Causal effects of financial education intervention aimed at University students on financial knowledge and financial self-efficacy

Salas-Velasco, Manuel Article Causal effects of financial education intervention aimed at University students on financial knowledge and financial self-efficacy Journal of Risk and Financial Management Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Salas-Velasco, Manuel (2022) : Causal effects of financial education intervention aimed at University students on financial knowledge and financial self-efficacy, Journal of Risk and Financial Management, ISSN 1911-8074, MDPI, Basel, Vol. 15, Iss. 7, pp. 1-16, https://doi.org/10.3390/jrfm15070284 This Version is available at: https://hdl.handle.net/10419/274806 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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Causal Effects of Financial Education Intervention Aimed at University Students on Financial Knowledge and Financial Self-Efficacy. Journal of Risk and Financial Management 15: 284. https://doi.org/10.3390/jrfm15070284 Academic Editor: Lucy F. Ackert Received: 2 June 2022 Accepted: 22 June 2022 Published: 27 June 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the author. 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/). Journal of Risk and Financial Management Article Causal Effects of Financial Education Intervention Aimed at University Students on Financial Knowledge and Financial Self-Efficacy Manuel Salas-Velasco Department of Applied Economics, Campus Cartuja, University of Granada, 18071 Granada, Spain; [email protected] Abstract: Based on a randomized controlled experiment among final-year undergraduate students, we provide an assessment of the treatment effects of financial education intervention focused on debt-financed graduate education decision-making. Specifically, this study finds positive treatment effects on both college seniors’ objective financial knowledge and subjective financial knowledge and self-confidence (i.e., perceived financial self-efficacy). Individual financial well-being is thought to be enhanced by improved financial knowledge test scores and perceived financial self-efficacy. In addition, we carry out a causal mediation analysis to investigate the extent to which objective financial knowledge plays a mediating role in the effect of financial education treatment on the intervention outcome (perceived financial self-efficacy). The mediation proportion, the proportion of treatment effect on outcome explained by the intermediate variable of financial knowledge, is around 21%, which is important. Thus, policies that aim to improve financial capabilities among college students through financial education programs should be aware that financial literacy is a significant antecedent of (a prerequisite for) financial self-efficacy. Keywords: financial education; financial literacy; financial self-efficacy; causal mediation analysis; randomized controlled experiment 1. Introduction Financial education programs aimed at university students to help them make sound financial decisions when incurring student loan debt are necessary and vital in the context of a considerable increase in the number of students borrowing to finance educational expenditures (Avery and Turner 2012), but also in which the default rates on student loans have been steadily climbing (Mueller and Yannelis 2019). These initiatives should show students explicit costs and risks associated with taking out loans and the consequences of debt financing their education. Experts say knowing the dangers of overborrowing and how to repay loans can help tackle student debt (Bidwell 2013). Yet, the reality is that nowadays most undergraduate and graduate students lack financial literacy and student loan literacy (Kantrowitz 2019). 1 Many authors already agreed that students do not have sufficient knowledge about loans and need more or better information (e.g., Holland and Healy 1989). Further, many parents of college-aged students are poorly equipped to provide financial guidance for their children due to their own lack of experience in managing high amounts of education debt (Brady et al. 2021). Students often misunderstand financial aid packages, which translates into poor financial decision-making (Rothstein and Rouse 2011). In this regard, in a qualitative study with a sample of students enrolled in a graduate degree program in public and private not-for-profit institutions in California, Dorado (2014), almost a quarter of the study participants lacked an understanding of student loan borrowing and 88% of the participants who borrowed student loans lacked knowledge of loan repayment. A similar result was found by Johnson et al. (2016), in their qualitative study many students indicated unfamiliarity with their loans and anxiety about paying them off. The Financial J. Risk Financial Manag. 2022,15, 284. https://doi.org/10.3390/jrfm15070284 https://www.mdpi.com/journal/jrfm J. Risk Financial Manag. 