The nexus between the demand for life insurance and institutional factors in Europe: new evidence from a panel data approach

Figures & data

Figure 1. The cut-off of income distribution for different levels of incomes. Source: created by the authors.

Table 1. Dependent and explanatory variables used in the regression models and the sources of data.

Variable	Codification	Source
(A) Endogenous variable
Life insurance density	LID	Insurance Europe, Statistics No. 49 and No.50, European Insurance for Total Life Premiums and Number of Population, Eurostat
(B) Exogenous variables
(B1) Control variables
Income	GDP_cap	World Bank, 2015
Inflation	Inflation	World Bank, 2015
Urban population	Urbanpop	World Bank, 2015
Health expenditure	Health	World Bank, 2015
Age dependency	Agedep	World Bank, 2015
Long-term interest rate	Interest	European Central Bank
Income distribution	Gini	World Bank, 2015
School enrolment tertiary	SchoolEnrol	World Bank, 2015
(B2) Institutional variables
Voice and accountability	Voice	Worldwide Governance Indicators
Political stability and absence of violence	Polstab	Worldwide Governance Indicators
Government effectiveness	Goveff	Worldwide Governance Indicators
Regulatory quality	Regqual	Worldwide Governance Indicators
Rule of law	Rulelaw	Worldwide Governance Indicators
Control of corruption	Ctrcorrup	Worldwide Governance Indicators

Source: Created by the authors, using data from Insurance Europe, World Bank (2015a), European Central Bank (2015) and Worldwide Governance Indicators World Bank (2015b).

Table 2. Descriptive statistics.

Variable		Minimum	Maximum	Mean	Standard deviation	Coefficient variation
LID	Developed	46	4511	1414	909	0.643
	Emergent	3	320	94	89	0.948
Voice	Developed	68.2	100	92.0	7.03	0.076
	Emergent	40.9	87.0	71.0	11.1	0.157
Polstab	Developed	30.1	100	78.9	17.4	0.221
	Emergent	13.3	92.8	65.4	17.5	0.267
Goveff	Developed	62.1	100	90.4	8.85	0.098
	Emergent	43.5	84.9	70.5	10.1	0.143
Regqual	Developed	68.4	100	90.2	7.26	0.080
	Emergent	51.5	91.7	76.0	9.00	0.118
Rulelaw	Developed	60.3	100	90.8	9.40	0.104
	Emergent	45.0	85.6	66.4	11.1	0.168
Ctrcorup	Developed	51.2	100	89.4	10.5	0.117
	Emergent	32.2	83.4	64.1	9.52	0.148
Gini	Developed	25.5	38.9	31.3	3.06	0.098
	Emergent	23.7	42.2	31.9	4.38	0.137
Urbanpop	Developed	49.9	97.7	70.7	12.6	0.179
	Emergent	59.6	93.8	76.3	9.69	0.127
Agedep	Developed	41.4	56.8	49.6	2.96	0.059
	Emergent	38.1	56.5	45.7	3.91	0.085
Inflation	Developed	−5.20	11.39	2.29	1.97	0.862
	Emergent	−10.2	37.42	4.97	5.61	1.129
GDP_cap	Developed	14,355	87,773	40,505	15,900	0.393
	Emergent	3,157	20,988	9,963	3,969	0.398
Interest	Developed	0.65	22.5	4.42	2.10	0.475
	Emergent	0.62	45.0	6.76	5.33	0.787
Healt	Developed	6.05	12.68	9.41	1.29	0.137
	Emergent	4.59	9.38	6.83	1.10	0.161
SchoolEnrol	Developed	10.3	116.6	62.3	18.3	0.293
	Emergent	26.2	88.5	59.7	14.8	0.248

Source: Created by the authors.

Table 3. Estimated impact of the institutional variables on life insurance density.

