How does income inequality affects economic growth at different income levels?

Figures & data

Table 1. Descriptive statistics of data.

Variable	Obs	Mean	Std. Dev.	Min	Max
Log(GDP pc)	1927	8.703	1.172	5.605	11.861
GROWTH	1927	0.077	0.207	−3.052	1.019
GINI	1177	0.384	0.088	0.178	0.672
INVS	1947	0.214	0.112	0.014	1.457
EDU	1876	5.34	3.258	0.0319	13.086
log (LIFEEX)	1958	4.145	0.196	3.047	4.438
GOVC	1947	0.189	0.097	0.007	0.929
OPEN	1947	−0.059	0.224	−6.529	0.800
INFL	1627	34.886	262.645	−6.628	6945.242
POLRIGHT	1520	3.666	1.855	1.000	7.000
FERT	1962	3.951	2.024	00.891	8.811
ECFR	1671	5.885	1.339	2.430	9.060

Source: self-created.

Table 2. Benchmark regression results.

Log(GDP pc)	(1(1) $$y_{it}-y_{it-1}=\alpha y_{it-1}+\beta h_{it}+\lambda {\varphi }_{it}+\theta X_{it}+{\eta }_i+{\zeta }_t+{\upsilon }_{it}$$(1) )	(2(2) $$y_{it}=(\alpha +1)y_{it-1}+\beta h_{it}+\lambda {\varphi }_{it}+\theta X_{it}+{\eta }_i+{\zeta }_t+{\upsilon }_{it}$$(2) )	(3(3) $$y_{it}=(\alpha +1)y_{it-1}+\beta h_{it}+{\lambda }_1{\varphi }_{it}1(y_{it-1}\le \gamma )+{\lambda }_2{\varphi }_{it}1(y_{it-1}>\gamma )+\theta X_{it}+{\eta }_i+{\zeta }_t+{\epsilon }_{it}$$(3) )	(4(4) $$\begin{array}{c}1(y_{it-1}\le \gamma )=\{\begin{array}{l}1\hspace{1em}if{y}_{it-1}\le \gamma \\ 0\hspace{1em}if{y}_{it-1}>\gamma ,\end{array}\\ 1(y_{it-1}>\gamma )=\{\begin{array}{l}1\hspace{1em}if{y}_{it-1}>\gamma \\ 0\hspace{1em}if{y}_{it-1}\le \gamma .\end{array}\end{array}$$(4) )	(5)	(6)
L.Log(GDP pc)	0.960*** (0.033)	0.896*** (0.045)	0.892*** (0.038)	0.905* (0.520)	0.867*** (0.033)	0.885* (0.515)
GINI	−1.419* (0.753)	−0.529* (0.320)	−0.687*** (0.261)	−0.417 (4.704)	−0.280 (0.292)	−0.053 (1.826)
INVS		1.400*** (0.204)	1.164*** (0.227)	0.994 (0.756)	0.583** (0.237)	0.444 (0.459)
EDU		0.005 (0.012)	0.003 (0.011)	0.003 (0.087)	0.008 (0.012)	0.004 (0.068)
log (LIFEEX)		0.378** (0.151)	0.455*** (0.161)	0.428 (2.313)	0.265 (0.221)	0.265 (0.567)
GOVC			−1.329*** (0.320)	−1.249 (3.663)	−0.684** (0.304)	−0.628 (1.622)
OPEN			0.356** (0.152)	0.370 (0.585)	0.486*** (0.134)	0.474*** (0.145)
INFL			−0.0001*** (0.00003)	−0.0002* (0.0001)	−0.0001 (0.0001)	0.0001 (0.0001)
POLRIGHT			0.018 (0.012)	0.020 (0.174)	0.025** (0.012)	0.029 (0.196)
FERT				−0.022 (0.221)		−0.023 (0.057)
ECFR					0.126*** (0.022)	0.108 (0.150)
Constant	−0.004 （0.117）	−0.664 (0.794)	−0.603 (0.714)	−0.634 (16.963)	−0.568 (1.043)	−0.555 (8.511)
Observations	1128	976	874	874	796	796
Countries	165	132	129	129	124	124
Hansen p-val	0.115	0.981	0.984	0.991	0.999	1.000
Diff-Hansen	0.893	1.000	1.000	1.000	1.000	1.000
AR(1) p-val	0.0001	0.000	0.000	0.000	0.000	0.000
AR(2) p-val	0.0592	0.100	0.2450	0.2316	0.1965	0.1755
Instruments	77	136	141	161	143	163

Note: This table provides two-step system GMM estimation results. All models were controlled for time fixed effects. The instrumental variable is the second lag value of the level explanatory variable of the difference equation, and the first lag value of the difference in the level equation.

