Issuu

Scholarly Research Journal for Interdisciplinary Studies, Online ISSN 2278-8808, SJIF 2021 = 7.380, www.srjis.com PEER REVIEWED & REFEREED JOURNAL, MAY-JUNE, 2021, VOL- 8/65 https://doi.org/10.21922/srjis.v8i65.1343 RELATIONSHIP BETWEEN FINANCIAL LITERACY AND INDEBTEDNESS: A CASE OF UNIVERSITY OF NAIROBI STUDENTS Morris Irungu Kariuki, Ph. D. Lecturer, University of Nairobi, Kenya

Paper Received On: 21 JUNE 2021 Peer Reviewed On: 30 JUNE 2021 Published On: 1 JULY 2021 Content Originality & Unique: 76%

The study objective was to determine the relationship between financial literacy and indebtedness a case of University of Nairobi Students. The study used a descriptive research design. The study was based at the University of Nairobi, Mombasa Campus. The study population was 2101. The sample size was 336 students. A questionnaire was used to collect the data. SPSS was used to analyze the data. The study attained 83% response rate. Money management, financial planning and financial planning were found to correlate strongly and positively with indebtedness and also significant at 5% level of significance. Therefore, they were found to be major contributors to student indebtedness. The study therefore found that money management, financial planning and financial decisions, affect indebtedness of the students at University of Nairobi. The study concluded that financial literacy affected indebtedness of the students at University of Nairobi. The study recommended that the University of Nairobi should roll out financial education, training, advice and counseling programs targeted at its students.

Scholarly Research Journal's is licensed Based on a work at www.srjis.com

1. Financial Literacy Financial literacy has been defined in various ways by several authorities. They have generally, termed it a measure of ones understanding of key financial concepts, the ability and confidence to manage personal finances. Others assert, it is the financial knowledge needed to work out compound interest and assess risk so as to diversify. Yet others aver, it is the decision making ability required in good retirement planning, good borrowing behavior and proper participation in the stock market (Nye & Hillyard, 2013, OECD, 2013 Lusardi, 2008). Financial literacy in many empirical studies has been measured by numeracy tests on percentage of questions which are answered right (Kariuki, 2018). Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14994

Klapper and Lusardi (2015) define financial literacy as the collection of skills and information held by a person enabling him to make informed decisions. On the other hand, Mandell (2007) defined financial literacy as the ability to evaluate financial instruments and make informed judgments and choice of instruments. Lusardi and Tufano (2015) contend that debt literacy is one important component of financial literacy which deals with the ability to take simple decisions on debt especially on compounding interest. Studies have modeled financial literacy into several comprehensive dimensions: financial knowledge, financial capability, financial experiences, financial attitude and financial behavior (Kariuki, 2018, OECD, 2013. Yet, Huston (2010) identified four main components of financial literacy namely basic money concepts, saving or investment, borrowing and protection concepts. Financial knowledge refers to abstract skills, education and current information possessed by a person with respect to managing his financial commitment. On the hand, financial capability is the ability to apply financial knowledge. While financial experiences refer to the practical experiences individuals encounter in the financial loan market (Kariuki, 2018). Financial attitude is the pre-disposition to behave in a particular manner in the financial market considering the attitudes and preferences of the market participant. Financial behavior is the way individuals behave in the market place (OECD, 2013). 2. Indebtedness Indebtedness refers to holding commitments which need to be redeemed in due time (Munster, Ruger, Ochsmann, Letzel, Toschke, 2009). Over-indebtedness comes with various negative social and economic consequences to the individual and the economy generally (Kariuki, 2018). Such consequences, at personal level will include financial stress, poor social relationships, absenteeism poor health, excessive alcohol consumption, physical and mental health, risk of social, financial and market exclusion, cases of divorce, mental disorders, homelessness and even fraudulent activities. At the macro level, over-indebtedness can lead to economic and financial fragility, unemployment, inequality and even financial crisis. Student debt and hence indebtedness has been on the rise in many countries around the world. This is because of increased availability of loans to cover higher education expenses. In many ways this expansion is beneficial to student because it addresses financial constraints that prevent students from investing in higher education (Solis, 2017). There is a growing worry that student loan debt is overburdening young graduates; delaying their important societal milestones, such as marriage, child rearing, and home ownership; and negatively affecting Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14995

