Determinants of Takāful and conventional insurance demand: A regional analysis

Figures & data

Table 1. Descriptive statistics of conventional insurance and Takāful demand

Region	Insurance demand			Takāful demand
	Mean	Median	S.D.	Mean	Median	S.D.
Overall	236.9201	226.3807	55.14612	43.52092	45.31873	20.12828
Middle east	329.8462	313.839	73.21793	65.95812	72.31181	28.18699
ASEAN	215.8705	206.4358	68.97616	17.1688	16.14509	9.747923
South Asia	14.15594	13.88243	3.731715	0.474206	0.574459	0.252421

Notes: The above table shows the descriptive statistics results for conventional insurance and Takāful demand. Conventional insurance demand is measured through insurance density (Insurance premiums written divided by total population). Takāful demand is measured through Takāful density (Takāful contributions written divided by total population). Middle East Region consists of countries of Saudi Arabia, Iran, Jordan, Lebanon, Kuwait, Qatar, United Arab Emirates and Bahrain. ASEAN Region consists of countries Malaysia, Indonesia and Thailand. South Asian region consists of Countries of Pakistan, Srilanka and Bangladesh.

Source: Authors’ own calculation using STATA 11 software.

Figure 1 Dependent and independent factors across sample regions.

Table 2. Results of fixed effects regression model for conventional insurance and Takāful demand

Variable	Insurance demand	Takāful demand
Income	0.589***	0.614**
	(5.59)	(1.98)
Inflation	0.001***	0.005***
	(3.61)	(4.81)
Financial developments	0.002**	0.003
	(2.49)	(0.93)
Education	0.011*	−0.029
	(1.75)	(−1.57)
Urbanization	0.033***	0.113***
	(4.53)	(5.07)
Dependency ratio	−0.002	−0.039***
	(−0.85)	(−5.29)
Constant	−2.673***	−3.517***
	(−5.80)	(−2.49)
Hausman test value	24.03***	12.96***
No. of observations	140	140

Notes: The above table shows the results of fixed effect regression for conventional insurance and Takāful demand. Conventional insurance demand is measured through insurance density (Insurance premiums written divided by total population). Takāful demand is measured through Takāful density (Takāful contributions written divided by total population). Income is measured through GDP per capita (GDP in millions US dollars divided by total population). Urbanization is measured through percentage of population in urban area. Education is measured through tertiary (%) school enrollment Education. Inflation is measured through change in CPI (consumer price index). Dependency ratio is measured through average number of dependents. Financial sector developments measured through credits of banks to private sector. Data for Conventional insurance and Takāful demand were collected from Swiss Re Sigma Reports and Ernst & Young Reports, respectively. Data for independent variables was taken from world development indicators. Hausman test is used to select fixed or random effect regression model. Values in parentheses show t-values of respective co-efficients using fixed effect models.

Source: Authors’ own calculation using STATA 11 software.

* Significance at 10% level.

** Significance at 5% level.

*** Significance at 1% level.

Table 3. Results of fixed effects regression model for conventional insurance and Takāful demand in ASEAN region

Variable	Insurance demand	Takāful demand
Income	1.232***	−0.154*
	(8.82)	(−1.69)
Inflation	−0.396***	0.618***
	(−4.31)	(4.75)
Financial developments	0.002***	0.002**
	(4.99)	(2.39)
Education	−0.004	−0.006**
	(−0.87)	(−2.17)
Urbanization	0.003***	0.121***
	(3.71)	(3.00)
Dependency ratio	−0.015***	−0.027**
	(−4.99)	(−1.99)
Constant	−1.19***	−7.023***
	(−4.74)	(−3.39)
Hausman test value	18.79**	47.05***
No. of observations	60	60

Notes: The above table shows the results of fixed effect regression for conventional insurance and Takāful demand in ASEAN region. Conventional insurance demand is measured through insurance density (Insurance premiums written divided by total population). Takāful demand is measured through Takāful density (Takāful contributions written divided by total population). Income is measured through GDP per capita (GDP in millions US dollars divided by total population). Urbanization is measured through percentage of population in urban area. Education is measured through tertiary (%) school enrollment Education. Inflation is measured through change in CPI (consumer price index). Dependency ratio is measured through average number of dependents. Financial sector developments measured through credits of banks to private sector. Data for Conventional insurance and Takāful demand were collected from Swiss Re Sigma Reports and Ernst & Young Reports, respectively. Data for independent variables was taken from world development indicators. Hausman test is used to select fixed or random effect regression model. Values in parentheses show t-values of respective co-efficients using fixed effect models.

South Asian countries have been merged with ASEAN countries as they have less than 5% Takāful share in the world Takāful market (Ernst & Young, 2015).

Source: Authors’ own calculation using STATA 11 software.

* Significance at 10% level.