* p < 0.1. ^** p < 0.05. ^***p < 0.01.

Source: self-created.

Table 3. The estimation results of one-step system GMM and difference GMM.

Log(GDP pc)	One-step system GMM			Difference GMM
	(3)	(4)	(6)	(3)	(4)	(6)
L.Log(GDP pc)	0.901*** (0.038)	0.902*** (0.035)	0.876*** (0.029)	0.500*** (0.092)	0.617*** (0.076)	0.609*** (0.071)
GINI	−0.645** (0.267)	−0.437* (0.244)	−0.081 (0.281)	−0.507 (0.635)	−0.419 (0.726)	−1.028 (0.64)
FERT		−0.017 (0.026)	−0.020 (0.024)		0.040 (0.033)	0.046 (0.028)
ECFR			0.117*** (0.021)			0.104*** (0.027)
Constant	−0.587 (0.668)	−0.637 (0.748)	−0.903 (0.929)	1.349 (1.691)	−0.580 (1.815)	0.299 (1.510)
Observations	880	880	796	745	745	796
Countries	129	129	124	128	128	124
Hansen p-val	0.811	0.998	0.998	0.292	0.526	0.839
Diff-Hansen	1.000	1.000	1.000
AR(1) p-val	0.0000	0.000	0.000	0.0280	0.0013	0.000
AR(2) p-val	0.2408	0.2171	0.1875	0.5286	0.4725	0.1875
Instruments	141	161	144	81	91	93

Note: Same as Table 2. In addition, we did estimates for the six models, but listed only the important ones. The control variables are the same as those in Table 2, but are not listed.

Source: self-created.

Table 4. Dynamic panel threshold model estimation results.

Log(GDP pc)	(3(3) $$y_{it}=(\alpha +1)y_{it-1}+\beta h_{it}+{\lambda }_1{\varphi }_{it}1(y_{it-1}\le \gamma )+{\lambda }_2{\varphi }_{it}1(y_{it-1}>\gamma )+\theta X_{it}+{\eta }_i+{\zeta }_t+{\epsilon }_{it}$$(3) )	(4(4) $$\begin{array}{c}1(y_{it-1}\le \gamma )=\{\begin{array}{l}1\hspace{1em}if{y}_{it-1}\le \gamma \\ 0\hspace{1em}if{y}_{it-1}>\gamma ,\end{array}\\ 1(y_{it-1}>\gamma )=\{\begin{array}{l}1\hspace{1em}if{y}_{it-1}>\gamma \\ 0\hspace{1em}if{y}_{it-1}\le \gamma .\end{array}\end{array}$$(4) )
Threshold	5263.442	5263.442
Inequality (below the threshold)	−2.062*** （0.746）	−1.485** （0.637）
Inequality (above the threshold)	−0.987 （0.743）	−0.048 (0.639)
L.Log(GDP pc)	0.623*** (0.027)	0.554*** 0.029
GINI	0.012 (0.128)	0.322** (0.146)
INVS	−0.040*** （0.017）	0.008 (0.018)
EDU	1.753*** (0.339)	2.101*** (0.285)
log (LIFEEX)	−2.653*** (0.115)	−2.495*** (0.132)
GOVC	−0.690*** (0.164)	−0.185 (0.151)
OPEN	−0.0007** (0.0002)	−0.0007*** (0.0002)
INFL	−0.048*** (0.016)	−0.039** (0.015)
POLRIGHT		0.120*** ( 0.027)
Constant	−2.484* (1.288)	−4.449*** (1.092)
Number of obs	874	874
Number of groups	129	129
Wald chi2	4176.48	6269.83
p-Value	0.000	0.000
instruments	73	79

Note: This table provides the estimated results for the panel threshold model. The models with insignificant estimation results are not shown here. All the models use robust standard errors.

* p < 0.1. ^**p < 0.05. ^***p < 0.01.

Source: self-created.

Table 5. Results of estimating the impact channel of inequality in low-income countries.