life satisfaction. However, these negative effects of student debt cannot outweigh positive market and non-market benefits to individuals and society associated with higher education (Gayardon, Callender, Deane & Desjardins, 2018). Student loan debt differs from other types of personal debt for several reasons. First, the loan is taken before the individual has the capacity to repay it and repayment does not usually start until the individual leaves higher education. Second, these debts are incurred when the individual has few assets. Third, the loan is used to pay for an intangible asset namely human capital, an investment that is hard to quantify. Unlike financial or physical capital, it is an investment that cannot be repossessed if a borrower defaults on repayment. Four, student debt is incurred early in life, and might alter life choices of the student on leaving college (Gayardon et al., 2018). 3. University of Nairobi Students The University of Nairobi is the largest institution of higher learning in Kenya and the region at large with a student population of over 84,000. The undergraduate and postgraduate students are spread across the various campuses in the country. The University of Nairobi is well endowed with sufficient resources both human and infrastructure that will enable students to be empowered and transform into a holistic graduate. The University encourages students to develop a culture of creativity and innovation (www.uonbi.ac.ke, 2020). To fund their education and upkeep at the university students take the Higher Education Loans Board (HELB) loans which are not sufficient to cover higher education expenses. Students resort to taking loans from other avenues including loan apps which offer easily accessible loans for upkeep and other academic expenses. These loan apps and other avenues of access to credit to the students are ubiquitous and easily used (Waithaka, Ngulube & Onyancha, 2018).This study concentrated on the students from University of Nairobi, Mombasa Campus which had population of about 2100 students. In the school of business, the students pursuing PhD are 110; those pursuing MBA are 499 whilst those pursuing Bachelor of Commerce are 765. In the school of law those pursuing Masters in Law are 33 and those pursuing Bachelors in Law are 145. In the school of arts those pursuing Masters in Arts are 6, Bachelor of Arts 196, Diploma 12. Those pursuing Diploma in ODel (Open, Distance and E-learning) are 335 (www.uonbi.ac.ke, 2020). 4. Research Problem The role of financial literacy with regards to sound personal finance management practice cannot be over-emphasized. Students are bound to use their financial literacy skills to make Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14996

decisions on how they will manage debt. Researchers have found lower level of financial literacy particularly among youth and elderly (Lusardi and Mitchell, 2011; Allgood and Walstad, 2013). Studies have recommended continuous financial literacy education and training to all age groups especially because of changing circumstances, changing individual needs and multiplicity of and and dynamic nature of financial products (Bernanke, 2011). Financial literacy facilitates proper decision making and provides greater control over finances, more effective use of financial products and services and reduces vulnerability to fraudulent schemes (Wachira & Kihiu, 2012). In Kenya, the conversation around student debt has only begun following an uproar on the planned recoveries from student debt defaulters which include proposals to name and shame bad debtors. Nevertheless, the government has seemingly taken notice of the impending doom to open up discussions on the containment of debt. The default on student loans has been attributed to financial literacy in a small scale, though majorly these students take loans to finance their university education. Recent graduates are therefore unable to fend for themselves much less repayment of personal debt. This has resulted to increased rate of student loan defaults in the country in spite of willingness to make repayments (Muiruri, 2019). Various studies have been done on financial literacy. Nikolaos and Soumya (2019) examined the financial literacy level of college students, and its implications on the repayment of student debt for public university in Massachusetts, America. The study showed that students with a deficit in financial literacy are more likely to underestimate future student loan payments; low-literacy students underestimate future payments, while high financial literacy reduces the probability of significant payment underestimation. Thus financial literacy affected indebtedness. Neha and Shveta (2018) sought to analyze the level of financial literacy among youth in the world based on previous studies based in India. The study found that the financial literacy among youth is low and has become a cause of concern. Also, it found socio-economic and demographic factors such as age, gender, income, marital status and educational attainment influenced the financial literacy levels of the youth and that there exists a relationship between financial knowledge, financial attitude and financial behavior. Panayiotis and Dennis (2018) attempted to examine financial literacy, financial aptitude and behavior among university students in Cyprus. The study established that the students do not get adequate financial education in high school hence joined Universities without possessing requisite financial literacy. Many studies on financial literacy have not delved directly into Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14997