2022,15, 284 2 of 16 Literacy and Education Commission (FLEC) also reported that many students do not fully understand student loans or available repayment plans (Financial Literacy and Education Commission 2019). Nevertheless, financial knowledge alone is insufficient to gain the necessary understanding of what someone is capable of in terms of making financial decisions (Amagir et al. 2020). In this regard, various studies have shown that greater financial knowledge can contribute, but does not guarantee, that individuals make adequate financial decisions (e.g., Friedline and West 2016). An individual also needs a sense of self-assuredness, or self-belief, in their own capabilities. This personal attribute is known within the psychology literature as “self-efficacy” 2 . It is expected that financial literacy is to be a key antecedent of financial self-efficacy, which in turn may influence financial behaviors (Singh et al. 2019). One of the first works in this regard that focused on university students was that of Heckman and Grable (2011). These authors used a sample of college students enrolled at a midwestern U.S. university and the results from the path analysis showed a positive association between financial knowledge and self-efficacy: more knowledgeable college students (tested on a 20-item personal finance quiz) had higher levels of perceived self-efficacy (how confident they felt about making decisions that dealt with money). More recently, the path analysis by Herawati et al. (2020) showed a direct effect of financial literacy on financial self-efficacy among undergraduate accounting students in Bali. Kartawinata et al. (2021), using a sample of Indonesian college students, showed that financial literacy has a significant effect on financial self-efficacy, which in turn has a significant effect on financial inclusion. Finally, Liu and Zhang (2021) investigated the mediating mechanisms in the relationship between Chinese college students’ financial literacy and risky credit behavior. Financial self-efficacy partially mediated the relationship between financial literacy and risky credit behavior. College students’ objective financial literacy was positively related to their financial self-efficacy. Nonetheless, very few academic papers have focused on student loan decision-making. Among these, the work of Shim et al. (2019) demonstrated that individuals with greater financial self-efficacy perceived less difficulty in repaying their student loans and, in turn, experienced less loan-related stress. More recently, Brady et al. (2021) examined factors associated with financial self-efficacy among student loan borrowers in the United States; their results showed that perceived student loan literacy prior to accruing higher education debt was significantly associated with financial selfefficacy. In truth, the literature on self-efficacy is abundant in psychology and related fields (e.g., Maddux and Gosselin 2012), but it has not been until recently that researchers have begun to study the concept of self-efficacy within the finance domain. In addition to the publications focused on university students that we have just cited, we summarize other key general contributions to the literature. First, we highlight the work of Farrell et al. (2016) who, using a 2013 survey of Australian women, showed that financial self-efficacy arises as one of the strongest predictors of the type and number of financial products that a woman holds. Specifically, their analysis revealed that women with higher financial self-efficacy, i.e., with greater self-assuredness in their financial management capacities, are more likely to hold investment and savings products, and less likely to hold debt-related products. 3 Second, Rothwell et al. (2016), using a national sample of low-income Canadians, showed that the association between objective financial knowledge and retirement saving and emergency saving passed through financial self-efficacy. Thus, these authors advocated that improving objective financial knowledge is necessary but not sufficient to build financial capability. Third, the results of Mindra et al. (2017) showed a strong positive and significant relationship between financial self-efficacy and financial inclusion among individual financial consumers in Uganda. Their results suggested that, when an individual possesses high levels of confidence to manage tasks specifically related to financial services, it indicates higher financial inclusion (access to and use of financial products and services). Finally, the structural equation model results by Asebedo et al. (2019) revealed that financial self-efficacy directly explains saving behavior and is central to J. Risk Financial Manag. 