) and demographic variables affect risk tolerance. The first aspect is the assumption that all choices are considered in relation to one's accumulated wealth position, with wealth increasing risk tolerance. The other is the premise of the variation of losses and gains and the perception of losses to be more important than gains in individual decision-making regarding risk-taking behaviour. Both theories relate to the probabilities of events which are useful for explaining individuals' propensity for financial risk. The theory of family development does it through the adoption of socio-demographics and socio-economics for the purposes of family profiling [49]. It recognises the changes in role expectations in the family over time which are a function of changes in a family membership, individual developmental needs, and direct societal expectations [49]. According to this theory, families form their expectations and behaviours on the basis of their stage requirements confirmed in their characteristics. Moreover, family stages have stochastic qualities that introduce life uncertainties that may influence current and future behaviour and decisions [50]. Features like gender, age, marital status, having dependents, and income level may thus alter the context for assessing potential gains and losses in an investment situation. The measures of subjective and objective risk tolerance we apply in the study can also be referred to the theory; however, to a limited extent. The single question self-classification has its roots in the economic theory, but households' perceptions of own risk attitude may remain under the influence of the current situation or insufficient information [30]. The same dependence may occur regarding the measure of financial risk behaviour, which in our study is a simplified behavioural measure and refers to the occurrence of risky assets in portfolios [51].

#### *2.2. Literature*

We based our research on existing literature related to both subjective financial risk tolerance and financial risk behaviour. Regarding the aim of the study, particularly essential for us were findings related to:


Risk tolerance estimations may be based on respondents' self-assessments of risk attitudes (subjective measure) or investment behaviours reflected in portfolio composition (objective measure). The reliability of risk tolerance measures depends on how free they are from measurement error and consistent from one use to another [16,52]. Regarding the single question, opinions are ambiguous. Grable and Lytton [16] indicate its limitation resulting from incomplete coverage of the spectrum of financial risk tolerance. Despite it, they find this method closely linked to investment choices and sufficient in explanatory studies, as long as researchers are aware of its limitation. Kimbal, Sahm and Shapiro [53] emphasise the problem of subjective wording of the single question, like 'substantial', 'above average', and 'average', which may be differently interpreted by respondents. Schooley and Worden [17] recognise the additional weakness, which is the lack of possible declaration of 'the willingness to take less-than-average financial risk', which, in their opinion, makes respondents choose risk

aversion. Grable and Schumm [54] describe the reasons for the popularity of the single question among researchers, such as a common belief in its high degree of face validity and similar reliability to longer risk scales, lack of alternative risk-tolerance questions in national surveys, or only a few alternatives to national finance databases. Regarding objective measures, their advantage is intrinsic validity, as the risk attitudes are evidenced in the natural environment [55]. Still, their weak side is limited control over contextual variables, such as liquidity needs, financial constraints, or market expectations, which influence behaviour beyond risk tolerance [56]. Moreover, Hanna, Gutter, and Fan [30] indicate an obvious limitation of the assessment of risk tolerance based on portfolio composition, which is the fact that not all households hold financial assets.

Vast studies are dedicated to socio-demographics and socio-economics determining financial risk tolerance in both approaches. These characteristics stand out from others, like latent psychological and behavioural biases, by their availability in nationally representative databases, and easy recognisability and verifiability at household level. The *age of a respondent* is one of the commonly recognised socio-demographic determinants. Generally, risk tolerance is concluded to decrease with age, but this relationship may not be linear [7,57–59]. Younger investors are more tolerant, since they have time to recover from losses. Yao, Sharpe, and Wang [6] and Bakshi and Chen [60] find risk tolerance declining along with the investment horizon, leading to shifting wealth holdings toward less risky assets. Opposed to general findings, Grable [61] concludes that there is a positive relationship between the age and risk tolerance of investors. Several studies recognise the inconsistencies between age and risk tolerance, and age and actual risk-taking. Finke and Huston [62] and Chang, DeVaney and Chiremba [15] find that older investors declare lower risk tolerance but tend to invest more aggressively than the young ones. *Gender* differences are also well documented in the literature and lead to an assumption that males are more risk-tolerant and take more risks than females do [15,25,61,63–65]. However, Roszkowski and Grable [16] argue that women may underestimate their risk tolerance, while men tend to overestimate it. Despite these findings, Bucciol and Miniaci [7] do not identify gender as a significant characteristic. Investors' *level of education* is recognised as a determinant positively influencing respondents' self-assessed risk tolerance and risk-taking, since more formal education makes it easier to assess the risk-return trade-offs [15,61,66]. *Wealth* and *income* are two related factors that are hypothesised to positively influence risk tolerance [7,15,22,61,67–69]. Regarding wealth, its significance indeed may not be so evident. On the one hand, wealthy individuals may afford to incur losses on risky investments, and their accumulated wealth may reflect high risk tolerance. On the other hand, however, the impoverished may perceive risky investments as a lottery and be more willing to bear the risk associated with a given payoff. Vissing-Jorgensen [70] argues that wealthy households own more risky assets because they can overcome market requirements, such as entry costs (advising fees) and a minimum value of an investment. Similar conclusions refer to income levels [70,71]. It should be noted that *the status on the labour market* matters for the risk tolerance as well. The self-employed distinguish themselves by higher declared risk tolerance [72] and greater risky asset allocation [73]. However, private business risk may crowd out participation in risky financial assets [74]. Many studies discuss the significance of *the marital status* of an investor; however, it should be noted that the estimated risk tolerance of a couple may reflect combined preferences [9]. Previous results find singles generally more risk-tolerant than married people [69,75], but select studies identify an opposite effect [61] or do not identify significant differences at all [68]. The results of a study by Jianakoplos and Bernasek [65] extend the above and find that single women are less risk-tolerant than single men. Less attention is paid to the *household size*, measured by the number of adult members and dependent children. Large households are found to be more conservative in their risk attitudes, since their size negatively influences the wealth per capita and positively the committed expenditure-to-wealth ratio. Furthermore, they are more exposed to the risk of the random needs of family members [74,76]. *Credit constraints* may also influence households' portfolio choices, not favouring the possession of risky assets [77,78].

The existing literature also discusses the relationship between subjective and objective financial risk tolerance; however, relatively little attention is paid to the EU populations in this regard. In most studies, this issue is examined in a similar manner, by adopting a model with an objective (subjective) risk tolerance measure as the dependent variable and a set of independent variables consisting of a subjective (objective) risk tolerance measure and at least one socio-demographic or socio-economic feature. It should be emphasised that still little is known about the factors commonly favouring the inconsistency of subjective and objective risk tolerance. Some researchers, like Chang, DeVaney, and Chiremba [15], Finke and Huston [62], and Schooley and Worden [17], agree that people who declare a willingness to take financial risk are more involved in risky assets than those who are risk-averse. Hallahan, Faff, and McKenzie [69] analyse the gap in a more sophisticated way. They explain the relations between investors' subjective and objective risk tolerance in conjunction with their portfolio choices. However, they define objective risk tolerance as a feature based on responses to detailed questions. They find it broadly consistent with the subjective (self-declared) risk tolerance within the single question. The results also allow to draw conclusions about the rationality of individuals' investment choices due to their compliance with both risk attitudes. The consistency of subjective risk tolerance and risk-taking is also examined by Gutter, Fox, and Montalto [79], who recognise it among 66% of households. However, select studies confirm an evident gap between what respondents say about their risk tolerance and what they have in portfolios. A study by Jianakoplos [80] recognises a significant fraction of respondents who self-assess as less risk-tolerant but hold considerable portions of risky assets. Even larger incoherence is presented in the study of Kannadhasan [81], described by the regression coefficient at the level of 0.107. The heterogeneity of results obtained so far for different countries encouraged us to conduct the study for an almost entire euro area. Although the countries we consider became similar due to their membership in the EU and adoption of the single currency, they still remain different in many dimensions, including cultural, institutional, structural, and macroeconomic, which affect not only households' wealth, but also their perceptions and behaviours.

Despite the noticeable discussion about the discrepancies between the declared risk tolerance and portfolio composition, little is known about their causes—whether they result from wrong self-assessments or unsuitable asset holdings. Both reasons should be taken into account since, as we explained earlier, the measures of subjective and objective risk tolerance have specific shortcomings. Based on data concerning German consumers, Ehm, Kaufmann, and Weber [18] find the phenomenon of enlarged commitment in risky assets of less risk-tolerant individuals, caused by inadequate portfolio choices rather than an inability to assess own risk attitude. In turn, the findings of Martin [19] for the US population and Moreschi [20] for clients of select financial institutions lead to conclusions about individuals' inability to assess risk attitude being a primary reason. Marinelli, Mazzoli and Palmucci [12] recognise two types of gaps on the basis of data for the clients of an Italian bank, i.e., arising from wrong self-assessments (related to over- and undervaluation) and incoherent portfolio composition (related to over- and underexposure to risk). However, this is the only research we have found which provides the results referred to socio-demographics and socio-economics of individuals affected by the gap resulting from a particular cause. Marinelli, Mazzoli and Palmucci [12] recognise male investors, homeowners, and heavy savers as being characterised by a lower self-assessment gap, in contrast to married people. On the other hand, wealthy individuals with a shorter investment horizon and less debt show a smaller portfolio composition gap. Generally, people who display cautious economic behaviour, such as homeowners, savers, and those not indebted, are recognised as more consistent in their financial risk-tolerance expressions.

#### **3. Methodology**

In the study, we applied a logit regression model. In general, regression modelling allows to determine what factors, and in what way, influence the studied phenomenon expressed as numbers in a dependent variable. If this variable is the so-called 'latent' variable, but ultimately expressed in a dichotomous way (dummy), then probability models including the logit model are suitable regression models [82]. Therefore, using various household characteristics, we modelled specific 'propensities' of households considered to be important for the purposes of the study. This model can take the following form:

$$\log \frac{P\_i}{1 - P\_i} = \beta\_0 + \sum\_{j=1}^k \beta\_j \chi\_{ij\prime} \tag{1}$$

where *P<sup>i</sup>* = *P*(*y<sup>i</sup>* = 1), and *xij* represents the value of the *j*-th independent variable for the *i*-th household.

