1.1 BACKGROUND OF THE STUDY

The financial system assumes strategically a very important role in channelling the funds from surplus units to deficit units. The financial system here refers to the group of institutions, markets and instruments which helps in formation of capital and thus accelerates to the pace of economic development.

The base of this study stems from the fact that there exists a gap between gross capital formation and gross domestic savings in India. So, there exists the need to augment the growth rate of voluntary domestic savings. This goal can be realized by widening and strengthening the working of different financial intermediaries which will result in mobilizing savings from various income level categories. .It is in this context that the role of the Non-Banking Financial Intermediaries like Chit Finance should be appreciated in supplementing the functions of the Banking Institutions.

Chit funds are Chit funds are the Indian equivalent of the Rotating Savings and Credit Associations (ROSCA). ROSCAs are famous in many parts of the world and is seen as an instrument to ‘save and borrow’ simultaneously. ROSCAs basically started as a way to help in fulfilling the needs of the low-income households as it enables the people to convert their small savings into lump sums. The concept of chit funds originated more than 1000 years ago. Initially it was in the form of an informal association of traders and households within communities, wherein the members contributed some money in return for an accumulated sum at the end of the tenure. Participation in Chit funds was mainly for the purpose of purchasing some property or, in other words, for ‘consumption’ purposes. However, in recent times, there have been tremendous alterations in the constitution and functioning of Chit funds. A significant difference between Chit Funds and ROSCAs are that in most places ROSCAs are user-owned and organized informally, but chit funds have been formally institutionalized in India. (Chit Funds-An innovative access to finance for low income households, 2009)

1.1.1 WHAT DO WE MEAN BY CHIT FUNDS?

Chit fund is a savings-cum-borrowing instrument. The basic aim of this instrument is to pool small amount of savings by all the members which is then managed by a foreman. The foreman has the responsibility to act as a trustee-cum-supervisors for the process of collection and allotment of the pooled amount.

Chit funds represent a traditional form of saving-cum-credit institution evolved before the bank system was introduced in rural India. There are many who avail themselves of this avenue for saving for a reasonable return.

1.1 NEED AND RATIONALE OF THE STUDY

Despite the growth of a wide range of savings avenues and the widespread network of banks and other financial institutions, it has been found that Chit scheme still forms an important part in the asset portfolio of many households and firms in India and especially in South India including Karnataka. Also, the review of literature shows that there are only a few studies on Chit Finance. Therefore, the need to conduct the study stems from the requirement to understand Chit Funds in Bangalore.

1.2 NEED TO CONDUCT THE STUDY

The research titled ‘A Study on Chit Funds in Bangalore to understand the behaviour and financial needs of the chit fund members as well as to identify the important predictors of regular participation in chit funds’ The study estimates the net returns and interest rate on Chit funds. This study tries to point out the limitations of the Chit Acts and suggests feasible recommendations for improving the working of such institutions.

.3.2 STATEMENT OF THE PROBLEM

‘A Study on Chit Funds in Bangalore to understand the behaviour and financial needs of the chit fund members as well as to identify the important predictors of regular participation in chit funds’.

VARIABLES UNDER INVESTIGATION

1. Age

2. Occupation

3. Monthly income

4. Gender

5. Bank loan

6. Regular participation in chit fund

7. Membership in multiple chit schemes

8. Cause for participating in multiple schemes

9. Preferred avenue of saving

10. Preferred source of finance

11. Safety

12. Better service

13. Flexibility

14. Timely Payment

15. Low commission

16. Personal contact

17. Unregistered chit funds membership

18. Cause for participating in unregistered chit funds

19. Cause for not participating in unregistered chit fund

3.5 OBJECTIVES OF THE STUDY

3.5.1 OBJECTIVE(PRIMARY)

1. To understand the behaviour and financial needs of the chit fund members.

2. To identify the important predictors behind chit fund participation

3.5.2 OHER OBJECTIVES OF RESEARCH

1. To estimate interest rates in registered chit funds.

2. To compare the relative ratings of Chit subscribers towards registered and unregistered chit funds on

3. To estimate the return on Chit Funds.

3.6 HYPOTHESIS

There are two types of statistical hypotheses.

1. Null hypothesis

2. Alternative hypothesis.

Hypothesis 1:

H0: There is no significant relation between gender and cause for participation in chit fund.

H1: There is significant relation between gender and cause for participation in chit fund.

