Impact of Demographic Factors on Saving and Investment Patterns of Bank Employees in Aizawl
Dr. Rajkumar Giridhari Singh1*, Ms. Saizampuii Sailo2
1Assistant Professor, Department of Management, Mizoram University, Mizoram
2Research Scholar, Department of Management, Mizoram University, Mizoram
*Corresponding Author E-mail: rkgiridhari@gmail.com
ABSTRACT:
Investing is an activity that attracts people from all walks of life irrespective of their background. People turn to banks for various financial services and to seek help for saving, retirement planning, starting business, buying homes, etc. It is generally perceived that bank employees have better financial literacy in comparison to other professionals. The present paper basically attempts to identify the relationship between demographic factors of bank employees and their investment patterns. Primary data from a sample of 100 bank employees from public and private sector bank were obtained through a survey in Aizawl, Mizoram (India). The study has revealed that investment was independent of the gender, martial-status and income of the employees however family sizes of the employees have an impact on the investment.
KEY WORDS: Investment, savings, employees, public sector bank and private sector bank.
INTRODUCTION:
Investing is an activity that attracts people from all walks of life irrespective of their economic status, education or family background. The savings and investment by individuals are important both for personal financial well-being and for economic growth of the country. Individual savings and investment pattern plays important role in any economy since it is a major component of resource market (Mathi and Kungumapriya, 2014). An increase in the rate of investment is made possible by increasing the rate of saving. Savings is an important factor for achieving economic investment of the country. The part of income which is unspent is called savings (Achar, 2012).
Investment is something where investor put his/her money to make it grow. In simple words, it means putting money in various products such as stocks, mutual funds, gold, etc in order to earn return and grow your wealth. The investment behaviour of the investor can be affected by many of internal as well as external environment. The demographic factors, rural /urban background of individuals, availability of information, accessibility of avenues, and investment companies/ colleagues, etc. can influence individuals in developing their perceptions on investment alternatives. Bank plays an important role in shaping the individual financial fortune as it provides many facilities including people’s savings through various services. Millions turn to banks every day for services and advice to help them save, plan for retirement, start businesses and buy homes. As a result, banks already provide their customers and potential customers with a wealth of educational material, information, tools and services geared to help them make the best financial choices. It is thus generally perceived that bank employees have better financial literacy in comparison to other professionals. It shall be worthy to do an exploration how the bank employees do savings and investment. This study basically attempts to identify the relationship between demographic factors of bank employees and their investment patterns.
The study was conducted in Aizawl city in India. Information were sought from the bank employees of three public sector banks viz. State Bank of India, United Bank of India and IDBI Bank and three private sector banks viz. Axis Bank, HDFC and ICICI Bank. This study shall be helpful in understanding the common problem faced by individual investors. The outcome of the study shall be helpful to the market players in the financial sector in designing a better financial instrument customized to suit the needs of the investors. It shall also be helpful to policymakers in designing tools for encouraging individual savings and investment behaviour.
REVIEW OF LITERATURE:
There are literatures that observe that in many economies, people are, on the whole, reluctant to save, even when they are aware of the benefits of doing so (Lewis and Messy, 2012). The motivation for an investor to invest is complex and depends upon a number of factors (Kaur and Vohra, 2012). The policy makers have been looking to a range of tools to encourage saving and enable households to provide the investors with a financial cushion. Nagy and Obenberger, (1994) have conducted a study entitled, “Factors Influencing Individual Investor Behavior”. They concluded that classical wealth maximization is important to investors, even though investors employ diverse criteria when choosing stock. Contemporary concerns like local or international operations, environmental track record and the firm’s ethical posture appear to be given only cursory considerations.
Lusardi (2003) observed that planning is a powerful predictor of wealth accumulation; those who plan have more than double the wealth of those who have not done any retirement planning. Sultana and Pardhasaradhi (2012) concluded that individual investor still prefer to invest in financial products which give risk free returns. They have highlighted that Indian investors are conservative investors who prefer to play safe in the market irrespective of their income, education, salaries, etc. Mohanta and Debashish (2011) concluded that people were ready to invest for meeting their financial, social and psychological need. They found out Safety and security, higher capital gain, secured future, tax benefit, getting periodic return or dividends, easy purchase and meeting future contingency are some of the reasons of investing by individuals
The high awareness of investment knowledge and investment opportunities of the respondents were found by Brahmabhatt, Kumari, and Malekar( 2012). They opined that Indians are more sensitive about their money and ponder hundred times before investing in any market. Contrary to this a study by Behrman, Mitchel, Soo, and Bravo (2012) on financial literacy amongst Chilean population found that the respondents had poor knowledge about basic concepts or retirement system. However, the study concluded that financial literacy increases the possibility of contribution to pension savings.