the relationship between financial literacy and indebtedness for University of Nairobi students. 5. Research Objective To determine the relationship between financial literacy and indebtedness a case of University of Nairobi Students 6. Literature Review This study was anchored on the goal setting theory, social learning theory, exchange theory and the consumer debt theory. A study by Lusardi and Tufano (2015) found many adults lack the financial literacy to make competent and effective financial choices in the market place. If individuals are illiterate concerning their personal finances, their financial management of new ventures will also be lacking and will lead to reduced new venture creation and possible failures of their investments. Excessively high debt levels, low saving rates, becoming targets of investment fraud, delinquency on credit cards and bankruptcy have all been found to be related to financial illiteracy in individuals (Kariuki, 2018). Kariuki found in a study done in Kenya that the respondents did not have emergency funds indicating financial illiteracy on the part of the borrowers. Kariuki also found workers were spending almost all of their income on repayment of debt, resulting in little, if any, of their income being left for savings or investments. Nikolaos and Soumya (2019) examined the financial literacy level of college students, and its implications on the repayment of student debt. The study found that students who are financially illiteracy are more likely to underestimate future student loan payments; lowliteracy lead to underestimation of future payments, while high financial literacy reduced the probability of significant payment underestimation. The study found a financial literacy wage gap as students with low financial literacy expect significantly lower starting salaries than their high-literate peers. As a result, low-literate students are more vulnerable to unexpected, adverse shocks on their payment-to-income ratios that can impair their future creditworthiness and undermine their ability to service debt post-graduation. Robb and Sharpe (2009) collected data from 6,520 students by electronic mail at Midwestern University in United States. The objective of the study was to examine whether financial knowledge affects the credit card decisions. The study found that financial knowledge is a significant factor in the credit card decisions. Results of a double hurdle analysis indicated that students with relatively higher levels of financial knowledge were not significantly different from students with relatively lower levels in terms of the probability of having a Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14998

credit card balance. The study had a unique finding that those with higher levels of financial knowledge had significantly higher credit card balances. The study used numeracy skills to proxy financial knowledge and also measure indebtedness using credit card balances. 7. Research Methodology This study used descriptive research design which was mainly survey, cross sectional, and correlational. Research design is the blueprint used to guide a research study to ensure that it addresses the research problem (Kothari, 2009). The population of the study was 2100 University of Nairobi-School of business students, based in Mombasa Campus. Purposeful sampling technique was used. The sample size was calculated by Slovin’s formula at a confidence level of 95 percent. Therefore sample size was 336 students. Data Collection was done using a questionnaire. The questionnaire was administered by the researcher and research assistants. The questionnaire utilized closed ended questions. Close ended questions allowed the investigator to easily quantify results. SPSS was used to analyze data. The relationship between

variables was determined using correlation analysis and regression

Analysis. Descriptive statistics were also done by way means, frequencies and percentages .The Regression Model was as follows; Y = β0 + β1X1 + β2X2+ β3X3+ ε Where Y = Indebtedness X1 = Money Management X2= Financial Planning X3= Financial Decisions β0 =the constant term β1; β2; β3= coefficients and ε= Stochastic term 8. Data Analysis, Results and Discussion 8.1 Population characteristics The study targeted 336 students. However, the questionnaire filled were 280, this represents a 83% response rate. The questionnaires not filled were 56 which represent 17%. According to Mugenda and Mugenda (2012), a response rate of 50% is adequate, 60% is good and 70% and above is excellent. Out of the total sample, 153 were male which represent 54.6% whilst the female students were 127, which represent 45.4%. Therefore both genders were well represented. The majority of the students were aged between 20-29 years at 242 representing 86.4%. Those Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

14999

aged 30-35 years were 25 which represent 8.9%. The students aged between 36-40 years were 6, which represent 2.2%. Those aged between 41-45 years were 4 representing 1.4% of the total. Finally those aged 46-55 years were 3 representing 1.1%. The study therefore asserts that the students were at a good age to utilize their financial literacy skills (or lack of) in a bid to avoid or land in indebtedness. A majority of the students were studying business (209) which represents 74.6%. Those studying law were 34 which represented 12.2%. Finally those in the school of Arts were 37 which represent 13.2%. All students had secondary education. Those pursuing a certificate qualification were 15 which represent 5.4% of the total. Those pursuing a Diploma were 31 which represent 11.0%. Those pursuing a degree were the majority at 215 at 76.8%. The students pursuing a Masters degree were 14 at 5% and finally those pursuing a PhD were 5 at 1.8%. 8.2 Money Management The students were asked to indicate their level of agreement with statements with respect to the money management of financial literacy. The responses were guided by a Likert Scale: Where 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree. The mean and the standard deviation of the responses were calculated and tabulated. Table 1 :Money Management Money Management

