Spillover effects of financial education: The impact of school-based programs on parents

Frisancho Robles, Verónica Working Paper Spillover effects of financial education: The impact of school-based programs on parents IDB Working Paper Series, No. IDB-WP-1452 Provided in Cooperation with: Inter-American Development Bank (IDB), Washington, DC Suggested Citation: Frisancho Robles, Verónica (2023) : Spillover effects of financial education: The impact of school-based programs on parents, IDB Working Paper Series, No. IDB-WP-1452, InterAmerican Development Bank (IDB), Washington, DC, https://doi.org/10.18235/0004736 This Version is available at: https://hdl.handle.net/10419/289963 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/3.0/igo/legalcode Spillover Effects of Financial Education: The Impact of School-based Programs on Parents Verónica Frisancho IDB WORKING PAPER SERIES Nº IDB-WP-1452 February 2023 Department of Research and Chief Economist Inter-American Development Bank February 2023 Spillover Effects of Financial Education: The Impact of School-based Programs on Parents Verónica Frisancho Inter-American Development Bank Cataloging-in-Publication data provided by the Inter-American Development Bank Felipe Herrera Library Frisancho Robles, Verónica C. Spillover effects of financial education: the impact of school-based programs on parents / Veronica Frisancho. p. cm. — (IDB Working Paper Series ; 1452) Includes bibliographic references. 1. Financial literacy-Peru. 2. Youth-Peru-Finance, Personal. 3. Credit bureausPeru. I. Inter-American Development Bank. Department of Research and Chief Economist. II. Title. III. Series. IDB-WP-1452 Copyright © Inter-American Development Bank. This work is licensed under a Creative Commons IGO 3.0 AttributionNonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license (http://creativecommons.org/licenses/by-nc-nd/3.0/igo/ legalcode) and may be reproduced with attribution to the IDB and for any non-commercial purpose, as provided below. No derivative work is allowed. Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC-IGO license. 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The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent. http://www.iadb.org 2023 Abstract This paper studies whether school-based financial education has spillover effects from children to parents. Leveraging data from a large-scale experiment with public high schools in Peru and credit bureau records on the parents of the youth targeted, this study measures the impact of providing personal finance l essons d uring secondary school on parental financial b ehavior. Financial education lessons in the school yield limited average spillover effects, but lead to sizable effects on parental financial behavior within disadvantaged households. Among parents from poorer households, the treatment reduces default probability by 26%, increases credit scores by 5%, and increases current debt levels by 40%. The treatment has stronger effects among the parents of daughters, who experience a significant 6.7% increase in their credit score and a 28% reduction in their loan portfolio in arrears. Among the parents of boys, most of the spillover effects are muted. Keywords: Financial Education, Youth, Spillovers, Financial Literacy, Credit records, Treatment Effects, Long-lasting impacts JEL Codes: C93, D14, G53, O16 1 1 Introduction Financial education has proven to be very effective to both increase financial knowledge and positively affect financial choices (14). Virtually all governments that have developed a financial inclusion strategy have included financial education as a key component. However, the challenge of reaching vulnerable adult populations persists. On one hand, it is difficult for large-scale financial education programs to achieve high levels of take up (7). Even those in greater need of the content may fail to attend in person or even online sessions due to competing uses of their time. On the other hand, national governments tend to face budget restrictions that limit the scope of their work. Even though financial education programs tend to be cost-effective (14), they still compete for resources with investments in other sectors such as education, health, or social protection. The literature supports the intergenerational impact of parental human capital on children’s outcomes. However, the reverse link has been relatively unexplored, despite the potential that children may have to deliver information and knowledge and, ultimately, influence household choices. This paper argues that investing in school-based financial education is a cost-effective way to reach adults. Leveraging data from a large-scale randomized experiment with public high schools in Peru (11), this study investigates whether financial education programs delivered in the classroom have spillover effects on parental financial outcomes. Relying on credit bureau records on over 10,000 parents of the children in the experimental sample, this paper supports the presence of intergenerational spillover from children to parents, specially within poorer households and among the parents of daughters. The data used in this paper comes from an impact evaluation of a school-based financial education program targeting grades nine through eleven. The experimental