Introduction

Everyday households are faced with the task of making decisions that have financial consequences. Most decisions are fairly small such as the decision whether to buy food in the supermarket or to go out for dinner tonight. However, some decisions have a more profound impact: can I afford to go on holiday this year or should I save up for a new car next year? Decision-making is a process that individuals go through in order to make a choice that best suits them. Notwithstanding all pitfalls that may occur in this process (see e.g. Kahneman’s Thinking, Fast and Slow; Kahneman, 2011), the ultimate goal of making a decision is aimed at a result that benefits the experienced quality of life of the individual, also known as subjective well-being (henceforth also referred to as SWB; Veenhoven et al., 2021).

For the larger purchases, particularly the more enduring form of SWB, also known as life satisfaction or happiness (Veenhoven, 2000), is of importance and not the short-term pleasure. Along these lines, it can be argued that people purchase financial products to improve their (future) SWB. By opening a bank savings account, building an investment portfolio, getting a mortgage, or getting a loan for consumption purposes, households enable themselves to make current expenses or to prepare for future expenses. By buying capital-, life- or health insurance policies, people insure themselves against possible future income loss, damage or medical expenses. The purchase of financial products can promote feelings of safety, reduce financial stress, and improve future expectations (all aspects of the concept of financial well-being (henceforth also referred to as FWB) as a domain of SWB (Brüggen et al., 2017)), which in turn can have a positive effect on SWB (e.g., Arampatzi et al., 2015; Ekici & Koydemir, 2016; Ngamaba et al., 2020; Sirgy, 2018). This is in line with empirical studies on savings, insurance and SWB, which have found that saving and insuring generally have a positive effect on SWB (Veenhoven et al., 2021).

However, purchasing financial products does not necessarily have a positive effect on SWB for a number of reasons. First, financial products that involve borrowing money can have a negative effect on people’s SWB by increasing financial stress caused by the obligation to repay debts. Moreover, “safe” financial products, such as a savings account and insurance, contribute more to SWB than more risky financial products, such as investments (Brown et al., 2005).Footnote 1 Second, consumers may not be satisfied with a certain financial product because the expected returns are disappointing or there is too much uncertainty about future returns (Howcroft et al., 2007). Third and related to the previous point, consumers can feel uncertain about whether they have purchased the right financial product (Kiplin, 2010). Indeed, contemporary financial products can sometimes be very complex and are often a combination of different types of financial products, such as saving, investing, insuring and borrowing.

In this decision-making process, households can choose to rely on their own financial capabilities, or to obtain assistance from other individuals outside the household. A study by Chang (2005) found that social networks are important in the financial decision-making process. Of the US households that indicated to save or invest (being 90% of respondents) over 40% of the households consult friends or family when making saving and investment decisions, and – response options not being exclusive - more than 35% consult a paid financial professional advisor.Footnote 2 Although obtaining advice from friends and family is most often free of charge, households have to consider whether family members and friends have sufficient knowledge to give good financial advice (Blanchett, 2019).

Professional financial advisors can have different roles helping to make financial decisions: (1) offering information, (2) defusing biases that lead to common mistakes, (3) facilitating cognition, (4) overcoming affective issues, and (5) mediating joint decision making (Collins, 2010, p. 308). By doing so, advisors can contribute to financial decision-making of households in two distinct ways.

First, professional financial advisors can assess whether it is necessary to buy a particular financial product given the personal situation of a consumer and assess what kind of financial products best suit a consumer given his or her living situation, personality and goals in life. Accordingly, financial advisors can help consumers to make life choices and realize their dreams, which can lead to higher levels of SWB. In this regard, a financial advisor can also make a financial plan for a consumer and monitor whether the consumer is making progress in achieving his or her main objectives.

Second, financial advisors have knowledge about the complexity of financial products and can separate the good financial products from the bad ones. Hence, financial advisors may also take away the concerns of the consumer regarding the financial products that are eventually bought, which in turn can result in higher financial satisfaction and higher levels of SWB. In addition, appropriate financial advice may lead to a positive effect on the disposable income of the consumer, while income has a positive association with SWB.