2022,15, 284 3 of 16 understanding the link between other psychological characteristics and the saving behavior of older U.S adults. However, the literature reviewed above has been based on correlational studies, and confusing correlation with causality is a critical flaw (Hathaway and Khatiwada 2008). The causal effects of financial education programs (i.e., their impact on financial outcomes) can only be evaluated experimentally. That is, we must separate “impact studies” (e.g., experiments) from “observational studies” (e.g., econometric analysis) (Miller et al. 2015). The novelty of the scientific approach of our study is that it uses a randomized controlled trial that allows us to evaluate the effectiveness of a financial education program aimed at college seniors in making the decision to finance a master’s degree with a graduate loan. In particular, the main objective of the article was to evaluate the impact of the educational intervention on financial knowledge and financial self-efficacy, variables that precede the intention to apply for a graduate student loan. Furthermore, we wanted to investigate to what extent objective financial knowledge plays a mediating role in the effect of the financial education treatment on the perceived financial self-efficacy. To this end, we propose causal mediation analysis, which has recently been used in medical research and psychology, but its use is practically non-existent in behavioral finance. The remainder of this paper is organized as follows. In Section 2, the study undertaken is justified and the main research questions to be answered are raised. Section 3summarizes the experimental design. Next, measures of financial knowledge and financial self-efficacy are introduced in Section 4. In Section 5, we evaluate the impact of the financial education intervention. In Section 6, we undertake causal mediation analysis to study the mediating role of financial literacy in the relationship between financial education and financial self-efficacy. The main conclusions are presented in Section 7. 2. Research Purpose and Rationale Financial education initiatives aim to improve people’s ability to process economic information to make informed financial decisions (financial knowledge), as well as their self-assessment of their own financial capability (financial self-efficacy) (Rothwell and Wu 2017). At higher education level, the extent to which financial education programs improve financial knowledge, financial self-efficacy, and financial behaviors is of primary interest to policymakers and higher education institutions alike. In the context of substantially higher tuition fees and the consequent increase in financing higher education with educational loans, better financial knowledge and self-efficacy could help improve financial decisionmaking among university students in relation to the possibility of taking out a student loan, avoiding situations of overborrowing or, at the other end of the spectrum, stopping studying if doing so implies financing the studies with debt but the individual lacks the knowledge and ability to successfully make the decision. However, limited research has been carried out into how financial education impacts outcomes such as financial knowledge and self-efficacy (Rothwell and Wu 2017). The causal mechanisms through which financial education operates are not well understood because it is difficult to separate correlation from causation (Carpena and Zia 2020). True experiments with random assignment of individuals to treatment and control groups are considered the gold standard for evaluating program effects and avoiding self-selection bias (Rossi et al. 2004). “Experiments are commonly designed to find out whether a certain kind of treatment has an effect or not” (Urbach 1985, p. 256). In financial education programs, the null hypothesis assumes that the intervention does not affect the financial knowledge and other financial outcomes such as attitudes, self-efficacy, and the behavior of the people subjected to the treatment (Miller et al. 2015). For example, Kaiser and Menkhoff (2019), in an updated meta-analysis of experimental studies of school financial education programs, found that financial education treatments have, on average, sizeable impacts on financial knowledge among students, although smaller effects on financial behaviors. Kaiser and Menkhoff (2019) only found 18 interventions using randomized control trials (RCTs) and focused on financial education in schools. Indeed, we must recognize that there is still little empirical evidence of the J. Risk Financial Manag. 