Mean

In my daily expenditure I usually have budget Mostly I spend/require more finances than what I have In my daily expenditure I stick to the budget set

3.65 3.28 3.12

Std. Deviation 1.054 1.368 1.117

Under money management, in my daily expenditure I usually have budget had a mean of 3.65 which is near 4 on the Likert scale and implied that the students agreed on this statement. The corresponding standard deviation of 1.054 was the least which showed that the responses were homogenous. Mostly I spend/require more finances than what I have had a mean of 3.28 which is can be rounded off to 3 on the Likert Scale implying the responses were neutral to this statement. The standard deviation of 1.368 was the largest which showed that the responses were highly varied. In my daily expenditure I stick to the budget set had a mean of 3.12 which is can be rounded off to 3 on the Likert Scale implying the responses were neutral to this statement. The standard deviation of 1.117 was the second least, showing the responses were second least in variation. The study therefore asserts that the students had a budget for their daily Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15000

expenditure. However these students were not sure whether they usually stick to the budget. In addition to this the students mostly spent and required more finances than available. This shows signs of poor money management. 8.3 Financial Planning The students were asked to indicate their level of agreement with statements with respect to the financial planning of financial literacy. The responses were guided by a Likert Scale: Where 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree. The mean and the standard deviation of the responses were calculated and tabulated. Table 2: Financial Planning Financial Planning I have/Intend to invest my finances for future return For my finances I usually have a savings plan I’m aware of my credit score and credit rating which I use to plan for my finances

Mean 4.09 3.60

Std. Deviation .907 1.228

3.16

1.272

On financial planning, I have/Intend to invest my finances for future return had a mean of 4.09 which can be rounded off to 4 on the Likert scale implying that the students agreed to this statement. The corresponding standard deviation of 0.907 was the least, showing that the responses were least varied. For my finances I usually have a savings plan had a mean of 3.60 which can be rounded off to 4 on the Likert scale implying that the students agreed to this statement. The corresponding standard deviation of 1.228 was the second least, showing that the responses were second least in terms of variation. I’m aware of my credit score and credit rating which I use to plan for my finances had a mean of 3.15 which can be rounded off to 3 on the Likert scale implying that the students were neutral to this statement. The standard deviation was the largest at 1.272 showing high variation on the responses. The study therefore asserts that the students planned to invest their finances for future returns and also had a savings plan. The students however did not take into cognizant their credit score and credit rating while planning for their finances. 8.4 Financial Decisions The students were asked to indicate their level of agreement with statements with respect to the financial decisions of financial literacy. The responses were guided by a Likert Scale: Where 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree. The mean and the standard deviation of the responses were calculated and tabulated.

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15001

Table 3: Financial Decisions Financial Decisions I usually own up on any wrong financial decision I ever make and try to correct the mistakes I usually gather financial information to help in my decisions I consider interest rates when undertaking any financial decision especially loans

Mean

Std. Deviation

4.01

1.078

3.53

1.154

3.34

1.329

On financial decisions, I usually own up on any wrong financial decision I ever make and try to correct the mistakes had a mean of 4.01 which can be rounded off to 4 on the Likert scale implying that the students agreed to this statement. The corresponding standard deviation of 1.078 was the least, showing that the responses were least varied. I usually gather financial information to help in my decisions had a mean of 3.53 which can be rounded off to 4 on the Likert scale implying that the students agreed to this statement. The corresponding standard deviation of 1.154 was the second least, showing that the responses were second least in terms of variation. I consider interest rates when undertaking any financial decision especially loans had a mean of 3.34 which can be rounded off to 3 on the Likert scale. This shows that the students were neutral on this statement. The standard deviation was the largest at 1.329 showing high variation on the responses. The study asserts that the students owned up on any wrong financial decision ever made and tried to make corrections. Also the students gathered financial information to help in decision making. However the interest rates when undertaking financial decisions especially taking loans was not out rightly considered. 8.5 Indebtedness The students were asked to indicate their level of agreement with statements with respect to the indebtedness. The responses were guided by a Likert Scale: Where 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree. The mean and the standard deviation of the responses were calculated and tabulated.