Hypothesis 2:

H0: There is no significant relation between occupation and cause for participation in chit fund.

H1: There is significant relation between occupation and cause for participation in chit fund.

Hypothesis 3:

H0: There is no significant relation between age and causes for participation in chit fund

H1: There is significant relation between age and cause for participation in chit fund

Hypothesis 4:

H0: There is no significant relation between monthly income and cause for participation in chit fund

H1: There is significant relation between monthly income and cause for participation in chit fund

Hypothesis 5:

H0: There is no significant relation between gender and causes for bidding in chit fund

H1: There is significant relation between gender and cause for bidding in chit fund

Hypothesis 6:

H0: There is no significant relation between occupation and cause for bidding in chit fund

H1: There is significant relation between occupation and cause for bidding in chit fund

Hypothesis 7:

H0: There is no significant relation between age and cause for bidding in chit fund

H1: There is significant relation between age and cause for bidding in chit fund

Hypothesis 8:

H0: There is no significant relation between monthly income and cause for bidding in chit fund

H1: There is significant relation between monthly income and cause for bidding in chit fund

Hypothesis 9:

H0: There is no significant relation between gender and cause for saving in chit fund

H1: There is significant relation between gender and cause for saving in chit fund

Hypothesis 10:

H0: There is no significant relation between occupation and cause for saving in chit fund.

H1: There is significant relation between occupation and cause for saving in chit fund.

Hypothesis 11:

H0: There is no significant relation between age and cause for saving in chit fund

H1: There is significant relation between age and cause for saving in chit fund

Hypothesis 12:

H0: There is no significant relation between having bank loan and membership in multiple chit schemes.

H1: There is significant relation between having bank loan and membership in multiple chit schemes.

Hypothesis 13:

H0: There is no significant relation between monthly income and participation in unregistered chit funds

H1: There is significant relation between monthly income and participation in unregistered chit funds

Hypothesis 14 :

H0: There is no significant relation between causes to prefer chit fund over bank and having bank loan.

H1: There is significant relation between causes to prefer chit fund over bank and having bank loan.

Hypothesis 15:

H0: Presence of safety, flexibility, timely payment, low commission, better service, personal contact, having a bank loan are no significant predictors of regular participation in chit fund.

H1: Presence of safety, flexibility, timely payment, low commission, better service, personal contact ,having a bank loan,are significant predictors of regular participation in chit fund.

.

3.8 SAMPLING METHOD

Members of four registered chit fund companies in Bangalore. The four registered chit fund companies were selected due to the large size of their subscriber base.

3.8.3 SIZE OF SAMPLE

150 respondents

3.9 MECHANISM OF STUDY

3.9.1 PRIMARY RESEARCH

Questions relating to behaviour and financial pattern will be found out through questionnares

3.9.2 SECONDARY RESEARCH

‘ Reports on chit fund industry

OVERVIEW OF INDIAN CHIT FUND INDUSTRY

4.1.1 NUMBER OF REGISTERED CHIT FUND COMPANIES:

According to the Ministry of Corporate Affairs, as on 31st December, 2013:

Volume of registered chit companies: 5412

Volume of chit companies in Karnataka: 703

Number of chit fund companies in Bangalore: 315

UNREGISTERED CHIT FUND INDUSTRY

Although unregistered chits are an informal source of finance but still they are a significant part of the chit fund industry. Though they are more easily accessible as compared to registered chit funds.

4.3 PURPOSE OF THE STUDY

The study titled ‘A Study on Chit Funds in Bangalore to understand the behaviour and financial needs of the chit fund members as well as to identify the important predictors of regular participation in chit funds’ attempt in The study estimates the net returns and interest rate on Chit funds. This study also examines the limitations of the Chit Acts and suggests suitable recommendations for improving the functioning of such institutions.

4.4 LIMITATION OF STUDY

‘ Unwillingness of the members to share their income and financial details made the task of data collection somewhat difficult.

‘ Collecting data became difficult since I don’t know the regional languages.

5.2 ANALYSIS OF DATA

The analysis is done on the primary data collected from 150 chit funds members in Bangalore

TESTING OF HYPOTHESES

5.4.1 Hypothesis 1:

H0: There is no significant relation between gender and cause for participation in chit fund.

H1: There is significant relation between gender and cause for participation in chit fund.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 31.070a 16 .013

Likelihood Ratio 35.945 16 .003

Linear-by-Linear Association 8.809 1 .003

N of Valid Cases 150

a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is .30.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .455 .013

Cramer’s V .228 .013

N of Valid Cases 150

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

INTERPRETATION:

The value of chi-square=31.070 was p=.013, less than 0.05.