2022,15, 284 4 of 16 positive causal effects of financial education programs at the personal level (Hastings et al. 2012). Lusardi and Mitchell (2014) already reported that few empirical studies can be considered serious evaluations of the effectiveness of financial education programs. Additionally, randomized experiments studying the impact of financial education on the financial decision-making of university students are practically non-existent. The present study attempts to fill that existing gap in the literature and its main contribution is to assess the effects of financial education intervention focused on debt-financed graduate education decision-making. The evidence comes from a randomized controlled experiment in which college seniors were given online training on the convenience of pursuing a master’s degree, using cost–benefit analysis, and the suitability of taking out a student loan to fund the graduate degree program. To our knowledge, this is the first randomized experiment targeting undergraduates in their decision making about graduate studies. This study conducts hypothesis testing and analyzes the causal relationship between related variables in order to answer three key research questions: (i) What is the association between financial education intervention and financial knowledge; (ii) What is the association between financial education intervention and financial self-efficacy; (iii) Is there an indirect effect of financial education intervention on financial self-efficacy via financial knowledge. Specifically, relying on a control group in the estimation of intervention impacts, this article aimed to evaluate: (i) Treatment effects on financial knowledge (i.e., performance on a standardized financial knowledge test); (ii) Treatment effects on subjective financial knowledge and self-confidence (i.e., perceived financial self-efficacy). Regression analysis was used to examine the impact of financial education on outcome variables, allowing for pre-treatment covariates. The study also contributes to a better understanding of financial knowledge-financial self-efficacy relationships (i.e., whether financial literacy is an antecedent of financial self-efficacy, as established in the literature). In this regard, we wanted to test whether an increase in perceived financial self-efficacy can be explained by the effect of the treatment alone or also by a greater objective financial knowledge that was in turn increased by the intervention. To formalize causal effects that can answer such a research question, we propose the use of causal mediation analysis (CMA), a formal statistical framework by which a researcher can assess the relative magnitude of these direct and indirect effects, which is rapidly growing in popularity in economics and finance, especially in experimental work (Celli 2022). In program evaluation, CMA has primarily focused on the question of whether or not a program, or package of policies, has an impact on the targeted outcome of interest (Keele et al. 2015). 3. Experimental Design In order to answer our research questions, we used data from the so-called FUNCAS research project. 4 Data were collected experimentally at the beginning of the 2019/2020 academic year at the business school of a southern Spanish university. Around 70% of the total number of college seniors enrolled at the business school participated in the experiment. 5 As part of the experiment, participants were randomly assigned to treatment and control groups. Specifically, two-thirds were assigned to what we named experimental group 1 and experimental group 2, while the other third formed the control group (Table 1). Table 1. Sample summary: Distribution of experiment participants. Frequency Percentage Experimental group 1 183 34.86 Experimental group 2 180 34.29 Control group 162 30.86 Total experiment participants 525 100.00 Source: author’s elaboration J. Risk Financial Manag. 2022,15, 284 5 of 16 During the experiment session, students had to complete two activities. The first one was structured in three parts. In Part I, experimental subjects were exposed to several stimuli. Experimental group 1 received a short online course about: (a) How to calculate the viability from an economic point of view of the investment in a master’s degree; (b) How to finance the master’s degree by requesting a student loan. In addition to the same economic and financial training, experimental group 2 received a stimulus consisting of information on the so-called availability bias (or availability heuristic). 6 It was briefly explained to them that it is a bias that may affect the decision of requesting a loan for a master’s degree, and they were recommended to base their decision on reliable and verified sources of information as well as expert advice. After the intervention (Part II), experiment participants were given a case study and they had to answer six objective questions about financial knowledge related to the case study. Additionally, they had to rate on a sevenpoint Likert scale several statements related to variables that precede the decision to request a student loan to pursue a master’s degree. In Part III, some sociodemographic questions and academic performance indicators were included. The control group was composed of participants who did not receive the experimental treatment and they started from the beginning of the experiment with Part II and then Part III.7 The second activity was carried out in an online behavioral economics lab in the last 15 min of the experiment. All subjects, including the control group, completed a series of experimental tasks aimed to determine their personality traits such as risk preferences, loss aversion, or cognitive reflection. Finally, we would like to highlight that participation in the experiment was voluntary and encouraged through economic rewards assigned by lottery, and the amount of money depended on the number of correct answers the winning participant had to certain questions raised in the second part of the first activity and the second activity of the experiment. 