sample included almost 20,000 students in 300 schools from six regions of the country who were tested and surveyed twice during the 2016 academic year, before and after the delivery of the lessons. Parents were not directly targeted by the intervention and were thus not tested on their financial knowledge or surveyed on their financial habits. However, baseline survey records include the full name of the students’ parent or guardian. These identifiers were provided to EQUIFAX, a private credit bureau, who used both first and last names to match parents with their credit records in October 2019. Credit bureau records provide information on credit access and delinquency for the parents of the children in the experimental sample more than three years after the intervention was launched. Financial education lessons in school yield limited average spillover effects on parental financial outcomes, but they lead to sizable intergenerational spillovers from children to parents within poorer households. On average, parents of treated students significantly increase their current debt levels three years after the intervention took place, but this effect does not survive multiple hypothesis testing. The positive spillover effects are more salient and robust among parents from poorer 2 households for whom the treatment reduces default probability by 26%, increases credit scores by 5%, and increases current debt levels by 40%. Heterogeneous treatment impacts by sex of the student suggest that parents are more receptive to girls in relation to money management advice. The financial education lessons have stronger spillover effects among the parents of daughters, who exhibit a significant 6.7% increase in their credit score and a 28% decrease in the size of the portfolio in arrears. The spillover effects among parents of boys are mostly muted; the only significant effect of the treatment is a 3.3 percentage point reduction in the probability of holding outstanding debt. This study contributes to the scarce literature that studies the role of children in parental human capital accumulation. Two notable studies rely on quasi-experimental variation in education investments to measure the degree of upward intergenerational transmission of human capital (16, 15). This study exploits credible random variation in children’s human capital levels to provide evidence on the intergenerational transmission of financial skills from high schoolers to their parents. This study builds on (6), the only other study providing experimental evidence on spillovers from students to parents in terms of financial outcomes, and goes a step forward in at least three ways. First, this study tracks parents over a longer period of time, with over three years between the treatment delivery and the measurement of financial outcomes. This longer term view gives more time to allow the newly acquired knowledge to be shared with the parents and have youth participate more actively in the household’s financial choices. Second, this study focuses on credit bureau administrative records that overcome misreporting biases present in self-reported survey data. Third, the focus on credit and repayment outcomes complement the results in (6), who look at the spillover effects of school-based financial education on parents’ probability of preparing a budget, probability of saving, and the share of income saved. The remainder of this article is organized into five sections. Section 2 goes over the related literature. Section 3 presents the experimental design and describes the data sources. Section 4 presents the estimation strategy and the main results and Section 5 concludes. 2 Literature Review Human capital accumulation models usually assume away that offspring’s human capital may have spillover effects on parents or other adults in the home. While there is extensive literature on the intergenerational transmission of human capital from parents to children including (5, 24, 20, 4, 8), much less is known about a potential reverse link, where children’s education or health status influence parental outcomes. Two notable exceptions rely on quasi-experimental variation in children’s education investments to assess their impact on parental human capital. (16) relies on the variation introduced 3 by a compulsory schooling reform in Sweden to study the causal effect of children’s schooling on their parents’ longevity. The authors do not find an average impact of children’s education on their parents’ longevity, but they identify heterogeneous effects by gender: female schooling increases the longevity of fathers, particularly in poorer households. In turn, (15) shows that children’s acquisition of human capital can also discourage adults living with them to make a similar investment. Exploiting variation in compliance with a school reform that replaced bilingual education with English immersion, the authors find that English instruction increased children’s English proficiency, but reduced that of the adults living with them. This result suggests that adults lean on their children’s English skills instead of trying to learn the language themselves. More recently, (6) has focused on the specific case of financial skills. They rely on experimental variation in children’s financial literacy, which is introduced by