We can see that the strength of association between the variables is moderate (Phi and Cramer’s V -0.455).

Therefore, the research hypothesis that differences in ’cause to participate in chit funds’ are related to differences in ‘age” is supported by this analysis. This means that different age groups of the chit fund members have different reasons of participating in chit funds. As can be seen from the table above that those who belong to ’36-45 years’ have saving as the predominant reason to participate whereas members of other age groups do not have any dominant reason to participate.

5.4.2 Hypothesis 2:

Hypothesis 2:

H0: There is no significant relation between occupation and cause for participation in chit fund.

H1: There is significant relation between occupation and cause for participation in chit fund.

Hypothesis 3:

. Hypothesis 3:

H0: There is no significant relation between age and causes for participation in chit fund

H1: There is significant relation between age and cause for participation in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 10.018a 4 .040

Likelihood Ratio 10.478 4 .033

Linear-by-Linear Association 6.876 1 .009

N of Valid Cases 150

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .258 .040

Cramer’s V .258 .040

N of Valid Cases 150

a. Not assuming the null hypothesis.

a. Using the asymptotic standard error assuming the null hypothesis.

INTERPRETATION:

The value of chi-square=10.018 was p=.040, less than 0.05.

.We can see that the strength of association between the variables is weak (0.258)

Therefore, the research hypothesis that differences in ’cause to participate in chit funds’ are related to differences in ‘gender” is supported by this analysis. This means that males and females have different reasons of participating in chit funds. As it can be seen that males participate in chit funds for business and personal consumption purposes apart from saving whereas women predominantly participate to save.

5.4

Hypothesis 4:

H0: There is no significant relation between monthly income and cause for participation in chit fund

H1: There is significant relation between monthly income and cause for participation in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 82.176a 12 .000

Likelihood Ratio 97.665 12 .000

Linear-by-Linear Association 15.696 1 .000

N of Valid Cases 150

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .740 .000

Cramer’s V .427 .000

N of Valid Cases 150

INTERPRETATION:

We can see that the strength of association between the variables is strong (0.740)

Therefore, the research hypothesis that differences in ‘reason to participate in chit funds’ are related to differences in ‘occupation” is supported by this analysis. It can be seen that the self-employed members mainly participate to avail for business reasons whereas salaried employee participate mainly for personal consumption purposes.

Hypothesis 5:

Hypothesis 5:

H0: There is no significant relation between gender and causes for bidding in chit fund

H1: There is significant relation between gender and cause for bidding in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 66.691a 20 .000

Likelihood Ratio 43.579 20 .002

Linear-by-Linear Association 4.804 1 .028

N of Valid Cases 150

a. 1 cell (10.0%) has expected count less than 5. The minimum expected count is .07.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .667 .000

Cramer’s V .333 .000

N of Valid Cases 150

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

INTERPRETATION:

The (chi-square=66.691) was p=.000, less than 0.05.

We can see that the strength of association between the variables is moderately strong (0.667)

Therefore, the research hypothesis that differences in ’cause to bid in chit funds’ are related to differences in ‘age” is supported by this analysis. It can be seen that the members of age group’36-45 years’ are more interested in bidding for business related purposes where members of other age groups bid mainly for emergency needs.

5.4.6 Hypothesis 6:

. Hypothesis 6:

H0: There is no significant relation between occupation and cause for bidding in chit fund

H1: There is significant relation between occupation and cause for bidding in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 7.167a 5 .209

Likelihood Ratio 7.885 5 .163

Linear-by-Linear Association 1.120 1 .290

N of Valid Cases 150

a. 5 cells (41.7%) have expected count less than 5. The minimum expected count is .81.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .219 .209

Cramer’s V .219 .209

N of Valid Cases 150

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

INTERPRETATION:

The probability of the chi-square test statistic (chi-square=7.167) was p=.209, more than the alpha level of significance of 0.05.

Therefore, the research hypothesis that differences in ‘reason to bid in chit funds’ are related to differences in ‘gender” is not supported by this analysis.