4. Measures of Financial Knowledge and Financial Self-Efficacy As part of the experiment, objective assessments of financial knowledge along with self-assessed financial knowledge and self-confidence (i.e., perceived financial self-efficacy) were carried out in the treatment and control groups. After the intervention, in Part II of the first activity (Part I for the control group), all participants were presented with a case study related to the possibility of pursuing a master’s program aimed at recent college graduates. They were provided with information on the direct costs of a master’s degree and cost of living for the year of completion of the program, data on the labor market in the two options of pursuing a master’s degree or not (earnings and employability rates associated with different levels of degree completion), and information on financial aid in the form of a graduate student loan offered by a financial institution. Typically, financial knowledge is objectively measured with a series of exam-style questions that are then scored as correct or incorrect. The more items correct, the higher the financial knowledge. In the FUNCAS experiment, all subjects were asked to respond to six objective multiple-choice questions related to the case study (Figure 1). The participants had economic incentives to make a concerted effort in their calculations, since if they got the answer correct they would enter a draw and could win up to 25 euros for each correct answer. The researchers of the FUNCAS project developed an ad hoc test to assess the level of financial knowledge of the participants because the “Big Three” financial literacy questions of Lusardi and Mitchell (2011), the most widely used test globally to assess the level of financial literacy of a country, was not suitable in the context of making investment and financing decisions in graduate studies. 8 It was pilot tested in several undergraduate classes in the academic year prior to the implementation of the experiment. J. Risk Financial Manag. 2022,15, 284 6 of 16 J. Risk Financial Manag. 2022, 15, x FOR PEER REVIEW 6 of 17 the level of financial knowledge of the participants because the “Big Three” financial literacy questions of Lusardi and Mitchell (2011), the most widely used test globally to assess the level of financial literacy of a country, was not suitable in the context of making investment and financing decisions in graduate studies.8 It was pilot tested in several undergraduate classes in the academic year prior to the implementation of the experiment. 1. Calculation of direct and opportunity costs of pursuing the master’s degree. 4. The total amount of interest on a student loan according to the repayment term. 2. Calculation of the expected income differential as a graduate. 5. Student loan installment based on borrowing capacity. 3. Calculation of the net present value (NPV) of the investment in the master’s degree. 6. Calculation of cash surplus. Figure 1. Objective financial knowledge measurement in the experiment. Source: author’s elaboration. Table 2 provides the results. As can be seen in Table 2, the average number of correct answers was 2.72 (S.D. = 1.35). Only 2.9% of the participants (n = 525) answered the six questions correctly, approximately 16% answered only one of them correctly and nearly 4% answered none of them correctly. Table 2. Number of correct answers in the objective financial knowledge test. Number of Correct Answers Freq. Percentage 0 20 3.8 1 83 15.8 2 126 24.0 3 150 28.6 4 101 19.2 5 30 5.7 6 15 2.9 Total 525 100.0 Mean 2.72 Std. Dev. 1.35 Source: author’s elaboration After testing their financial knowledge, all participants were next instructed to assume that a master’s degree was viable from an economic point of view and they had funds available for an amount equivalent to 50% of its total cost,9 but they were able to obtain financial aid in the form of a graduate student loan, according to the bank’s financing conditions shown in the experiment. Participants then had to respond to various subjective items on a seven-point Likert scale about their perceived control over applying for a student loan to pursue a master’s degree. In particular, the FUNCAS project research team developed a 3-item financial self-efficacy scale specific to debt-financed graduate education decision-making. As can be seen in Table 