	INVS	EDU	POLRIGHT	FERT
GINI	0.093 (0.202)	−3.139*** (1.101)	−6.739* (3.942)	8.248** (3.275)
Log(GDP pc)	0.066 (0.025)	2.742*** (0.136)	−0.450 (0.322)	−1.866*** (0.374)
Constant	−0.378* (0.204)	−15.765*** (1.259)	10.581*** (2.749)	15.755*** (3.518)
Observations	419	343	385	417
Countries	88	70	84	87
Hansen p-val	0.247	0.523	0.203	0.341
AR(1) p-val	0.000	0.000	0.507	0.000
AR(2) p-val	0.971	0.814	0.781	0.707
Instruments	67	67	39	46

Note: Same as Table 2. In addition, the AR(1) tests in the Table are all larger than expected, a phenomenon that also appears in Berg et al. (2018) estimation results on political stability, which is explained by the fact that some of the estimated channels may have little time-series variation, or the model does not include lagged dependent variables.

Source: self-created.

Table 6. Differences in impact channels due to country differences (Education).

EDU	Economic freedom		Savings share		Religious beliefs
	Low	High	Low	High	Christianity	no
GINI	−15.183* (7.764)	3.511 (8.335)	−1.582 (1.784)	−8.798*** (1.249)	−23.319* (13.256)	5.147* (2.992)
Log(GDP pc)	3.525*** (0.865)	4.822*** (1.001)	3.433*** (0.207)	1.219*** (0.106)	3.047*** (0.681)	2.265*** (0.549)
Constant	−16.821** (7.903)	−34.610*** (8.536)	−21.742*** (1.531)	−1.590 (1.056)	−9.808 (7.749)	−15.007*** (4.375)
OBS	168	157	222	417	229	114
Countries	55	49	55	87	47	23
Hansen p	0.386	0.635	0.203	0.341	0.654	1.000
AR(1) p-val	0.003	0.042	0.000	0.000	0.022	0.024
AR(2) p-val	0.147	0.359	0.632	0.707	0.498	0.122
Instruments	42	40	44	46	44	63

Note: Same as Table 2. In addition, high or low ECFR is defined by the mean value; since inequality does not affect growth through investment in the low-income stage, we do not consider this investment in our analysis of heterogeneity.

Source: self-created.

Table 7. Differences in impact channels due to country differences (political stability).

POLRIGHT	Economic freedom		Savings share		Religious beliefs
	Low	High	Low	High	Christianity	no
GINI	−1.308 (6.143)	−9.958** (4.758)	−5.063*** (1.609)	−0.195 (6.084)	−7.683* (4.532)	−2.982 (5.065)
Log(GDP pc)	0.698 (0.574)	−0.468* (0.268)	0.365** (0.169)	−0.493 (0.371)	−0.118 (0.270)	−0.244 (0.439)
Constant	−0.115 (3.939)	12.051*** (2.954)	3.458** (1.455)	8.401* (4.637)	8.543** (3.323)	7.103* (4.091)
OBS	96	289	236	149	267	118
Countries	37	82	64	48	60	24
Hansen p	0.820	0.485	0.583	0.261	0.922	1.000
AR(1) p-val	0.327	0.724	0.899	0.334	0.471	0.056
AR(2) p-val	0.458	0.553	0.263	0.116	0.799	0.298
Instruments	42	57	39	39	75	57

Note: Same as Table 6.

Source: self-created.

Table 8. Differences in impact channels due to country differences (fertility rate).

FERT	Economic freedom		Savings share		Religious beliefs
	Low	High	Low	High	Christianity	no
GINI	6.764 (6.698)	12.482*** (3.636)	9.844 (5.513)	10.950** (4.705)	14.088*** (4.968)	7.798* (4.374)
Log(GDP pc)	−0.774 (0.475)	−2.001*** (0.331)	−2.019*** (0.586)	1.520*** (0.381)	−1.540*** (0.416)	−2.363 (0.231)
Constant	8.571** (4.001)	14.891*** (3.138)	16.306*** (5.156)	11.870*** (3.225)	10.996*** (4.142)	19.008*** (2.260)
OBS	101	316	258	159	294	123
Countries	38	86	68	49	62	25
Hansen p	0.829	0.173	0.308	0.530	0.289	0.990
AR(1) p-val	0.006	0.004	0.004	0.021	0.000	0.025
AR(2) p-val	0.124	0.301	0.882	0.607	0.932	0.623
Instruments	46	44	44	44	44	43

Note: Same as Table 6.

Source: self-created.

Berg, A., Ostry, J. D., Tsangarides, C. G., & Yakhshilikov, Y. (2018). Redistribution, inequality, and growth: New evidence. Journal of Economic Growth, 23(3), 259–305. https://doi.org/10.1007/s10887-017-9150-2

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