a financial education program targeting high school students in Brazil, and measure upward spillovers. The authors rely on parents’ self-reported records collected through a survey a year after the treatment delivery and find meager impacts of school-based financial education on parental financial behavior.1 Another strand of this literature focuses on the role of children in household choices. (10) tests the predictions of the collective model using expenditures data in the UK and shows that adolescents living with their parents influence household consumption choices. This effect is stronger among children ages 16 to 21 and daughters, irrespective of their age. (3) rely on instrumental variables to test if the provision of broadband to schools fosters household internet adoption in Portugal. The authors find that broadband use in schools led to a year-over-year increase of 3.5 percentage points in internet adoption in households with children. 3 Experimental Design 3.1 Context The PISA 2015 assessment of financial literacy exposed the poor levels of financial literacy among youth in Peru. Fifteen year old students in Peru scored below the average of the 10 OECD countries and economies that were assessed in 2015. In fact, Peru ranked next-to-last, only surpassing Brazil. Almost half of students in Peru performed at level 1 (compared to 22% among OECD countries and economies), which is below the baseline level of proficiency in financial literacy that is required to participate in society. Only 1% of students in Peru are top performers (compared to 12% on average across OECD countries and economies) (18). Peru’s poor performance in financial literacy is one of the drivers of low levels of financial 1It should be noted that the experiment in Brazil tried to directly target parents through an adult financial education workshop, but attendance levels were very low. 4 inclusion, particularly among poor and informal segments of society. While gaps in access persist, the demand for financial services is still limited. This is partly explained by distrust in financial institutions as well as low levels of financial literacy that only deepen trust issues.2 In 2015, the Peruvian government launched the National Financial Inclusion Strategy, which included, as a high-priority goal, the provision of financial education as a key policy to foster usage of financial services. A key sub-goal in this agenda was the delivery of school-based financial education to all primary and secondary students by 2021. 3.2 The Intervention Following the launch of Peru’s National Financial Inclusion Strategy in 2015, the Ministry of Education (MINEDU), the Superintendency of Banks and Insurance (SBS), and the Center of Studies (CEFI) of the Peruvian Association of Banks joined forces to develop and implement a financial education program targeting high school students in grades 9 through 11. The program was implemented in full-day public high schools in urban areas in six regions of the country: Lima and Callao, Arequipa, Piura, Junin, Puno, and San Martin. The treatment consisted of the delivery of financial education lessons during the regular school day. Teachers of the course “History, Geography, and Economics” (HGE) were asked to deliver the lessons during their regular lecture time. The suggested number of hours required to cover all the lessons in the workbooks varied by grade: 16 hours in 9th grade, 24 hours in 10th grade, and 32 hours in 11th grade. The implementation partners developed materials and activities to support teachers in the delivery of the lessons. First, they developed workbooks following a grade-specific curriculum and using a mix of case analysis, exercises, group activities, and homework. The 9th grade curriculum focused on the differences between needs and resources as well as on budgeting. Tenth graders focused on financial products and services and forward-looking choices, while 11th graders covered topics on becoming a responsible financial consumer and access to/usage of personal information in financial markets. Second, teachers were provided with a hard copy of a teaching guide covering all grades. Finally, teachers were encouraged to attend a 20-hour training offered over the course of five days. Training participants received transport subsidies, a full meal during each session of the training, and a completion certificate that counted towards the evaluation of their performance. All intervention activities were conducted during 2016. Teachers’ training workshops took place between mid-February and March. The delivery of the lessons occurred during the second semester of the 2016 academic year, August through December. Students were tested on their 2The 2017 Global Financial Inclusion Database (FINDEX) collects data on the main reasons for not having a bank account in Peru. Lack of trust is the third top reason provided by respondents (39%), surpassed only by services being too expensive (58%) or lack of money (45%). 