Definición conceptual

After eliminating missing values and outliers, the complete sample includes 424 households out of 464 responses. In the sample, there are 212 Muslim households (50 percent), 173 belong to the religion of Hinduism (40 percent), 34 are Christian (8 percent), and only 5 respondents are Buddhist (2 percent). In sum, the sample distribution deviates slightly from the population distribution. Therefore, the author

decided to introduce sampling weights to ensure that the results are at least representative for the areas under study. The details on sampling weights are reported in the corresponding Stata do-file.

As presented in Table 27, total 174 households out of 424 currently have a micro insurance policy, whereas 250 are not covered by any kind of insurance. As 159 households in the sample (37.5 percent) have health insurance, it can be inferred that the households are most likely to have health insurance, if they are insured. In comparison, 29.5 percent or 125 of the participants have accident coverage and 25.2 percent or 108 households have life insurance. Only 26 households or 6 percent have vehicle insurance. It can also be concluded that several participants are protected against multiple risk. On average an insured respondent has 2.4 kinds of coverage.

Table 27: Micro insurance coverage of the sample

No. of households Percentage

Health 159 37.5%

Accident 125 29.5%

Life 108 25.4%

Vehicle 26 6.0%

Source: Author’s own

Out of the 108 life insured households, a credit life product is held by 52 households. In these cases, the borrower is obliged to take up insurance coverage provided by the microfinance institution from where she would like to borrow. These cases of credit- motivated micro life insurance uptake are not the focus of this study in general as this research aims to identify intrinsic demand factors. The total number of voluntary micro life insurance policyholders included in this sample amounts to 56. Further detailing the micro life insurance ownership based on religious denomination, the author finds that out of 56 voluntary micro life insurance households in the data set, 34 are Hindus, 13 are Muslims, 8 are Christians, and only 1 is Buddhist. Overall, both forms of micro life insurance, conventional and Takaful are almost equally demanded and multiple policy ownership is possible as the total number of Takaful and conventional policies is 60 for 56 households. However, as the sampling strategy did not further distinguish between conventional micro insurance and Micro Takaful ownership, Muslims exclusively purchased Family Micro Takaful and Christians bought conventional products. In total,

voluntary Family Micro Takaful coverage is bought by 13 Muslims, 18 Hindus, and 1 Buddhist. Whereas, voluntary conventional micro life insurance is purchased by 20 Hindus, 7 Christians, and only 1 Buddhist. Credit-linked micro life insurance is bought by 32 Hindus, 14 Muslims, and 6 Christians. Interestingly, the people who have mandatory insurance products are more likely to have two policies than voluntarily insured people. In addition, for credit life products the percentage of Takaful products exceeds the share of conventional products. Hindus are more likely to have Family

Micro Takaful coverage, whereas the uptake of either form of insurance is the same for

Muslims. These numbers clearly show how life insurance ownership is impacted by the underlying credit uptake. Figure 10 summarizes the sample distribution dependent on micro life insurance status and religious denomination.

Figure 10: Sample distribution of micro life insurance ownership and religion

Source: Author’s own illustration

Note: In some cases, subtotals presented for mandatory and voluntary micro life insurance coverage are not equal to the sum across the subcategories of Takaful and conventional. Totals are presented in brackets. Differences are caused by participants who have both kinds of insurance forms or if data did not allow for determining any insurance form.

Table 28 reports the summary statistics of the explanatory variables for the full sample, including micro life insurance policyholders as well as non-policyholders. As suggested by the young dependency ratio of 0.49, an average respondent’s household comprises of two children and two adults, which is in line with the average household size of 3.9 in

the Eastern Province (Department of Census and Statistics, 2014: 5). An average participant is about 40 years old and earns an average annual income of LKR 223,690 (approx. EUR 1,245.63), translating to LKR 18,640 per month (approx. EUR 103.80).

