Measurements and determinants of multifaceted poverty in South Africa

Figures & data

Table 1: Poverty headcount ratio, by method

	Method 1	Method 2	Method 3	Method 4	Method 5
All	0.4055	0.4000	0.4216	0.4352	0.4417
Race
Black	0.4841	0.4778	0.4748	0.4903	0.5217
Coloured	0.2212	0.2064	0.3616	0.3449	0.2106
Indian	0.0854	0.0854	0.1243	0.1616	0.0760
White	0.0112	0.0112	0.1350	0.1524	0.0872
Gender
Male	0.3486	0.3430	0.4148	0.4362	0.4397
Female	0.4539	0.4471	0.4273	0.4343	0.4434
Area type
Urban	0.2759	0.2698	0.3796	0.3793	0.3578
Rural	0.5883	0.5818	0.4815	0.5168	0.5599

Source: Authors' own calculations using NIDS 2010/11 data.

Table 2: Racial and gender composition of the poor, by method

	Method 1	Method 2	Method 3	Method 4	Method 5
Race (%)
Black	94.56	94.79	88.40	88.62	93.56
Coloured	4.67	4.43	7.61	6.92	4.09
Indian	0.49	0.50	0.70	0.88	0.41
White	0.27	0.28	3.29	3.58	1.95
Total	100.00	100.00	100.00	100.00	100.00
Gender (%)
Male	39.56	39.53	45.31	46.07	45.78
Female	60.44	60.47	54.69	53.93	54.22
Total	100.00	100.00	100.00	100.00	100.00
Area type (%)
Urban	39.83	39.57	52.94	51.70	47.36
Rural	60.17	60.43	47.06	48.30	52.64
Total	100.00	100.00	100.00	100.00	100.00

Source: Authors' own calculations using NIDS 2010/11 data.

Table 3: Percentage of poor in one method being defined as poor in another method

	Method 1	Method 2	Method 3	Method 4	Method 5
Method 1	100.00	98.45	56.43	59.13	58.14
Method 2	100.00	100.00	56.45	59.15	58.29
Method 3	53.21	52.33	100.00	66.88	58.88
Method 4	54.17	53.35	64.76	100.00	58.27
Method 5	53.42	52.72	57.18	58.95	100.00

Source: Authors' own calculations using NIDS 2010/11 data.

Table 4: Number of times a person is defined as poor according to race and gender

	None	At least one method	At least two methods	At least three methods	At least four methods	All five methods
All (%)	26.07	73.94	57.77	40.88	22.52	10.81
Race (%)
Black	16.54	83.47	67.43	49.35	27.40	13.36
Coloured	42.30	57.70	39.50	21.14	10.95	3.76
Indian	67.80	32.20	15.02	5.75	1.57	0.06
White	74.06	25.95	10.84	2.38	0.65	0.22
Gender (%)
Male	27.63	72.38	54.66	37.45	19.70	9.67
Female	24.73	75.27	60.43	43.82	24.93	11.79
Area type (%)
Urban	35.44	64.56	46.10	29.91	14.95	7.03
Rural	12.49	87.51	74.66	56.76	33.48	16.29

Source: Authors' own calculations using NIDS 2010/11 data.

