Figures and data in The redistribution effect of taxation in emerging economies: Evidence from a microsimulation exercise in Zambia

Abstract

The study investigates taxation, poverty, and income inequality in Zambia, aiming to identify fiscal reforms that boost revenue, alleviate poverty, and reduce inequality. It examines the effects of Personal Income Tax (PIT), Value-Added Tax (VAT), Turnover Tax (TOT), and Excise Duties using the MicroZamod microsimulation model and STATA modelling from 2010 to 2019. Key findings show that taxes increased the poverty rate by an average of 2 percentage points, with VAT as the main contributor (72.6%), followed by TOT (19.3%), PIT (4.2%), and Excise Duties (3.8%). VAT, though a major revenue source, fails to reduce poverty, while PIT significantly reduces inequality, contributing 70% of the reduction in the Gini coefficient. This study assesses the cost-effectiveness of various taxes in relation to poverty reduction and inequality by calculating welfare multipliers per 1 billion Kwacha of revenue generated. By doing so, it significantly contributes to the existing literature and advances our understanding of how cost-effectiveness indices can inform the formulation of optimal tax policy. VAT increases the national poverty rate by 0.45 percentage points per billion Kwacha raised, whereas PIT raises poverty by only 0.04 percentage points but reduces the Gini coefficient by 0.68 percentage points. Excise Duties slightly improve income distribution with a 0.05 percentage point reduction in the Gini coefficient, while TOT marginally worsens inequality with a 0.06 percentage point increase per billion Kwacha raised. The research emphasises PIT’s potential in reducing inequality and proposes tax reforms to reduce poverty and inequality. Policymakers can use these insights to optimize tax policies, balancing revenue generation with the goals of reducing poverty and inequality.

This article contains 8 figures and 16 tables.

Figures

**Figure 1.** The trends for the tax-to-GDP ratio, Gini index, and absolute poverty, 1995–2020.

**Figure 2.** Poverty trends in Zambia, 2006, 2010 and 2015 .

**Figure 3.** Income share across the population distribution 1996–2015.

**Figure 4.** Structure of public tax revenues in Zambia, 2010–2019.

**Figure 5.** Tax revenues by selected tax type as a percentage of GDP.

**Figure 6.** Contributions of different taxes to simulated tax revenue in Zambia, 2010–2019.

**Figure 7.** Contributions of different taxes to the national consumption-based severe poverty rate in Zambia, 2010–2019.

Tables

Table 1. Effects of taxes on the Gini coefficient.

	2010	2015	2016	2017	2018	2019
Consumption-based Gini before taxes	57.03	57.16	55.63	54.99	55.11	55.22
Effect of PIT	-2.35	-1.02	-1.29	-1.37	-1.22	-1.51
Effect of TOT	+0.09	+0.13	+0.11	-0.12	-0.11	+0.15
Effect of VAT	-0.29	-0.34	-0.38	-0.42	-0.41	-0.42
Effect of Excise Duties	-0.15	-0.16	-0.15	-0.15	-0.14	-0.13
Consumption-based Gini after taxes	54.33	55.78	53.92	52.94	53.23	53.30
*Contribution shares*
Effect of PIT	-87.2%	-73.9%	-75.1%	-66.7%	-64.8%	-78.8%
Effect of TOT	+3.5%	+9.7%	+6.5%	-5.6%	-6.1%	+7.7%
Effect of VAT	-10.9%	-24.5%	-22.4%	-20.5%	-21.7%	-21.9%
Effect of Excise Duties	-5.4%	-11.4%	-9.0%	-7.2%	-7.4%	-7.0%
Effect of all taxes on consumption-based Gini	-100%	-100%	-100%	-100%	-100%	-100%

Source: Author’s elaboration based on MicroZAMOD simulations.

Table 2. Cost-effectiveness of different taxes in terms of changes in poverty.

	2010	2015	2016	2017	2018	2019
Effect of PIT	+0.12 pp.	+0.01 pp.	+0.03 pp.	+0.03 pp.	+0.01 pp.	+0.04 pp.
Effect of TOT	+0.28 pp.	+0.20 pp.	+0.14 pp.	+0.03 pp.	+0.02 pp.	+0.28 pp.
Effect of VAT	+0.78 pp.	+0.49 pp.	+0.53 pp.	+0.49 pp.	+0.53 pp.	+0.45 pp.
Effect of Excise Duties	+0.03 pp.	+0.01 pp.	+0.01 pp.	+0.02 pp.	+0.01 pp.	+0.02 pp.

Source: Author’s elaboration based on MicroZAMOD simulations.