The study was conducted for each of the countries in three stages. Since it concerns households self-assessed as risk-averse, the first stage covered all surveyed households and provided an answer to the following question: *which socio-demographics and socio-economics determine the likelihood of declaring risk aversion by households in the euro area countries?* We used the model (1) with the dichotomous dependent variable *R\_averse*. We assigned the value of 1 to households declaring aversion to risk, and 0 to the others. Therefore, among statistically significant independent variables, one could distinguish:


The detailed results obtained in this stage were used in the further part of the study to identify the causes of the gap between subjective and objective risk tolerance of households, i.e., the ranges of survey responses for targeted re-examination.

In the second stage of the study, we focused only on households that declared no willingness to take any financial risk in each country. The following research question was posed: *which of the socio-demographics and socio-economics determine the likelihood of possession of risky financial assets by households that declare risk aversion? In other words, which household characteristics can be considered as favouring the occurrence of the considered inconsistency of information in the countries analysed?* In this part of the study, we used the model (1) for the dichotomous dependent variable *R\_assets* that identifies households which simultaneously declared risk aversion and possessed at least one type of risky asset. A value of 1 was assigned to such households, while the others (being risk-averse and risk-free) were assigned 0. At this stage, the profiles of households whose inconsistent information should be subject to re-examination were determined.

The results from the second stage also allowed us to identify similarities and differences in the profiles of households (specified for individual countries) whose survey responses would be classified for re-examination. Thus, we asked the question: *to what extent are the profiles of households a*ff*ected by the information inconsistency similar among the euro area countries?* Based on the characteristics favouring the occurrence of inconsistent information and the confirmed strengthening influence of incomes, and the education and age of the responding person along with their ranges, we classified the countries according to the similarities of the profiles of risk-averse but risk-taking respondents. For this purpose, the hierarchical taxonomic method with Ward's formula was used with the input dataset consisting of dummies identifying the profile for each country based on the parameter estimates of logit regression. Therefore, if a statistically significant parameter characterised a given variable in this regression, then 1 was assigned to a given country; otherwise it was 0. Based on this set of dummies, a Jaccard distance matrix was determined [83].

In the third stage of the study, we combined the results obtained in the two previous stages, relating to the statistical significance and directions of the impact of individual independent variables on the probability of occurrence of the phenomena explained. The goal of this stage was to provide answers to the following questions: *can we conclude on the causes of information inconsistency in each country? If so, then for which households is the incorrect self-assessment of risk aversion the most probable cause*

*and for which is it the participation in inadequate (risky) assets?* This part of the study allowed, therefore, to recognise the causes of the analysed information inconsistency in households of specified profiles. They were indicated by the characteristics that played the role of:


In the above cases, the re-examination might therefore be carried out with a focus on a specific area of information obtained from households, which, based on the results of the study, was indicated as the most probable cause of inconsistency. It should be noted, however, that the need for re-examination also applies to households with characteristics of which statistical significance was not confirmed at the adopted level of significance regarding the declared risk aversion (in stage 1), but it was confirmed regarding the possession of risky assets (in stage 2). In their case, one can only conclude that there is an increased tendency to provide inconsistent information, without suggesting its cause.

It should be noted that the recognition of the declared risk aversion as one of the reasons for the information inconsistency and the need for its re-examination indicates the limitations of the single question method. In this case, the following question should be raised: *for which households may the usefulness of the single question be limited?*

The overall procedure applied in the study is presented in Figure 1.

**Figure 1.** Graphical description of the study. Source: Created by the authors.

#### **4. Data**

Our study is based on the second wave data of the Eurosystem HFCS [84], which is a unique source of information about the distribution of socio-demographic and socio-economic features within the populations of the EU countries, including the self-assessed financial risk tolerance and the classes of financial assets held. The data are confidential and made available on request for research purposes.

In the euro area, information inconsistency was related to diverse domestic fractions of risk-averse household (Figure 2). On the basis of the adopted threshold at 5%, we selected 16 out of 18 countries surveyed for the study, in which from 5.2% to 35.3% of households with subjective risk aversion held risky assets in their portfolios. These were Austria (AT), Belgium (BE), Cyprus (CY), Estonia (EE), Finland (FI), France (FR), Germany (DE), Ireland (IE), Italy (IT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Portugal (PT), Slovakia (SK), Slovenia SI), and Spain (ES). We omitted Greece (GR) and Latvia (LV) since the fractions in question were much below the threshold there—0.7% and 1.6%, respectively. Taking into account that risk aversion was the most popular attitude in these two countries (declared by about 80% of Greeks and Latvians), one may conclude that subjective risk intolerance of households residing there was generally reflected in their portfolios. This consistency could result from the significantly worse living standards when compared with the remaining euro area countries, as evidenced by the Eurostat for 2014 (the reference year for both countries). The data reveal low satisfaction from own financial situation of more than half of each population and annual median equivalised net incomes of both countries classified to the lowest.

**Figure 2.** Households declaring risk aversion and their fractions responsible for information inconsistency in the population of individual countries. Source: Created by the authors and based on the Eurosystem HFCS data.

The total number of households covered by our study was 70,730, while in individual countries it ranged from 999 (in Malta) to 12,035 (in France). In most countries, including Austria, Belgium, Cyprus, France, Germany, Luxembourg, Italy, Slovakia, and Slovenia, 2014 was the reference year, but for Estonia, Finland, Ireland, Malta, the Netherlands, and Portugal, it was 2013. This difference should not be perceived as relevant for our study, since we did not use data in monetary units, subject to decline under the European sovereign debt crisis.

In the HFCS database, the information on the attitudes of households towards financial risk was obtained only by the single question self-classification method. We were interested in respondents declaring the attitude 'Not willing to take any financial risk', distinguished by the unequivocal self-assessment (risk aversion), and thus excluding the possibility of interest in any risky assets. In the study, it was described by the dummy variable *R\_averse*.

As concerns the information on financial asset classes held by households, we focused solely on the assets with capital-loss risk, no matter whether they were perceived as risky or fairly risky. We included into this group publicly traded shares, other equities related to non-self-employment, not publicly traded businesses, mutual fund units, bonds except state or other general government, and sums on managed accounts. Based on them, the dummy variable *R\_assets* was created that identifies the participation of a household in at least one type of these assets. It should be explained that the decision to use the dummy resulted from the shortage of data about the values of risky assets in households' portfolios for selected countries.

For the purposes of statistical analysis, we used a set of independent variables related to sociodemographics and socio-economics. A household's members typically own financial assets jointly

and declare a common attitude towards financial risk, but many of its attributes are personal-specific. In the HFCS, the most knowledgeable member regarding the situation of a household and a primary decision-maker is the responding person, thus we also controlled for his or her attributes. The set was composed of the following:


It should be added that we also took into account other variables related to the type of household, such as being credit constrained or receiving intergeneration transfers (gifts and inheritances), as well as a responding person's labour status. Due to their statistical insignificance or lack of data for selected countries, these variables were finally omitted in the multidimensional statistical analysis. Summary statistics of the independent variables which were used in the model (1) are presented in Tables A1 and A2. They were computed using sampling weights according to the HFCS guidelines [85].

The sampling weights were also applied to gather in-depth information for each country regarding the distribution of:


The information allowed us to supplement the findings from the regression modelling in stages 1 and 2 of the study.

### **5. Results and Discussion**

### *5.1. Risk-Averse Households but Participating in Risky Assets*

Since the providers of inconsistent information were selected from households declaring risk aversion, in the first stage of the study we profiled the latter for each country. The results of regression modelling are presented in Table A3. Some of the distinguishing characteristics of these households turned out to be statistically significant in larger groups of countries, showing supranational significance. They referred to the following:

	- its income level, primarily the lowest within the first quintile group in the country of residence (in 16 countries). Risk aversion was declared by the majority of such households, representing from 72% (in Italy) up to 98% (in Portugal) of domestic populations;
	- its sources of income, in particular pensions and regular social transfers (in 8 and 6 countries respectively). Within these subsets of countries, risk aversion was declared from 65% (in Italy) up to 96% (in Portugal) of retired households, and from 57% (in Austria) up to 86% (in France) of living from social transfers;
	- its size, expressed by a large number of adult members (in 13 countries). Among the households of at least three adult members, risk aversion was declared by from 66% (in Malta) up to 93% (in Cyprus).
	- level of education, most of all primary and lower (in 15 countries). Risk aversion was declared by from 75% (in Italy) up to 97% (in Portugal) of households distinguished by this feature;
	- gender, as risk aversion was more common among women (in 14 countries);
	- age, primarily not below 55 (in 11 countries). Taking into account the structure of households from the highest age range regarding risk attitude, between71% (in Austria) and 95% (in Portugal) of them declared risk aversion;
	- marital status; risk aversion was declared mainly by the widowed and the divorced (in 10 and 9 countries, respectively). Among widowed responding persons, the share of risk-averse ranged from 74% (in Italy) up to (94% in Estonia), while among divorced persons from 75% (in Germany) up to 90% (in France).

In turn, earning income from self-employment was the most often destimulant of declaring risk aversion (in 10 countries). Our results are therefore in line with the results dominating in the literature, regarding the significance of the characteristics and the directions of their impact. Detailed results from this part of the study were used in its third stage.

Profiling of the providers of inconsistent survey information (subject to re-examination) was performed in the second stage of the study, based on the same set of socio-demographics and socioeconomics. Detailed modelling results are contained in Table A4. It should be noted that characteristics such as the level of household income, education, and age of respondents were described by more than one independent variable. When considering these characteristics, we primarily focused on the variables that had the greatest positive impact on the probability of having risky assets by those declaring aversion to risk. Table 1 lists for each country the characteristics that favoured the occurrence of inconsistencies in survey information, and therefore can be treated as helpful in profiling respondents whose answers burdened with the greatest risk of inconsistency. As can be seen, these households were not homogeneous in 16 countries.