Variable	Model 1 F.E.^†	Model 2 R.E.^‡	Model 3 F.E.	Model 4 R.E.	Model 5 R.E.	Model 6 R.E.
Voice	−0.006 [0.0077]	–	–	–	–	–
Polstab	–	0.0001 [0.0053]	–	–	–	–
Goveff	–	–	0.0170 [0.0112]	–	–	–
Regqual	–	–	–	0.0348^*** [0.0094]	–	–
Rulelaw	–	–	–	–	0.0407^*** [0.0131]	–
Ctrcorrup	–	–	–	–	–	0.0172 [0.0110]
Gini	0.0073 [0.0117]	0.0050 [0.0125]	0.0084 [0.0117]	0.0035 [0.0118]	0.0065 [0.0118]	0.0035 [0.0121]
Urbanpop	0.0663 [0.0510]	0.0226 [0.0252]	0.0852^* [0.0501]	0.0256 [0.0228]	0.0323 [0.0225]	0.0266 [0.0258]
Agedep	−0.0132 [0.0312]	−0.0088 [0.0270]	−0.0056 [0.0324]	0.0046 [0.0281]	−0.0036 [0.0290]	−0.0020 [0.0289]
Inflation	0.0011 [0.0074]	−0.0023 [0.0085]	0.0020 [0.0077]	0.0042 [0.0057]	0.0014 [0.0065]	0.0009 [0.0075]
GDP_cap	0.00007^*** [0.00002]	0.00007^*** [0.00002]	0.00006^*** [0.00002]	0.00006^*** [0.00002]	0.00005^*** [0.00002]	0.00006^*** [0.00002]
Interest	−0.0064 [0.0055]	−0.0043 [0.0063]	−0.0027 [0.0058]	0.0004 [0.0053]	−0.0015 [0.0069]	0.0047 [0.0092]
Health	0.0448 [0.0661]	0.0724 [0.0612]	0.0419 [0.0627]	0.0481 [0.0494]	0.0271 [0.0527]	0.0672 [0.0595]
SchoolEnrol	0.0072 [0.0049]	0.0085^* [0.0049]	0.0084^* [0.0046]	0.0119^*** [0.0038]	0.0090^** [0.0040]	0.0105^** [0.0042]
Constant	−0.7831 [3.9352]	1.2278 [2.0963]	−4.4802 [4.3241]	−2.3064 [2.3995]	−2.2434 [2.7197]	−0.6190 [3.0677]
Hausman (p)	0.018	0.251	0.002	0.185	0.600	0.764
R^2 within	0.351	0.331	0.365	0.426	0.445	0.348
R^2 between	0.320	0.568	0.324	0.597	0.607	0.590
R^2 overall	0.342	0.570	0.349	0.610	0.600	0.588
F	6.37		10.26
Prob > F	0.000		0.000
Wald Chi^2		116.87		454.94	203.09	115.83
Prob > Chi^2		0.000		0.000	0.000	0.000

Notes: This table reports the results of panel regressions (the models from Equation (1)) for the impact of institutional indicators on life insurance industry size across countries for the period 2002–2012, controlling for socio-demographic and economic development.

Coefficient [Robust standard errors].

^*** significant at 1%.

^** significant at 5%.

^* significant at 10%.

^† Fixed effects.

^‡ random effects.

Source: authors’ computations in STATA 14 (StataCorp LLC, Texas, USA).

Table 4. Estimated impact of the institutional variables on life insurance density using a dummy variable for transition and emerging countries.

Variable	Model 2 R.E.^†	Model 4 R.E.	Model 5 R.E.	Model 6 R.E.
Polstab	0.0043 [0.0040]	–	–	–
Regqual	–	0.0396^*** [0.0100]	–	–
Rulelaw	–	–	0.0404^*** [0.0125]	–
Ctrcorrup	–	–	–	0.0221^** [0.0100]
D × Polstab	−0.0098 [0.0076]	–	–	–
D × Regqual	–	−0.0132^** [0.0053]	–	–
D × Rulelaw	–	–	0.0006 [0.0057]	–
D × Ctrcorrup	–	–	–	−0.0125 [0.0077]
Gini	0.0027 [0.0128]	0.0009 [0.0119]	0.0066 [0 .0116]	0.0029 [0.0124]
Urbanpop	0.0226 [0.0239]	0.0307 [0.0202]	0.0313 [0.0210]	0.0313 [0.0239]
Agedep	−0.0146 [0.0267]	−0.0040 [0.0290]	−0.0035 [0.0298]	−0.0103 [0.0310]
Inflation	−0.0013 [0.0085]	0.0043 [0.0059]	0.0013 [0.0062]	0.0010 [0.0077]
GDP_cap	0.00006^*** [0.00002]	0.00005^*** [0.00002]	0.00005^*** [0.00002]	0.00005^*** [0.00002]
Interest	−0.0027 [0.0065]	0.0010 [0.0051]	−0.0015 [0.0070]	0.0025 [0.0099]
Health	0.0763 [0.0597]	0.0413 [0.0479]	0.0281 [0.0528]	0.0614 [0.0588]
SchoolEnrol	0.0101^** [0.0045]	0.0139^*** [0.0038]	0.0089^** [0.0043]	0.0122^*** [0.0045]
Constant	1.6277 [2.0027]	−1.9503 [2.3976]	−2.1837 [2.6907]	−0.3502 [3.1218]
R^2 within	0.333	0.427	0.445	0.349
R^2 between	0.617	0.665	0.606	0.6423
R^2 overall	0.606	0.664	0.599	0.633
Wald Chi^2	143.8	574.19	203.27	151.29
Prob > Chi^2	0.000	0.000	0.000	0.000