Table 28: Summary statistics – Micro life insured and non-insured households (voluntary take-up)

Full sample Voluntary life insured Non-voluntary life insured P-Value of

Variable Mean Std. dev. Mean (2) Std. dev. Mean (3) Std. dev t-test (2) – (3)

Socio-economic characteristics

Income 225.4021 163.6685 305.8832 232.4072 213.1549 147.1103 0.0001***

Wealth 0.0288 1.6354 0.7372 1.6072 -0.0790 1.6147 0.0005***

Ratio of young dependents 0.4943 0.2652 0.744 0.2221 .4974 0.2713 0.5467

Age 40.4859 10.4849 37.1429 10.3123 40.9946 11.0056 0.0143** Education 2.0735 1.0619 2.2407 1.1645 2.0489 1.0455 0.2155 Financial literacy 1.2429 0.9276 1.1607 0.8692 1.2554 0.9367 0.4772 Social capital Membership 0.8679 0.9804 1.1071 1.1549 0.8315 0.9476 0.0499** Generalized trust 0.5354 0.4993 0.5000 0.5045 0.5407 0.4990 0.5699 Awareness / understanding 0.7217 0.4489 0.6607 0.4778 0.7310 0.4441 0.2755 Imitation 0.3208 0.4673 0.6071 0.4928 0.2772 0.4482 0.0000*** Trust-building 0.1262 0.3325 0.2364 0.4288 0.1098 0.3128 0.0082***

Informal risk sharing 0.6887 0.4636 0.4821 0.5042 0.7201 0.4496 0.0003***

Religion

Interest 0.5425 0.4988 0.7500 0.4369 0.5109 0.5006 0.0008***

Mutuality 2.3821 1.2586 3.2500 1.3108 2.2500 1.1983 0.0000***

Risk aversion – Small losses 1.3188 1.0429 1.3671 1.1159 1.3115 1.0327 0.7103

Risk aversion – High losses 1.6176 1.1080 1.6204 1.1170 1.6171 1.1081 0.9834

Observations 424 56 368

According to the National Household Income and Expenditure Survey from 2012/2013, this accounts to about two thirds of the mean monetary household income in the Eastern Province (LKR 27,477 / month or LKR 329,724 annually) and is slightly below the median annual income (Department of Census and Statistics, 2015). As displayed in Table 29, the surveyed households pertain to the lower income groups, following the national classification of income groups. The households with a mean monthly income of about LKR 21,273 (approx. EUR 118.46) belong to the poorest 40 percent and are low to mid income groups. For comparison, the lowest income group (20 percent of the cumulative population) receives a mean household monthly income of LKR 10,245 (approx. EUR 57.05) (Department of Census and Statistics, 2014: 5). The below average income situation of the survey participants is also confirmed by a slightly negative asset endowment index.

Table 29: Breakdown of household income 2012/13

Household income quintile

2012/2013 Lowest Low-mid Middle Mid-upper Upper

1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile Mean household

income per month (LKR)

10,245 21,273 30,944 45,569 121,368

Mean household income per month (approx. EUR) 57.05 118.26 172.31 253.75 675.84 Share of income (%) 4.5% 9.3% .13.5% 19.9% 52.9% Cumulative share of income (%) 4.5% 13.7% 27.2% 47.1% 100%

Source: Adapted from Department of Census and Statistics (2014: 5)

The average respondent’s level of financial literacy is rather low. Out of three questions, only average 1.24 correct answers are given by the participants. Mean values of the characteristics related to social capital show that the average respondent belongs to 0.87 formal organizations and about half of the respondents from the sample believe that “most people can be trusted” (54 percent), whereas the others opt for the statement that “generally speaking you cannot be too careful in dealing with people” (46 percent). Almost 72 percent of the sampled households have exchanged information with their peers on insurance, meaning that they have either consulted their friends, relatives or neighbors for advice or given advice to them. The analysis reveals that 32 percent of the

respondents know someone who has purchased insurance. Moreover, it is observed that 69 percent of the respondents usually borrow from their friends, relatives or neighbor if they are facing an unexpected event which affects their financial situation.

Concerning the demand factor of religion and potential explanations for an effect of religious denomination on micro life insurance consumption, the descriptive statistics show that more than half of the respondents (54 percent) currently pay interest on their borrowings or receive interest payments on their savings. On average, respondents do not acknowledge the mutual character of insurance because they do not perceive insurance as a form of institutionalized solidarity. Instead, they are more likely to disagree with the statement that by purchasing insurance “others in need are supported” (the mean value of a 5 point Likert is 2.35, whereby the value of 2 correspondents to “disagree” and the value 3 to “neither agree nor disagree”). On average, the respondents are severely risk averse.

When directly questioned about their lack of insurance coverage, most of the non- policyholders state that they cannot afford the regular insurance premium payment (127 responses). Religious reasons (93 responses) are ranked second, followed by a lack of information about insurance (36 responses). Furthermore, the survey participants do not trust in the performance of the insurers. They believe that processes take long or insurers do not settle claims (19 responses).