Table 5: Description of explanatory variables

Variable	Description
wc	Province: Western Cape dummy (1 = yes, 0 = no)
ec	Province: Eastern Cape dummy (1 = yes, 0 = no)
nc	Province: Northern Cape dummy (1 = yes, 0 = no)
fs	Province: Free State dummy (1 = yes, 0 = no)
kzn	Province: Kwazulu-Natal dummy (1 = yes, 0 = no)
nw	Province: North West dummy (1 = yes, 0 = no)
gau	Province: Gauteng dummy (1 = yes, 0 = no)
mpu	Province: Mpumalanga dummy (1 = yes, 0 = no)
lim	Province: Limpopo dummy (1 = yes, 0 = no)
urban	Area type: urban dummy (1 = yes, 0 = no)
rural	Area type: rural dummy (1 = yes, 0 = no)
index1	Public asset index – derived from the following variables, using the MCA method: dwelling type, roof material, wall material, water, sanitation, fuel for cooking, fuel for lighting, refuse removal, street lighting
index2	Private asset index – derived from the following variables, using the MCA method: telephone, music player, television, satellite dish, VCR/DVD, computer, camera, stove, microwave oven, fridge/freezer, washing machine, sewing/knitting machine, lounge suite, motor vehicle, bicycle, boat, farming equipment
crime	Very common to be victims of crime dummy (1 = yes, 0 = no)
negative	Experience any negative events dummy (1 = yes, 0 = no)
head	Household head dummy (1 = yes, 0 = no)
black	Race: black dummy (1 = yes, 0 = no)
coloured	Race: coloured dummy (1 = yes, 0 = no)
indian	Race: Indian dummy (1 = yes, 0 = no)
white	Race: white dummy (1 = yes, 0 = no)
male	Gender: male dummy (1 = yes, 0 = no)
female	Gender: female dummy (1 = yes, 0 = no)
age	Age in years
age2	Age in years squared
married	Married or living with a partner dummy (1 = yes, 0 = no)
none	Education: no schooling dummy (1 = yes, 0 = no)
primary	Education: incomplete primary education dummy (1 = yes, 0 = no)
secondary	Education: incomplete secondary education dummy (1 = yes, 0 = no)
matric	Education: matric dummy (1 = yes, 0 = no)
certdip	Education: matric plus certificate or diploma dummy (1 = yes, 0 = no)
degree	Education: bachelor degree dummy (1 = yes, 0 = no)
inactive	Labour status: inactive dummy (1 = yes, 0 = no)
discouraged	Labour market status: discouraged workseekers (1 = yes, 0 = no)
unemployed	Labour market status: unemployed (under the narrowed definition) (1 = yes, 0 = no)
employer	Labour market status: self-employed (1 = yes, 0 = no)
nonperm	Labour market status: non-permanent employees (1 = yes, 0 = no)
perm	Labour market status: permanent employees (1 = yes, 0 = no)
h_excellent	Health status: excellent dummy (1 = yes, 0 = no)
h_vgood	Health status: very good dummy (1 = yes, 0 = no)
h_good	Health status: good dummy (1 = yes, 0 = no)
h­_fair	Health status: fair dummy (1 = yes, 0 = no)
h_poor	Health status: poor dummy (1 = yes, 0 = no)
medical	Covered by medical aid dummy (1 = yes, 0 = no)
r_important	Religion: regarding religion as important dummy (1 = yes, 0 = no)
r_vimportant	Religion: regarding religion as very important dummy (1 = yes, 0 = no)
member	Member of any group dummy (1 = yes, 0 = no)

Table 6: Probit regression on likelihood to be poor in each method

	Marginal fixed effects
	Method 1	Method 2	Method 3	Method 4	Method 5
ec	0.1006***	0.1015***	–0.0162	–0.0056	–0.0050
nc	0.1164***	0.1209***	–0.0764***	0.0459**	–0.0656***
fs	0.1311***	0.1299***	–0.1124***	–0.0756***	–0.0827***
kzn	0.0092	0.0061	–0.2135***	–0.1054	0.0392*
nw	0.0428*	0.0424	–0.0823***	0.0122***	–0.2139***
gau	–0.0551**	–0.0683***	–0.0459**	–0.0986***	–0.1294***
mpu	0.0038	0.0017	–0.0523**	0.0948***	0.2381***
lim	0.1241***	0.1211***	–0.1620***	–0.1221***	0.0510**
urban	–0.0358***	–0.0385***	0.0727***	0.0981***	0.0605***
index1	–0.0378***	–0.0352***	–0.0439***	–0.0502***	–0.0267***
index2	–0.1826***	–0.1816***	–0.1462***	–0.1185***	–0.0948***
crime	0.0190	0.0176*	–0.0191**	–0.0281***	0.0196**
negative	0.0089	0.0086	0.0424***	0.0242**	–0.0273***
head	–0.0074	–0.0052	0.0166	0.0016	–0.0171
coloured	–0.0645***	–0.0782***	0.0066	0.0005	–0.2253***
indian	–0.1738***	–0.1636***	0.0704	–0.0581	–0.3754***
white	–0.3032***	–0.2922***	–0.0169	–0.0674**	–0.2421***
male	–0.0240***	–0.0187*	–0.0135	0.0026	0.0057
age	0.0036**	0.0040***	0.0026*	0.0025*	0.0028**
age2	–0.0001***	–0.0001***	0.0000**	0.0000	0.0000**
married	–0.0232**	–0.0234**	–0.0580***	–0.0308***	–0.0144
primary	–0.0269	–0.0215	–0.0296*	0.0058	–0.0205
secondary	–0.0494***	–0.0424**	–0.0465***	–0.0252	–0.0214
matric	–0.1098***	–0.1012***	–0.1194***	–0.1203***	–0.0482***
certdip	–0.1792***	–0.1710***	–0.1495***	–0.1477***	–0.0173
degree	–0.2823***	–0.2634***	–0.1409***	–0.1228***	–0.0021
discouraged	0.0568***	0.0571***	0.0966***	0.051***	0.0486**
unemployed	0.0425***	0.0422***	0.1609***	0.0742***	0.0291*
employer	–0.1402***	–0.1388***	0.0130	–0.0057	0.0092
nonperm	–0.2333***	–0.2337***	0.0312**	–0.0094	–0.0189
perm	–0.3225***	–0.3224***	–0.0695***	–0.0430***	–0.0683***
h_excellent	0.0353	0.0305	–0.1723***	–0.1654***	–0.2602***
h_vgood	0.0317	0.0242	–0.2022***	–0.1265***	–0.1817***
h_good	0.0336	0.0238	–0.1026***	–0.1375***	–0.0761***
h_fair	0.0318	0.0258	–0.0786***	–0.0786***	–0.0686***
medical	–0.2529***	–0.2589***	–0.1681***	–0.1952***	–0.0740***
r_important	0.0180	0.0245	–0.0647***	–0.0571***	–0.1049***
r_vimportant	0.0400**	0.0504***	–0.0423***	–0.0710***	–0.1995***
member	–0.0509***	–0.0515***	–0.0236**	–0.0448***	–0.0564***
children	0.1178***	0.1191***	0.0067***	0.0149***	0.0052**
elderly	–0.0542***	–0.0594***	–0.0053	–0.0093	–0.0208***
sample size	16 883	16 883	15 786	15 898	16 849
Pseudo-R^2	0.3039	0.3036	0.1151	0.1064	0.1478
Probability > chi-squared	0.0000	0.0000	0.0000	0.0000	0.0000