Note: the cells indicate the increase in the national poverty rate (in percentage points) associated with raising 1 billion Kwacha of revenue from a specific tax. Larger estimates (red) hence point to cases where raising tax revenue leads to larger relative increases in poverty.

Table 3. Cost-effectiveness of different taxes in terms of changes in the Gini index.

	2010	2015	2016	2017	2018	2019
Effect of PIT	-0.95 pp.	-0.41 pp.	-0.52 pp.	-0.55 pp.	-0.49 pp.	-0.60 pp.
Effect of TOT	+0.04 pp.	+0.05 pp.	+0.04 pp.	-0.05 pp.	-0.05 pp.	+0.06 pp.
Effect of VAT	-0.12 pp.	-0.14 pp.	-0.15 pp.	-0.17 pp.	-0.16 pp.	-0.17 pp.
Effect of Excise Duties	-0.06 pp.	-0.06 pp.	-0.06 pp.	-0.06 pp.	-0.06 pp.	-0.05 pp.

Source: Author’s elaboration based on MicroZAMOD simulations.

Note: The cells indicate the change in the Gini coefficient (in percentage points) associated with raising 1 billion Kwacha of revenue from a specific tax. Larger estimates (red) hence point to cases where raising tax revenue leads to larger relative increases in the Gini.

Table 4. Baseline and proposed policy reforms.

Parameter	Baseline	Reform 1	Reform 2	Reform 3	Reform 4
PAYE/PIT Band 1	61,200–85,200	61,200–90,000	Same as baseline	61,200–90,000	66,000-92,400
PAYE/PIT Band 1 Rate	20.0%	25.0 %	Same as baseline	25.0 %	25.0%
PAYE/PIT Band 2	85,200–110,400	90,000–144,400	Same as baseline	90,000–144,400	92,400-130,000
PAYE/PIT Band 2 Rate	30%	34.0%	Same as baseline	34.0%	33%
PAYE/PIT Band 3	Over 110,400	Over 144,400	Same as baseline	Over 144,400	Over 144,000
PAYE/PIT Band 3 Rate	37.0%	37.5%	Same as baseline	37.5%	38%
Clear beer excise duty (ad valorem rate)	40.0%	Same as baseline	65.0%	65.0%	65%
Wine and spirits excise duty (ad valorem rate)	60.0%	Same as baseline	80.0%	80.0%	80%
Opaque beer excise duty (Kwacha per litre)	0.25	Same as baseline	0.6	0.6	0.6
Tobacco excise duty (Kwacha per single piece)	0.4	Same as baseline	0.75	0.75	0.75
VAT rate	16%	15.0%	15.5%	15.0%	15.5%
Turnover Tax Upper Limit	800,000	Same as baseline	Same as baseline	Same as baseline	1,200,00
Turnover Tax Rate	4%	Same as baseline	Same as baseline	Same as baseline	5.5%

Source: Constructed by the author using ZRA practice notes.

Source: note that PIT/PAYE rates for those under the first band are 0% (e.g. those earning under K61,200 in the baseline). Only parameters that are changed in one or more of the scenarios are included.

Table 5. Simulation results of the hypothetical policy reforms.

