Measuring efficiency and productivity changes: A non-parametric analysis of Ghanaian life insurance industry

Figures & data

Table 1. The assets of Ghana’s life insurance sector (2014–2020)

	2014	2015	2016	2017	2018	2019	2020
Total Assets (GHS’Million)	2212	3027	3667	4653	5490	6540	7693
Growth in Assets (%)	23	37	21	27	18	19	18
Total Asset/GDP(%)	1	2	2	2	2	2	2
Share of financial sector Assets	3	3	3	3	3	4	4

Source: NIC (2020)

Table 2. Descriptive statistics of input and output variables used

	Inputs			Outputs
	Labour	Equity	Claims	Gross premium	Investment income
Mean	832,010	7,461,700	2,2827,99	22,390.2	2,904,128
Std dev	520,582	8,308,500	8,174,504	1460.01	954,444
Minimum	561,490	6,051,730	1,553,580	3,185,943	500,630
Maximum	908,1924	15,999,500	29,923,540	20,213,254	5,132,850

Source: authors’ computations

Table 3. Correlation coefficients of input and output variables

Variable	Labour	Equity	Claims	Gross premium	Investment income
Labour	1.0000	0.8631	0.6538*	0.8745	0.9003
Equity	0.8631	1.0000	0.8654	0.5789**	0.9832
Claims	0.6538*	0.8654	1.0000	0.7645**	0.9032
Gross premium	0.8745	0.5789**	0.7645**	1.0000	0.8097**
Investment income	0.9003	0.9832	0.9032	0.8097**	1.0000

Source: authors’ computations

Single asterisk (*) denotes significant differences from unity at 90%; double asterisk (**) denotes significant difference from unity at 95% and triple asterisk (***) denotes significant difference from unity at 99%.

Table 4. Bootstrap estimates for the period 2015 –2020

Year	Estimated Efficiency	Bias-corrected	Bias	Lower bound	Upper bound
2015	0.85645	0.81792	0.03853	0.66320	0.83563
2016	0.98792	0.90763	0.08029	0.87685	0.98185
2017	0.91374	0.87061	0.04313	0.85220	0.90369
2018	0.98382	0.89914	0.08468	0.89630	0.91382
2019	0.93350	0.87150	0.06200	0.80399	0.92135
2020	0.66580	0.62453	0.04127	0.60896	0.64419
Mean	0.89020	0.83189	0.05832	0.78358	0.86676

Source: authors’ computations

Table 5. Bias-corrected productivity changes for each insurer for the period 2015–2020

DMU	2015/16	2016/17	2017/18	2018/19	2019/20	2015/20
L1	1.0943	1.0031	1.0931	1.0035	0.9203	1.0207
L2	0.9489	0.7485	1.0995	1.0488	1.0434	0.9691
L3	0.7093	0.6095	0.8085	0.7098	0.6086	0.6852
L4	1.0806	0.9806	1.0805	0.9058	1.0209	1.0115
L5	0.7017	0.5017	0.6875	0.6067	1.0686	0.6905
L6	1.1908	1.0492	1.0299	1.0809	0.6092	0.9675
L7	0.3134	0.5291	0.5295	0.4929	0.5293	0.4699
L8	0.2851	0.3695	0.9651	1.0365	1.0607	0.6452
L9	1.1072	0.8072	0.8879	0.9072	1.0908	0.9528
L10	1.0671	0.9061	1.0909	0.9065	1.0952	1.0093
L11	1.0750	0.9950	1.1399	1.005	0.1885	0.7459
L13	0.7015	0.8015	1.0815	1.0615	0.9081	0.8987
L14	1.0413	1.1005	1.0945	1.1005	1.3405	1.1309
L15	1.0146	0.9942	1.1042	0.8942	0.9855	0.9963
L16	1.0808	0.8085	1.0180	0.9985	1.0885	0.9933
L17	0.4029	0.8025	1.0165	0.9927	1.0881	0.8129
L18	0.9122	1.1094	1.1021	0.9535	1.0881	1.0296
L19	1.1350	1.0252	1.1588	1.0653	0.9015	1.0531
Mean	0.8151	0.8084	0.9823	0.9137	0.8616	0.8739

Source: authors’ computations

Table 6. Source of productivity change for life insurance industry for the entire period

Insurer	MPI	EFFECH	TECH	PTEC	SEC
L1	1.02070	1.00190	1.01876	0.85275	1.19468
L2	0.96910	2.62270	0.36950	2.39341	0.15438
L3	0.68520	0.63530	1.07855	1.78756	0.60336
L4	1.01150	1.10930	0.91184	1.21781	0.74875
L5	0.69050	0.63290	1.09101	0.76024	1.43509
L6	0.96750	0.88380	1.09470	0.81569	1.34206
L7	0.46990	0.47040	0.99894	0.48455	2.06158
L8	0.64520	0.60530	1.06592	0.57077	1.86751
L9	0.95280	0.85890	1.10933	0.79103	1.40238
L10	1.00930	1.02890	0.98095	1.02327	0.95864
L11	0.74590	0.68660	1.08637	0.63194	1.71911
L13	0.89870	1.12230	0.80077	1.23032	0.65086
L14	1.13090	1.03420	1.09350	1.15669	0.94537
L15	0.99630	1.10590	0.90090	1.10040	0.81870
L16	0.99330	0.90340	1.09951	0.86991	1.26394
L17	0.81290	0.80850	1.00544	1.60067	0.62814
L18	1.02960	1.01770	1.01169	1.42435	0.71028
L19	1.05310	1.14570	0.91918	2.96078	0.31045
G.Mean	0.87380	0.82670	1.05697	1.09383	0.96631

Source: authors’ computations