In this article, we examine whether professional financial advice (henceforth also referred to as PFA) is positively associated with SWB. The first sub-question is whether regarding PFA as most important source of financial advice when making financial decisions is more positively associated with SWB compared to relying on one’s own capabilities or on obtaining advice from friends and family. The second sub-question is for which groups of households PFA is most conducive for SWB.

The study presented here aims to contribute to the existing literature on financial help-seeking behavior and SWB in several ways. First, few studies have addressed the relationship between PFA and SWB. This is, to the best of our knowledge, the first paper to examine the relationship between PFA and SWB using a global judgment indicator of SWB. Second, using panel data over a period of 24 years, this is one of the first studies that examines the effect of PFA using data that follows people over a longer period. By utilizing panel data methods, we can account for many individual characteristics that potentially confound the relationship between PFA and SWB. Third, we pay attention to the heterogeneous relationship between PFA and SWB by examining for whom PFA is most conducive for SWB. Fourth, our research is of importance from a societal point of view. Many households make important financial decisions without any assistance. As many important financial decisions are aimed at improving the experienced quality of life or SWB of the household, learning about the association between PFA and SWB and knowing for whom these effects are most significant may provide policy makers with instruments to encourage people to obtain PFA. Accordingly, this paper is of importance to professionals and organizations providing financial advice.

The remainder of this article is organized as follows. “Literature Review” section describes the related literature, while “Data, Variables, and Estimation Strategy” section provides an overview of our data and methodology. “Empirical Results” section presents the results. The discussion and concluding remarks follow in “Discussion and Conclusion” section.

Literature Review

Professional Financial Advice (PFA)

As indicated by Collins (2010), the term ‘professional financial advice’ lacks a standard definition. Overall, it can be argued that the general aim of PFA is to assist consumers at making financial decisions. Financial advisory fields are abundant, ranging from specialists’ topics such as retirement advice, budget advice, investment advice, tax advice, mortgage advice and estate planning advice to broad and comprehensive advice such as financial planning. They can be grouped by two properties: specific or holistic advice versus specialist advice (Heckman et al., 2016) and dependent advice versus independent advice (Finke, 2013; Finke et al., 2009). Especially in the second division, dangers of conflicts of interest lurk, possibly leading to suboptimal enhancements of SWB or even lead to dissatisfaction in case advisors put the interests of their own business model (or of their employers) before the interests of their clients (Finke et al., 2009; Inderst & Ottaviani, 2012).

The decision to engage with PFA is subject of the last stages in the framework of financial help-seeking behavior as provided by Grable and Joo (1999). Their framework shows that after exhibiting financial behavior (stage 1), evaluating that financial behavior (stage 2), and identifying the causes of the exhibited behavior (stage 3) individuals make a decision to seek and use help or not (stage 4). When deciding to seek help, individuals decide whom to ask for help (stage 5).

Examples of fields in which financial advisors can provide assistance are: providing information, financial education, counselling, coaching, and advice (Collins, 2010). Individuals may decide to choose PFA for assistance for a number of reasons: advisors can offer information and with that make up for shortfalls in financial knowledge, they can defuse biases that lead to common mistakes, they can facilitate cognition, can help overcome affective issues and they can mediate in joint decision making (Bae & Sandager, 1997; Haslem, 2008, 2010). For several reasons, individuals can decide not to seek help. As indicated in the Introduction, the costs of advice burden engaging with PFA (Chang, 2005; Schmeiser & Hogarth, 2013). Another factor is trust in financial advisors (Schmeiser & Hogarth, 2013). Those who choose to use advice tend to be older, have higher income and are wealthier (Finke et al., 2009; Hung & Yoong, 2013). Furthermore, they tend to be more financially literate (Collins, 2012).

Subjective Well-Being and the Domain of Financial Well-Being

Following Veenhoven (2000), subjective well-being van be regarded as ‘the experienced quality of life’ (Veenhoven, 2000) and is comprised of both affective experiences (i.e., moods, emotions, affectivity) and cognitive comparisons (Diener, 1984; Diener et al., 1999; Veenhoven, 2000).