Despite the visible differences in household profiles, some similarities could be seen within specific groups of countries. The statistical significance of *the level of income classified as the highest* in the country was confirmed particularly often (in all countries except the Netherlands and Slovakia), *ceteris paribus*. Its importance as a determinant of the gap between subjective and objective risk attitude of an investor was confirmed by a study by Marinelli, Mazzoli and Palmucci [12] and Moreschi [20] who found that the inclination to provide inconsistent information increases along with increasing income. They explain this positive relationship with the smaller significance of potential losses for wealthy people, and thus by their lower precision in assessing their risk attitude and selecting financial assets. In our study, we also confirm the increase in the probability of information inconsistency with the rise in the level of income starting from the first quintile group in Austria, Belgium, Cyprus, Finland, France, Germany, Italy, Malta, and Spain, while in other countries within its higher ranges, *ceteris paribus*. The significance of the incomes from the highest range was evidenced in the structure of domestic

populations, as from 13% in Estonia up to 56% in Finland of households declaring aversion to risk and achieving such incomes had risky assets. The results of our study also confirmed the significance of *the source of income*, since in Estonia, Finland, Ireland, Luxembourg, Portugal, and Slovakia, the problem of inconsistent information in particular concerned those living on *self-employment incomes* (*ceteris paribus*). In Finland, it related to every second such household. The results of Stewart and Roth's [72] study suggest that its cause may be the hidden willingness to risk of these households. It can also be added that the provision of inconsistent information least often concerned those living on incomes from employment in Cyprus, Germany, Ireland, Italy, Malta, Portugal, Slovenia, and Spain, as well as from regular social transfers in Estonia, Finland, France, Ireland, Luxembourg, the Netherlands, Portugal, and Spain, *ceteris paribus*. The negative impact of the last characteristic seems obvious, due to the difficult financial situation of such households limiting their activity on the market for retail financial services. Their lowest subjective and objective risk appetite is also emphasised by Chang, DeVaney and Chiremba [15].

A characteristic favouring the provision of inconsistent information was also the *size of the household*, expressed in both the number of adult members and dependent children. Previous studies differ with regard to its significance. Some indicate a greater susceptibility of small households, explaining it with a smaller sense of mutual responsibility and less pressure among their members [22,86]. We find this regularity in our results for Austria, Belgium, France, Germany, Italy, Luxembourg, Malta, and Spain. It is worth adding that in Belgium, for instance, every fourth two-person household declaring risk aversion possessed risky assets. However, some studies emphasize that the problem of inconsistent information mainly concerns large households due to difficulties in determining a common risk attitude for the group of people and the selection of adequate assets. In such a situation, the information provided may be influenced by the objectives and preferences of one of the household members [9,10,66]. In our study, the increased propensity to provide inconsistent information by large households has been confirmed for Finland, *ceteris paribus*. More than half of Finnish households with at least three adult members and declared risk aversion participated in risky assets. As concerns the number of dependent children, the results of our study confirmed the significance of this characteristic in five countries, while the direction of its impact was not consistent. In the case of Belgium and Estonia, households distinguished by their higher number showed a greater tendency to provide inconsistent information, *ceteris paribus*. However, the study of Marinelli, Mazzoli and Palmucci [12] shows that the fact of raising children may make adult household members more diligent in assessing their own attitude towards risk and selecting assets, due to the consequences of their current financial decisions for the forthcoming status of children. In our study, the negative impact of the number of children was confirmed for France, Malta, and Slovakia.

Households whose responding persons completed *a tertiary level of education* were evidently more susceptible to providing inconsistent information. This characteristic turned out to be statistically significant in all countries except Austria, Cyprus and Malta. Numerous studies recognise it as conducive to subjective risk tolerance and risk-taking, thus signalling that the information inconsistency we analysed could have originated from declaring false risk aversion. Marinelli, Mazzoli and Palmucci [12] do not confirm the significance of the level of education for the gap between subjective and objective risk tolerance which, however, could be due to the non-representativeness of their research sample. It should be added that in Finland, France, Luxembourg, Portugal, and Spain, the impact of education on the likelihood of providing inconsistent information increased gradually, starting from its lowest level, *ceteris paribus*. However, in Estonia, Germany, Ireland, Italy, and the Netherlands, it strengthened within the two highest levels—upper secondary and tertiary. It is noteworthy that in Finland nearly half of the households that declared risk aversion and had responding persons with a tertiary level of education possessed risky assets, while in France, Spain, and Belgium it was about 25%.

Our results confirmed the significance of *the responding person's age of at least 55 years* in nine countries. It should be added that in some of them, a higher age range was related to a higher probability of information inconsistency, *ceteris paribus*. In France, the strength of the impact of the respondent's

age started to increase from the lowest range (up to 24 years), while in Belgium, Finland, and Spain within the two highest ranges. Moreover, the significance of being at least 55 was strengthened by the significance of *incomes derived from pensions*. Together these two characteristics signalled that the problem of increased information inconsistency could have affected senior households in 13 countries. The significance of the age of the responding person has not been confirmed in Estonia, Slovakia, and Slovenia. In Finland, 40% of households declaring risk aversion and having responding persons at least 55 years old had risky assets. In Belgium, Cyprus, and Malta, this ratio was around 20%. It is worth noting that not only the lower subjective risk tolerance of people nearing retirement and on retirement is emphasized in the literature, but also the lower level of their financial literacy and cognitive abilities, which make seniors more exposed to wrong investment choices and falling victim to financial frauds [87,88].

*The marital status of the responding person* proved to be significant in eight countries. We observed an increased tendency to provide inconsistent information among households of the married and in a consensual union, *ceteris paribus,* most of all in Belgium, Cyprus, and Slovakia, while this was the case for the divorced in Slovakia and the widowed in Slovenia. The reasons for the significance of being married or in a consensual union can be explained by the possible conflict in risk tolerance of couples, often resulting in separate portfolios or decisions made on the basis of the risk tolerance of one household member [66]. For instance, among Cypriot households of the married and in a consensual union declaring risk aversion, 27% participated in risky assets. The statistical significance of the divorced and the widowed for the occurrence of the phenomenon of information inconsistency in Slovakia and Slovenia could result from the possession of risky assets previously belonging to the common property [15]. In turn, the increased propensity of singles to provide inconsistent information could be inferred primarily for the population of Spain, but also of Austria, France, and Germany.

Our study also confirmed the relevance of *the gender of the responding person*, pointing to the increased tendency of males to provide inconsistent information in France, Ireland, Luxembourg and Malta, *ceteris paribus*. In the literature, this characteristic is widely documented as a determinant of both subjective risk tolerance and risk-taking, which indicates that the reason for the inconsistency of survey responses in the countries indicated could be the erroneous declarations of male respondents regarding the household's attitude towards risk.

The results of our study revealed the heterogeneity of the profiles of households susceptible to providing inconsistent information within selected countries. In Belgium, these were households with extremely different income status, both the richest (with incomes from the fifth quintile range) and the relatively poor (living on social transfers), while in Germany, France, and Luxembourg at a different stage of development, with responding persons assigned to the lowest and highest age ranges. In Austria, both of the above cases were identified.

Following the characteristics indicated in Table 1, we grouped the countries according to the degree of similarity of the profiles of households that provided inconsistent information. Based on the hierarchical classification method with Ward's formula with a Jaccard distance matrix determined (Table A5), this similarity could be confirmed within the following subsets of countries (Figure 3): Ireland and Portugal; Germany and Italy; Finland and Spain; Austria and Belgium; France and Malta. For each of the pairs indicated, it is, therefore, possible to assume a similar approach to the suitability assessment regarding the households analysed. It was also possible to cut the dendrogram at higher levels of aggregation and to obtain the following subsets of countries: Austria, Belgium, Germany, and Italy; Cyprus, Finland, France, Malta, and Spain; Estonia, Luxembourg, Slovakia, and Slovenia; Ireland, the Netherlands, and Portugal. However, the diversity of household profiles within each of the extended groups was found to be significantly larger. The distinct differences of risk-averse but risk-taking households concerned Slovakia, the Netherlands, Slovenia, and Cyprus. The above findings may prove useful for practitioners when providing investment products, advisory, and portfolio management services to retail clients in the euro area, primarily if operating cross-border.


**Table 1.**The sets of socio-demographics and socio-economics favouring the occurrence of inconsistency in the information provided by a household.

 Notes: variables named as in Section 'Data and Methodology'; the shaded fields relate to the characteristics statistically significantly increasing the likelihood of providing inconsistent information; (\*) signifies a gradual strengthening of influence of a characteristic; (H) marks the level of a characteristic at which the possession of risky assets is most likely.

**Figure 3.** Hierarchical clustering dendrogram of 16 euro area countries with households risk-averse but risk-taking. Source: Created by the authors.

The heterogeneity of domestic profiles of households that provide inconsistent information may raise a question about its causes. It should be noted that the countries analysed vary in terms of vast institutional, structural, and macroeconomic features which shape risk tolerance and risk behaviour [48,89]. Thus, among the possible causes might be the differences in national pension systems, taxation, public wealth (including medical coverage and unemployment insurance), availability of financial products, as well as the differences in asset price dynamics. Additionally, a cause might be a diversity of populations in terms of socio-demographic and socio-economic features, related, among others, to wealth, income, age, and education.

#### *5.2. Targeted Re-Examination of Household Survey Responses*

Joining the results of regression modelling from stages 1–2 (Tables A3 and A4), we were able to indicate for individual countries the primary scopes of survey information to re-examination if provided by households of specific socio-demographics and socio-economics (Table 2). In the case of characteristics such as the level of household income, education, and age of the respondent, we focused primarily on their ranges, which in stages 1–2 were of the strongest impact, since in their case the cause of information inconsistency was most visible.

The problem of information inconsistency that might result from the inaccurate perception of own risk attitude concerned all countries, however, it referred to households with different characteristics. Due to the risk aversion declared, they can be considered potentially affected by the underestimation of own risk attitude. In some countries, such households were distinguished by the highest incomes, originating from self-employment, and male respondents with a tertiary level of education completed. It should be emphasised that all these characteristics are indicated in the existing subject literature as conducive to subjective risk tolerance, and therefore not constituting the attribute of risk-averse households. In Austria, Cyprus, and the Netherlands, the need to focus re-examination on the risk attitude was indicated by incomes classified into the highest. In Belgium, Germany, Italy, Slovenia, and Spain, in addition to the highest level of income, an important characteristic was also the tertiary education of respondents, while in Malta—male responding persons. In France and Luxembourg, apart from the highest level of income and tertiary education of the respondents, the representation of households by males was also important. In Ireland, the household profile consisting of all the above characteristics was complemented by the source of income from self-employment. In Portugal, in turn, potential difficulties with self-assessments of risk attitude were recognised among households achieving the highest incomes in the country, including those obtained from self-employment and represented by

persons with higher education. In Finland, the need to focus re-examination on risk attitudes signalled the highest income and its origin from self-employment. In the case of Slovakia, households with incomes from self-employment, and responding persons with tertiary education completed, *ceteris paribus*, were mainly perceived as unable to assess own attitudes towards financial risk.