Notes: This table reports the results of panel regressions (the models from Equation (2)) for the impact of institutional indicators on life industry size across countries for the period 2002–2012, controlling for socio-demographic and economic development.

Coefficient [Robust standard errors].

^*** significant at 1%.

^** significant at 5%.

^* significant at 10%.

^† Random effects.

Source: authors’ computations in STATA 14.

Table 5. Evaluation of the ad-joint effect of regulatory quality and the degree of economic development on life insurance density.

Effect tested	Chi^2	p-value
Regqual + D × Regqual	8.49	0.004

Source: authors’ computations in STATA 14.

Table 6. Estimated impact of the institutional variables on life insurance density for transition and emerging countries.

Variable	Model 1 F.E.^†	Model 2 R.E.^‡	Model 3 R.E.	Model 4 R.E.	Model 5 R.E.	Model 6 R.E.
Voice	−0.0035[0.0078]	–	–	–	–	–
Polstab	–	−0.004 [0.0043]	–	–	–	–
Goveff	–	–	−0.0069 [0.0134]	–	–	–
Regqual	–	–	–	0.0126^* [0.0070]	–	–
Rulelaw	–	–	–	–	0.0246^*** [0.0096]	–
Ctrcorrup	–	–	–	–	–	0.0065 [0.0089]
Gini	0.0161 [0.0094]	0.0174 [0.0078]^**	0.0177 [0.0085]^**	0.0183 [0.0074]^**	0.0169 [0.0062]^***	0.0159 [0.0070]^**
Urbanpop	0.1096 [0.0264]^***	0.0664 [0.0244]^***	0.0661 [0.0287]^**	0.0576 [0.0228]^**	0.0666 [0.0224]^***	0.0652 [0.0239]^***
Agedep	0.0199 [0.0394]	0.0092 [0.0377]	0.0121 [0.0383]	0.0173 [0.0384]	−0.0004 [0.0333]	0.0160 [0.0426]
Inflation	0.0033 [0.0054]	−0.0010 [0.0046]	−0.0014 [0.0041]	0.0003 [0.0050]	0.0009 [0.0037]	−0.0004 [0.0040]
GDP_cap	0.0003^*** [0.00007]	0.0003^*** [0.00007]	0.0003^*** [0.00007]	0.0003^*** [0.00007]	0.0003^*** [0.00006]	0.0003^*** [0.00007]
Interest	−0.0012 [0.0065]	0.0041 [0.0068]	0.0021 [0.0066]	0.0025 [0.0069]	0.0030 [0.0069]	0.0075 [0.0053]
Health	−0.0025 [0.0537]	−0.0025 [0.0576]	0.0028 [0.0656]	−0.0104 [0.0552]	−0.0400 [0.0457]	−0.0117 [0.0627]
SchoolEnrol	−0.0062 [0.0094]	0.0002 [0.0089]	−0.0005 [0.0090]	−0.0010 [0.0094]	−0.0009 [0.0088]	0.0011 [0.0085]
Constant	−8.3537 [3.5942]^**	−5.0100 [3.0010]^*	−4.9007 [4.1350]	−5.8279 [3.2704]^*	−5.7921 [3.1431]^*	−5.8198 [3.7516]
Hausman (p)	0.020	0.249	0.403	0.166	0.359	0.172
R^2 within	0.789	0.785	0.782	0.785	0.806	0.783
R^2 between	0.197	0.4692	0.486	0.532	0.498	0.489
R^2 overall	0.329	0.536	0.557	0.598	0.568	0.559
F	3268.4
Prob > F	0.000
Wald Chi^2		789.89	359.63	611.19	1210.07	281.86
Prob > Chi^2		0.000	0.000	0.000	0.000	0.000

Notes: This table reports the results of panel regressions (the models from Equation (1)) for the impact of the level of institutional indicators on life industry size across transition and emerging countries for the period 2002–2012, controlling for socio-demographic and economic development.