	Baseline	Reform 1		Reform 2		Reform 3		Reform 4
	Results	Results	Change	Results	Change	Results	Change	Results	Change
Tax-benefit policy (million Kwacha)
Government revenue	15,043.59	15,048.13	+4.54	15,039.18	-4.41	15,177.14	+133.55	15,569.14	+525.55
... direct taxes	5,074.75	5,347.25	+272.50	5,074.75	0.00	5,347.25	+272.50	5,613.22	+538.47
... indirect taxes	4,688.62	4,420.66	-267.96	4,684.21	-4.41	4,549.67	-138.95	4,675.70	-12.92
... social security contributions	5,280.23	5,280.23	0.00	5,280.23	0.00	5,280.23	0.00	5,280.23	0.00
Gov. expenditure on social transfers	3,964.93	3,964.93	0.00	3,964.93	0.00	4,095.06	+130.14	4,485.48	+520.55
Poverty
Share of poor population, in %, FGT (0)	41.72*** (0.0069)	41.70*** (0.0072)	-0.03	41.70*** (0.0068)	-0.02	41.56*** (0.0074)	-0.16	41.54*** (0.0068)	-0.18
... male-headed households	41.80	41.78	-0.02	41.79	-0.02	41.71	-0.09	41.85	+0.05
... female-headed households	41.40	41.36	-0.04	41.37	-0.03	40.95	-0.45	40.27	-1.12
... households with children	43.15	43.13	-0.02	43.14	-0.02	43.00	-0.16	43.05	-0.11
... households with older persons	46.02	46.00	-0.02	46.02	0.00	45.39	-0.63	44.13	-1.89
Poverty gap, FGT (1)	0	0	0	0	0	0	0	0.00	0.00
Inequality and household income
Gini coefficient (0–100)	54.24*** (0.0044)	54.19*** (0.0046)	-0.06	54.24*** (0.0046)	-0.01	54.08*** (0.0045)	-0.16	53.96*** (0.0046)	-0.003
P80/P20 ratio	4.98	4.98	0.00	4.98	0.00	4.95	-0.03	4.90	-0.08
Quantiles of distribution and median
20^th	1,764.99	1,766.71	+1.72	1,766.28	+1.28	1,777.85	+12.86	1,792.14	+27.15
40^th	2,978.38	2,986.27	+7.89	2,979.90	+1.52	2,994.20	+15.82	3,012.41	+34.03
50^th	3,812.19	3,818.94	+6.75	3,815.05	+2.85	3,828.21	+16.02	3,839.29	+27.10
60^th	4,934.12	4,947.87	+13.75	4,933.12	-1.00	4,941.18	+7.06	4,950.22	+16.10
80^th	8,781.77	8,791.08	+9.31	8,790.14	+8.37	8,798.51	+16.74	8,778.92	-2.86
Absolute national poverty line, per year	3,127.68	3,127.68	-	3,127.68	-	3,127.68	-	3,128.00	0.00

Note: Standard errors in parentheses. * p < 0.10, ** p <0.05, *** p <0.01.

Source: Constructed by the author based on MicroZAMOD simulations.

Table A1. Baseline and proposed policy reforms.

Parameter	Baseline	Reform 1	Reform 2	Reform 3	Reform 4
Turnover Tax Upper Limit	800,000	Same as baseline	Same as baseline	Same as baseline	1,200,00
Turnover Tax Rate	4%	Same as baseline	Same as baseline	Same as baseline	5.5%
VAT rate	16%	15.0%	15.5%	15.0%	15.5%
Opaque beer excise duty (Kwacha per litre)	0.25	Same as baseline	0.6	0.6	0.6
Clear beer excise duty (ad valorem rate)	40.0%	Same as baseline	65.0%	65.0%	65%
Tobacco excise duty (Kwacha per single piece)	0.4	Same as baseline	0.75	0.75	0.75
Wine and spirits excise duty (ad valorem rate)	60.0%	Same as baseline	80.0%	80.0%	80%
PAYE/PIT Band 1	61,200–85,200	61,200–90,000	Same as baseline	61,200–90,000	66,000-92,400
PAYE/PIT Band 1 Rate	20.0%	25.0 %	Same as baseline	25.0 %	25.0%
PAYE/PIT Band 2	85,200–110,400	90,000–144,400	Same as baseline	90,000–144,400	92,400-130,000
PAYE/PIT Band 2 Rate	30%	34.0%	Same as baseline	34.0%	33%
PAYE/PIT Band 3	Over 110,400	Over 144,400	Same as baseline	Over 144,400	Over 130,000
PAYE/PIT Band 3 Rate	37.0%	37.5%	Same as baseline	37.5%	38%

Table A2. Simulation results of the hypothetical policy reforms.