**Table 2.** Variables indicating the scopes of information for re-examination.

Notes: variables named as in the section 'Data and Methodology'; the fields shaded in grey mean that the discerned cause of information inconsistency is a false self-assessment of risk aversion; the fields shaded in black mean that the discerned cause of information inconsistency is inappropriate decisions about financial asset allocation; (H) signifies the level of a characteristic at which the cause of information inconsistency is the clearest.

Recognition of households whose self-assessed risk aversion raises objections, in practice, gives grounds for focusing the re-examination on the declared attitude. In the case of false declarations, such households can be considered risk-tolerant and offered financial assets from classes other than safe. It is noteworthy that the identification of households potentially affected by underestimation of own risk attitude reveals the imprecision of the single question method as well, i.e., its limitations if applied to households of the indicated characteristics.

The need for re-examination primarily targeted to the adequacy of risky assets holdings, with an assessment of households' knowledge about characteristics of and risks related to financial assets and their investment experience, was recognised in 11 countries. It refers to households that could be potentially affected by overexposure to financial risk. In their case, the most recurring characteristics in the euro area were the responding person's age from the highest range and income from pensions, signalling that the problem of inadequacy of assets could be related to senior households (Table 2). The significance of the first characteristic was confirmed in Cyprus, Finland, France, Ireland, the Netherlands, and Portugal, while the second—in Austria and Italy. As already explained, current literature addresses the problem of misallocation of assets among seniors, indicating as its cause the deficit of financial literacy and cognitive abilities [87,88]. The characteristics we recognise are reflected in the results of the study by Marinelli, Mazzoli and Palmucci [12], which confirms the positive effect of age on the occurrence of the gap between subjective and objective risk tolerance due to the overexposure to financial risks. Our findings are partly in line with the research results of Chang, De Vaney and Chiremba [15], which also signal the positive effect of age on objective risk tolerance. It should be added that the profile of Austrian households was supplemented with incomes derived from social transfers, while those of Finnish with a set of characteristics related to the respondents' secondary level of education (most of all the upper one), as well as a large number of adult members of a household. The significance of the last feature is signaled in the EU regulations [10] and previous studies, indicating the difficulties in

choosing the assets adequate to risk tolerance of all adult members of a large household [9,66]. In Spain, an incorrect selection of assets was signalled concerning the households represented by people aged from 40 to 54. Its intensification at this stage of life could result from the increased investment activities, described in the existing theory and empirical findings [90,91]. In Slovakia, in turn, the characteristic indicating the need to focus re-examination on the issue of asset selection was the divorced status of a responding person, *ceteris paribus*. This can be explained by the findings of Chang, DeVaney and Chiremba [15] showing that divorced singles may participate in assets that reflect their previous status as part of a couple.

Referring the results to the sphere of practice, one can conclude that the recognised inadequacy of participation in risky assets provides the basis for offering retail clients the asset switching or rebalancing portfolios under management by professionals.

#### **6. Conclusions**

The study allowed us to recognise the risk-averse but risk-taking households in 16 euro area countries. Particular socio-demographics and socio-economics distinguished them from consistent households, i.e., risk-averse and risk-free. Some of these characteristics were found statistically significant within larger groups of countries, causing the problem of information inconsistency to partly take an international dimension. It should be emphasised, however, that in every country, the profile of households analysed was complemented by characteristics of significance shaped at the domestic level.

The results of our study can be considered important for the sustainable development of financial institutions providing to retail clients the investment products, and advisory and portfolio management services under the new regulatory environment of MiFID II and MiFIR. They can be useful, among others, for entities operating cross-border, since we recognise the similarities in the profiles of households providing inconsistent information within the subsets of countries. Heterogeneity of the profiles of risk-averse but risk-taking households across the euro area indicates the need for shaping the consumer protection regulations to some extent at the domestic level, to take into account the specificities of particular populations.

Our study has identified certain socio-demographics and socio-economics that predispose households to declare untrue risk aversion or make wrong asset allocation decisions at the country level. Therefore, the results gave the basis to propose the orientation of re-examination towards particular scopes of survey information. The identification of household profiles having difficulties with self-assessment of risk attitude based on the single question self-classification indicates the limitations of this method. We identified the type of households regarding which its results should be applied with utmost caution in each country. In turn, the possible inadequacy of having risky assets was signalled in 11 countries, and related, among others, to senior households. In every country, the profile of households covered by targeted re-examination was supplemented by characteristics of domestic importance. This leads to conclusions that the approach to targeted re-examination should be individualised within the countries.

The presented research has two limitations that should be kept in mind when interpreting the results. Analysing the problem of information inconsistency, we rely on the fact that households participate in risky assets instead of on their amounts. This is due to the limited availability of appropriate data for households in selected countries. However, since we focus solely on risk-averse respondents, i.e., the most conservative ones regarding their risk attitude, we can expect them to be risk-free. The second limitation has to do with the factors omitted by us, which are also presented in the literature as determinants of households' risk attitudes and risk behaviour, such as psychological traits. This also stems from their unavailability in the database. Moreover, we were primarily interested in applying the households' characteristics which are readily available for practitioners and thus could facilitate the identification of potential providers of inconsistent information. It is worth noting that there is no alternative database to the HFCS, which would allow us to take up the discussed issue for such a large group of euro area countries.

**Author Contributions:** Conceptualization, K.K.; methodology, K.K. and P.U.; software, P.U.; validation, P.U.; formal analysis, K.K. and P.U.; investigation, K.K. and P.U.; resources, K.K. and P.U.; data curation, P.U.; writing—original draft preparation, K.K. and P.U.; writing—review and editing, K.K. and P.U.; visualization, K.K. and P.U.; supervision, K.K.; project administration, K.K.; funding acquisition, K.K. and P.U. All authors have read and agreed to the published version of the manuscript.

**Funding:** This paper is funded by the subsidy granted to the Cracow University of Economics.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A**



Notes: *TGI*—total gross income of a household. Source: The authors' own calculations.


**Table A2.** Summary statistics for independent variables—stage 2 of the study.

Notes: *TGI*—total gross income of a household. Source: The authors' own calculations.


**Table A3.** Parameter estimates of logit regression model for individual countries—stage 1 of the study (dependent variable—*R \_averse*).

Notes: <sup>1</sup> denotes significance at the level of 0.051–0.1. Source: The authors' own calcul.ations.

**Table A4.** Parameter estimates of logit regression model for individual countries—stage 2 of the study (dependent variable—*R \_assets*).



**Table A4.** *Cont.*

Notes: <sup>1</sup> denotes significance at level 0.011–0.05; <sup>2</sup> denotes significance at the level of 0.051–0.1; <sup>3</sup> Reference variable, lack of observations in the HFCS database for a lower range of a feature. Source: The authors' own calculations.

**Table A5.** Jaccard distance matrix.


Source: The authors' own calculations.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Financial Knowledge, Confidence, and Sustainable Financial Behavior**

**David Aristei \* and Manuela Gallo**

Department of Economics, University of Perugia, 06123 Perugia, Italy; manuela.gallo@unipg.it **\*** Correspondence: david.aristei@unipg.it

**Abstract:** This paper analyzes the effect of financial knowledge and confidence in shaping individual investment choices, sustainable debt behavior, and preferences for socially and environmentally responsible financial companies. Exploiting data from the "Italian Literacy and Financial Competence Survey" (IACOFI) carried out by the Bank of Italy in early 2020, we address potential endogeneity concerns in order to investigate the causal effect of objective financial knowledge on individual financial behaviors. To this aim, we perform endogenous probit regressions, using the respondent's long-term planning attitude, the use of information and communication technology devices, and the financial knowledge of peers as additional instrumental variables. Our main empirical findings show that objective financial knowledge exerts a positive and significant effect on financial market participation and preferences for ethical financial companies. Moreover, we provide strong empirical evidence about the role of confidence biases on individual financial behaviors. In particular, overconfident individuals display a higher probability of making financial investments, experiencing losses due to investment fraud, and being over-indebted. Conversely, underconfident individuals exhibit suboptimal investment choices, but are less likely to engage in risky financial behaviors.


**Citation:** Aristei, D.; Gallo, M. Financial Knowledge, Confidence, and Sustainable Financial Behavior. *Sustainability* **2021**, *13*, 10926. https://doi.org/10.3390/su131910926

Academic Editor: Chia-Lin Chang

Received: 23 August 2021 Accepted: 26 September 2021 Published: 30 September 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**Keywords:** financial knowledge; overconfidence; underconfidence; sustainable financial behavior; financial market participation; investment fraud; over-indebtedness; ethical financial companies

#### **1. Introduction and Motivation**

The literature has provided strong evidence that higher levels of financial knowledge are associated with more sustainable financial behaviors and higher levels of financial health [1–6]. As observed by van Raaij [7], responsible financial behaviors improve personal financial well-being: individuals with responsible financial behavior are less likely to have financial problems, such as over-indebtedness, financial anxiety, and fragility, and to be exposed to investment fraud. Financial behaviors performed in a responsible and sustainable way entail taking controllable and calculated risks, retaining a sufficient part of income for unforeseen expenditures, preventing excessive debt accumulation, engaging in financial planning activities, avoiding impulsive decisions and purchases, and seeking financial advice when one's own competencies are insufficient.

Financial knowledge significantly contributes to improving individuals' economic performance, with beneficial effects on their well-being and, as a consequence, on the wellbeing of the society at large [1]. In fact, people with lower levels of financial knowledge engage in high-cost transactions, incur higher fees and high-cost borrowing [4], and are characterized by greater financial fragility and less ability to manage unexpected financial difficulties [5]. Individuals who are more financially literate are more willing to seek professional financial advice or counselling than people who are less financially literate [8] and are better able to detect financial fraud [9]. Furthermore, they also have high awareness of the potential financial losses or gains derived from suboptimal financial decisions and thus are more willing to seek financial advice [10]. As demonstrated by van Rooij et al. [11], financial literacy could improve wealth accumulation and saving plans, being positively

related to the likelihood of investing in the stock market. Long-term financial planning capabilities also affect retirement planning behavior, which is associated with better retirement security [12,13]. Lusardi and Tufano [4] also emphasize the significant role of knowledge of the concepts related to debt (i.e., debt literacy) and financial experiences in reducing over-indebtedness.