Genetic factors and personality traits are important drivers of differences in happiness and life satisfaction between people (Bartels, 2015), but other personal characteristics, including age (Clark, 2019), health (Graham, 2008), income and poverty (Clark et al., 2008; Samuels & Stavropoulou, 2016; Tang et al., 2021), income inequality (Ding et al., 2021; Ngamaba et al., 2018), marital status (Chen & Van Ours, 2018; Stutzer & Frey, 2006), social contacts (Arampatzi et al., 2018; Helliwell, 2006), and employment status (Barros et al., 2019; Winkelmann, 2014), also play a role. Cross-country variation in SWB is mainly driven by economic development, the quality and access to healthcare services, freedom, and the availability of social support (Clark, 2018). Although there is variation in the relative importance of different domains across countries, several papers have shown that cross-cultural differences in general drivers of SWB are quite limited (Diego-Rosell et al., 2018; Helliwell et al., 2010). There are also positive spillovers of SWB, as SWB also tend to increase firm productivity (DiMaria et al., 2020; Ma et al., 2021; Oswald et al., 2015), consumption (Zhu et al., 2021), health (Graham, 2008; Steptoe, 2019), and good citizenship (Guven, 2011).

As indicated by Veenhoven (2000), SWB consists of both enduring context-free states (e.g., life satisfaction and positive affect) and enduring context-specific states (for example health, family, work and financial satisfaction). Focusing here on satisfaction in the financial domain as one of the domains within SWB, numerous studies have found that there is a strong association between household income and SWB, although there seem to be decreasing returns (e.g., Clark et al., 2008; Diener & Oishi, 2000; Muresan et al., 2020). Concurrently, researchers more and more acknowledge that the use of household income as sole indicator for financial well-being (FWB) has severe limitations for establishing how well households are doing financially.

Following the operationalization of the US Consumer Financial Protection Bureau (CFPB),Footnote 3 Brüggen et al. (2017, p.229) define subjective FWB as “the perception of being able to sustain current and anticipated desired living standards and financial freedom”. Individuals can experience high or low levels of subjective FWB irrespective of their objective financial situation. Moreover, the definition by Brüggen et al. (2017) has two temporal dimensions comprising of present and expected future financial situation. Furthermore, desired living standard is included in the definition, and finally, the definition contains financial freedom, implying that a person does not experience stress with regard to making ends meet.

In this regard, Netemeyer et al. (2018, p. 780) studied the relation between SWB and FWB, using a two-component view of FWB consistent with these definitions: current money management stress and expected future financial security.Footnote 4 Their results identify both these components as predictors of SWB. In addition, they showed that these components explain substantial variance in SWB beyond other life domains (i.e. job satisfaction, relationship support satisfaction and physical health). Also other studies that have examined the relationship between different domain satisfactions and overall subjective well-being have found a medium to strong correlation between FWB and SWB (e.g., Busseri & Mise, 2020; Diego-Rosell et al., 2018; Hsieh, 2021; Ng & Diener, 2014; Sirgy, 2018) and the domain has been generally labeled as an essential element for SWB (e.g. Kruger, 2011; Layard, 2011).Footnote 5

The Relationship between PFA and SWB

This study focuses on context-free states of SWB when examining the effect of PFA on people’s SWB, where it is assumed that PFA is conducive to SWB through its effect on financial status and FWB. Building on the FWB framework of Brüggen et al. (2017), PFA can be regarded as an intervention on both personal factors and financial behavior (both factors being explained in more detail below), and thereby affecting FWB. Considering the described relation between FWB and SWB, an effect of PFA on SWB can be expected through three major paths (Fig. 1). First, seeking PFA can enhance the sense of control of individuals and their sense of reaching their goals, both having a psychological nature. Second, seeking PFA can increase the financial knowledge of individuals, both general financial knowledge and a better understanding the individual’s own financial situation. Third, PFA can assist in improving financial behavior, resulting in an improved objective financial status. Through these paths an improvement of perceived financial well-being can be expected, which in turn may lead to higher levels of SWB.