5.4.7 Hypothesis 7:

Hypothesis 7:

H0: There is no significant relation between age and cause for bidding in chit fund

H1: There is significant relation between age and cause for bidding in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 180.915a 15 .000

Likelihood Ratio 160.460 15 .000

Linear-by-Linear Association 28.379 1 .000

N of Valid Cases 150

a. 1 cell (10.0%) has expected count less than 5. The minimum expected count is .13.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi 1.098 .000

Cramer’s V .634 .000

N of Valid Cases 150

INTERPRETATION:

The (chi-square=180.915) was p=.000, less than 0.05.

We can see that the strength of association between the variables is extremely strong (1.098)

Therefore, the research hypothesis that differences in’ are related to differences in ‘occupation” is supported by this analysis. It can be clearly seen that self-employed people bid in chit scheme mostly for business purposes, salaried people for emergency needs and housewives for household purposes.

5.4.8 Hypothesis 8:

Hypothesis 8:

H0: There is no significant relation between monthly income and cause for bidding in chit fund

H1: There is significant relation between monthly income and cause for bidding in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 123.331a 35 .000

Likelihood Ratio 106.298 35 .000

Linear-by-Linear Association 4.957 1 .026

N of Valid Cases 150

INTERPRETATION:

The probability of the chi-square test statistic (chi-square=123.331) was p=.000, less than the alpha level of significance of 0.05.

We can see that the strength of association between the variables is extremely strong (.907)

Therefore, the research hypothesis that differences in ‘reason to bid in chit funds’ are related to differences in ‘income” is supported by this analysis. It can be clearly seen that low income members bid mostly for consumption reasons whereas higher income members bid for business related and emergency purposes.

SUMMARY:

Reason to bid in chit fund has the strongest association with the occupation of the chit fund members as the probability of the chi-square test statistic (chi-square=180.915) was p=.000 and the strength of association between the variables is extremely strong (1.098).

5.4.

Hypothesis 9:

H0: There is no significant relation between gender and cause for saving in chit fund

H1: There is significant relation between gender and cause for saving in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 21.702a 16 .153

Likelihood Ratio 23.775 16 .095

Linear-by-Linear Association 2.397 1 .122

N of Valid Cases 150

INTERPRETATION:

The chi-square=123.331) was p=.153, more than 0.05. Therefore, the research hypothesis that differences in ’cause to save in chit funds’ are related to differences in ‘age” is not supported by this analysis.

5.4.10 Hypothesis 10:

H0: There is no significant relation between occupation and cause for saving in chit fund.

H1: There is significant relation between occupation and cause for saving in chit fund.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 20.510a 4 .000

Likelihood Ratio 29.038 4 .000

Linear-by-Linear Association 7.062 1 .008

N of Valid Cases 150

a. 1 cell (10.0%) has expected count less than 5. The minimum expected count is .81.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .370 .000

Cramer’s V .370 .000

N of Valid Cases 150

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

INTERPRETATION:

The chi-square=20.510) was p=.000, less than 0.05.

We can see that the strength of association between the variables is weak (.370).Therefore, the research hypothesis that differences in ’cause to save in chit funds’ are related to differences in ‘gender” is supported by this analysis.

5.4.11 Hypothesis 11:

Hypothesis 11:

H0: There is no significant relation between age and cause for saving in chit fund

H1: There is significant relation between age and cause for saving in chit fund

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 67.261a 12 .000

Likelihood Ratio 60.380 12 .000

Linear-by-Linear Association 9.507 1 .002

N of Valid Cases 150

a. 1 cell (10.0%) has expected count less than 5. The minimum expected count is .13.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .670 .000

Cramer’s V .387 .000

N of Valid Cases 150

INTERPRETATION:

The chi-square=67.261 was p=.000, less than 0.05.

We can see that the strength of association between the variables is moderately strong(.670).Therefore, the research hypothesis that differences in ‘reason to cause in chit funds’ are related to differences in ‘occupation” is supported by this analysis. Salaried people save their money in chit fund with no particular purpose. But self-employed people are equally interested in saving for house purchase as well as for general purpose.

SUMMARY:

chit fund is most closely associated with occupation of the chit fund members as it has the highest value of chi-square statistic and Phi coefficient.

5.4.12 Hypothesis 12:

Hypothesis 12:

H0: There is no significant relation between having bank loan and membership in multiple chit schemes.

H1: There is significant relation between having bank loan and membership in multiple chit schemes.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 56.697a 3 .000

Likelihood Ratio 67.900 3 .000

Linear-by-Linear Association 36.400 1 .000

N of Valid Cases 150

INTERPRETATION:

The probability of the chi-square test statistic (chi-square=56.697) was p=.000, less than the alpha level of significance of 0.05.