3, the perceived financial self-efficacy scale was intended to measure students’ beliefs about their abilities to achieve and succeed in making a decision about applying for a graduate student loan. Bandura’s concept of self-efficacy provided the theoretical framework: “Perceived self-efficacy is a judgment of one’s ability to organize and execute given types of performances” (Bandura 1997, p. 21). Financial self-efficacy is thus the extension of efficacy to the area of financial management Figure 1. Objective financial knowledge measurement in the experiment. Source: author’s elaboration. Table 2provides the results. As can be seen in Table 2, the average number of correct answers was 2.72 (S.D. = 1.35). Only 2.9% of the participants (n= 525) answered the six questions correctly, approximately 16% answered only one of them correctly and nearly 4% answered none of them correctly. Table 2. Number of correct answers in the objective financial knowledge test. Number of Correct Answers Freq. Percentage 0 20 3.8 1 83 15.8 2 126 24.0 3 150 28.6 4 101 19.2 5 30 5.7 6 15 2.9 Total 525 100.0 Mean 2.72 Std. Dev. 1.35 Source: author’s elaboration After testing their financial knowledge, all participants were next instructed to assume that a master’s degree was viable from an economic point of view and they had funds available for an amount equivalent to 50% of its total cost, 9 but they were able to obtain financial aid in the form of a graduate student loan, according to the bank’s financing conditions shown in the experiment. Participants then had to respond to various subjective items on a seven-point Likert scale about their perceived control over applying for a student loan to pursue a master’s degree. In particular, the FUNCAS project research team developed a 3-item financial self-efficacy scale specific to debt-financed graduate education decision-making. As can be seen in Table 3, the perceived financial self-efficacy scale was intended to measure students’ beliefs about their abilities to achieve and succeed in making a decision about applying for a graduate student loan. Bandura’s concept of self-efficacy provided the theoretical framework: “Perceived self-efficacy is a judgment of one’s ability to organize and execute given types of performances” (Bandura 1997, p. 21). Financial selfefficacy is thus the extension of efficacy to the area of financial management and involves understanding patterns of attitudes, beliefs, and confidence in relation to financial decisions and behaviors (Rothwell and Wu 2019). As can be seen in Table 3, the mean score of the participants is below the central point of the scale, which reflects a relatively low perceived self-efficacy of the individuals to make the decision of indebtedness (request a loan for graduate studies).10 J. Risk Financial Manag. 2022,15, 284 7 of 16 Table 3. The decision to apply for a graduate loan: Perceived financial self-efficacy. Obs. Mean S.D. Range 525 3.903 1.146 1–7 1. My level of financial knowledge regarding the decision to apply for a student loan to pursue a master’s degree is: Very low 1–2–3–4–5–6–7 Very high 525 3.823 1.324 1–7 2. For me, making the decision about requesting a student loan to pursue a master’s degree is: Extremely difficult 1–2–3–4–5–6–7 Extremely easy 525 3.438 1.419 1–7 3. Rate from 1 (totally disagree) to 7 (totally agree) the following statement: I am confident that I can make the best decision about whether to apply for a student loan to pursue a master’s degree 525 4.450 1.587 1–7 Cronbach’s alpha = 0.7021 Cronbach’s alpha assesses the internal consistency of the scale items. The scale has an adequate internal consistency because of a Cronbach’s alpha coefficient equal to or greater than 0.70 is considered “acceptable” in most social science research situations (Hair et al. 2013). In bold: the mean value of the scale. Source: author’s elaboration 5. Impact Evaluation of Financial Education Intervention Financial education program evaluation is the process of systematically assessing the implementation of a financial education intervention (National Endowment for Financial Education 2016). Is there a significant change in participants’ financial outcomes before and after program participation? For estimating causal effects (impact of financial education), we are interested in the difference between treatment and control conditions. One of the more common ways of estimating causal effects with experimental data in many disciplines is based on regression methods (Imbens and Rubin 2015). We can write the following regression equation for the outcome measure (dependent variable): Yi=α+θTi+Xiβ+errori(1) Equation (1) includes the indicator variable for the receipt of treatment ( Ti ) and additional pre-treatment variables ( Xi represents the vector of pre-treatment covariates). It is important to highlight that it is appropriate to only allow for pre-treatment predictors when estimating causal effects in experiments (Gelman and Hill 2006). The parameters of the regression equation are estimated by least squares, with the primary focus on the coefficient for the treatment indicator (Imbens and Rubin 2015). Using separate regressions for outcomes Y i (financial knowledge and financial selfefficacy), our randomized experiment allows us to estimate average treatment effects (ATE) on financial outcomes by comparing each treatment arm against the control arm. The average causal effect can be identified as the observed difference in mean outcomes between the treatment and control groups. The results of ordinary least square (OLS) regressions are shown in Table 4. 