5 Greater usage of credit among low SES households suggests that their credit usage was not constrained by the credit market, but that it was instead limited due to their own demand. The material provided in the financial education program teaches children about the workings of the financial market and focuses on the way in which financial products and services can contribute to better management of personal finances. The material also provides students with examples about situations in which the use of credit is not advised and other cases in which it is welfare-improving. The transmission of this information to parents clearly affected the intensity of their use of credit. A positive average treatment effect on current debt suggests that poorer households had the possibility to rely more on credit before the treatment, but they were probably not aware that they could do so and/or were not able to identify productive uses of these services. The accompanying negative effect on the size of the loan portfolio in arrears confirms that the expansion of credit among poorer households was healthy and did not lead to overindebtedness. This result is aligned with cross-country evidence from (12). They show that usage of financial services is positively correlated with a country’s financial literacy level. More importantly, the average marginal effect of financial literacy on usage is higher for countries with lower private credit to GDP ratios. (16) show that the effects of children on parental human capital may be gendered, as they find that daughters’ education significantly impacted fathers’ longevity. This source of heterogeneity may also be relevant in the case of financial skills if daughters and sons interact differently with parents about money matters. While the treatment did not have differential effects on students’ participation levels on household finances by sex (see Table A2 in the Appendix), it may be that parents are more receptive to boys, since money management is traditionally associated with masculine traits. Alternatively, since adolescent girls are in general more mature than boys of the same age, their views and advice may be better received by parents. Table 4 presents the treatment impacts on parental credit outcomes by the sex of their offspring. The results show that the financial education program has stronger spillover effects among the parents of daughters. The treatment leads to a significant 6.7% increase in the credit score of the parents of female students. Within this sample, important changes in the loan portfolio are also recorded: the size of the portfolio in arrears goes down by 28%, while the amount of current debt increases by 18% (though this last effect is not significant). Parents of girls also record a slight decrease in the probability to have past-due debt. Among the parents of boys, most of the effects are muted. The only significant effect of the treatment is a reduction in the probability of holding outstanding debt by 3.3 percentage points. All in all, these results suggest that school-based financial education can have a multiplier effect on the adults surrounding the direct beneficiaries, particularly when focusing on specific this can be attributed to power issues, particularly in the case of debt outcomes. 12 Table 4 Treatment Impacts on Parents’ Credit and Delinquency Outcomes, by Students’ Sex Pr(Debt) Pr(Arrears) Credit Score Current Debt Debt Arrears Loans Other Loans Other (1) (2) (3) (4) (5) (6) (7) Panel A. Female Student Treatment 0.014 -0.010* -0.002 4.157** †0.173 -0.258* 0.022 (0.011) (0.006) (0.011) (1.657) (0.121) (0.132) (0.086) Number of Observations 5968 5968 5968 2793 2100 2100 2103 Number of schools 291 291 291 290 289 289 282 Mean in Control 0.352 0.061 0.349 61.243 8.192 1.369 6.460 Panel B. Male Student Treatment -0.033*** †† 0.001 -0.019 -1.810 0.081 0.090 0.082 (0.012) (0.005) (0.012) (1.775) (0.120) (0.118) (0.090) Number of Observations 5122 5122 5122 2396 1780 1780 1773 Number of schools 285 285 285 281 278 278 280 Mean in Control 0.362 0.047 0.356 64.190 8.434 0.995 6.419 Note: Credit and default outcomes measured in October 2019. Debt amounts are measured in US dollars and expressed using the inverse hyperbolic sine transformation. Low (high) SES is defined as having an asset index below (above) the median in the sample of parents. Stars denote significance levels (* 10%; ** 5%; *** 1%) based on unadjusted p-values. Daggers denote significance levels based on the Romano-Wolf adjusted p-values (†10%, †† 5%, †††1%) resulting from 1,000 bootstrap replications. Correction for multiple testing implemented for two families of outcomes: (i) probability of having debt, probability of having loan arrears, probability of having arrears from other bills, and credit score; and (ii) current debt, debt arrears in loans, and debt arrears from non-credit obligations. OLS estimates, standard errors clustered at the school level are reported in parentheses. All specifications include a set of dummy variables that correspond to the matched-pairs of schools and the following set of controls: student’s grade, household asset index, and sex, age, and education level of the parent. sub-groups. The sizeable impacts on the credit outcomes of parents from poorer households and with female offspring confirm that there is an intergenerational transmission of knowledge within the household. Natural interaction of the parents with their teenage children seems to ease access to financial knowledge for parents of sub-groups of students in the treatment group. While this study was not able to measure the impact on the knowledge of