Income inequality and economic growth: An empirical investigation in South Africa

Figures & data

Figure 1. Gini coefficient and growth rate of real GDP of South Africa for the period 1989 to 2018.

Source: Authors’ own construction using data from Atkinson et al. (2017), Quantec EasyData (2022), SWIID 9.2, and World Bank (2022c).

Figure 2. Gini index of upper-middle-income countries for 2018.

Source: Authors’ own construction using data from the World Bank (2022a).

Table 1. Summary of empirical studies on the relationship between income inequality and economic growth

Author(s)	Region/country	Measures of income inequality	Method(s) used	Results*
Negative findings
Alesina and Rodrik (1994)	46 countries, 1960–1985	Gini coefficient	OLS 2SLS	-
Persson and Tabellini (1994)	56 countries, 1960–1985	Share of the fourth quintile	OLS 2SLS	-
Perotti (1996)	67 countries, 1960–1985	Share of the third and fourth quintiles	OLS 2SLS	-
Panizza (2002)	U.S., 1920–1980	Gini index	FE GMM	-
Knowles (2005)	40 countries,1960–1990	Gini coefficient	OLS	-Rich: 0 Poor: -
Wan et al. (2006)	China, 1987–2001	Regional urban–rural income ratio to measure inequality	3SLS	-
Malinen (2008)	60 countries, 1971–2000	Gini index	Panel dynamic OLS Panel dynamic SUR	-
Cingano (2014)	OECD countries, 1980–2012	Gini index	GMM	-
Iyke and Ho (2017)	Italy, 1967–2012	Gini coefficient	ARDL	-
Besarria et al. (2018)	27 Brazilian states (1994–2014)	Gini coefficient	FE, RE, Instrumental variables	-
Braun et al. (2019)	150 countries, 1978–2012	Gini coefficient	Pooled OLS Dynamic panel IV regressions	-
Royuela et al. (2019)	15 OECD countries, 2003–2013	Gini coefficient	Pooled OLS RE IV	-
Breunig and Majeed (2020)	152 countries, 1956–2011	Gini coefficient	GMM	-
Seo et al. (2020)	43 countries (1991–2014)	Gini coefficient	3 SLS	-
Topolewski (2020)	32 European countries (2001–2018)	Gini coefficient	Dynamic panel models	-
Shen and Zhao (2022)	167 economies (1950–2020)	Gini coefficient of income	2 step system GMM; Dynamic panel threshold	-Low income level: -
Topuz (2022)	143 countries	Gini coefficient	Pooled OLS; FE; RE; 2 SLS	-
Positive findings
Partridge (1997)	U.S., 1960–1990	Gini coefficient	Open pooled OLS	+
Li and Zou (1998)	46 countries, 1947–1994	Gini coefficient	FE RE	+
Forbes (2000)	45 mid- to high-income countries, 1966–1995	Gini coefficient	First-difference GMM	+
Rangel et al. (2002)	Brazilian minimum comparable areas, 1991–2000	Gini index	Various estimated regressions	+
Bhorat and Van der Westhuizen (2008)	South Africa, 1995–2005	Gini coefficient	Distribution-neutral measure	+
Shahbaz (2010)	Pakistan, 1971–2005	Gini coefficient	ARDL	+
Majeed (2016)	Pakistan, 1975–2013	Gini coefficient	ARDL	+
Scholl and Klasen (2019)	122 countries, 1961–2012	Gini coefficient	FE GMM IV	+
Da Silva (2020)	Brazil (1992–2011)	Gini coefficient; Theil index; To 10-bottom 40 income ratio	Panel VAR approach	+
Hailemariam et al. (2021)	OECD countries (1870–2016)	Gini coefficient; the income share of the top 10% of the population	Panel vector auto regression	+
Panzera and Postiglione (2022)	245 European Union NUTS-2 regions (from 22 European countries)	Gini index	Spatial Durbin model (SDM); Lagrange multiplier	Less developed regions: +
Inconclusive findings
Deininger and Squire (1998)	66/87 countries, 1960–1992	Gini index	OLS	Poor: - Rich: +
Barro (2000)	84 countries, 1965–1995	Gini coefficient	2SLS	Poor: - Rich: +
Voitchovsky (2005)	21 developed countries, 1975–2000	Gini coefficient	System GMM	Lower decile: - Upper decile: +
Castelló-Climent (2010)	102 countries, 1960–2000	Gini coefficient Distribution of education by quintiles	System GMM	Low- and middle-income countries: - High-income countries: +
Fawaz et al. (2014)	111 high- and low-income developing countries, 1960–2010	Gini coefficient	GMM	Low income countries: - High-income countries: +
Halter et al. (2014)	106 countries, 1965–2005	Gini coefficient	System GMM First-difference GMM	Short run: + Long run: -
Ostry et al. (2014)	90 countries, 1960–2010	Gini coefficient	System GMM	Early stage: + Mature stage: -
Brueckner and Lederman (2018)	144 countries, 1970 to 2010	Market Gini coefficient; net Gini coefficient	2SLS GMM	Low income countries: + High-income countries: -
Hailemariam and Dzhumashev (2020)	Broad panel of countries (1965–2014)	Net Gini coefficient; Market Gini coefficient	Dynamic panel models	Non-linear relationship Moderate inequality: + High inequality: -
No relationship
Niyimbanira (2017)	Mpumalanga 18 municipalities, 1996–2014	Gini coefficient	FE Pooled regression	0
Benos and Karagiannis (2018)	US state-level data, 1929 to 2013	Gini coefficient	2SLS GMM	0