Fig. 1
figure 1

Conceptual framework of the association between PFA and SWB

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Brüggen et al. (2017) describe how FWB is influenced by three main factors: (1) contextual factors, (2) personal factors and (3) financial behavior. The contextual factors are the factors that influence the financial well-being of all individuals in an environment on which the individual himself has no influence. Personal factors are factors bound to the characteristics of the individual, some of which can be influenced by the individual himself, including skills (such as financial knowledge and abilities) and financial practices (financial socialization, spending behavior and wealth management). Financial behavior influences financial well-being when changes can be made by breaking with financial destructive habits, stimulating sound financial behaviors and stabilizing critical or vulnerable life situations.

In line with our specified conceptual framework, PFA as an intervention can be considered to affect both personal factors and financial behavior. First, PFA can cause effect on personal factors when advice leads to more financial knowledge and higher financial ability. Second, PFA can cause effect on financial behavior leading to better financial decisions, which in turn can lead to a better objective financial status (for example a higher disposable income, less debt, better retirement perspective or higher net wealth).

Paths 1 and 2: PFA and Personal Factors

Research on enhancing financial knowledge and financial sophistication tends to focus on either enhancing financial literacy through counselling and educational programs (Collins & O’Rourke, 2010) or on the relation between financial literacy and the propensity of engaging with PFA (Calcagno & Monticone, 2015; Debbich, 2015; Robb et al., 2012). Although Bae and Sandager (1997) and Haslem (2008, 2010) argue that PFA should make up for lack of financial knowledge or sophistication, research is limited on the effect of PFA on the levels of financial literacy of households.

In addition to being an intervention aimed at enhancing financial knowledge and sophistication, PFA can improve personal factors related to FWB in two other ways. First, Hanna and Lindamood (2010) argue that a financial plan helps people to feel more organized and to become more aware of their financial situation, both positively influencing financial satisfaction. Furthermore, people that are less financially knowledgeable often lack sense of control, which can be enhanced through PFA (Irving, 2012). Second, Winchester and Huston (2014) argue that financial satisfaction is increased when people have more insight in their financial situation, which can be enhanced by engaging with PFA, when they reach their goals or when they make progress in reaching them.

Path 3: PFA and Financial Behavior

Schmeiser and Hogarth (2013) studied the effect of PFA on financial behaviors: keeping emergency funds, paying (credit card) bills in full. They concluded that PFA is associated with improved financial behavior for non-retired individuals and that the relationships tends to be weaker for retired respondents. Enhanced portfolio savings programs after PFA assistance are reported by Gerhardt and Hackethal (2009). In addition, diversification and the composition of portfolios tend to be more structured: portfolios of households who make use of PFA contain a larger use of mutual funds and show better geographical diversion (Bluethgen et al., 2008; Kramer, 2012). However, PFA has many faces ranging from financial planning to transactional advice focusing on specific products. In this regard, Blanchett (2019) studied the effect of PFA on financial decision-making, concluding that households consulting financial planners make the ‘best’ financial decisions, while advice from transactional advisors has the least added value (also compared to consulting the internet and advice from friends).Footnote 6

PFA and FWB in Relation to SWB

Empirical evidence on the end-to-end relationship between PFA and SWB is limited. However, research has been conducted on the association between PFA and FWB and factors influencing FWB. With FWB having an effect on overall SWB (Netemeyer et al., 2018), the relationship between PFA and SWB is expected to be mediated by FWB.

The studies that have examined the relationship between PFA and levels of FWB generally show a positive association between the two variables. Kiplin (2010) found that people who make use of PFA are happier with their investments. Helman et al. (2010), reported the greatest benefit of working with a PFA is contributing to decreasing financial stress and worries about the future (both the opposite of financial satisfaction). Schmeiser and Hogarth (2013) found PFA to have a positive effect on FWB (financial satisfaction and financial preparedness) and on financial behaviors (as discussed in the previous subsection). Newton et al. (2015) reported that financial planning and financial advice have positive effects on clients’ financial satisfaction, particularly for longer-term users, also positively affecting other life domains (see also Xiao & Porto, 2016).