We can see that the strength of association between the variables is strong (.615).

Therefore, the research hypothesis that differences in ‘membership in multiple chit schemes are related to differences in ‘having currently bank loan” is supported by this analysis. It is clearly evident that those members currently having bank loan have invested in only one chit scheme whereas those members who do not have availed bank loan have invested in more than one chit schemes.

5.4.13 Hypothesis 13:

Hypothesis 13:

H0: There is no significant relation between monthly income and participation in unregistered chit funds

H1: There is significant relation between monthly income and participation in unregistered chit funds

.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 96.660a 7 .000

Likelihood Ratio 85.378 7 .000

Linear-by-Linear Association 59.577 1 .000

N of Valid Cases 150

a. 1 cell(10.0%) has expected count less than 5. The minimum expected count is 1.08.

INTERPRETATION:

The chi-square=96.660 was p=.000, less than 0.05.

We can see that the strength of association between the variables is extremely strong (.803).

Therefore, the research hypothesis that differences in ‘participation in unregistered chit funds’ are related to differences in ‘income” is supported by this analysis. It is clearly evident that mostly low- income members have participated in unregistered funds. This is because the registered funds have become expensive due to the increase in their operational cost as a result of stringent regulations.

5.2.14 Hypothesis 14 :

H0: There is no significant relation between causes to prefer chit fund over bank and having bank loan.

H1: There is significant relation between causes to prefer chit fund over bank and having bank loan

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 28.049a 5 .000

Likelihood Ratio 31.806 5 .000

Linear-by-Linear Association 2.967 1 .085

N of Valid Cases 150

a. 2 cells (15.0%) have expected count less than 5. The minimum expected count is 1.79.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Phi .432 .000

Cramer’s V .432 .000

N of Valid Cases 150

INTERPRETATION:

The probability of the chi-square test statistic (chi-square=28.049) was p=.000, less than the alpha level of significance of 0.05.

We can see that the strength of association between the variables is moderate (.432).

Therefore, the research hypothesis that differences in ’cause to prefer chit fund over bank’ are related to differences in ‘having bank loan” is supported by this analysis. It is clearly evident that members who have bank loan have preferred chit fund over bank mainly due to better dividends. But those who do not have bank loan prefer chit fund over bank mainly due to better service in terms of more personalized service.)

5.2..15 Hypothesis 15: To identify significant predictors of regular participation in chit funds using Binary Logistic Regression

Hypothesis 15:

H0: Presence of safety, flexibility, timely payment, low commission, better service, personal contact, having a bank loan are no significant predictors of regular participation in chit fund.

H1: Presence of safety, flexibility, timely payment, low commission, better service, personal contact ,having a bank loan,are significant predictors of regular participation in chit fund.

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step 0 Constant -1.046 .186 31.574 1 .000 .351

Model Summary

Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square

1 37.170a .533 .576

a. Estimation terminated at iteration number 6 because parameter estimates changed by less than .001.

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step 1a bank_loan(1) 1.068 1.265 14.715 1 .000 11.720

reason_2 2.286 4 .683

reason_2(1) 1.336 1.077 1.540 1 .215 3.805

reason_2(2) .134 2.239 .004 1 .952 1.143

reason_2(3) -.559 1.896 .087 1 .768 .572

reason_2(4) .731 1.347 .294 1 .588 2.076

reason_3 4.874 5 .431

reason_3(1) 1.188 .924 1.652 1 .199 3.279

reason_3(2) 1.661 2.048 .658 1 .417 5.263

reason_3(3) -1.654 1.228 1.813 1 .178 .191

reason_3(4) .404 1.192 .115 1 .735 1.497

reason_3(5) -17.379 20.722 .000 1 .700 .000

reason_4 .355 4 .986

reason_4(1) -1.047 1.850 .320 1 .571 .351

reason_4(2) -.839 1.979 .180 1 .672 .432

reason_4(3) -.932 1.637 .324 1 .569 .394

reason_4(4) 3.519 4.199 .000 1 .600 3.746

reason_5 8.553 5 .128

reason_5(1) -.254 1.768 .021 1 .886 .776

reason_5(2) -19.245 9.890 .000 1 .999 .000

reason_5(3) 1.420 1.338 1.126 1 .289 4.136

reason_5(4) -.747 1.306 .327 1 .567 .474

reason_5(5) .561 1.342 .174 1 .676 1.752

B S.E. Wald df Sig. Exp(B)