A further aspect, still scarcely explored in the literature, is the link between financial knowledge and socially responsible investments. Financial literacy and environmental knowledge (i.e., eco-literacy) are generally considered factors that increase preferences for ethical financial companies, which in turn play a key role in promoting sustainable investments [14]. As discussed in Phillips and Johnson [15], a lack of knowledge of the social investment market and inadequate financial literacy represent significant barriers to participation in socially responsible investments. Gutsche and Zwergel [16] point out that basic knowledge and trust in providers of socially responsible investment products are required to overcome at least some of the barriers that limit this kind of investment. Moreover, they find that eco-labelling schemes (especially sustainability certificates) contribute to decreasing information costs for individual investors, encouraging their participation in socially responsible investments. However, Gutsche et al. [17] show that financially literate individuals in Japan, despite being more aware of sustainable investments and having lower participation costs, tend to shun sustainable financial products, possibly to avoid limited risk diversification and restricted investment opportunities related to sustainable investment strategies (e.g., negative screening). In this respect, Rossi et al. [18] also show that individuals who perceive themselves as very knowledgeable in financial matters tend to allocate much lower amounts to socially responsible investments; conversely, individuals who have more objective financial knowledge are significantly more likely to participate in social investments.

Besides objective financial knowledge, self-assessed financial knowledge provides a measure of confidence in one's own financial capabilities and is generally considered an important element for understanding individual financial behavior [10,19]. However, several authors have highlighted that individuals tend to misjudge their skills, incurring cognitive biases. Over- and underestimation of one's actual performance, as well as overand underplacement of one's own performance relative to others, lead to overconfidence and underconfidence biases, respectively [20]. Recent studies have focused on confidence biases in the self-assessment of financial competencies, showing that individuals tend to misjudge their financial skills. The misperception of one's own financial competences and skills may entail negative consequences for financial behavior and decision-making, which affect individual financial well-being in the short- and medium-long term [21]. Specifically, overconfident individuals present a higher likelihood of having carried out some retirement planning, but they do not demonstrate actual retirement preparedness [22]. The condition of overconfidence is associated with various risky behaviors that can have detrimental effects on financial health [23]. A higher self-perception of financial literacy results in a lower propensity to seek financial advice and leads to riskier financial behavior [24–26]. Moreover, overconfident individuals are found to be more likely to experience losses due to investments, or to suffer fraud through unauthorized use of payment cards [27]. Coherently, underconfidence bias leads to investment choices that are not value-maximizing [28] and has a significant negative impact on wealth accumulation and on stock market participation [11,29]. Perceived financial knowledge is relevant for information-searching behavior with regard to socially responsible investments and affects the manner in which consumers make investment decisions [15].

Previous literature has also pointed out the existence of significant gender gaps in financial knowledge and self-confidence. Both financial literacy and confidence matter for financial decision making and, as demonstrated by Bucher-Koenen et al. [30], much of the gender gap in financial knowledge can be attributed to differences in confidence and the remainder to true knowledge differences. Accordingly, Aristei and Gallo [31] provide international evidence that women are less likely than men to overestimate their financial skills but tend instead to underestimate their actual financial competencies.

Our work aims at contributing to the literature by providing new insights into the role of financial knowledge and confidence in shaping individual financial behaviors. Using microdata from the "Italian Literacy and Financial Competence Survey" (IACOFI) and addressing potential endogeneity issues, we assess the effects of objective financial knowledge and of confidence biases in the self-assessment of one's own competencies on financial market participation and sustainable financial behaviors. More specifically, following previous literature, we focus on the individual propensity to invest in financial assets, to be exposed to investment fraud, and to engage in unsustainable debt behavior. Furthermore, we assess respondents' preferences for socially and environmentally responsible companies as a proxy for individual attitudes towards sustainable investments.

Based on the above considerations, we posit our first two research hypotheses:

**Hypothesis 1 (H1).** *Financial knowledge exerts a positive effect on financial market participation, contributes to limit hazardous and unsustainable financial behaviors, and increases preferences for socially and environmental responsible financial companies.*

**Hypothesis 2 (H2).** *Controlling for the actual level of financial knowledge, confidence biases affect individual financial behaviors and play a crucial role in sustainable debt behaviors.*

We further explore the role of misperception of one's own financial competencies on financial behaviors and test the following two additional hypotheses:

**Hypothesis 3a (H3a).** *Overconfident individuals are characterized by higher financial market participation but tend to engage in riskier and less sustainable financial behaviors.*

**Hypothesis 3b (H3b).** *Underconfident individuals show suboptimal investment choices and more passive investment patterns but are less likely to make hazardous financial choices.*

The remainder of the paper is organized as follows. Section 2 describes the data and the main variables used for the analysis. Section 3 illustrates the econometric methods, while the empirical results are presented and discussed in Section 4. Finally, Section 5 draws conclusions and discusses policy implications.

#### **2. Data and Measurement**

#### *2.1. Data*

We use data from the 2020 "Italian Literacy and Financial Competence Survey" (IA-COFI), carried out by the Bank of Italy between January and February 2020 on a stratified sample (by gender, age, and area of residence) of approximately 2000 adult individuals between 18 and 79 years old. This survey provides detailed information on respondents' financial knowledge, behavior, and attitudes, based on the harmonized methodology defined by the OECD International Network on Financial Education (OECD/INFE) [32,33], together with their socio-demographic and economic characteristics.

#### *2.2. Financial Behaviors*

In our empirical analysis, we focus on different dimensions of individual financial behavior that are commonly considered in the literature. First, as in most previous studies [11,13,19,29,34–37], we focus on individual portfolio choices and consider the decision to invest in financial assets. In particular, we define a binary indicator (*Financial investment*) that equals 1 if the respondent, in the last two years, has invested in stocks and shares, public and private bonds, mutual and pension plans, cryptocurrencies, or initial coin offerings (ICOs). From Table 1, which presents descriptive statistics for all the variables considered in the empirical analysis, we notice that only 9.3% of the respondents have invested in

financial products during the last two years, confirming the low levels of financial market participation in Italy [38–40].

**Table 1.** Descriptive statistics.


Notes: The table reports average values of all the dependent and explanatory variables, computed using sample weights. Source: Own elaboration on data from the Bank of Italy.

We then account for the respondent's propensity to engage in risky and unsustainable financial behaviors. To this aim, as in Di Salvatore et al. [27], we first define the dummy variable *Investment fraud*, which is equal to one if the individual accepted advice to invest in a financial product that was later found to be a scam. Furthermore, following Lusardi and Tufano [4] and Kurowski [41], we consider a self-reported measure of over-indebtedness and identify those individuals who declare to have too much debt at the time of the interview as over-indebted (*Over-indebted*). Table 1 shows that 4.8% of the respondents have been victims of financial scams, while more than 8% perceive themselves as excessively indebted.

Finally, we focus on respondents' stated preferences towards ethical financial companies, which provide a proxy for individuals' awareness of socially responsible investments and potential demand for sustainable financial products [16,18,42]. We thus define a dichotomous variable (*ESR attitude*) identifying respondents who report preferring dealing with financial companies that have a strong ethical stance (e.g., investing in renewable energies, excluding investments in businesses perceived to have negative social and environmental effects, etc.). In our sample, about one-quarter of the individuals (24.1%) report to prefer maintaining relationships with ethical financial companies.

Complete variable definitions are reported in Table A1 in the Appendix A.

#### *2.3. Objective and subjective financial knowledge*

As in most empirical studies (see e.g., [43,44]), we measure individual objective financial knowledge (*Objective FK*) as the number of correct answers to the seven financial knowledge questions defined by the OECD/INFE harmonized methodology and included in the IACOFI questionnaire. Financial knowledge questions are related to the time value of money, interest paid on a loan, interest plus principal, compound interest, risk and return, inflation, and risk diversification [32,33]. Furthermore, in line with Allgood and Walstad [10] and Pikulina et al. [28], we also consider self-assessed financial knowledge (*Subjective FK*), measured on an ordinal scale with five possible values: Very low (1), quite low (2), about average (3), quite high (4), and very high (5), as a proxy for the respondent's perception of her/his own financial competencies. As can be noted from Table 1, Italian adults are characterized by average objective and subjective financial knowledge scores equal to 3.92 and 2.12, respectively. Additional descriptive information on objective and subjective financial knowledge (as well as on financial behaviors) disaggregated by individual and household characteristics are presented in Table A2 in the Appendix A.

Once objective and subjective knowledge measures have been defined, in order to assess confidence biases in the self-assessment of one's own financial competencies, we consider the mismatch between actual and self-reported financial knowledge. Specifically, in line with Allgood and Walstad [10] and Xia et al. [29], we define a binary variable (*Overconfident*) that identifies as overconfident those individuals ranked below the sample mean of the objective financial knowledge score (equal to 3.924), but whose self-reported financial knowledge is above the sample mean (equal to 2.200). Accordingly, the binary indicator *Underconfident* defines as underconfident those respondents with an objective financial knowledge score higher than the mean, but whose self-reported financial knowledge is lower than the mean. Figure 1 shows the joint and marginal distributions of objective and subjective financial knowledge and highlights the incidence of overconfidence and underconfidence biases. We notice that only 55.2% of the respondents correctly assess their financial capabilities: less knowledgeable people who correctly recognize their financial illiteracy represent 24.9% of the sample, while those with higher-than-average levels of both objective and subjective knowledge are 30.3%. Conversely, 44.8% of the respondents are affected by confidence biases in the self-assessment of their own financial competencies: 14.5% of the respondents overestimate their financial abilities, while 30.3% of them understate their actual knowledge.

**Figure 1.** Joint and marginal distributions of objective and subjective financial knowledge. Source: Own elaboration on data from the Bank of Italy.

Table 2 reports the observed proportions and the unconditional differences in the proportions of the financial behavior indicators for the subsamples of individuals with

> − −

objective financial knowledge below and above the average (panel *(a)*). The proportion of individuals who have invested in financial assets in the last two years is significantly higher, by 5.5 percentage points, in the high financial knowledge group. At the same time, more financially knowledgeable respondents are, on average, 3.0 and 3.5% less likely to have fallen victim of investment scams and to be over-indebted than individuals in the low knowledge group, respectively. Furthermore, higher levels of knowledge are associated with a greater preference for ethical financial companies: the proportion of individuals declaring to prefer to use financial companies that have a strong ethical stance is 13.7% higher in the high knowledge group than in the group of less knowledgeable individuals. These results provide preliminary evidence about the crucial role exerted by financial knowledge in shaping individuals' responsible and sustainable financial behavior.