	Baseline	Reform 1		Reform 2		Reform 3		Reform 4
	Results	Results	Change	Results	Change	Results	Change	Results	Change
Tax-benefit policy (million Kwacha)
Government revenue	15,043.59	15,048.13	+4.54	15,039.18	-4.41	15,177.14	+133.55	15,569.14	+525.55
... direct taxes	5,074.75	5,347.25	+272.50	5,074.75	0.00	5,347.25	+272.50	5,613.22	+538.47
... indirect taxes	4,688.62	4,420.66	-267.96	4,684.21	-4.41	4,549.67	-138.95	4,675.70	-12.92
... social security contributions	5,280.23	5,280.23	0.00	5,280.23	0.00	5,280.23	0.00	5,280.23	0.00
Gov. expenditure on social transfers	3,964.93	3,964.93	0.00	3,964.93	0.00	4,095.06	+130.14	4,485.48	+520.55
Poverty
Share of poor population, in %, FGT (0)	41.72	41.70	-0.03	41.70	-0.02	41.56	-0.16	41.54	-0.18
... male-headed households	41.80	41.78	-0.02	41.79	-0.02	41.71	-0.09	41.85	+0.05
... female-headed households	41.40	41.36	-0.04	41.37	-0.03	40.95	-0.45	40.27	-1.12
... households with children	43.15	43.13	-0.02	43.14	-0.02	43.00	-0.16	43.05	-0.11
... households with older persons	46.02	46.00	-0.02	46.02	0.00	45.39	-0.63	44.13	-1.89
Poverty gap, FGT (1)	0	0	0	0	0	0	0	0.00	0.00
Inequality and household income
Gini coefficient (0–100)	54.24	54.19	-0.06	54.24	-0.01	54.08	-0.16	0.5396	-0.0029
P80/P20 ratio	4.98	4.98	0.00	4.98	0.00	4.95	-0.03	4.90	-0.08
Quantiles of distribution and median
20^th	1,764.99	1,766.71	+1.72	1,766.28	+1.28	1,777.85	+12.86	1,792.14	+27.15
40^th	2,978.38	2,986.27	+7.89	2,979.90	+1.52	2,994.20	+15.82	3,012.41	+34.03
50^th	3,812.19	3,818.94	+6.75	3,815.05	+2.85	3,828.21	+16.02	3,839.29	+27.10
60^th	4,934.12	4,947.87	+13.75	4,933.12	-1.00	4,941.18	+7.06	4,950.22	+16.10
80^th	8,781.77	8,791.08	+9.31	8,790.14	+8.37	8,798.51	+16.74	8,778.92	-2.86
Absolute national poverty line, per year	3,127.68	3,127.68	-	3,127.68	-	3,127.68	-	3,128.00	0.00

Table A3. Complex survey estimates of Generalized Entropy inequality indices.

Baseline	GE(-1)	1.049384	0.047619	22.04	0.956052	1.142715
	MLD	0.542851	0.010005	54.26	0.523241	0.56246
	Theil	0.589716	0.014859	39.69	0.560593	0.618838
	GE(2)	1.374182	0.099984	13.74	1.178218	1.570147
	GE(3)	10.13423	2.16161	4.69	5.897555	14.37091
Reform 1	GE(-1)	1.045456	0.047423	22.05	0.952509	1.138402
	MLD	0.541628	0.010006	54.13	0.522016	0.56124
	Theil	0.588791	0.014898	39.52	0.559591	0.617991
	GE(2)	1.374785	0.100439	13.69	1.177928	1.571641
	GE(3)	10.18034	2.177292	4.68	5.912928	14.44776
Reform 2	GE(-1)	1.048209	0.047524	22.06	0.955064	1.141353
	MLD	0.542627	0.01	54.26	0.523029	0.562226
	Theil	0.589402	0.014842	39.71	0.560312	0.618493
	GE(2)	1.371418	0.099579	13.77	1.176247	1.56659
	GE(3)	10.07179	2.143049	4.7	5.871496	14.27209
Reform 3	GE(-1)	1.030026	0.046737	22.04	0.938422	1.121629
	MLD	0.53854	0.009958	54.08	0.519022	0.558059
	Theil	0.58638	0.014851	39.48	0.557273	0.615487
	GE(2)	1.366659	0.099702	13.71	1.171246	1.562072
	GE(3)	10.06418	2.148857	4.68	5.852493	14.27586
Reform 4	GE(-1)	1.00002	0.045593	21.93	0.910659	1.089381
	MLD	0.534232	0.009902	53.95	0.514826	0.553639
	Theil	0.584206	0.014812	39.44	0.555175	0.613236
	GE(2)	1.361715	0.099264	13.72	1.167162	1.556269
	GE(3)	9.998477	2.129615	4.69	5.824507	14.17245

Notes: Number of obs = 12250, Number of strata = 1, Number of PSUs= 12250, Population size=15473850, GE(-1): Focuses on inequality among the poorest. MLD (Mean Log Deviation): Measures lower-end inequality (α = 0). Theil: Includes: · Theil T (GE(1)): Entire income distribution. Theil L (GE(0)): Same as MLD. GE(2): Highlights inequality among the wealthiest. GE(3): Stronger emphasis on top-end inequality.

Table A4. Complex survey estimates of Atkinson inequality indices.