This Study

In summary, the existing literature has provided some insights on the relationship between PFA and SWB. However, several issues have remained unaddressed in this strand of research. First, the literature tends to focus on the effect of PFA on (mediators of) financial well-being, and not on subjective well-being. Given that individual’s financial situation affects more life domains than just the financial domain (although PFA is likely to affect SWB primarily through its effect on financial well-being), it is important to examine the effect of PFA using a more global judgment of subjective well-being in itself. Second, most presented studies that shine some light on the relation between PFA and FWB/SWB, are based on cross-sectional data and do not account well for selection effects. In this regard, some studies have found higher levels of FWB among PFA users. However, these higher levels could be due to selection effects, such as wealthy people having better access to these services because they can afford them. Another disadvantage of cross sectional analysis, is that individuals have different determined set-points (Lykken & Tellegen, 1996) and personality traits (Lucas & Fujita, 2000) that typically influence reported SWB levels. Third, earlier research into the association between PFA and FWB / SWB has focused on average effects of PFA, rather than on addressing the heterogeneous relationship between PFA and SWB and specifying what matters for whom. Key is to find out what works for whom under which circumstances and the question is rather how the effect of PFA differs within the general population.

Building on the discussed research and trying to overcome its limitations, we (1) examine in the remainder of this article the relationship between PFA and SWB performing a time series analysis, (2) assess to what extent the relationship between PFA and SWB is heterogeneous using (3) panel data from a long period (1995–2018). Please note that due to data limitations, we will not be able to empirically assess the mechanisms (e.g., FWB or income increase) through which PFA affects SWB and this should be addressed in future research.

Data, Variables, and Estimation Strategy

Data

In this study, we utilize panel data from the Dutch Household Survey (hereafter: DHS), conducted by the Dutch Central Bank. The DHS covers a wide range of questions regarding the financial position of households and includes questions on the evaluation of the quality of life and on the most important sources of financial advice. For our research, we use the DHS waves 1995–2018.Footnote 7

The panel data that we use is unbalanced: the surveys in the waves used were filled out by 3750 households on average per year; in total 118,302 individuals in 89,991 households have participated in these waves. All members of the household were invited to fill out the survey, e.g. the spouse, children or parents that are part of the household. Participation by households ranges from one-year of participation only, up until participating in all 24 waves. Because we use the DHS data to perform a time series analysis, only the respondents participating in two or more waves and filling out both the questions on SWB and PFA, form part of our full sample. This full sample consists of 14,245 individuals, together filling out the survey more than 50,000 times, spread over the 24 waves used. On average, these respondents filled out the survey in 3 to 4 waves. Not all respondents filled out all questions in all waves on the relevant control variables (see below) for our analysis. Discrimination of the full sample to those individuals who actually filled out all relevant questions in all waves leads to a subset that includes 9567 individuals (of which 22,050 are the head of the household and 10,979 are their spouse or partner, the remaining 33 being other members of the household) over the period from 1995 to 2018 that filled out all relevant questions, in total 33,062 times. We refer to this subsample as our common sample.

Variables

Subjective Well-Being

To measure SWB, respondents were asked the following general well-being question: “All in all, to what extent do you consider yourself a happy person?”, measured on a scale from “1 = very unhappy” to “5 = very happy”.Footnote 8

Measuring the effect of independent variables and moderators on SWB with a single item score has found to be sufficiently reliable and valid in survey research (Abdel-Khalek, 2006; Cheung & Lucas, 2014; Krueger & Schkade, 2008). Compared to their multi-scale counterparts, the use of a single item measure is generally less reliable (see Diener et al., 2013). Nevertheless, recent research by Cheung and Lucas (2014) that compares single-item life satisfaction to multi-item life satisfaction scales showed that the two types of measures do not give very different pictures of people’s SWB and, more importantly, that the two measures do not correlate differently with important predictor variables.

On average and in line with other SWB surveys in the Netherlands (Veenhoven, 2022), most respondents report in the survey to consider themselves to be happy persons (64%) or very happy persons (21%), while 14% reports to consider themselves to be neither happy nor unhappy persons, and only a few respondents (1%) report to consider themselves to be unhappy or very unhappy persons.