Step 1a Safety -.075 .320 4.377 1 .011 0.928

Flexi -.178 .426 3.337 1 .021 0.837

commision -.185 .188 1.868 1 .026 0.831

payment -.267 .178 1.657 1 .097 0.766

service -.859 .412 1.348 1 .083 0.424

personal -1.122 .163 .996 1 .079 0.329

Constant 3.058 2.440 1.571 1 .010 21.291

a. Variable(s) entered on step 1: : bank_loan, reason_2, reason_3, reason_4, reason_5.imp1, imp2, imp3, imp4, imp5, imp6.

INTERPRETATION:

‘ -2 Log Likelihood statistic is 37.170. This statistic how poorly the model predicts the decisions — the smaller the statistic the better the model. Since, 37.170 is a relatively small number therefore, this model is able to predict the decisions in a better way.

‘ Here Cox & Snell R Square statistic indicates that 53.3% of the variation in the regular participation in chit funds is explained by the logistic model.

‘ In our case Nagelkerke R Square is 0.576, indicating a moderate relationship of 57.6 % between the predictors and the prediction.

‘ If it is less than .05 then, we will reject the null hypothesis and accept the alternative hypothesis.

‘ In this case, we can see that bank loan, safety, flexibility and low commission have contributed signi’cantly to the prediction of regular participation in chit funds but other variables are not significant predictors of regular participation in chit funds.

‘ Since only bank loan has p=.000, therefore we can say that bank loan is the most significant predictor

among other significant predictors. This is followed by safety (p=.011), flexibility (p=.021) and low commission (p=.026).

‘ Here, the EXP (B) bank loan is 11.727. Hence when bank loan is availed by one unit (one person) the odds ratio is 11 times as large and therefore people are 11 more times likely not to regularly participate in chit funds.

‘ Here, the EXP (B) with safety is .928. Hence when safety is increased by one percent the odds ratio is .928 times as large and therefore people are .928 more times likely to regularly participate in chit funds.

‘ Here, the EXP (B) flexibility is 837. Hence when flexibility is increased by one percent the odds ratio is .928 times as large and therefore people are .837 more times likely to regularly participate in chit funds.

‘ Here, the EXP (B) low commission is .831. Hence when flexibility is increased by one percent the odds ratio is .928 times as large and therefore people are .831 more times likely to regularly participate in chit funds.

SUMMARY

Bank loan is the most significant predictor of regular participation in chit funds. This is followed by safety, flexibility and low commission.

Instalment no No of months remaining Monthly subscription Prize amount PV of monthly subscription(PV of outlow at 10%) PV of Prize amount(PV of inflow at 10%) Net Present Value(PV of inflow – PV of outflow)

1 24 2000 50000 2000 50000 10444.9

2 23 1500 35000 1488.1 34723.1 -4832.0

3 22 1500 35000 1476.4 34448.4 -5106.7

4 21 1500 35000 1464.7 34175.9 -5379.2

5 20 1500 35000 1453.1 33905.5 -5649.6

6 19 1500 35000 1441.6 33637.3 -5917.8

7 18 1500 35000 1430.2 33371.2 -6183.9

8 17 1500 35000 1418.9 33107.2 -6447.9

9 16 1620 38000 1520.3 35660.6 -3894.5

10 15 1620 38000 1508.2 35378.5 -4176.6

11 14 1700 40000 1570.2 36945.9 -2609.2

12 13 1700 40000 1557.8 36653.6 -2901.5

13 12 1780 42000 1618.2 38181.8 -1373.3

14 11 1780 42000 1605.4 37879.8 -1675.3

15 10 1780 42000 1592.7 37580.1 -1975.0

16 9 1860 44000 1651.1 39058.2 -496.9

17 8 1860 44000 1638.0 38749.2 -805.9

18 7 1860 44000 1625.1 38442.6 -1112.5

19 6 1940 46000 1681.6 39872.1 317.0

20 5 1940 46000 1668.3 39556.6 1.5

21 4 1940 46000 1655.1 39243.7 -311.4

22 3 1940 46000 1642.0 38933.2 -621.8

23 2 1940 46000 1629.0 38625.2 -929.8

24 1 1940 46000 1616.1 38319.7 -1235.4

25 0 1940 46000 1603.3 38016.5 -1538.6

39555.1 934465.9 -54411.4

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