**Table 2.** Financial behaviors, financial knowledge, and confidence.

Notes: The table reports average values and (unconditional) differences in the proportions of the outcome variables between the subsamples of individuals with an objective financial knowledge below and above the average value (equal to 3.92) (panel *(a)*), the subsamples of individuals with a subjective financial knowledge below and above the average value (equal to 2.20), conditional on being below (panel *(b)*) and above (panel *(c)*) the average value of the objective financial knowledge score. \*\*\*, \*\*, and \* denote the significance of the differences in proportions at 1, 5, and 10% levels, respectively. Source: Own elaboration on data from the Bank of Italy.

> From panel *(b)* of Table 2, we notice that overconfident individuals who incorrectly self-report higher-than-average knowledge are not only 5.7% more likely to have invested in financial assets but are also 10.3 and 9% more likely to have fallen victim to investment scams and to be over-indebted than respondents who properly assess their low financial knowledge, respectively. This evidence highlights the higher financial market participation of overconfident individuals, but also their higher propensity to engage in risky and unsustainable financial behaviors, as documented in Calcagno and Monticone [8], Kramer [26], Xia et al. [29], and Bannier and Neubert [45]. Furthermore, panel *(c)* of Table 2 shows that underconfident individuals who understate their high financial knowledge are 9% less likely to invest in financial assets than those who correctly consider themselves as more knowledgeable than the average. At the same time, they are also characterized by a 3.5% lower vulnerability to investment fraud. This preliminary evidence suggests that

underconfidence is associated with more passive investment behavior, which may have harmful effects on financial planning and wealth accumulation [11,28], but also with a greater tendency to engage in more sustainable investment decisions.

#### *2.4. Individual Characteristics*

To properly assess the effects of financial knowledge and confidence biases on individual financial behaviors, and mitigate omitted variable bias as much as possible, we control for a large set of individual socio-demographic characteristics (gender, age (included as a linear and quadratic term), educational attainment, working and marital status, and variables related to the household's composition (size and presence of young children) and economic conditions (net monthly disposable income and homeownership). We also include a dummy identifying risk-averse individuals, as previous studies have highlighted the significant role of risk preferences on individual financial behaviors [11,29,43]. Furthermore, we control for homeownership with and without a mortgage and include a dummy variable indicating whether the individual is responsible for the household's budget; these proxies allow us to partly account for the role of financial and debt experience in affecting financial behaviors and knowledge [4]. Finally, we consider a set of dummies to control for the area of residence and municipality size. Summary statistics for all the explanatory variables considered are reported in Table 1.

#### **3. Methods**

We first consider a baseline standard probit regression of the binary indicators of individual financial behaviors discussed in Section 2.2 on the number of correct responses to financial knowledge questions (*Objective FK*), controlling for a large set of other individual observable characteristics. Formally:

$$\mathbf{Y}\_{i} = \mathbf{1}\left(\gamma \text{Objective } \mathbf{F} \mathbf{K}\_{i} + \mathbf{x}\_{i}^{\prime} \mathbf{\mathcal{B}} + \varepsilon\_{i} > \mathbf{0}\right) \tag{1}$$

where **1**(·) is an indicator function (equal to 1 if the expression in parentheses is true and 0 otherwise), *Y<sup>i</sup>* represents different financial behaviors (i.e., *Financial investment*, *Investment fraud*, *Over-indebted*, *ESR attitude*), *x<sup>i</sup>* is a vector of covariates, *β* is the corresponding parameter vector, and errors *ε<sup>i</sup>* are assumed to follow a standard normal distribution.

Previous literature [43,44,46] has emphasized that an individual's objective financial knowledge may be endogenously determined with respect to her/his financial behavior. Endogeneity of financial knowledge may be due to an omitted variable bias stemming from the existence of unobservable factors that simultaneously influence individual financial behaviors and financial knowledge [26,47]. At the same time, endogeneity may be due to a reverse causation channel, as financial knowledge may be affected by the experience gained from previous financial decisions and by individuals' efforts to improve their own financial competencies to better manage their investments [13,48,49]. Furthermore, testbased measures of financial knowledge may not allow to properly measure "true" financial knowledge, and this measurement error may give rise to an endogeneity issue, possibly leading to downwardly biased estimates of the impact of financial knowledge [11,12]. All these potential endogeneity concerns should be properly taken into account to allow for a causal interpretation of the effect of financial knowledge on financial behavior. Following Klapper et al. [2] and Fornero and Monticone [13], we extend the standard (exogenous) probit model in Equation (1) to account for the potential endogeneity of financial knowledge. To this aim, we consider a probit model with one endogenous continuous regressor, which can be formalized as the following two-equation recursive system:

$$\begin{cases} \ Y\_i = 1 \left( \gamma O \text{objective } \mathcal{F} \mathbf{K}\_i + \mathbf{x}\_i' \boldsymbol{\mathfrak{f}}\_1 + \varepsilon\_i > 0 \right) \\\ O \text{objective } \mathcal{F} \mathbf{K}\_i = \mathbf{x}\_i' \boldsymbol{\mathfrak{f}}\_2 + \mathbf{z}\_i' \boldsymbol{\mathfrak{a}} + \boldsymbol{u}\_i \end{cases} \tag{2}$$

where the second equation defines a reduced-form equation for *Objective FK* (i.e., the number of correct answers to financial knowledge questions) as a linear function of the exogenous individual-level covariates in *x<sup>i</sup>* and a set of additional instrumental variables *z<sup>i</sup>* , assumed to directly affect an individual's financial knowledge (i.e., relevant) but not to directly impact individual financial behaviors (i.e., exogenous). The error terms *ε<sup>i</sup>* and *u<sup>i</sup>* in model (2) are assumed to follow a bivariate normal distribution with zero means, variances respectively equal to 1 and *σ* 2 *u* , and arbitrary correlation *ρσ<sup>u</sup>* (i.e., (*εi* , *ui*) ∼ *BVN*- (0, 0); 1, *σ* 2 *u* ; *ρσ<sup>u</sup>* ). Endogeneity of financial knowledge arises from the error correlation: when *ρ* 6= 0, then *Objective FK<sup>i</sup>* and *ε<sup>i</sup>* are correlated and a standard probit of *Y* on *Objective FK<sup>i</sup>* and *x<sup>i</sup>* will lead to inconsistent estimates of the *γ* and *β* parameters.

Following Pikulina et al. [28] and Xia et al. [29], we further extend the baseline model to take into account the role of confidence in one's own financial competencies. Specifically, controlling for objective financial knowledge and other individual observable characteristics, we aim to assess the impact of overconfidence and underconfidence biases on individual financial behaviors. In our empirical analysis, we thus extend model (1) and consider the following extended standard probit specification:

$$\mathbf{Y}\_{l} = \mathbf{1} \left( \gamma \mathbf{O} \mathbf{b} \text{jective } \mathbf{F} \mathbf{K}\_{l} + \delta \mathbf{O} \text{over} \text{con} \mathbf{f} \text{dent} + \theta \mathbf{L} \text{Ind} \mathbf{e} \text{con} \mathbf{f} \text{dent} + \mathbf{x}\_{i}' \mathbf{f} + \varepsilon\_{i} > 0 \right) \tag{3}$$

which includes the binary indicators *Overconfident* and *Underconfident* as additional regressors. Further, in this case, differently from previous studies [28,29], we explicitly allow *Objective FK* to be endogenously determined with respect to financial behaviors and specify the following bivariate recursive system:

$$\begin{cases} \ Y\_i = \mathbf{1} \left( \gamma \mathbf{Objective} \, \text{FK}\_i + \delta\_1 \text{Overconfident} + \theta\_1 \mathbf{I} \, \text{Index} \, \text{ofident} + \mathbf{x}'\_i \mathbf{\mathcal{B}}\_1 + \varepsilon\_i > 0 \right) \\\ \text{Objective} \, \text{FK}\_i = \delta\_2 \text{Overconfident} + \theta\_2 \mathbf{I} \, \text{Underconfident} + \mathbf{x}'\_i \mathbf{\mathcal{B}}\_2 + \mathbf{z}'\_i \mathbf{\mathcal{a}} + \mathbf{u}\_i \end{cases} (4)$$

where cross-equation error correlation *ρ* allows us to directly assess the endogeneity of financial knowledge with respect to individual financial behaviors.

In the next Section, we present and discuss results obtained from maximum likelihood (ML) estimation of the standard and endogenous probit models for the four binary indicators of individual financial behavior and compute average marginal effects to properly gauge the magnitude of the effects of objective financial knowledge and confidence indicators, while controlling for individual-level socio-demographic characteristics.

#### **4. Results and Discussion**

#### *4.1. Financial Market Participation*

Table 3 reports average marginal effects of the regressors, estimated from both standard and endogenous probit models for the probability of having invested in financial assets during the last two years.

We first consider an empirical specification (model (a)) that focuses on the role of objective financial knowledge on financial behavior. Focusing on standard probit results (column 1 of Table 3), we notice that objective financial knowledge exerts a positive and statistically significant (at the 1% level) effect on financial market participation. In particular, an additional correct answer to the financial literacy questions increases the probability of investing in financial assets by about one percentage point. Moreover, the investment decision is positively and significantly associated with having a high disposable income and a high education level, being married, and owning a home (with a mortgage). Working status also exerts a significant effect, with self-employed, employed, and retired individuals having a significantly higher investment probability than those unemployed or not in the labor force. Conversely, household size and risk aversion significantly reduce the investment probability, while a respondent's gender and age have no effect.


**Table 3.** The determinants of financial investment: Average marginal effects.

Notes: The table reports the average marginal effects on the probability of having invested in financial assets in the last two years, estimated from standard and endogenous probit models. Estimated average marginal effects on the number of correct answers to financial knowledge questions are also reported in columns (3) and (6). All the regressions include macro area and municipality size dummies. Robust standard errors, clustered by macro area and age class, are reported in parentheses below the estimates. The *p*-values of the exogeneity test, the Amemiya–Lee–Newey overidentification test, and the *F* test for weak instruments are reported in square brackets. \*\*\*, \*\*, and \* denote significance at 1, 5, and 10% levels, respectively. Source: Own elaboration on data from the Bank of Italy.