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15002

Table 4: Indebtedness Indebtedness Due to my financial planning I have to borrow monies from credit cards, mobile money overdraft to finance my expenses Due to my financial decisions I have been listed at the Credit Reference Bureau (CRB) I’m highly indebted and use many apps due to my money management skills

Mean

Std. Deviation

1.95

1.256

1.85

1.222

1.84

1.145

Under indebtedness as influenced by financial literacy, due to my financial planning I have to borrow monies from credit cards, mobile money overdraft to finance my expenses had a mean of 1.95 which can be rounded off to 2 on the Likert Scale. This shows that the students disagreed to this statement. The standard deviation was the largest showing high variation on the responses. Due to my financial decisions I have been listed at the Credit Reference Bureau (CRB) had a mean of 1.85 which can be rounded off to 2 on the Likert Scale. This shows that the students disagreed to this statement. The standard deviation was the second largest implying the responses were second highly varied. I’m highly indebted and use many apps due to my money management skills had a mean of 1.84 which can be rounded off to 2 on the Likert Scale. This shows that the students disagreed to this statement. The corresponding standard deviation of 1.145 was the smallest showing near homogeneity. The study therefore asserts that the students did not borrow monies from credit cards; mobile money overdraft to finance expense and most students had not been listed at the Credit Reference Bureau (CRB) due to their financial decisions. Most students were not highly indebted and did not use many apps due to their money management skills. 8.6 Correlation Analysis The Pearson Correlation coefficient was used to test the strength of the relationship between the variables. The task is one of quantifying the strength of the association and direction of the variables. Table 5: Correlation Matrix 1 Pearson Correlation 1 Sig. (2-tailed) N 280 Pearson Correlation .982** Financial Sig. (2-tailed) .000 Planning N 280 Pearson Correlation .972** Financial Sig. (2-tailed) .000 Decisions N 280 Pearson Correlation .809** Indebtedness Sig. (2-tailed) .000 N 280 **. Correlation is significant at the 0.01 level (2-tailed).

Money Management

1 280 .980** .000 280 .769** .000 280

1 280 .744** .000 280

1 280

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15003

Money management was found to correlate strongly and positively with indebtedness and also significant (r=.809 p= .000). Money management is therefore a contributor to student indebtedness. Financial planning was found to correlate strongly and positively with indebtedness and also significant (r=0.769, p=.000). Financial planning is therefore a contributor to student indebtedness. Financial decisions was found to correlate strongly and positively with indebtedness and also significant (r= .744, p =.000). Financial planning is therefore a contributor to student indebtedness. 8.7 Regression Analysis Regression analysis was carried out to determine the linearity of the relationship between the dependent and the independent variables of the study. Table 6 shows the value of Adjusted R-square of 0.688 implies that 68.8% of the total variance of indebtedness is explained by the model. This means that 31.2% of the total variance of indebtedness cannot be explained by the model. Hence the results reveal that money management, financial planning and financial decisions, affect indebtedness of the students at University of Nairobi. The Table 6 shows the results for variations between the study variables. Table 6: Model Summary Model

R Square

Adj. R Std. Error of the Square Estimate a 1 .831 .691 .688 .66860 a. Predictors: (Constant), Financial Decisions, Money Management, Financial Planning b. Dependent Variable: Indebtedness

From the ANOVA Table 7, it was established that money management, financial planning and financial decisions affected indebtedness significantly since Fcritical at (3, 276) degrees of freedom is 2.70< Fcalculated 205.651 at 5% level of significance. The ANOVA table was generated from the Analysis. Table 7: ANOVA Model

Sum of Df Mean F Sig. Squares Square Regression 275.795 3 91.932 205.651 .000b Residual 123.380 276 .447 Total 399.174 279 a. Dependent Variable: Indebtedness b. Predictors: (Constant), Money Management, Financial Planning, Financial Decisions

The standardized regression model was;Y= 1.732X1-0.297X2- 0.649X3

where Y =

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15004

Table 9: Coefficients of the Regression Model Coefficientsa Model

(Constant) Money Management 1 Financial Planning Financial Decisions

Unstandardized Coefficients B Std. Error -.545 .152 1.806 .193 -.322 .234

Standardized Coefficients Beta

-.678

.180

Sig.