parents, the treatment effects on parental financial literacy in (6) suggest that adults are not leaning on their children to make choices, but that instead they are learning with them and applying this knowledge when making household financial choices. The heterogeneous results by SES highlight the opportunity that school-based financial education programs provide when trying to reach vulnerable segments of the population. On one hand, poorer individuals usually have lower levels of financial literacy (17). On the other hand, adults in poorer households are more likely to hold informal jobs and depend on variable revenue sources that imply high opportunity costs when directly targeting them as beneficiaries of financial education programs. Targeting their children provides a cost-effective mechanism to reach those facing relatively greater knowledge gaps. 13 The heterogeneous results by sex of the offspring suggest that daughters tend to be a more effective channel to transmit financial knowledge and information to parents. This result is interesting since the PISA 2018 results show that girls in Peru outperformed boys in reading, but were outperformed by boys in mathematics (2). Daughters greater influence over parental financial choices may thus be related to other household internal dynamics that position them as having a stronger voice in family money matters. These gendered effects, aligned with (16), may also be driven by the traditional view of women as being better suited to provide care to children and aging parents. Notice that the spillovers identified may be context specific, since a high share of high school students report that they either discuss household finances with their parents or directly contribute to the preparation of a family budget. Nevertheless, this is still a novel and valuable result since these spillover effects manifest in the absence of any direct guidance or instruction for students to share the content of the financial lessons with the adults in the household. This suggests that school-based financial education programs that explicitly involve parents (either through homework or by providing them with useful material relying on the children as messengers) may be effective in providing financial knowledge and information to adults. 5 Conclusion Since the 2008 financial crisis, the financial literacy agenda has become much more salient and has received increasing support from multilateral organizations, governments, and the private sector. While considerable progress has been made in providing financial education to children and youth in educational institutions, the challenge of reaching vulnerable adult populations persists. First, funding shortages limit both public and private large-scale initiatives. Second, capturing the interest of adults is quite complicated, as they may perceive low net returns due to high opportunity costs. This paper puts forward an alternative way to reach adults, particularly the most vulnerable for whom a bad financial choice may have larger negative effects on welfare. Leveraging data from a large-scale experiment with public high schools in Peru and credit bureau records on over 10,000 parents of the targeted youth, this paper supports the presence of intergenerational spillovers from children to parents. The positive spillover effects are more salient and robust among parents from poorer households: among them, the treatment reduces default probability by 26%, increases credit scores by 5%, and increases current debt levels by 40%. The treatment also has stronger effects among the parents of daughters, who experience a significant 6.7% increase in their credit score and a 28% reduction in their loan portfolio in arrears. These results highlight the opportunity that school-based financial education programs pro14 vide when trying to reach adults in vulnerable segments of the population in a cost-effective way. They also uncover important household dynamics that suggest that boys and girls have differential voices within the household in relation to money matters. Moreover, this paper contributes to the experimental evidence that shows robust and cost-effective returns to the investment in financial education programs. 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Journal of Personality (2004), 271–324. 21 18 Appendix A Table A1 Balance Check in the Endline Sample Variable Control mean T-C N Panel A. Students Male 0.455 0.023 11090 [0.498] [0.014] Age 16.748 0.010 10979 [1.278] [0.025] Works 0.399 –0.010 10859 [0.490] [0.012] Ratio of household members to bedrooms 1.869 0.001 10714 [0.998] [0.019] Lives with both parents 0.607 0.007 10818 [0.488] [0.011] Asset index –0.024 –0.049 10886 [0.998] [0.032] High level of parental supervision 0.768 0.006 10372 [0.422] [0.008] Has dinner with parents 7 days a week 0.338 –0.009 10930 [0.473] [0.009] Financial literacy raw score at baseline (0–15) 8.215 0.040 11006 [2.936] [0.087] GPA 2015 (0–20) 13.879 –0.033 10236 [1.483] [0.046] Panel B. Parents Male 0.620 –0.000 11090 [0.485] [0.012] Age 50.493 0.002 11090 [10.909] [0.164] Complete Secondary or higher 0.550 –0.000 10667 [0.498] [0.012] NOTE: Data from the baseline survey and exam for the sample of students present at the exit survey and exam. Test for joint covariates orthogonality p−value = 0.5269. Significance levels (* 10%; ** 5%; *** 1%) captured through OLS estimation accounting for clustered (school) standard errors. Standard errors (deviations) of coefficients (control means) are in parentheses. 