11 Descriptive statistics and variable description can be found in Table A1 in the Appendix A. Table 4shows the estimated coefficients for treatments, controlling pre-treatment covariates of gender, academic ability, and majors. On the one hand, Model I estimates causal treatment effects of financial education on objective financial knowledge. The dependent variable of interest, Yi , takes values from 0 to 6 depending on the number of correct responses to the questions shown in Figure 1. According to Model I, both treatments increased financial knowledge in relation to the control group (the estimated coefficients associated with treatment dummies are positive and statistically significant). Specifically, once we allow for gender, academic ability, and majors, experimental subjects in treatment group 1 answered correctly on average 0.65 more questions than those in the control group, and experimental subjects in treatment group 2 answered correctly on average 0.74 more J. Risk Financial Manag. 2022,15, 284 8 of 16 questions than those in the control group. 12 However, the difference between the two coefficients is not statistically significant (test shown at the bottom of Table 3). On the other hand, the results of the econometric estimation of Model II also reveal that financial education can be effective by increasing financial self-efficacy (greater perceived financial knowledge and self-confidence) in student loan decision-making. In the estimation, for each participant, the dependent variable of interest ( Yi ) was the mean value of the 3item financial self-efficacy scale shown in Table 3. Once more, the difference between the two treatment coefficients is not statistically significant (test shown at the bottom of Table 4). In summary, the results of this section show that financial education aimed at university students is effective, increasing not only their objective financial knowledge but also increasing their perceived financial self-efficacy. Our main results are of high relevance for policymakers because there is a public debate questioning the effectiveness of financial education interventions (e.g., Fernandes et al. 2014). Table 4. Financial education for decision making on graduate studies: Assessing the intervention effectiveness. Model I Model II Coef. Robust Std. Err. Coef. Robust Std. Err. Control group Ref. cat. Ref. cat. Experimental group 1 0.647 *** 0.136 0.316 ** 0.121 Experimental group 2 0.739 *** 0.142 0.354 ** 0.123 Gender (=1 female) −0.421 *** 0.111 −0.478 *** 0.097 Academic ability 0.362 *** 0.082 −0.024 0.068 Majors (=1 Finance and Accounting) 0.612 ** 0.186 0.820 *** 0.134 Constant −0.053 0.560 3.997 *** 0.455 Number of obs. 525 525 F (5, 519) 14.83 *** 14.01 *** R-squared 0.128 0.105 Dependent variable Correct answers in the objective financial knowledge test Average scores on the perceived financial self-efficacy scale Testing the equality of two coefficients H0:β1and β2are not statistically different F(1, 519) 0.49 0.12 Prob. > F 0.483 0.730 0.647 and 0.739 are not statistically different 0.316 and 0.354 are not statistically different *** p< 0.001 ** p< 0.01 Source: author’s elaboration Although our results show that online financial education can be effective in increasing financial knowledge, we cannot directly compare them with other published studies. The main reason is that financial education experiments targeting undergraduate students on taking out graduate loans are practically non-existent. We have only found a couple of academic works that experimentally demonstrate the effectiveness of online resources in increasing the financial knowledge of the subjects. In an important experiment by Heinberg et al. (2014), a representative sample of the U.S. population was exposed to videos explaining basic financial concepts such as compound interest, risk diversification, and inflation. Compared to a control group that received no such training, the subjects exposed to the informational videos were more knowledgeable and better able to answer J. Risk Financial Manag. 2022,15, 284 15 of 16 Gelman, Andrew, and Jennifer Hill. 2006. Causal inference using regression on the treatment variable. In Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press, pp. 167–98. 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