Impact of demographic factors on investment decision of investors were conducted by different scholars (Jain and Mandot, 2012; Harikanth and Pragathi, 2012; Sellapan, Jamuna, and Kavitha, 2013). Harikanth and Pragathi (2012) indicated that there is a significant role of income and occupation in investment avenue selection by the male and female investors. Geographical horizon of the investors, risks bearing capacity, educational level, age, gender and risk tolerance capacity etc, also impacts their selection. Jain and Mandot (2012) found demographic factors like Gender and City have no impact on investment decision of investors. Sellapan, Jamuna, and Kavitha (2013) found that married women are more curious in making investment than the unmarried; the younger are mostly like to invest in shares, mutual funds, insurance and fixed deposits than the older women; and the middle age persons prefer to invest in real estate source of investment. Wubie, Dibabe, and Wondmagegn (2015) found gender, age, family size, social ceremony expense having significant relationship with savings and investment of the high school teachers.
OBJECTIVES OF THE STUDY:
The present study is an attempt to undertake the analysis of savings and investment pattern of bank employees. Considering the state of literature available and the fact that that there have not been much studies conducted on the savings and investment behaviour of the bank employees, this paper intends to find the relationship between demographic factors of bank employees and their investment patterns.
Hypotheses:
The following null hypotheses were tested
1. There is no significant association between gender and investment
2. There is no significant association between marital status and investment
3. There is no significant association between income and investment
4. There is no significant difference between investors and non-investors in terms of their age
5. There is no significant difference between investors and non-investors in terms of their family size.
METHODOLOGY:
The study was conducted by collecting data both from primary and secondary sources. The primary data were collected from the employees of public sector and private sector banks in Aizawl. Convenience sampling method was adopted whereby 200 questionnaires were distributed to the employees of the branches of these banks in Aizawl. Out of 200, one hundred eighteen questionnaires could be collected. Out of which, 52 questionnaires from public sector bank (State Bank of India, United Bank of India and IDBI Bank) employees and 48 questionnaires from private sector bank (Axis Bank, HDFC and ICICI Bank) employees were found to be valid. Hence, the total sample size of the study is 100 employees constituting 52 and 48 from public and private sector bank respectively. Therefore, employees of the banks are the sampling unit and the 100 bank employees are the sampling size of the study. The questionnaire contained detailed quantitative questions on income, expenditures and wealth as well as on socio-demographic characteristics of the respondents. A pilot study were undertaken in order to know the accuracy of questionnaire. The final questionnaires were arrived after certain changes were incorporated. The data were tabulated using MS Excel as well as SPSS. Mean, percentage, Chi-square and Mann-Whitney test have been used for analysis of the data.