19 Table A2 Treatment Impacts on Student Participation in Household Finances, by Students’ Sex Talks to Parents Helps Parents Female Male Female Male (1) (2) (3) (4) Treatment 0.014 0.008 -0.000 -0.001 (0.010) (0.009) (0.010) (0.009) Number of Observations 6703 6496 6660 6478 Number of schools 291 286 291 286 Mean in Control 0.796 0.728 0.775 0.672 Note: Dependent variables are defined as indicator variables that are equal to one when the students self-reports that she talks to parents about household finances or helps them to prepare a household budget in the endline survey. Stars denote significance levels (* 10%; ** 5%; *** 1%) based on unadjusted p-values. Daggers denote significance levels based on the Romano-Wolf adjusted p-values (†10%, †† 5%, †††1%) resulting from 1,000 bootstrap replications. OLS estimates, standard errors clustered at the school level are reported in parentheses. All specifications include a set of dummy variables that correspond to the matched-pairs of schools and the following set of controls: grade, currently working, received financial education lessons in the past, ratio of household members to bedrooms, asset index, high level of parental supervision, lives with both parents, and has dinner with parents each day of the week. The value of the dependent variable at baseline is also included as a control. 20 Appendix B Data Appendix Appendix B.1 Data Sources Survey Data. Survey and exam data were collected for in the 300 schools of the experimental sample, both at baseline and endline. Within each school, one classroom per grade was chosen at random. Students’ baseline survey collects basic information on socioeconomic characteristics of the household, students’ future aspirations, parental supervision, truancy, and the number of hours the student works per week. The survey also measures students’ school engagement10 and collects data on previous exposure to financial education programs. Financial behavior is measured in the survey through several constructs: holding savings, budgeting, consumption and saving habits, and financial autonomy.11 The survey also measured monthly cash flows derived from different income sources including allowances, gifts from family and friends, and labor. Additionally, the questionnaire gathers information on five personality constructs and preferences that may influence financial choices: conscientiousness, self-control, intertemporal preferences, impulsiveness, and risk aversion. Conscientiousness, which is closely related to deliberative thinking, was measured using the Big Five Scale for this attribute (22). Self-control is measured by (25)’s scale, which attempts to measure people’s ability to control their impulses in general, not only those related to financial behavior. Impulsiveness is measured by the Barratt Impulsiveness Scale (21), which reflects six correlated first-order constructs (attention, motor, self-control, planfullness, cognitive complexity, perseverance, and cognitive instability), which in turn, form three second-order factors (attention, motor, and non-planning). The survey focuses on the attention and non-planning factors only. Time inconsistency is defined as in (1). These preferences and personality traits are measured relying on extensively tested scales that are specifically designed to be self-rated. The design of the questionnaire was challenging task as it included several educational and psychological scales, as well as financial literacy questions. The instrument required several rounds of piloting and in-depth interviews with adolescents to adapt well-known scales to Peruvian high schoolers. Credit Bureau Records. EQUIFAX collects credit information from all banks and most microfinance institutions. Their data contains records on all individuals at or above legal age, irrespective of previous access to credit from financial institutions or other creditors. EQUIFAX’s data used in this study corresponds to a single snapshot of credit behavior in October 2019. The records gathered include information on loan balances by repayment status of the loan (i.e., current and past due debt), source of the funds (i.e., type of lender), and type of loan according to intended purpose (i.e., productive loans funding micro-enterprise and small business and non-productive loans including consumption loans, credit card debt, mortgages, and auto financing). The credit bureau’s data also capture negative records corresponding to delinquency on non-credit related bills (e.g. cellphone, water, electricity, gas, etc.), taxes, or credit cards balances. Negative signals from non-credit bills stay active in the bureau’s database until the pending balance has been paid off or until five years have passed since the service provider has reported a late or missed payment. By law, EQUIFAX has to stop disclosing negative records after this exposure 10The scale to measure student engagement comes from the Student Engagement in Schools Questionnaire and measures behavioral engagement: effort and persistence (13). 11The financial autonomy scale was borrowed from (6). 21