1.732 -.297

-3.589 9.360 -1.376

.000 .000 .170

-.649

-3.760

.000

a. Dependent Variable: Indebtedness

Using the unstandardized model, when the independent variables are all zeros, this means that indebtedness will be at -0.545 units. However using the standardized model, when money management increases by one unit, indebtedness increases by 1.732 units. When financial planning increases by one unit, indebtedness decreases by 0.297 units. When financial decisions increases by one unit, indebtedness decreases by 0.649 units. 9 Hypothesis Testing The first null hypothesis stated money management has no influence on the indebtedness of University of Nairobi Students. The results indicated that money management had a significant effect on indebtedness as shown in Table 4.13 (B1=1.732, t=9.360, p=0.000). Hence the study rejected H01 leading to the conclusion that money has a significant effect on the indebtedness of University of Nairobi Students. The second null hypothesis stated financial planning has no influence on the indebtedness of University of Nairobi Students. The results indicated that financial had an insignificant effect on indebtedness as shown in Table 4.13 (B2=-0.297, t=-1.376, p=0.170). Hence the study failed to reject H02 leading to the conclusion that financial planning has no significant effect on the indebtedness of University of Nairobi Students. The third null hypothesis stated financial decisions have no influence on the indebtedness of University of Nairobi Students. The results indicated that financial decisions had a significant effect on indebtedness as shown in Table 4.13 (B3=-0.649, t=-3.760 & p=0.0005). Hence the study rejected H03 leading to the conclusion that financial decisions has a significant effect on the indebtedness of University of Nairobi Students. 10. Summary of the Findings The study attained 83% response rate. The results for gender were within the requirements of the law, that no gender should surpass two thirds of a population in any establishment. The Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15005

respondents were at a good age to utilize their financial literacy skills (or lack of) in a bid to avoid or land in indebtedness. The majority of the students are well versed with financial literacy skills by virtue of being majorly from the school of business. The students were well educated to be able to understand the contents of the questionnaire and answer well in line with the study objective. On money management the students had a budget for their daily expenditure. However these students were not sure whether they usually stick to the budget. In addition to this the students mostly spent and required more finances than available. This shows signs of poor money management. On financial planning the students planned to invest their finances for future returns and also had a savings plan. The students however did not take into cognizant their credit score and credit rating while planning for their finances. On financial decisions, the study asserts that the students owned up on any wrong financial decision ever made and tried to make corrections. Also the students gathered financial information to help in decision making. However the interest rates when undertaking financial decisions especially taking loans was not out rightly considered. On indebtedness the students did not borrow monies from credit cards; mobile money overdraft to finance expense and most students had not been listed at the Credit Reference Bureau (CRB) due to their financial decisions. Most students were not highly indebted and did not use many apps due to their money management skills. Money management was found to correlate strongly and positively with indebtedness at 0.809 and also significant with 0.000<0.05 at 5% level of significance. Money management is therefore a contributor to student indebtedness. Financial planning was found to correlate strongly and positively with indebtedness at 0.769 and also significant with 0.000<0.05 at 5% level of significance. Financial planning is therefore a contributor to student indebtedness. Financial decisions was found to correlate strongly and positively with indebtedness at 0.744 and also significant with 0.000<0.05 at 5% level of significance. Financial planning is therefore a contributor to student indebtedness. The study rejected H01 leading to the conclusion that money management has a significant effect on the indebtedness of University of Nairobi Students. The failed to reject H02 leading to the conclusion that financial planning has no significant effect on the indebtedness of University of Nairobi Students. The study rejected H03 leading to the conclusion that financial decisions has a significant effect on the indebtedness of University of Nairobi Students. Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15006