RESULTS AND DISCUSSIONS:
Table 1: Sample Characteristics of the Respondents
|
Demographic variables |
Category |
No of Respondents |
|
Gender |
Male |
51 |
|
Female |
49 |
|
|
Total |
100 |
|
|
Age |
20-29 |
48 |
|
30-39 |
48 |
|
|
40-49 |
1 |
|
|
50-55 |
3 |
|
|
Total |
100 |
|
|
Marital Status |
Unmarried |
64 |
|
Married |
34 |
|
|
Widowed |
2 |
|
|
Total |
100 |
|
|
Income (per month) |
Less than 10,000 |
2 |
|
10,000-19,999 |
31 |
|
|
20,000-29,999 |
37 |
|
|
30,000-39,999 |
14 |
|
|
40,000-49,999 |
5 |
|
|
50,000-59,999 |
6 |
|
|
60,000-69,999 |
2 |
|
|
70,000 and above |
3 |
|
|
Total |
100 |
|
|
Family size |
2 |
4 |
|
3 |
19 |
|
|
4 |
23 |
|
|
5 |
18 |
|
|
6 |
18 |
|
|
7 |
7 |
|
|
8 |
5 |
|
|
9 |
4 |
|
|
10 |
1 |
|
|
14 |
1 |
|
|
Total |
100 |
|
|
Source: Primary data from the questionnaire |
||
Table 1 presents the demographic profile of the respondents. It can be observed that 51 percent of the respondents are male while the remaining 49 percent are female. In terms of age, it can be found that 48 percent of the respondents were from age group of 20 to 29 years. Also, similar numbers of respondents i.e. 48 per cent were from the age group of 30-39 years, one percent were from the age group of 40-49 years, three percent were from the age group of 50-55 years. Thus, the table indicates that majority of the respondents were less than 40 years and only three percent were above 40 years. The table shows that 64 percent of the respondents were unmarried while 34 percent were married and two percent of the respondents were widowed. The investors in this study are classified into eight (8) income groups as shown in Table 1. It is observed from the table that respondents having a monthly income of between Rs.20, 000 and Rs. 29,999 constitute 37 per cent and, thereby, have the highest concentration of respondents among the income groups. The income group between Rs.10, 000 and Rs. 19,999 constitute 31 percent followed by income group of 30,000-39,999 constituting 14 percent. 3 percent of the respondents were having income of 70,000 and above. As regards family size, maximum of the respondents were having a family size of 4 constituting 23 percent of the total respondents followed by 19 percent of respondents having a family size of 3. There were 18 percent of the respondents having family size of 5. Similarly, there were 18 percent of the respondents having family size of 6. Seven percent of respondents were having family member of 7; 5 percent of the respondents were having family member of 8; 4 percent of the respondents were having family member of 9 and 1 percent the respondents were having family member of 10 similarly, another 1 percent the respondents were having family member of 14. Only 4 percent of the respondents were having family member of 2.
Table 2 : Composition Based on Periodical Savings Plan Availed by the Employees
|
Savings plan |
Savings Bank Account |
Bank Recurring Deposit |
Mutual Fund |
Bank Fixed Deposit |
Public Provident Fund |
Company Deposits |
Stock and Equity |
Post Office Deposits |
|
% |
77 |
22 |
20 |
17 |
12 |
11 |
4 |
2 |
|
Rank |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
|
Source : Field survey |
||||||||
As shown in the Table 2, maximum employees have availed periodical savings on savings bank account constituting seventy seven (77) percent of the total sample. Bank Recurring Deposit was availed by 22 percent of the respondents while 20 percent of the respondents availed periodical savings on Mutual fund. Bank fixed deposit was availed by 17 percent of the employees. Public Provident Fund was availed by 12 percent of the employees. Company Deposit was availed by 11 percent. Stock and Equity, and Post Office Deposits were availed by only 4 and 2 percent of the employees respectively.
Table 3: Investment decision in households
|
Sl. No. |
Decision by |
Yes |
No |
|
1 |
Self |
76 |
24 |
|
2 |
Spouse alone |
1 |
15 |
|
3 |
Together with spouse |
21 |
4 |
|
4 |
With others |
11 |
19 |
|
5 |
Spouse with others |
18 |
18 |
|
Source: Field Survey |
|||
Table 3 shows that 76 percent of the respondents made investment decision by themselves; only one percent of the employees responds that their spouse made investment decision alone; 21 percent of the respondents made investment decision with their spouse; 11 percent of the respondents made investment decision with others and 18 percents of the respondents answered that their spouse made investment decision with others.
Table 4: Classification based on top three reasons for savings and investment
|
Particulars |
Rank 1 |
Rank 2 |
Rank 3 |
|||
|
Freq |
% |
Freq |
% |
Freq |
% |
|
|
Higher education of children |
13 |
13.98 |
9 |
10.47 |
8 |
9.76 |
|
Buying house or land |
15 |
16.13 |
9 |
10.47 |
5 |
6.10 |
|
Tax savings |
29 |
31.18 |
4 |
4.65 |
7 |
8.54 |
|
High return from invested amount |
10 |
10.75 |
5 |
5.81 |
7 |
8.54 |
|
Capital gains |
3 |
3.23 |
15 |
17.44 |
4 |
4.88 |
|
Compulsion from family members |
6 |
6.45 |
10 |
11.63 |
12 |
14.63 |
|
Marriage of children |
1 |
1.08 |
11 |
12.79 |
3 |
3.66 |
|
Buying durable goods |
2 |
2.15 |
8 |
9.30 |
13 |
15.85 |
|
To meet medical expenses |
8 |
8.60 |
7 |
8.14 |
15 |
18.29 |
|
For retirement |
4 |
4.30 |
7 |
8.14 |
7 |
8.54 |
|
Any other |
2 |
2.15 |
1 |
1.16 |
1 |
1.22 |
|
Total |
93 |
100 |
86 |
100 |
82 |
100 |
Source: Field survey
As can be seen from the Table 4, tax saving is the most important reasons for savings and investments for the maximum bank employees constituting 31 percent. Buying house or land is the most important reason for 16 percent of the bank employees followed by saving for higher education of children (14%); high return from invested amount (11%); to meet medical expenses (8.60%); Compulsion from family members (6.45%); Retirement (4.30%), Capital gains (3.23%), Buying durable goods (2.15%).