Source: Mdingi and Ho (2021). Note: - denotes negative, + denotes positive, 0 denotes inconclusive, FE denotes a fixed effect, RE denotes random effect, OLS denotes ordinary least squares, GMM denotes generalised methods of moments, 2SLS denotes two-stage least squares, ARDL denotes autoregressive distributed lag, IV denotes an instrumental variable.

Table 2. Stationarity of the variables

Augmented Dickey Fuller Test (ADF)					Perron Test				Zivot-Andrews Test
Variables	Order of integration at level I(0)		Order of integration at the first difference I(1)		Order of integration at level I(0)		Order of integration at the first difference I(1)		Order of integration at level I(0)		Order of integration at the first difference I(1)
	Intercept	Trend and intercept	Intercept	Trend and intercept	Intercept	Trend	Intercept	Trend	Intercept	Trend	Intercept	Trend
Y	-	-	−5.826***	−5.780***	-	-	−6.287***	−4.913**	−4.260	−4.293*	−4.976**	−4.612**
LNGINI	−5.445***	−5.932***	−3.071**	-	-	-	−7.915***	−4.705*	-	-	−7.790***	−6.431***
LNHC	-	-	−2.637*	−2.525	-	-	−9.764***	−3.672	-	−5.061***	−9.894***	−5.061***
LNPOP	−3.401**	−4.780***	-	-	-	-	-	-	−5.141**	−5.010**	-	-
LNK	0.282	−3.374*	-	-	−5.506**	−4.872**	-	-	−5.126**	−5.440***	-	-
LNGOVT	-	-	−5.398***	−5.701***	-	-	−6.597***	−6.133***	-	-	−6.639***	-

Source: Computed by the authors. Notes: *, ** and *** denote the stationarity of variables at 10%, 5% and 1% levels of significance, respectively; – denotes “not applicable”.

Table 3. ARDL bounds test for cointegration results without structural breaks

Country	Dependent variable	Function	F-statistic		Status of cointegration
South Africa	Y	F (Y l lnGINI, lnHC, lnPOP, lnK, lnGOVT)	9.992***		Cointegrated
Critical values
Pesaran et al. (2001: p. 300)	1%		5%		10%
	I(0)	I(1)	I(0)	I(1)	I(0)	I(1)
	3.41	4.68	2.62	3.79	2.26	3.35

Source: Computed by the authors. Notes: *** denotes 1% level of significance.