	Index	Estimate	Std.Err.	z	[95% Conf.Interval]
Baseline	A(0.5)	0.244544	0.004384	55.78	0.235952	0.253136
	A(1)	0.418911	0.005814	72.05	0.407516	0.430306
	A(1.5)	0.555707	0.00696	79.84	0.542065	0.569348
	A(2)	0.677291	0.009918	68.29	0.657852	0.69673
	A(2.5)	0.790498	0.013498	58.57	0.764043	0.816953
Reform 1	A(0.5)	0.244103	0.004392	55.58	0.235495	0.252711
	A(1)	0.4182	0.005822	71.84	0.40679	0.42961
	A(1.5)	0.554894	0.006966	79.65	0.54124	0.568547
	A(2)	0.676471	0.009928	68.14	0.657013	0.695928
	A(2.5)	0.789801	0.013547	58.3	0.763249	0.816353
Reform 2	A(0.5)	0.244456	0.004382	55.79	0.235869	0.253044
	A(1)	0.418781	0.005812	72.06	0.40739	0.430172
	A(1.5)	0.555527	0.006957	79.85	0.541892	0.569163
	A(2)	0.677046	0.009913	68.3	0.657616	0.696476
	A(2.5)	0.790229	0.01351	58.49	0.76375	0.816708
Reform 3	A(0.5)	0.243093	0.004382	55.47	0.234505	0.251682
	A(1)	0.416401	0.005812	71.65	0.40501	0.427791
	A(1.5)	0.552332	0.006955	79.42	0.538701	0.565963
	A(2)	0.673208	0.009982	67.44	0.653643	0.692773
	A(2.5)	0.786693	0.013891	56.63	0.759466	0.813919
Reform 4	A(0.5)	0.24193	0.004373	55.32	0.233358	0.250501
	A(1)	0.413881	0.005804	71.32	0.402506	0.425256
	A(1.5)	0.548151	0.006966	78.69	0.534498	0.561803
	A(2)	0.666671	0.010132	65.8	0.646814	0.686529
	A(2.5)	0.776982	0.014157	54.88	0.749234	0.80473

Notes: Number of obs = 12250, Number of strata = 1, Number of PSUs = 12250, Population size = 15473850, A(0.5): Moderate sensitivity to lower-end inequality, A(1): Stronger focus on lower-end disparities, A(1.5): Increased inequality aversion, A(2): High sensitivity to the poorest individuals. A(2.5): Extreme focus on lower-end inequality.

Table A5. Bootstrap results robustness checks for Poverty incidence.

		Observed	Bootstrap			Normal-base [95% Conf.Interval]
		coefficient	std.err	z	P>\|z\|	Normal-base [95% Conf.Interval]
Baseline	fgt0^[1]	0.4172189	0.006894	60.52	0.000	0.403706	0.430731
	fgt1	0.1804008	0.003562	50.65	0.000	0.173419	0.187382
	fgt2	0.1023088	0.002563	39.93	0.000	0.097286	0.107331
Reform 1	fgt0	0.4170619	0.007152	58.32	0.000	0.403045	0.431079
	fgt1	0.1799028	0.003592	50.08	0.000	0.172863	0.186943
	fgt2	0.1019693	0.002501	40.76	0.000	0.097067	0.106872
Reform 2	fgt0	0.4170422	0.006848	60.9	0.000	0.40362	0.430465
	fgt1	0.1803269	0.003726	48.39	0.000	0.173023	0.18763
	fgt2	0.1022465	0.00265	38.59	0.000	0.097053	0.10744
Reform 3	fgt0	0.4156818	0.007402	56.16	0.000	0.401174	0.43019
	fgt1	0.178704	0.003784	47.22	0.000	0.171287	0.186121
	fgt2	0.1009785	0.002639	38.26	0.000	0.095805	0.106152
Reform 4	fgt0	0.4154426	0.006795	61.14	0.000	0.402125	0.42876
	fgt1	0.1766634	0.003453	51.16	0.000	0.169895	0.183432
	fgt2	0.0993168	0.002445	40.62	0.000	0.094524	0.104109

Notes: Number of obs = 12,251, Replications =250, (Replications based on 12,251 clusters in idhh).

Table A6. Bootstrap results robustness check for Inequality Indices.

		Observed	Bootstrap			Normal-based [95%- Conf.Interval]
		coefficient	St. Err	z	P>\|z\|	Normal-based [95%- Conf.Interval]
Baseline	gini	0.542417	0.004442	122.11	0.000	0.533711	0.551123
Baseline	ge0	0.542851	0.009705	55.94	0.000	0.52383	0.561871
Reform 1	gini	0.541855	0.004571	118.55	0.000	0.532896	0.550814
Reform 1	ge0	0.541628	0.010218	53.01	0.000	0.521602	0.561654
Reform 2	gini	0.542341	0.004584	118.32	0.000	0.533357	0.551325
Reform 2	ge0	0.542627	0.009945	54.56	0.000	0.523136	0.562119
Refrom 3	gini	0.540778	0.004539	119.13	0.000	0.531882	0.549675
Refrom 3	ge0	0.53854	0.010202	52.79	0.000	0.518546	0.558535
Refrom 4	gini	0.539561	0.00461	117.06	0.000	0.530527	0.548596
Refrom 4	ge0	0.534232	0.01007	53.05	0.000	0.514496	0.553969