As discussed in Section 3, financial knowledge may be endogenous with respect to individual financial behavior, due to omitted-variable bias, reverse causality, and measurement errors, leading to biased parameter estimates. For this reason, we explicitly allow for the possibility that financial knowledge is endogenously determined and extend the standard probit approach by jointly modelling financial market participation and objective financial knowledge by means of a bivariate system of equations. Columns 2 and 3 of Table 3 report the average marginal effects on financial investment probability and on the number of correct responses to financial knowledge questions, respectively. Before commenting on the estimated effects, we discuss the identification strategy and formally test the exogeneity of financial knowledge.

Despite the difficulties in finding valid instruments for financial knowledge [13,43,50], in all the endogenous probit models we consider two types of instrumental variables related to the knowledge of the respondent's reference group and to her/his financial attitudes. The first instrumental variable (*Peer-group objective FK*) hinges on the idea that an individual's financial knowledge is influenced by the financial knowledge of her/his peer or reference group [2,11,48,51], defined as those individuals living in the same macro-area and belonging to the same age class of the respondent. The assumption behind the choice of this instrument is that the there is no "reflection problem" [52], that is the respondent cannot significantly affect the behavior of the peer. In particular, following Bucher-Koenen and Lusardi [49], we assume that individuals exposed to financially knowledgeable people become more knowledgeable themselves and that the financial knowledge of the group is beyond the control of the individual. The second set of instruments relates to the respondent's tendency to plan for the long-term (*Long-term attitude*) and to use information and communications technology (ICT) instruments (i.e., banking apps or money management tools on a computer, mobile phone, and/or tablet) to keep note of payment deadlines and track income and expenses (*ICT use*). As in Fornero and Monticone [13] and French et al. [53], the assumption is that these factors contribute to directly affecting the incentive to increase financial competencies, but they only indirectly affect financial choices through the financial knowledge channel. To assess the validity of our identification strategy, we first test the exogeneity of the additional instrumental variables by means of the Amemiya–Lee–Newey overidentification test. Results clearly indicate that the additional instruments considered are exogenous (*p*-value equal to 0.1792). Furthermore, results of the *F* test for the joint significance of the instrumental variables in the reduced-form equation of financial knowledge allow us to reject the null hypothesis that the instruments are weak at the 1% level (*p*-value equal to 0.0002). After having provided support for the instruments' validity, we assess the endogeneity of financial knowledge by means of a significance test of the cross-equation error correlation *ρ*. Results of this formal exogeneity test indicate that financial knowledge cannot be considered as exogenously determined with respect to investment choices (*p*-value equal to 0.0000). The endogenous probit model should thus be preferred against the standard probit, as it allows us to address the endogeneity of financial knowledge and obtain consistent parameter estimates. To further assess the appropriateness of our identification strategy and the robustness of our empirical findings, we also use linear probability models estimated using both two-stage least squares and the generated instruments method proposed by Lewbel [54]. Results of these analyses, not reported here but available upon request, confirm the validity of our identification strategy and provide estimates of the effects of financial knowledge that are in line with those obtained from endogenous probit regressions.

Column 2 of Table 3 reports the average marginal effects of the covariates on the probability of investing in financial assets estimated from the endogenous probit model. The estimated impact of financial knowledge remains positive and statistically significant at the 1% level, but the magnitude of the effect strongly increases. Specifically, when endogeneity is properly taken into account, a unit increase in the number of correct answers to financial knowledge questions raises the likelihood of participating in financial markets by about 11.5 percentage points. In this application, the marginal effect estimated by means

of the endogenous probit is thus more than 11 times larger than that estimated from the standard probit. This evidence provides support for the significant downward bias in the estimation of the impact of financial knowledge that arises when its endogenous nature is not modelled, as already pointed out in most previous empirical studies [13,46,50].

With respect to the effect of the other control variables, most of the results obtained in the standard probit remain confirmed. In particular, respondents who are married, employed, and homeowners (with and without a mortgage) are characterized by a higher probability to invest in financial assets, while financial market participation decreases with risk aversion and household size. Conversely, when the endogeneity of the financial knowledge is taken into account, income and education levels do not exert a significant impact on individual financial investment behavior.

Finally, estimated marginal effects obtained from the reduced-form equation for *Objective FK* (column 3 of Table 3) allows for assessing the main determinants of objective financial knowledge. Coherently with the findings of Bucher-Koenen et al. [30,55], Cupák et al. [56], Swiecka et al. [57], Kadoya and Khan [58], and Aristei and Gallo [59], we provide evidence of a significant gender gap in objective financial knowledge: all other things being equal, women are characterized by a number of correct answers 0.235 lower than that of men. Moreover, individuals who are responsible for the household's budget, have higher education levels and higher disposable income, and more risk averse have significantly higher objective financial knowledge, supporting the significant role of financial experience, educational attainment, and income levels in increasing financial competencies [4].

We further extend the baseline specification to account for the effect of confidence in one's own financial competencies on financial behavior. To this aim, we include the dummies *Overconfident* and *Underconfident* as additional regressors in the probit regressions (model (b)), considering as the omitted reference group those individuals who correctly assess their financial knowledge (i.e., those with high subjective and high objective knowledge and those with low subjective and low objective knowledge). It is worth remarking that, due to the 126 missing values related to subjective financial knowledge, the estimation sample is reduced to 1910 observations. Results reported in column 4 of Table 3 largely confirm the evidence obtained in the baseline standard probit. In particular, an additional correct answer to the financial knowledge questions significantly increases the probability of financial market participation by about 1.3% percentage points. At the same time, overconfidence bias does not affect investment behavior, while underconfident individuals are 2.47% less likely to invest in financial assets than those correctly assessing their financial knowledge. Furthermore, in this case, we allow for the potential endogeneity of objective knowledge by specifying an endogenous probit model, using the same identification strategy discussed above. Results reported in columns 5 and 6 of Table 3 support the validity of the additional instruments considered and confirm that financial knowledge is endogenously determined with individual investment choices. Focusing on the estimated marginal effects, a unit increase in the number of correct responses significantly raises investment probability by about 8.9 percentage points. Coherently with the evidence obtained in the baseline specification, this result confirms that the standard probit produces severely downwardly biased estimates of the impact of financial knowledge and further highlights the necessity of accounting for the endogeneity of objective knowledge with respect to individual financial behaviors. Furthermore, we provide strong empirical evidence about the role of confidence biases in affecting investment choices. In line with the results of Allgood and Walstad [10], Pikulina et al. [28], and Xia et al. [29], we find that individuals overestimating their actual financial knowledge are 16.28% more likely to invest in financial assets than similar individuals who correctly assess their competencies; at the same time, underconfident individuals have a participation probability about 13.6% lower than the reference group. Thus, taking into account the endogeneity of actual financial knowledge and controlling for other socio-demographic characteristics, we show that overconfidence bias leads to excess entry into financial markets, while underconfidence

bias makes individuals more likely to refrain from investing in financial assets. Overall, the evidence obtained suggests that overconfident individuals tend to engage in excess trading, whereas underconfident individuals inappropriately choose passive investment patterns; both of these investment behaviors may have negative consequences on financial planning and wealth accumulation [11,28].

#### *4.2. Vulnerability to Investment Fraud*

After having assessed the determinants of financial investment, we focus on financial investment behavior and analyze the role of financial knowledge and confidence on individual vulnerability to investment fraud. To this aim, we estimate standard and endogenous probit models for the probability of having invested in a financial product that later proved to be a scam, adopting the same empirical approach used in the analysis of financial market participation. Results reported in Table 4 show that financial knowledge is also endogenously determined with respect to hazardous investment choices: for both the baseline and extended specifications, exogeneity of financial knowledge is rejected at the 5% level and results of the instrument validity tests support the appropriateness of our identification strategy. Based on this evidence, in discussing estimation results, we mainly focus on the average marginal effects estimated from the endogenous probit. In particular, from column 2 of Table 4 we find that objective financial knowledge, despite having the expected sign, has no significant effect on the probability of being a victim of financial fraud. This evidence is in line with the findings of DeLiema et al. [60] who show that more financially literate and educated adults are not immune to investment fraud. At the same time, the determinants of the probability of having experienced an investment fraud are similar to those of financial market participation, suggesting that individuals who are more likely to invest in financial assets are also more exposed to financial scams, as they are more likely to be targeted by fraudsters [7].

Focusing on the extended specification (model (b)), we find that financial knowledge remains statistically insignificant, whereas confidence biases in assessing one's own financial competencies emerge as significant determinants of individual susceptibility to investment fraud. Specifically, we find that respondents who overestimate their financial knowledge are about 6% more likely to have experienced fraud than those correctly assessing their capabilities. At the same time, individuals who understate their financial competencies are 4.9% less likely to experience financial scams than the reference group. Thus, misperception of one's own financial abilities rather than actual knowledge seems to determine individual propensity to engage in hazardous financial behaviors. This evidence is in line with the findings of Di Salvatore et al. [27] and clearly points out the detrimental role of financial knowledge overconfidence on financial decision-making. As discussed in van Raaij [7] and Deevy et al. [61], individuals who are excessively confident in their actual financial capabilities are more prone to underestimate actual investment risks and this makes them particularly vulnerable to financial scams and investment fraud.

#### *4.3. Sustainable Debt Behavior and Over-Indebtedness*

Table 5 reports results the determinants of the probability of being excessively indebted. As in the previous analyses, we find that the endogenous probit model is necessary to take into account the endogeneity of objective financial knowledge and avoid biased estimates; moreover, results of overidentification and weak-instrument tests confirm, once again, the validity of our identification strategy. Analyzing the average marginal effects estimated from the baseline endogenous probit (column 2 of Table 5), we find that having low income and education levels and being risk averse significantly reduce over-indebtedness probability. Moreover, we point out that objective financial knowledge significantly increases the probability of being over-indebted: a unit increase in the number of correct answers to financial knowledge questions raises over-indebtedness probability by more than 12.7 percentage points. This evidence seems to be at odds with the findings of French and McKillop [62] and Meyll and Pauls [63], which indicate that higher levels of financial

knowledge are associated with lower debt burdens and a lower over-indebtedness probability. However, it should be kept in mind that in our analysis we consider a self-reported measure of over-indebtedness, while the above-mentioned studies consider objective measures of excessive indebtedness based on either debt-servicing ratios or arrears indicators.