Maximum of the bank employees i.e. 17 percent have given capital gains as the second most important reason for their savings and investment. Marriage of children is second most important reason for 13 percent of the bank employees. Regarding the third reason for savings and investment, covering medical expenses is opted by the maximum of the employee constituting 18 percent.
Relationship between Investment and Demographic Factors:
In order to analyse the relationship between investment and demographic characteristics of the investors, hypotheses are framed and tested statistically. For the present study the operational definition of an investor is considered as any employee who has atleast a saving and investment in any of the following instruments such as bank recurring deposit, bank fixed deposit, company deposit, post office deposit, insurance, mutual funds, stock and equities and small saving schemes other than savings bank account. The analysis and interpretation of the same is presented as follows:
Composition based on investors and non-investors in public and private sector banks
Table 5: Composition of investors and non-investors in public and private sector banks
|
|
Public |
Private |
Total |
|
Investors |
42 (51.22) |
40(48.78) |
82 |
|
Non-investors |
10 (55.56) |
8(44.44) |
18 |
Source: Field survey
*figures in the bracket indicate percentage
Table 5 shows that out of the total investors, 51.22 percent were the employees of public sector banks while 48.78 percent were the employees of private sector banks. Out of the total non-investors, 55.56 percent were the employees of public sector bank while 44.44 percent were the employees of private sector banks. Thus, 82 percent of the respondents were having investment while 18 percent of the total respondents do not invest. To identify the relationship between investment and demographic factors of the respondents, the following hypotheses are tested.
Hypothesis 1
H0: There is no significant association between gender and investment
H1: There is a significant association between gender and investment
Table 6: Comparative analysis of Gender of the respondents and Investment
|
|
|
Investors |
Non investors |
|
Male
|
Observed |
42 |
9 |
|
Expected Count |
41.82 |
9.18 |
|
|
Female
|
Observed |
40 |
9 |
|
Expected Count |
40.18 |
8.82 |
|
|
X2 = 0.009; df=1; p = 0.925; insignificant |
|||
Source: Computed from field survey
As can be seen from the Table 6, there are 82 respondents who have an investment while 18 respondents are not having any investment. Out of 82 respondents, 42 are male investors while other 40 are female investors. Chi-square test was conducted to find out whether there is any significant association between gender of the respondents and the investment. Chi-square test revealed no relationship, X2 (1, N =100) = 0.01, p=0.93.Hence, the null hypothesis is failed to be rejected meaning that there is no significant association between gender and investment.
Hypothesis 2:
H0: There is no significant association between marital status and investment
H1: There is a significant association between marital status and investment
Table 7: Comparative analysis of Marital status of the respondents and Investment
|
|
|
Investor |
Non investor |
|
Unmarried |
Observed |
51 |
13 |
|
Expected Count |
52.5 |
11.5 |
|
|
Married |
Observed |
29 |
5 |
|
Expected Count |
27.9 |
6.1 |
|
|
Widowed |
Observed |
2 |
0 |
|
Expected Count |
1.6 |
0.4 |
|
|
X2 = 0.921; df=2; p = 0.631; insignificant |
|||
Source: Computed from Field survey
As can be seen from the Table 7, out of the 82 respondents who have an investment 51 are unmarried, 29 are married and another 2 are widowed. Chi-square test found no relationship between marital status and investment, X2 (2, N =100) = 1.28, p=0.53. Hence, the null hypothesis is failed to be rejected meaning that there is no significant association between marital status and investment.