Notes: Number of obs = 12,251, Replications=250, (Replications based on 12,251 clusters in idhh), fgt0: Proportion of people below the poverty line (headcount ratio), fgt1: Average income shortfall below the poverty line (poverty gap), fgt2: Emphasizes severe poverty by weighing larger shortfalls more heavily, gini: Measures overall income inequality (0 = equality, 1 = inequality), ge(0): Focuses on lower-end inequality; also called Mean Log Deviation (MLD).

Table A7. Quantile group shares, cumulative shares (Lorenz ordinates), generalized Lorenz ordinates, and Gini (Baseline).

Group Share	Linearized Std.Err	Estimate	z	P>\|z\|	[95% Conf.Interval]
1	0.011232	0.000333	33.731	0.000	0.010579	0.011885
2	0.02185	0.000421	51.878	0.000	0.021024	0.022675
3	0.030284	0.000497	60.984	0.000	0.029311	0.031258
4	0.038959	0.000625	62.348	0.000	0.037734	0.040184
5	0.050331	0.000768	65.499	0.000	0.048825	0.051837
6	0.064566	0.000952	67.829	0.000	0.062701	0.066432
7	0.08433	0.001155	73.008	0.000	0.082066	0.086594
8	0.111215	0.00143	77.786	0.000	0.108413	0.114017
9	0.164839	0.00221	74.593	0.000	0.160507	0.16917
10	0.422395	0.005543	76.201	0.000	0.41153	0.433259
Cumul.
share
1	0.011232	0.000333	33.731	0.000	0.010579	0.011885
2	0.033082	0.000698	47.411	0.000	0.031714	0.034449
3	0.063366	0.001124	56.399	0.000	0.061164	0.065568
4	0.102325	0.001645	62.185	0.000	0.0991	0.10555
5	0.152656	0.002283	66.868	0.000	0.148181	0.15713
6	0.217222	0.003027	71.75	0.000	0.211288	0.223156
7	0.301552	0.003881	77.703	0.000	0.293946	0.309158
8	0.412767	0.004744	87.001	0.000	0.403468	0.422066
9	0.577605	0.005543	104.201	0.000	0.566741	0.58847
10	1
Gen.
Lorenz
1	75.59	2.18	34.672	0.000	71.317	79.863
2	222.637	4.414	50.441	0.000	213.986	231.287
3	426.447	6.959	61.277	0.000	412.807	440.088
4	688.639	10.444	65.939	0.000	668.17	709.108
5	1027.363	15.065	68.194	0.000	997.836	1056.891
6	1461.891	21.226	68.872	0.000	1420.288	1503.493
7	2029.427	29.069	69.813	0.000	1972.452	2086.402
8	2777.896	39.312	70.662	0.000	2700.846	2854.947
9	3887.25	56.32	69.021	0.000	3776.865	3997.634
10	6729.94	98.554	68.287	0.000	6536.777	6923.102
Gini	0.54242	0.004598	117.971	0	0.533408	0.551431

Notes: Number of orbs = 12251, Population size=154,739,35.69, Design df=1225.

Table A8. Quantile group shares, cumulative shares (Lorenz ordinates), generalized Lorenz ordinates, and Gini (Reform 1).