Sources of Financial Advice

The DHS survey contains the following question regarding financial advice: ‘What is your most important source of advice when you have to make important financial decisions for the household?’ Respondents could choose between (1) parents, friends or acquaintances, (2) information from the newspapers, (3) financial magazines, guides, books, (4) brochures from my bank or mortgage advisor, (5) advertisements on TV, in the papers, or in other media, (6) professional financial advisors, (7) financial computer programs, (8) financial information on the internet,Footnote 9and (9) other. The distribution of the responses in the waves used is presented in Appendix 1, 3.

Two of these answering categories involve interaction with other individuals: (1) parents, friends or acquaintances, and (6) professional financial advisors. The other answering options are all sources where information is presented (analog or digital) that is most likely not specific to the households’ situation, except (7) financial computer programs. When respondents indicate that they regard one of these information source as their most important source when making important financial decisions, this entails that they rely on processing the presented information by themselves, at least they do not regard the advice of friends, parents and/or acquaintances nor form professional financial advisors as more important.

In our analysis, we group the different categories to make a distinction between (A) professional financial advice, (B) advice from parents, friends, or acquaintances, and (C) self-study and other, which includes categories (2), (3), (4), (5), (7), (8), and (9). Although the question on sources of financial advice is a single option question about regarding a source as most important and not about having used a source, choosing the option indicates that a respondent has used at least the chosen source. A limitation of this questioning method can be that a respondent has used a PFA, and for some reason does not regard this as his most important source. However, when the respondent regards PFA as most important source, this indicates the use of PFA. Another aspect to take in to account is that the answering option “professional financial advisor” is a generic description and answering options do not give any information on the advisor type.

Figure 2 shows the distribution of most important sources of advice over time in the full sample as used in our analysis, with the distinction between (A) professional financial advice, (B) advice from parents, friends, or acquaintances, and the compounded category (C) self-study and other. Most respondents indicated that one of the information sources of “self-study and other” is their most important source of advice (42–52%), family, friends and acquaintances represent (24–32%), and professional financial advisors (20–28%). The percentage of people using PFA as most important source is declining slowly over the last years, with the other two categories (B) and (C) increasing over time, although no clear driver can be identified from the development of this distribution.Footnote 10

Fig. 2
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Sources of financial advice for Dutch households when making important financial decisions (DHS, 1995–2018)

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Regarding performing a time series regression analysis, of which our estimation strategy follows below, we examine ‘switchers’ over the period 1995–2018. In this way we examine whether respondents consider themselves to be happier or unhappier persons in different waves before and after they have switched between the sources of information they regard as most important.

We observed that 14% of the respondents in the full sample switched (at some point) to (A) regarding PFA as most important source of financial advice from regarding (B) parents, friends and acquaintances or (C) self-study and other. In the other direction 44% switched (at some point) from regarding (A) PFA as most important to regarding another source of advice (B) or (C) as most important source in this period.Footnote 11 This switch is predominantly to (B) parents, friends and acquaintances and “financial information on the internet”, within category (C).

Control Variables

To account for any confounding effects with regard to the relationship between PFA and SWB, we control for several socio-economic characteristics, including health, home ownership, occupational status, marital status, education level, age, financial situation, income, and perceived financial knowledge. Please note that (some of) the economic variables are endogenous, in that they are mediator variables and also explain the association between PFA and SWB. Hence, estimations including these endogenous control variables should be perceived as more conservative estimations. Descriptive statistics and a detailed description of the control variables can be found in Appendix 2, Tables 4 and 5.

Estimation Strategy

We analyze the relationship between PFA and SWB using the following individual-year regression model:

$${SWB}_{it}={\beta}_0+{\beta}_1{PFA}_{it}+{\beta}_2{X}_{it}+{\mu}_i+{\mu}_t+{\varepsilon}_{it},$$
(1)

The model links whether person i in year t regards a PFA as most important source of advice to our subjective-well-being variable SWBit for person i in year t; a set of control variables Xit which capture time-varying control variables; a set of individual dummies for time-invariant individual characteristics μi (capturing e.g. gender and personality), and a vector of time dummies μt for global shocks.