Hypothesis 3:
H0: There is no significant association between income and investment
H1: There is a significant association between income and investment
Table 8: Comparative analysis of income and investment of the respondents
|
|
|
Investors |
Non-investors |
|
Less than 10,000 |
Observed |
2 |
0 |
|
Expected Count |
1.6 |
0.4 |
|
|
10,000-19,999 |
Observed |
25 |
6 |
|
Expected Count |
25.4 |
5.6 |
|
|
20,000-29,999 |
Observed |
31 |
6 |
|
Expected Count |
30.3 |
6.7 |
|
|
30,000-39,999 |
Observed |
9 |
5 |
|
Expected Count |
11.5 |
2.5 |
|
|
40,000-49,999 |
Observed |
5 |
0 |
|
Expected Count |
4.1 |
0.9 |
|
|
50,000-59,999 |
Observed |
6 |
0 |
|
Expected Count |
4.9 |
1.1 |
|
|
60,000-69,999 |
Observed |
2 |
0 |
|
Expected Count |
1.6 |
0.4 |
|
|
70,000 and above |
Observed |
2 |
1 |
|
Expected Count |
2.5 |
0.5 |
|
|
X2 = 8.949; df=7; p = 0.256; insignificant |
|||
Source: Computed from Field survey
As can be seen from the Table 8, Chi-square test was conducted to find out whether there is any significant association between income and the investment. Chi-square test found no relationship between income and investment, X2 (7, N =100) = 8.95, p=0.26. Hence, the null hypothesis is failed to be rejected meaning that there is no significant association between marital status and investment. Hence, the null hypothesis is failed to be rejected meaning that there is no significant association between income and investment.
Hypothesis 4:
H0: There is no significant difference in the average age of the investors and non-investors
H1: There is a significant difference in the average age of the investors and non-investors
Table 9: Mann Whitney Mean Ranks of age of the investors and non-investors
|
Category |
Frequency |
Mean Rank |
Sum of Ranks |
U |
P |
|
Investors |
82 |
52.68 |
4320 |
559 |
0.107 |
|
Non-investors |
18 |
40.56 |
730 |
|
|
|
Total |
100 |
|
|
|
|
Source: Computed from Field survey
In order to find out whether there is a significant difference in the average age of the investors and non-investors, the normality assumption test of the dependent variable age was conducted. The normality test was found to be significant indicating that the variable is not normally distributed. Hence the Mann-Whitney U test, a non-parametric test was conducted for the hypothesis. As can be seen from the Table 9, the mean rank of the investors was found to be 52.68 while the mean rank of the non-investors was 40.56. The Mann-Whitney U value was found to be 559 which was insignificant with 0.11 value. Hence, we failed to reject the null hypothesis meaning that there is no significant difference in the average age of the investors and non-investors.
Hypothesis 5:
H0: There is no significant difference between investors and non-investors in terms of their family size
H1: There is a significant difference between investors and non-investors in terms of their family size
Table 10: Mann Whitney Mean Ranks of family size of the investors and non-investors
|
Category |
Frequency |
Mean Rank |
Sum of Ranks |
U |
P |
|
Investors |
80 |
45.33 |
3626.5 |
386.50 |
0.002 |
|
Non-investors |
18 |
68.03 |
1224.5 |
|
|
|
Total |
98 |
|
|
|
|
Source: Computed from Field survey
In order to find out the whether there is a significant difference in the average family size of the investors and non-investors, the normality test assumption of the variable family size was conducted. The box-plot test was also conducted and the test revealed two observations as outlier. The two outliers were removed. The normality test after removing outlier was found to be significant indicating that the variable is not normally distributed. Hence, the Mann-Whitney U test, a non-parametric test was conducted for testing the hypothesis. The Table 10 shows that, the mean rank of the investors was found to be 45.33 while the mean rank of the non-investors was 68.03. The Mann-Whitney test result found the Mann-Whitney U value to be 386.5 which was significant with 0.002 value. Hence, we reject the null hypothesis and accept the alternative hypothesis. Therefore, it can be concluded that there is a significant difference in the average family size of the investors and non-investors.