** Significance at 5% level.

*** Significance at 1% level.

Table 4. Results of fixed and random effects regression model for conventional insurance and Takāful demand in middle east region

Variable	Insurance demand	Takāful demand
Income	0.273**	−0.636**
	(2.10)	(−2.43)
Inflation	0.862***	0.351**
	(3.91)	(2.58)
Financial developments	0.006*	0.007
	(1.67)	(0.38)
Education	0.026***	−0.031*
	(2.70)	(−1.79)
Urbanization	0.033**	0.128***
	(2.52)	(4.70)
Dependency ratio	−0.005*	−0.041***
	(−1.79)	(−5.73)
Constant	−3.588***	−5.635**
	(−3.12)	(−2.40)
Hausman test value	26.79***	11.43**
No. of observations	80	80

Notes: The above table shows the results of fixed and random effect regression for conventional insurance and Takāful demand in Middle East region. Conventional insurance demand is measured through insurance density (Insurance premiums written divided by total population). Takāful demand is measured through Takāful density (Takāful contributions written divided by total population). Income is measured through GDP per capita (GDP in millions US dollars divided by total population). Urbanization is measured through percentage of population in urban area. Education is measured through tertiary (%) school enrollment Education. Inflation is measured through change in CPI (consumer price index). Dependency ratio is measured through average number of dependents. Financial sector developments measured through credits of banks to private sector. Data for Conventional insurance and Takāful demand were collected from Swiss Re Sigma Reports and Ernst & Young Reports, respectively. Data for independent variables was taken from world development indicators. Hausman test is used to select fixed or random effect regression model. Values in parentheses show t-values of respective co-efficients using fixed effect models.

Source: Authors’ own calculation using STATA 11 software.

* Significance at 10% level.

** Significance at 5% level.

*** Significance at 1% level.

Table 5. Overall results summary

Variable	Overall sample		ASEAN		Middle east
	Insurance demand	Takāful demand	Insurance demand	Takāful demand	Insurance demand	Takāful demand
Income	+***	+**	+***	−*	+**	−**
Inflation	+***	+***	−***	+***	+***	+**
Finan. develop	+**	+	+***	+***	+*	+
Education	+*	−	−	−**	+***	−*
Urbanization	+***	+***	+***	+***	+**	+***
Dependency ratio	−	−***	−***	−**	−*	−***

* Significance at 10% level.

** Significance at 5% level.

*** Significance at 1% level.

Table 6. Results summary of hypotheses tested

Hypotheses	Overall sample	ASEAN	Middle east
Hypothesis I-A: Significant relationship exists between Per capita income and conventional insurance demand	Accepted	Accepted	Accepted
Hypothesis I-B: Significant relationship exists between Per capita income and Takāful demand	Accepted	Accepted	Accepted
Hypothesis II-A: There is significant relationship existing between inflation rate and conventional insurance demand	Accepted	Accepted	Accepted
Hypothesis II-B: There is significant relationship exist between inflation rate and Takāful demand	Accepted	Accepted	Accepted
Hypothesis III-A: There is significant relationship existing between financial sector developments and conventional insurance demand	Accepted	Accepted	Accepted
Hypothesis III-B: There is significant relationship existing between financial sector developments and Takāful demand	Rejected	Accepted	Rejected
Hypothesis IV-A: There is significant relationship existing between education level and conventional insurance demand	Accepted	Rejected	Accepted
Hypothesis IV-B: There is significant relationship existing between education level and Takāful demand	Rejected	Accepted	Accepted
Hypothesis V-A: There is significant relationship between urbanization and conventional insurance demand	Accepted	Accepted	Accepted
Hypothesis V-B: There is significant relationship between urbanization and Takāful demand	Accepted	Accepted	Accepted
Hypothesis VI-A: There is significant relationship existing between dependency ratio and conventional insurance demand	Rejected	Accepted	Accepted
Hypothesis VI-B: There is significant relationship existing between dependency ratio and Takāful demand	Accepted	Accepted	Accepted

Note: These results of hypotheses were accepted and rejected at 5% and 1% level only.

Table

Location	Number	Location	Number	Location	Number
1. Saudi Arabia	23	12. Syria	4	23. Singapore	1
2. Jordan	3	13. Yemen	1	24. Sri Lanka	2
3.UAE	7	14. Algeria	1	25. Iran	15
4.Bahrain	9	15. Indonesia	6	26. Australia	1
5. Kuwait	11	16. Luxemburg	2	27. Thailand	1
6.Egypt	4	17. Malaysia	9	28. Trinidad	1
7. Lebanon	1	18. Mauritania	1	29. Turkey	2
8.Palestine	2	19. Pakistan	5	30. Bahamas	1
9.Qatar	5	20. Ghana	1	31. Britain	1
10. Libya	1	21. Brunei	4	32. Bangladesh	1
11. Sudan	15	22. Senegal	2	33. Gambia	1

Ernst & Young. (2015). Global Takāful insight Report 2014. Chennai: Author.

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