An empirical investigation of the effect of corruption on domestic savings in Nigeria

Figures & data

Figure 1. Plots of domestic savings in selected developing countries including Nigeria. Source: Authors’ compilation based on data obtained from the World Development Indicators.

Table 1. Summary of empirical literature on corruption and savings relationship (and other determinants of savings).

Author(s) and year	Country/region	Method/model	Findings
Savings and corruption
Dietz et al. (2007)	115 countries for a period of 18 years	GMM	Negative effect of resource abundance on genuine savings reduces as corruption reduces.
Swaleheen (2008)	53–100 countries for a 10 year period.	GMM	Corruption has a significant negative influence on savings.
Abu et al. (2015)	ECOWAS countries from 1996 to 2012.	OLS/TSLS	Negative impact of corruption on savings reduces as income level increases.
Boateng et al. (2019)	Sub-Saharan Africa from 1980 to 2015	2S-IV-GMM	Quality of institutions (including control of corruption) has positive influence on savings.
Savings and its determinants (other than corruption)
Bamidele et al. (2015)	Nigeria	Error correction method	Real interest rate, per capita income, rate of inflation, current account position, and financial reforms are significant drivers of savings.
Adelakun (2015)	Nigeria	Error correction technique	Inflation and interest rates are the major drivers of savings
Ozioma et al. (2016)	Nigeria	Error correction approach	Rate of interest and level of income are core determinants of domestic savings
Mojekwu and Ogbulu (2017)	Nigeria	Multiple regression	Financial deepening promotes savings.
Imoisi et al. (2018)	Nigeria	OLS	Income level and deposit rate have strong influence on savings.
Otiwu et al. (2018)	Nigeria	Error correction method	Income level and financial inclusion are important drivers of savings.

Source: Authors’ compilation.

Table 2. Descriptive statistics.

	LSAV	COR	LGDPC	GDPG	INF	DEPR	LOILP	UNEM
Mean	12.3135	2.9414	4.8641	1.3313	2.8987	2.6229	1.0663	3.7420
Max.	12.8036	7.0390	5.0180	3.9905	4.9514	4.2139	1.4494	7.9929
Min.	11.6346	−0.1101	4.7048	−0.4853	1.2240	1.3334	0.4713	0.6859
Std. Dev.	0.3424	3.0310	0.0997	0.8872	0.9639	0.7220	0.2807	1.6696
Obs.	88	88	88	88	88	88	88	88

Source: Authors’ calculation using quarterly data. L denotes logarithm.

Table 3. Results of unit root tests.

	ADF		PP
Variable	Level	1st Diff.	Level	1st Diff.
LSAV	−2.1687	−3.6328***	−1.5407	−5.9257***
COR	−0.8628	−3.0352**	−0.6472	−5.2310***
LGDPC	−1.6442	−2.7462*	−1.5146	−2.7958*
GDPG	−2.1455	−3.4705**	−2.1154	−5.6854***
INF	−3.5101**	–	−2.9294**	–
DEPR	−2.5193	−4.8313***	−1.9715	−5.0308***
LOILP	−1.8578	−4.4453***	−1.4913	−4.6031***
UNEM	−2.5743	−2.7390*	−2.4868	−5.8209***

Source: Authors’ calculation using quarterly data. ^*, ^** and ^*** indicate a rejection of the null hypothesis of no unit root at 10%, 5% and 1%, respectively. L denotes logarithm.

Table 4. Results of bounds test to cointegration.

Dependent variable: LSAV		Function: f(LSAV/COR,LGDPC,GDPG,INF,DEPR,LOILP,UNEM)					F-Stat.: 4.5976***
Critical values bounds
10%		5%		2.5%		1%
I(0)	I(1)	I(0)	I(1)	I(0)	I(1)	I(0)	I(1)
1.92	2.89	2.17	3.21	2.43	3.51	2.73	3.90

Source: Authors’ calculation using quarterly data. ^*** denotes a rejection of the null hypothesis of no cointegration at 1% level. L denotes logarithm.

Table 5. Results of estimation of ARDL model.

Regressor	Coefficient	Standard error	T-ratio	Prob.
Panel A: Long-run coefficients – Dependent variable is LSAV
C	5.5676	2.1567	2.5814	0.0124
COR	0.0319	0.0138	2.3055	0.0247
LGDPC	1.1457	0.4830	2.3717	0.0210
GDPG	−0.0356	0.0221	−1.6112	0.1126
INF	0.0386	0.0151	2.5482	0.0135
DEPR	0.1003	0.0352	2.8469	0.0061
LOILP	0.9001	0.1715	5.2480	0.0000
UNEM	−0.0569	0.0244	−2.3257	0.0236
Panel B: Short-run coefficients – Dependent variable is ΔLSAV
ΔLSAV−1	0.3889	0.0875	4.4445	0.0000
ΔLSAV−2	0.1647	0.0746	2.2085	0.0312
ΔLSAV−3	0.1201	0.0716	1.6780	0.0987
ΔCOR	0.0496	0.0107	4.6411	0.0000
ΔCOR−1	−0.0206	0.0112	−1.8317	0.0721
ΔCOR−2	−0.0195	0.0104	−1.8643	0.0673
ΔLGDPC	−0.1590	0.2669	−0.5956	0.5537
ΔINF	−0.0224	0.0072	−3.1099	0.0029
ΔDEPR	0.1072	0.0215	4.9766	0.0000
ΔDEPR−1	−0.0575	0.0220	−2.6104	0.0115
ΔDEPR−2	−0.0296	0.0193	−1.5288	0.1317
ΔLOILP	0.8895	0.0955	9.3057	0.0000
ΔLOILP−1	−0.3549	0.1109	−3.1995	0.0022
ΔUNEM	−0.0193	0.0062	−3.1085	0.0029
ΔUNEM−1	0.0125	0.0063	1.9635	0.0544
ΔUNEM−2	0.0103	0.0065	1.5859	0.1182
ΔUNEM−3	0.0164	0.0065	2.5085	0.0149
ΔECT−1	−0.3131	0.0456	−6.8619	0.0000

Source: Authors’ calculation using quarterly data. L denotes logarithm. Δ is the first difference operator.

Table 6. Results of diagnostic tests.

Test statistic	Results
Serial Correlation: χ^2	2.6030[0.2721]
Functional Form (Ramsey Test): F-Stat.	0.0518[0.8206]
Heteroscedasticity: χ^2	19.3690[0.7791]

Source: Authors’ calculation. Probability values are in parentheses.

Figure 2. Cumulative sum of recursive residuals plots.

Source: Authors’ calculation.

Figure 3. Cumulative sum of squares of recursive residuals plots.

Source: Authors’ calculation.

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