CONCLUSIONS:
Savings and investments are mutually interconnected economic variables. Many new instruments have been introduced during the last two decades to attract the potential investors. Though various new avenues are introduced majority of the bank employees still opted for savings bank accounts for their periodic savings and investments. Majority (i.e. 82 percent) of the employees were having investment in different investment alternatives. Investment was found to be independent of the gender, martial-status and income of the employees however family sizes of the employees have an impact on the investment. Jain and Mandot (2012) also found out that demographic factors like Gender and City have no impact on investment decision of investors. In contradiction to this; Joseph and Prakash (2014) observed that income level of a respondent is an important factor which affects investment portfolio of the respondent. The present study found Tax saving to be the most important reasons for savings and investments for the maximum (i.e. 31.18 percent) bank employees. Capital gain is the second most important reason for their savings and investment. Regarding the third reason for savings and investment, covering medical expenses is opted by the maximum of the employee. Jeyakumari and Soundaravalli (2015) have also observed that most of the college teachers in Thanjavur City, Tamil Nadu were saving their money for the purpose of tax benefit, house building, future requirements, children education and marriage.
Thus, from the analysis, it is revealed that investment was independent of the gender, martial-status and income of the employees however family sizes of the employees have an impact on the investment. No significant difference was found between the average age of the investors and non-investors however, in terms of average family size there was a significant difference between investors and non investors.
REFERENCES:
1. Achar, A. (2012, August). Saving and investment behaviour of Teachers - An empirical study. International Journal of Physical and Social Sciences, 2(8), 263-286.
2. Behrman, J. R., Mitchel, O. S., Soo, C. K., and Bravo, D. (2012, May). How financial literacy affects household wealth accumulation. American Economic Review, 102(3), 300-304.
3. Brahmabhatt, Kumari, P., and Malekar, S. (2012). A study of investor behavior on investment avenues in Mumbai Fenil. TRANS Asian Journal of Marketing and Management Research, 1(1), 49-70.
4. Harikanth, D., and Pragathi, B. (2012, November). Role of behavioural finance in investment decision making - A study on select districts of Andhra Pradesh, India. Shiv Shakti International Journal in Multidisciplinary and Academic Research, 1(4), 1-15.
5. Jain, D., and Mandot, N. (2012, April). Impact of demographic factors on investment decision ofn investors in Rajasthan. Journal of Arts, Science and Commerce , 3(2(3)), 81-92.
6. Jeyakumari, J. J., and Soundaravalli, S. V. (2015). A study on saving and investment pattern of college teachers with reference to Thanjavur City Corporation. Intercontinental Journal of Finance Research Review, 3(9), 1-9.
7. Joseph, A. L., and Prakash, M. (2014, April). A study of preferred investment avenues among the people and factors considered for investment. International Journal of Management and Commerce Innovations, 2(1), 120-129.
8. Kaur, M., and Vohra, T. (2012, December). Understanding individual investor's behavior: A review of empirical evidences. Pacific Business Review International, 5(6), 10-18.
9. Lewis, S., and Messy, F.-A. (2012). Financial education, savings and investments: An overview. OECD Working Paper on Finance, Insurance and Privarte Pesnsions, 22.
10. Lusardi, A. (2003). Saving and investment of financial education. Pension Research Council Working Paper(PRC WP 2003-14), 1-43.
11. Mathi, K. M., and Kungumapriya, A. (2014, July). Review of literature on investment behavior of rural investors. International Journal of Science and Research, 3(7), 351-353.
12. Mohanta, G., and Debashish, S. S. (2011). A study on investment preferences among urban investors in Orissa. PRERANA Journal of Management Thoughts and Practice, 3(1), 1-17.
13. Nagy, R. A., and Obenberger, R. W. (1994). Factors influencing individual investor behavior. Financial Analysts Journal, 50(4), 63-68.
14. Sellapan, R., Jamuna , S., and Kavitha , T. (2013). Investment attitude of women towards different sources of securities - A factor analysis approach. Global Journal of Management and Business Research, 13(3), 26-30.
15. Sultana, S. T., and Pardhasaradhi, S. (2012). An empirical analysis of factors influencing Indian individual equity investors' decision maming and behavior. European Journal of Business and Management, 4(18), 50-61.
16. Wubie, A. W., Dibabe, T. M., and Wondmagegn, G. A. (2015). The influence of demographic factors on saving and investment decision of high school teachers in Ethiopia: A case study on Dangila Woreda. Research Journal of Finance and Accounting, 6(9), 64-68.
Received on 13.05.2017 Modified on 18.09.2017
Accepted on 28.10.2017 © A&V Publications all right reserved
Asian J. Management; 2017; 8(4):1304-1310.
DOI: 10.5958/2321-5763.2017.00197.4