11 Conclusion of the Study The study concluded that money management, financial planning and financial decisions, affect indebtedness of the students at University of Nairobi. 12 Recommendation of the Study The University should periodically organise financial education seminars or clinics where professional finacial education, training, advice and counselling can be imparted to the student body. References Allgood, S. & Walstad, W. (2013), financial literacy and credit card behaviours: A cross sectional analysis by age. Numeracy, 6(2), 1-26. Atkinson, A. & Messy, F. A. (2012), Measuring financial literacy: Results of the OECD/ international network on financial education (INFE) pilot study. OECD Working Papers on Finance, Insurance and Private Pensions No. 15, 1-73. Gayardon, A., Callender, C., Deane, K.C. & Desjardins, S. (2018) Graduate indebtedness: Its perceived effects on behaviour and life choices-A literature review. Centre for Global Higher Education working paper series. Centre for Global Higher Education, UCL Institute of Education, London. Huston, S. J. (2010). Measuring financial literacy. The Journal of Consumer Affairs, (44) 2, 296-316. Kariuki. M.1. (2018). Effect of debt literacy on the indebtedness of formal sector employees in Kenya. An Unpublished Doctoral Thesis. Jomo Kenyatta University of Agriculture and Technology. Klapper, L & Lusardi, A (2015). Financial literacy around the World. Journal of Pension Economics and Finance. 10:497-508 Kothari, C. (2009). Research methodology: Methods and techniques (2nd ed.). New Delhi: New age international (P) Limited. Lusardi, A. (2008). Household saving behavior: The role of financial literacy, information, and financial education programs (No. w13824). National Bureau of Economic Research. Lusardi, A., & Mitchell, O. S. (2011).Financial literacy and retirement planning in the United States. Journal of Pension Economics and Finance, 10(04), 509-525. Lusardi, A., & Tufano, P. (2015). Debt literacy, financial experiences, and overindebtedness. Journal of Pension Economics and Finance, 14(04), 332-368. Mandell, L. (2007). Financial literacy of high school students, in Xiao, J.J. (Ed.), Handbook of Consumer Finance Research, Springer, New York, NY, 163-183. Mugenda, O. M., & Mugenda, A. G. (2012). Research methods dictionary. Nairobi, Kenya: Applied Research and Training Services. Muiruri, K. (2019, November). Broke, Unemployed, and in debt University students in Crisis. Citizen Digital. Nairobi, Kenya Münster. E., Ruger, H., Ochsmann, E., Letzel, S. & Toschke, A.M(2009)/ Over-indebtedness as a marker of socioeconomic status and its association with obesity: A cross-sectional study. BMC Public Health , 9(286)1–6. Neha, G.& Shveta, S. (2018). Financial literacy among youth in India as well as around the worlD-A literature review. International Journal of Social Economics. DOI:10.1108/ijse-11-20160303 Copyright © 2021, Scholarly Research Journal for Interdisciplinary Studies

Dr. Morris Irungu Kariuki

(Pg. 14993-15007)

15007

Nikolaos, A.& Soumya, K.(2019) Financial literacy and student debt. The European Journal of Finance. 26, 4-5 Nye, P., & Hillyard, C. (2013). Personal financial behavior: The influence of quantitative literacy and material values. Numeracy, 6(1), 3. OECD (2013). Financial literacy framework, in OECD (Ed.), PISA 2012 Assessment and Analytical Framework: Mathematics, Reading, Science, Problem Solving and Financial Literacy, OECD Publishing, Paris, 139-166. Panayiotis, C. & Dennis, P.(2018). Financial knowledge among university students and implications for personal debt and fraudulent investments. The Journal of Economic Perspectives, 25(2), 95-116. Robb, C. A., & Sharpe, D. L. (2009). Effect of personal financial knowledge on college students’ credit card behavior. Journal of Financial Counseling and Planning, 20(1), 25-44. Wachira, I.M. & Kihiu, E.N(2012). Impact of financial literacy on access of financial services in Kenya. International Journal of Business and Social Science. 10(19) Waithaka, M., Ngulube, P. & Onyancha, B. O.(2018). Internet use among university students in Kenya: A case study of the University of Nairobi. Innovation. 57: 46-63

Acknowledgement Special thanks to my research assistants namely Said Issa Ali, Mohsin Fatma Swaleh, Dawood Shazia Mohamed, Shahid Mohamed Shaffi and Noordin Osman Correspondence Author Morris Irungu Kariuki (PhD). Lecturer, University of Nairobi, Nairobi, Kenya. Tel+254722496174. Email Addresses: mikariuki@uonbi.ac.ke, mikariuki2003@gmail.com