Table 4. Long-run and short-run estimation results of the model without structural breaks

Dependent variable: Y Panel A: The long-run coefficient results
Regressor	Coefficient	Standard error	t-statistics	Probability
lnGINI	−17.728***	1.801	−9.843	0.000
lnHC	63.501**	19.56388	3.246	0.012
lnPOP	−5.113***	0.980	−5.219	0.001
lnK	−39.177***	10.990	−3.565	0.007
lnGOVT	−18.061***	5.257	−3.435	0.009
Panel B: The short-run coefficient results
Regressor	Coefficient	Standard Error	t-statistics	Probability
∆Y (−1)	0.691***	0.144	4.799	0.001
∆Y (−2)	0.150	0.097	1.536	0.163
∆lnGINI	−7.641	4.276	−1.787	0.112
∆lnGINI(−1)	14.958***	4.325	3.458661	0.009
∆lnHC	−150.183**	54.660	−2.748	0.025
∆lnHC (1)	−101.278	68.768	−1.473	0.179
∆lnPOP	−77.602***	11.938	−6.500	0.000
∆lnPOP (−1)	81.778***	10.644	7.683	0.000
∆lnK	125.419***	36.938	3.395	0.009
∆lnK (−1)	−162.305***	35.730	−4.542	0.002
∆lnGOVT	−11.826**	4.202	−2.814	0.023
∆lnGOVT (1)	9.191	5.357	1.716	0.125
C	1519.328***	153.918	9.871	0.000
CointEq(−1)*	−2.341***	0.237	−9.870	0.000

Source: Computed by the authors. Notes: *, ** and *** denote the stationarity of variables at 10%, 5% and 1% levels of significance, respectively; ∆ is the first difference operator.

Figure 3. The plot of the cumulative sum of the recursive residuals.

Source: Author’s own compilation. Notes: The straight-line represents critical bounds at 5% significant level.

Figure 4. The plot of the cumulative sum of squares of recursive residuals.

Source: Author’s own compilation. Note: The straight lines represent critical bounds at 5% significant level.

Table 5. Long-run and short-run results with structural breaks

Dependent variable: Y Panel A: The long-run coefficient results
Regressor	Coefficient	Standard error	t-statistics	Probability
lnGINI	−25.594***	5.198	−4.924	0.001
lnHC	72.732**	30.885	2.355	0.040
lnPOP	−5.128***	1.327	−3.865	0.003
lnK	−42.045*	19.267	−2.182	0.054
lnGOVT	−23.546***	7.259	−3.244	0.009
Panel B: The short-run coefficient results
Regressor	Coefficient	Standard Error	t-statistics	Probability
∆Y (−1)	0.315**	0.102	3.090	0.011
∆lnGINI	−3.071	5.053	−0.608	0.557
∆lnGINI(−1)	16.843***	4.674	3.603	0.005
∆lnHC	−102.683	60.583	−1.695	0.121
∆lnHC(−1)	−117.58*	64.754	−1.816	0.010
∆lnPOP	−50.340***	12.851	−3.917	0.003
∆lnPOP(−1)	68.992***	11.874	5.810	0.000
∆lnK	94.752**	37.474	2.528	0.030
∆lnK(−1)	−218.649***	36.725	−5.954	0.000
∆lnGOVT	−17.498***	4.667	−3.749	0.004
DUM_Y	0.730	0.510	1.430	0.183
C	1242.878***	109.033	11.399	0.000
CointEq(−1)*	−1.694***	0.149	−11.398	0.000

Figure 5. The plot of the cumulative sum of the recursive residuals with structural breaks.

Figure 6. The Plot of the cumulative sum of squares of recursive residuals with structural breaks.

Table A1. Descriptive statistics of economic growth, income inequality, human capital, population growth physical capital, and government expenditure, 1989–2018

Y	LNGINI	LNHC	LNK	LNPOP	LNGOVT
Mean
2.312978	4.181506	0.818136	0.478814	14.51313	2.874480
Median
2.542735	4.192744	0.799235	0.410644	14.44770	2.877240
Maximum
5.603806	4.260725	1.049997	0.915048	14.86080	2.963809
Minimum
−2.137057	4.052368	0.643771	0.197015	14.28154	2.763847
Standard deviation.
1.957419	0.055204	0.131884	0.239916	0.192184	0.062752
Skewness
−0.440567	−0.713658	0.283156	0.727961	0.472730	−0.115348
Kurtosis
2.787342	2.556730	1.695318	2.127935	1.788137	1.781813
Jarque-Bera
1.027028	2.792147	2.528631	3.600260	2.953134	1.921499
Probability
0.598389	0.247567	0.282433	0.165277	0.228420	0.382606
Sum
69.38933	125.4452	24.54409	14.36442	435.3940	86.23439
Sum sq. dev.
111.1132	0.088376	0.504410	1.669234	1.071106	0.114196
Observations
30	30	30	30	30	30

Source: Authors’ computation.

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