Group share	Linearized Std.Err	Estimate	z	P>\|z\|	[95% Conf.Interval]
1	0.011234	0.000334	33.676	0.000	0.01058	0.011888
2	0.021901	0.000421	52.042	0.000	0.021076	0.022726
3	0.030362	0.000498	60.939	0.000	0.029386	0.031339
4	0.038988	0.000627	62.184	0.000	0.037759	0.040217
5	0.050621	0.000769	65.8	0.000	0.049113	0.052129
6	0.064614	0.000956	67.568	0.000	0.06274	0.066488
7	0.084086	0.00115	73.142	0.000	0.081833	0.08634
8	0.111535	0.001435	77.742	0.000	0.108723	0.114347
9	0.164679	0.002194	75.049	0.000	0.160378	0.16898
10	0.42198	0.005554	75.976	0.000	0.411094	0.432866
Cumul.
share
1	0.011234	0.000334	33.676	0.000	0.01058	0.011888
2	0.033135	0.000698	47.476	0.000	0.031767	0.034503
3	0.063497	0.001125	56.422	0.000	0.061291	0.065703
4	0.102485	0.001649	62.158	0.000	0.099253	0.105716
5	0.153105	0.002288	66.926	0.000	0.148622	0.157589
6	0.217719	0.003034	71.752	0.000	0.211772	0.223666
7	0.301806	0.003885	77.681	0.000	0.294191	0.30942
8	0.413341	0.004751	87.002	0.000	0.404029	0.422652
9	0.57802	0.005554	104.07	0.000	0.567134	0.588906
10	1
Gen.
Lorenz
1	75.608	2.185	34.605	0.000	71.326	79.89
2	223.008	4.412	50.54	0.000	214.36	231.656
3	427.355	6.969	61.32	0.000	413.696	441.015
4	689.758	10.473	65.863	0.000	669.232	710.284
5	1030.453	15.088	68.297	0.000	1000.882	1060.025
6	1465.327	21.287	68.837	0.000	1423.605	1507.048
7	2031.259	29.069	69.877	0.000	1974.284	2088.233
8	2781.929	39.339	70.717	0.000	2704.826	2859.031
9	3890.278	56.182	69.244	0.000	3780.163	4000.393
10	6730.354	98.549	68.294	0.000	6537.201	6923.508
Gini	0.541858	0.004608	117.59	0	0.532826	0.550889

Notes: Number of obs = 12251, Population size = 15,473,935.69, Design df =12250.

Table A9. Quantile group shares, cumulative shares (Lorenz ordinates), generalized Lorenz ordinates, and Gini (Reform 2).

Group Share	Estimate	Linearized Std.Err	z	P>\|z\|	[95% Conf.Interval]
1	0.011243	0.000333	33.731	0.000	0.01059	0.011897
2	0.021854	0.000421	51.891	0.000	0.021028	0.022679
3	0.030309	0.000496	61.049	0.000	0.029336	0.031282
4	0.038914	0.000625	62.277	0.000	0.03769	0.040139
5	0.050335	0.000769	65.486	0.000	0.048829	0.051842
6	0.064484	0.000949	67.915	0.000	0.062623	0.066345
7	0.0842	0.001154	72.973	0.000	0.081939	0.086462
8	0.111554	0.001435	77.725	0.000	0.108741	0.114367
9	0.165098	0.002185	75.548	0.000	0.160815	0.169381
10	0.422008	0.005548	76.058	0.000	0.411133	0.432883
Cumul.
share
1	0.011243	0.000333	33.731	0.000	0.01059	0.011897
2	0.033097	0.000698	47.418	0.000	0.031729	0.034465
3	0.063406	0.001123	56.44	0.000	0.061204	0.065608
4	0.10232	0.001645	62.187	0.000	0.099095	0.105545
5	0.152656	0.002283	66.865	0.000	0.148181	0.15713
6	0.217139	0.003026	71.762	0.000	0.211209	0.22307
7	0.30134	0.003879	77.683	0.000	0.293737	0.308942
8	0.412894	0.004745	87.026	0.000	0.403595	0.422193
9	0.577992	0.005548	104.171	0.000	0.567117	0.588867
10	1
Gen.
Lorenz
1	75.671	2.183	34.67	0.000	71.393	79.949
2	222.752	4.416	50.442	0.000	214.097	231.407
3	426.738	6.96	61.31	0.000	413.096	440.38
4	688.642	10.45	65.902	0.000	668.161	709.123
5	1027.412	15.079	68.137	0.000	997.859	1056.966
6	1461.406	21.219	68.874	0.000	1419.818	1502.994
7	2028.096	29.052	69.809	0.000	1971.155	2085.037
8	2778.884	39.346	70.627	0.000	2701.767	2856
9	3890.039	56.13	69.305	0.000	3780.027	4000.051
10	6730.267	98.527	68.309	0.000	6537.158	6923.376
Gini	0.542343	0.004597	117.98	0.000	0.533334	0.551353

Notes: Number of obs = 10344, Population size = 13165710.22, Design df = 10343.

Table A10. Quantile group shares, cumulative shares (Lorenz ordinates), generalized Lorenz ordinates, and Gini (Reform 3).