We utilize a fixed effects estimatorFootnote 12 to model our dependent variable SWB with values 1 to 5. In the SWB literature there has been a debate about treating the well-being variables as cardinal or ordinal variables. In this regard, Ferrer-i-Carbonell and Frijters (2004) have reported that treating the SWB variable as ordinal or cardinal in econometric estimations does not significantly affect the conclusions (especially not when the scale has many points). Given the straightforward interpretation of the coefficients using a general linear regression, we present these as main results below; fixed effects ordered logit regressions (Baetschmann et al., 2020) have been performed as a sensitivity analysis.

As follows from our estimation model, we focus on the end to end relation between PFA and SWB. Given the composition of the DHS questionnaire, we are not able to empirically assess the mechanisms through which PFA affects SWB.

Empirical Results

Baseline Results

Our baseline results, shown in Table 1 (full estimations are provided in Appendix 3), are the results of the fixed effects estimations, including individual and year fixed-effects and SWB as the dependent variable. In the first and second column of Panel A, we show the results of the full sample (Model (1)) and the common sample (Model (2)) respectively, without the addition of demographic and economic control variables. Overall, we find that regarding PFA as most important source of financial advice is associated with a 0.02 to 0.03 higher score on the SWB scale running from 1 to 5. This result is robust to controlling for health, home ownership, occupational status, marital status, education level, age (personal controls) and financial situation, income, and perceived financial knowledge (economic and behavioral controls). In addition, in Models (3) and (4) we distinguish in the non-PFA group (that is, the group of respondents that does not regard PFA as most important source of advice) between “parents, friends, or acquaintances” as main source of advice, and the compiled group “self-study and other” (Table 1, Panel B). Here we find that regarding PFA as most important source of financial advice is associated with a 0.02 to 0.04 higher SWB score (scale 1–5), compared to both other categories in all Models. At the same time, there are no significant differences between regarding “parents, friends, or acquaintances” and “self-study and other” as most important source of advice. When re-estimating our models using fixed-effects ordered logit estimation, our main conclusions do not change (see Appendix 4).

Table 1 The relationship between PFA and SWB – Fixed Effects Estimation
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Reverse Causality

An obvious concern when analyzing the relationship between PFA and SWB is that PFA is endogenous in that happy people may be more likely to engage with a PFA (because e.g. they have more financial means to do so). The linear fixed effect model controls to some extent for selection effects by eliminating time-invariant confounding effects, i.e., the phenomenon that fixed individual characteristics, such as personality, may influence the choice to engage with a PFA and regard it as most important source. However, the linear fixed effect model does not consider possible reverse causality, e.g., the fact that an individual whose SWB increases (e.g. due to income increases) is more likely to engage with a PFA (due to the fact that it has become more affordable).

To examine whether changes in SWB influence the decision to switch to regarding PFA as most important source of financial advice, we estimated linear fixed effects models in which the dependent variable is the dummy variable indicating whether the most important source of financial advice the respondent uses is not PFA and the independent variable are the SWB variables at earlier points in time. If past SWB (using a one-year lag) is significantly associated with regarding PFA as most important source in the observed year then we could have a reverse causality issue. Table 2 shows the relevant parameter estimates of lagged SWB in our common sample. These estimations indicate that a positive shock to SWB does not increase the probability to switch to regarding a PFA as most important source of financial advice a year later. From this we conclude that reverse causality from SWB to regarding PFA as most important source in future is probably not a large issue.

Table 2 The relationship between PFA and SWB – Reverse Causality
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Heterogeneous Relationship

The effects of switching to regarding PFA as most important source of advice on SWB may obscure differences across different kinds of people. Since we aim at giving in depth insights whether PFA is conducive to SWB, we introduce interaction effects in our model to examine whether the effect of PFA on SWB varies across subgroups. Specifically, we explored whether certain demographic, psychological and economic variables moderate the effect between PFA and SWB, including age, gender, education level, occupational status, marital status, living environment, income, financial situation, perceived financial knowledge and personality characteristics.

The most striking and statistically relevant differences across subgroups are shown in Table 3, in which we re-estimated Model 4 from Panel A in Table 1, now including interaction effects.