Coefficient [Robust standard errors].

^*** significant at 1%.

^** significant at 5%.

^* significant at 10%.

^† Fixed effects.

^‡ random effects.

Source: authors’ computations in STATA 14.

Table 7. Estimated impact of the institutional variables on life insurance density for developed countries.

Variable	Model 1 F.E.^†	Model 2 F.E.	Model 3 F.E.	Model 4 R.E.^‡	Model 5 R.E.	Model 6 F.E.
Voice	−0.0072[0.0091]	–	–	–	–	–
Polstab	–	−0.0030 [0.0038]	–	–	–	–
Goveff	–	–	0.0095 [0.0079]	–	–	–
Regqual	–	–	–	0.0252^** [0.0117]	–	–
Rulelaw	–	–	–	–	0.0057 [0.0109]	–
Ctrcorrup	–	–	–	–	–	−0.0023 [0.007]
Gini	0.0422 [0.0236]^*	0.0427 [0.0231]	0.0433^* [0.0225]	0.0333 [0.0230]	0.0371 [0.0250]	0.0410 [0.0236]
Urbanpop	0.0161 [0.0435]	0.0169 [0.0403]	0.0315 [0.0414]	0.0071 [0.0093]	0.0007 [0.0117]	0.0179 [0.0495]
Agedep	0.0118 [0.0327]	0.0129 [0.0341]	0.0166 [0.0329]	0.0216 [0.0287]	0.0215 [0.0300]	0.0140 [0.0334]
Inflation	−0.0201 [0.0136]	−0.0186 [0.0129]	−0.0199 [0.0131]	−0.0176 [0.0101]^*	−0.0180 [0.0110]	−0.0191 [0.0132]
GDP_cap	0.00005^*** [0.00001]	0.00005^*** [0.00001]	0.00005^*** [0.00001]	0.00002^*** [0.00001]	0.00003^*** [0.000009]	0.00005^*** [0.00001]
Interest	−0.0122 [0.0120]	−0.0115 [0.0106]	−0.0059 [0.0101]	−0.0128 [0.0110]	−0.0189 [0.0137]	−0.0092 [0.0087]
Health	0.0163 [0.0532]	0.0131 [0.0535]	0.0212 [0.0524]	−0.0010 [0.0372]	0.0080 [0.0388]	0.0181 [0.0534]
SchoolEnrol	−0.0033 [0.0053]	−0.0032 [0.0053]	−0.0027 [0.0051]	0.0048 [0.0033]	0.0007 [0.0043]	−0.0032 [0.0057]
Constant	2.8018 [1.9852]	2.3836 [1.2901]^*	−0.1597 [2.2143]	0.7540 [1.4002]	2.9605 [1.5705]^*	2.1735 [2.8197]
Hausman (p)	0.000	0.002	0.000	0.387	0.176	0.049
R^2 within	0.213	0.215	0.219	0.256	0.182	0.209
R^2 between	0.090	0.097	0.082	0.226	0.176	0.090
R^2 overall	0.068	0.075	0.059	0.203	0.152	0.068
F	4.22	6.61	4.76			3.64
Prob > F	0.004	0.0003	0.002			0.008
Wald Chi^2				183.57	64.67
Prob > Chi^2				0.000	0.000

Notes: This table reports the results of panel regressions (the models from Equation (1)) for the impact of the level of institutional indicators on life industry size across developed countries for the period 2002–2012, controlling for socio-demographic and economic development.

Coefficient [Robust standard errors].

^*** significant at 1%.

^** significant at 5%.

^* significant at 10%.

^† Fixed effects.

^‡ random effects.

Source: own computations in STATA 14.

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