Group share	Estimate	Linearized Std.Er	z	P>\|z\|	[95% Conf.Interval]
1	0.011365	0.000333	34.124	0.000	0.010712	0.012018
2	0.022042	0.000424	51.951	0.000	0.02121	0.022874
3	0.030494	0.000497	61.337	0.000	0.029519	0.031468
4	0.039152	0.000628	62.365	0.000	0.037921	0.040382
5	0.050583	0.000769	65.794	0.000	0.049076	0.05209
6	0.064647	0.000947	68.254	0.000	0.062791	0.066504
7	0.084688	0.001159	73.042	0.000	0.082415	0.08696
8	0.11128	0.00143	77.827	0.000	0.108477	0.114082
9	0.164583	0.002173	75.726	0.000	0.160323	0.168843
10	0.421167	0.005549	75.899	0.000	0.410291	0.432043
Cumul.
share 1
share 1	0.011365	0.000333	34.124	0.000	0.010712	0.012018
2	0.033407	0.000701	47.683	0.000	0.032034	0.03478
3	0.0639	0.001127	56.708	0.000	0.061692	0.066109
4	0.103052	0.001651	62.415	0.000	0.099816	0.106288
5	0.153635	0.002289	67.122	0.000	0.149149	0.158121
6	0.218283	0.003031	72.023	0.000	0.212342	0.224223
7	0.30297	0.003887	77.952	0.000	0.295353	0.310588
8	0.41425	0.004747	87.264	0.000	0.404946	0.423554
9	0.578833	0.005549	104.312	0.000	0.567957	0.589709
10	1
Gen.
Lorenz 1
Lorenz 1	76.488	2.176	35.147	0.000	72.223	80.754
2	224.837	4.427	50.782	0.000	216.159	233.514
3	430.066	6.968	61.723	0.000	416.41	443.722
4	693.569	10.475	66.21	0.000	673.038	714.1
5	1034.006	15.096	68.494	0.000	1004.417	1063.594
6	1469.1	21.208	69.272	0.000	1427.533	1510.666
7	2039.07	29.089	70.099	0.000	1982.057	2096.082
8	2788.011	39.319	70.908	0.000	2710.948	2865.074
9	3895.697	55.961	69.615	0.000	3786.016	4005.378
10	6730.264	98.328	68.447	0.000	6537.545	6922.984
Gini	0.540781	0.004607	117.383	0	0.531752	0.549811

Notes: Number of obs = 12251, Population size = 15473935.69, Design df = 12250.

Table A11. Quantile group shares, cumulative shares (Lorenz ordinates), generalized Lorenz ordinates, and Gini (Reform 4).

Group share	Estimate	Linearized Std.Err	z	P>\|z\|	[95% Conf.Interval]
1	0.011577	0.00034	34.06	0.000	0.010911	0.012243
2	0.02228	0.000421	52.874	0.000	0.021454	0.023106
3	0.030642	0.000497	61.593	0.000	0.029667	0.031617
4	0.039481	0.000634	62.25	0.000	0.038238	0.040724
5	0.05074	0.000765	66.285	0.000	0.04924	0.052241
6	0.064658	0.000945	68.401	0.000	0.062806	0.066511
7	0.084248	0.001144	73.674	0.000	0.082006	0.086489
8	0.111196	0.00143	77.771	0.000	0.108394	0.113998
9	0.164158	0.002178	75.375	0.000	0.159889	0.168426
10	0.42102	0.005535	76.07	0.000	0.410172	0.431867
Cumul. share
1	0.011577	0.00034	34.06	0.000	0.010911	0.012243
2	0.033857	0.000704	48.092	0.000	0.032477	0.035237
3	0.064499	0.001131	57.042	0.000	0.062283	0.066715
4	0.10398	0.001661	62.607	0.000	0.100725	0.107235
5	0.15472	0.002295	67.409	0.000	0.150222	0.159219
6	0.219379	0.003035	72.29	0.000	0.213431	0.225327
7	0.303626	0.003882	78.217	0.000	0.296018	0.311234
8	0.414822	0.004741	87.492	0.000	0.40553	0.424115
9	0.57898	0.005535	104.611	0.000	0.568133	0.589828
10	1
Gen. Lorenz
1	77.93	2.225	35.023	0.000	73.569	82.291
2	227.903	4.436	51.38	0.000	219.21	236.597
3	434.165	6.963	62.355	0.000	420.519	447.812
4	699.923	10.513	66.578	0.000	679.318	720.528
5	1041.472	15.084	69.046	0.000	1011.909	1071.036
6	1476.709	21.174	69.741	0.000	1435.209	1518.21
7	2043.808	28.894	70.735	0.000	1987.176	2100.439
8	2792.305	39.124	71.371	0.000	2715.624	2868.987
9	3897.306	55.82	69.819	0.000	3787.9	4006.711
10	6731.328	98.214	68.537	0.000	6538.832	6923.825
Gini	0.539564	0.004607	117.112	0	0.530534	0.548594

Notes: Number of obs = 10338, Population size = 13156031.80, Design df = 10337.