Table 3 The relationship between PFA and SWB – Heterogeneous Relations
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First, we find that income moderates the relationship between PFA and SWB. When the household experiences an increase in income, the relationship between regarding PFA as most important source of advice and SWB becomes more positive. This could be explained by financial issues within the household becoming more complex when income increases, which makes the use of PFA more warranted. In addition, the financial burden of hiring a PFA becomes lower when income increases. This might also explain why we did not find any indication that people with debts obtain a SWB advantage from regarding a PFA as most important source of advice.

Second, we find that the relationship between regarding PFA as most important source of advice and SWB is less positive for people with who consider themselves to some extent financial knowledgeable compared to people that consider themselves not financially knowledgeable. Since PFA can increase SWB through providing general financial knowledge and a better understanding the individual’s own financial situation (Kiplin, 2010) it is not surprising that the households considering themselves least knowledgeable would be affected most by PFA. In addition, people that are less financially knowledgeable often lack sense of control, which can also be enhanced through PFA (Irving, 2012). However, it should be noted that the relationship is weakly significant in Model 2 of Table 3 and becomes insignificant in our full specification.

Third, we find a more positive effect of regarding a PFA as most important source of advice for those individuals that have a weaker internal locus of control (the degree to which an individual attributes success to his or her own efforts and abilities) and for those individuals that have a lower degree of conscientiousness (the degree of self-discipline). This finding can be explained by the mechanism that seeking PFA can enhance the sense of control and the sense of reaching goals, which is typically lower in individuals with a lower internal locus of control and conscientiousness level (Saint-Germain et al., 2011).Footnote 13

We did not find differences across age groups, gender, education level, occupational status, marital status, and living environment.

Please note that the significant interactions were only significant at the 10% level. Furthermore, it should be noted that our findings with regard to conscientiousness are only significant in Model 4 at the 10% level and become insignificant when adding the other interaction terms. In addition, it is important to mention that our results become less significant when including all four interaction terms at the same time (see Model 5 of Table 3). Further research has to be conducted to verify the conclusions drawn in this subsection.

Discussion and Conclusion

In this research we examined the relationship between PFA and SWB using a global happiness measure. We found that regarding PFA as most important source of financial advice is positively associated with SWB compared to having “friends families or acquaintances” or “self-study or other” as most important source when making important financial decisions. Using panel data over a period of 24 years we accounted to a large extent for selection effects and unobserved individual characteristics that potentially confound the relationship between PFA and SWB.

In addition, we found regarding PFA as most important source mainly has a more positive effect for households whose income has recently increased. Moreover, we find that PFA has a more positive effect on the SWB for individuals that consider themselves to have limited financial knowledge, a weaker internal locus of control and/or a lower degree of conscientiousness. Since these latter findings were only marginally significant, further research has to be conducted to verify these results.

Research Limitations and Future Directions

Where panel data and a fixed effects estimation enabled us to overcome most selection effects and omitted variable bias, our dataset does not contain all the desired variables for establishing the mechanisms that are at play. In other words, we would like to know more about how PFA affects SWB. Another limitation of this study is the that the data contains reports of “most important source” of advice, instead of a “use/not use” question for indication the use of PFA. In addition, limited information is available on specific personal circumstances and the type of financial advice that is provided. Likewise, our data does not include information on either the relation between advisor and household or on the quality of the advisor. Future research capturing these variables and performing mediation analyses would therefore be worthwhile extensions for future research.

Our finding that regarding PFA as most important source when making financial decisions may be inspiring from both a managerial as policy making view. As productivity and consumption tend to increase when people are happier, it may be worthwhile stimulating them to engage with PFA when making important financial decisions. This may, for example, be achieved through incorporating the use of PFA in employee benefits programs and poverty alleviation programs pointing out these well-being benefits. More generally, this could be achieved by increasing accessibility to PFA, for example by subsidizing PFA for certain groups or granting tax allowances when engaging with PFA. Furthermore, as the relation between PFA and SWB is more positive for those who find themselves not or not very financially knowledgeable, policymakers could focus on these groups to stimulate them to engage with PFA.

By obtaining more knowledge about the mechanisms through which PFA has an effect on SWB (as shown in this research) in future research, the road that leads to greater happiness when engaging with PFA becomes clearer and with that, policymakers should be better positioned to assess more precisely in which way and for which groups the use of PFA should be stimulated.