**Table 4.** The determinants of having invested in a fraud: Average marginal effects.

Notes: The Table reports the average marginal effects on the probability of having invested in a fraud, estimated from standard and endogenous probit models. Estimated average marginal effects on the number of correct answers to financial knowledge questions are also reported in columns (3) and (6). All the regressions include macro area and municipality size dummies. Robust standard errors, clustered by macro area and age class, are reported in parentheses below the estimates. The *p*-values of the exogeneity test, the Amemiya–Lee–Newey overidentification test, and the *F* test for weak instruments are reported in square brackets. \*\*\*, \*\*, and \* denote significance at 1, 5, and 10% levels, respectively. Source: Own elaboration on data from the Bank of Italy.


**Table 5.** The determinants of over-indebtedness: Average marginal effects.

Notes: The table reports the average marginal effects on the probability of being over-indebted, estimated from standard and endogenous probit models. Estimated average marginal effects on the number of correct answers to financial knowledge questions are also reported in columns (3) and (6). All the regressions include macro area and municipality size dummies. Robust standard errors, clustered by macro area and age class, are reported in parentheses below the estimates. The *p*-values of the exogeneity test, the Amemiya–Lee–Newey overidentification test, and the *F* test for weak instruments are reported in square brackets. \*\*\*, \*\*, and \* denote significance at 1, 5, and 10% levels, respectively Source: Own elaboration on data from the Bank of Italy.

> The empirical evidence obtained can be thus explained by the fact that more financially knowledgeable individuals are not only more likely to participate in investment and credit markets, but they are also better able to correctly judge their debt position. These two

mechanisms may contribute to determining the positive impact of objective financial knowledge on the probability of self-reporting an excessive debt burden. The relevance of the first mechanism can be tested by modelling individuals' self-selection into the credit market (i.e., by jointly analyzing the probability of having debt and the conditional probability of being over-indebted). Unfortunately, the available data do not allow us to carry out such analysis and account for potential selectivity bias.

Extending the model to account for the effect of confidence, we find that the positive impact of objective financial knowledge remains confirmed and that misperception of one's own financial abilities significantly affects the probability of being over-indebted. In particular, controlling for objective knowledge and other socio-demographic characteristics, overconfident individuals are about 24% more likely to report being excessively indebted than those who correctly assess their financial competencies; conversely, those who understate their financial knowledge are about 15% less likely to be over-indebted than the control group. The evidence obtained further stresses the adverse impact of overconfidence bias on the sustainability of individual financial choices, supporting the findings of Lusardi and Tufano [4] and Gathergood [64]. Excessive self-confidence, combined with lack of skill or cognition, significantly impairs individuals' ability to manage their finances correctly and leads to unsustainable levels of debt. Empirical results also highlight individuals who are responsible for the household's budget and those with mortgage loan experience have a significantly lower probability of being over-indebted. This evidence confirms the beneficial role of financial and credit experience on debt sustainability, coherently with the findings of Lusardi and Tufano [4] and Kurowski [41],

#### *4.4. Preference for Socially and Environmentally Responsible Financial Companies*

Finally, we analyze individuals' attitudes towards environmentally and socially responsible financial companies. Table 6 reports results on the drivers of the probability of preferring financial companies that have a strong ethical stance, obtained from standard and endogenous probit models. Even in this case, financial knowledge is endogenously determined with respect to preferences for responsible financial companies and instrument validity is confirmed.

From the average marginal effects estimated from the baseline endogenous probit (column 2 of Table 6), we find that women are about 3% more likely to prefer ethical financial companies than men. Similarly, older individuals and those with lower income levels, higher education attainment, and lower risk aversion are characterized by a greater preference for financial companies with an ethical stance.

Objective financial knowledge significantly contributes to increasing the likelihood of preferring environmentally and socially responsible financial companies. Specifically, a unit increase in the number of correct responses to financial knowledge questions raises the probability of dealing with ethical financial companies by more than 14 percentage points. As it can be noticed, accounting for the endogeneity of financial knowledge allows avoiding downwardly biased estimates of its effect on the preference for ethical financial companies: the corresponding marginal effect estimated from the standard (exogenous) probit regression is more than 4 times lower (3.33%) than that obtained from the endogenous model. This result provides strong empirical evidence that greater preference for environmentally and socially responsible financial companies characterizes more financially knowledgeable individuals and suggests that inadequate financial knowledge represents a significant barrier to individuals' participation in socially responsible investments. Coherently with Phillips and Johnson [14], Gutsche and Zwergel [16], and Gutsche et al. [17], our findings point out that improvements in financial knowledge levels may significantly contribute to increasing trust in providers of sustainable investment products, overcoming initial entry hurdles for individual investors, and encouraging participation in the socially responsible investment market.


**Table 6.** The determinants of preferring ethical financial companies: Average marginal effects.

Notes: The table reports the average marginal effects on the probability of preferring socially and environmentally responsible financial companies, estimated from standard and endogenous probit models. Estimated average marginal effects on the number of correct answers to financial knowledge questions are also reported in columns (3) and (6). All the regressions include macro area and municipality size dummies. Robust standard errors, clustered by macro area and age class, are reported in parentheses below the estimates. The *p*-values of the exogeneity test, the Amemiya–Lee–Newey overidentification test, and the *F* test for weak instruments are reported in square brackets. \*\*\*, \*\*, and \* denote significance at 1, 5, and 10% levels, respectively. Source: Own elaboration on data from the Bank of Italy.

> Results from the extended specification (model (b)) confirm the significant role of objective financial knowledge and also suggest that self-confidence in one's own financial

competencies affects individual preferences for ethical financial companies. In particular, overconfident individuals are not only more likely to invest in financial assets, but they have greater preference for environmentally and socially responsible financial companies than individuals who correctly self-report their financial abilities. Similarly, those who underestimated their financial knowledge are less likely to prefer dealing with ethical financial companies (by about 21 percentage points), as their lower propensity to participate in financial markets and their passive investment behavior may contribute to reducing their awareness about environmentally and socially responsible investing. Since sustainable investment products are more complex than conventional products, information and search costs are higher compared to conventional investing and this may represent an important barrier for those individuals who are, by their very nature, less interested in pursuing financial investment.

#### **5. Conclusions**

This paper contributes to the existing literature by providing evidence about the role of financial knowledge and confidence in shaping individual financial market participation, sustainable debt behavior, and preferences for socially and environmentally responsible financial companies.

In line with previous empirical studies [30,34,46], we find that objective financial knowledge exerts a positive and statistically significant effect on financial market participation. Furthermore, we point out that overconfident individuals tend to engage in excess trading, being more likely to invest in financial assets than similar individuals who correctly assess their competencies, whereas underconfident individuals inappropriately choose passive investment patterns and refrain from riskier investments. This evidence supports the findings of previous literature [10,28,29] and suggests that the systematic misjudgment of one's own financial abilities may lead to negative consequences on financial planning and wealth accumulation.

Focusing on risky investment behavior and analyzing, in particular, the role of financial knowledge and confidence on an individual's vulnerability to investment fraud, our results demonstrate that objective financial knowledge has no significant effect on the probability of being a victim of financial fraud; nevertheless, individuals who are more likely to invest in financial assets are also more exposed to financial scams. Confidence biases in assessing one's own financial competencies emerge as significant determinants of individual susceptibility to investment fraud. In particular, we find that overconfident individuals are more likely to have experienced fraud than those correctly assessing their capabilities; at the same time, individuals who understate their financial abilities are less likely to expose themselves to hazardous financial behaviors. This evidence clearly points out the detrimental role of financial knowledge overconfidence on financial decision-making, confirming the results of previous studies [7,27,61]. The analysis of debt sustainability highlights that overconfidence and less financial knowledge significantly impair individuals' ability to manage their finances correctly and lead to unsustainable levels of debt.

Finally, objective financial knowledge significantly contributes to increasing the likelihood of preferring environmentally and socially responsible financial companies, suggesting that inadequate financial knowledge represents a significant barrier to individuals' participation in socially responsible investments. Coherently, those who underestimated their financial knowledge are less likely to prefer dealing with ethical financial companies, as their lower level of investment experience and their passive investment behavior may reduce their awareness of environmentally and socially responsible investments and their understanding of sustainable financial products, usually characterized by a more complex structure than conventional products.

Our main results provide significant insights into the crucial role played by financial knowledge and self-confidence in improving individual well-being and social and environmental wealth. Therefore, programs aimed at increasing the average level of financial knowledge and the awareness of one's own financial competencies could significantly

contribute to reduce riskier financial behaviors and build a culture of sustainability, both maintaining debt at sustainable levels and encouraging the choice of ethical financial companies and sustainable financial products. These policies could be pursued through the implementation of financial education programs starting from primary schools and through financial inclusion and information plans aimed at the most vulnerable and fragile groups in society (e.g., women, young people, persons with low income levels). Moreover, the reduction of information deficit and asymmetries, by means of targeted and transparent information documents and contracts, could improve understanding of the financial structure of socially and environmentally sustainable investments and the performance of this kind of investment. Since individual investors are prone to judgment and decision-making errors in their investment choices, the promotion of cost-controlled financial advisory activities could also ensure greater awareness of investment choices and a more sustainable debt burden in the medium–long term. Nevertheless, policy interventions supporting environmental values and the ecological political identification of a country could also play a significant role in incentivizing individual sustainable investment behavior.

**Author Contributions:** The authors equally contributed to the development of this research. Both authors have read and agreed to the published version of the manuscript.

**Funding:** This research was conducted within the project "Bank management, finance and sustainability" financed by the University of Perugia (Fondo Ricerca di Base, 2019).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A**

**Table A1.** Variable definitions.



**Table A2.** Descriptive statistics disaggregated by individual and household characteristics.

Notes: The table reports average values of financial behavior indicators and objective and subjective financial knowledge disaggregated by individual and household characteristics, computed using sample weights. Source: Own elaboration on data from the Bank of Italy.

#### **References**

1. Hira, T.K. Promoting sustainable financial behaviour: Implications for education and research. *Int. J. Consum. Stud.* **2012**, *36*, 502–507. [CrossRef]


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