Notes: ***Significant at 1%; **significant at 5%; *significant at 10%. Reference variables: province: wc; race: black; education: none; labour status: inactive; health: poor; importance of religious activities: not important at all or unimportant.

Source: Authors' own calculations using NIDS 2010/11 data.

Table 7: Ordered probit regression on Methods 3 to 5

	Coefficient
	Method 3	Method 4 (re-coding categories)	Method 5 (re-coding categories)
ec	0.1431***	–0.0546	0.1644***
nc	–0.1106***	0.0569	–0.1230***
fs	–0.0378	–0.1971***	–0.1079**
kzn	–0.4099***	–0.3197***	0.0952**
nw	–0.0338	–0.0747	–0.5441***
gau	0.0889***	–0.2412***	–0.1138***
mpu	–0.1298***	0.0727	0.4323***
lim	–0.2562***	–0.3298***	0.2041***
urban	0.2360***	0.1836***	0.0828***
index1	–0.1772***	–0.1278***	0.0080
index2	–0.2076***	–0.2711***	–0.2323***
crime	–0.0669***	–0.0376**	0.0405**
negative	0.1218***	0.0380*	–0.0344*
head	0.0612***	0.0088	–0.0360*
coloured	0.1180***	–0.0961***	–0.5187***
indian	0.3002***	–0.1309	–0.9714***
white	0.0897	–0.2115***	–0.5711***
male	–0.0363**	0.0105	–0.0223
age	0.0005	0.0078***	0.0067***
age2	–0.0000	–0.0001***	–0.0001***
married	–0.1166***	–0.0752***	–0.0324
primary	–0.0592*	–0.0072	–0.0233
secondary	–0.1242***	–0.0772***	–0.0303
matric	–0.2816***	–0.2947***	–0.0760**
certdip	–0.3050***	–0.3043***	–0.0587
degree	–0.2868***	–0.3309***	–0.0694
discouraged	0.2713***	0.0554	0.1118***
unemployed	0.3870***	0.2040***	0.0610**
employer	0.0385	0.0097	0.0478
nonperm	0.1212***	–0.0437	–0.0296
perm	–0.0922***	–0.1099***	–0.1191***
h_excellent	–0.4508***	–0.4418***	–0.6072***
h_vgood	–0.4874***	–0.3543***	–0.4144***
h_good	–0.2740***	–0.3492***	–0.2010***
h_fair	–0.1732***	–0.2235***	–0.2716***
medical	–0.2310***	–0.3855***	–0.1085***
r_important	–0.1295***	–0.1290***	–0.2234***
r_vimportant	–0.0456	–0.1290***	–0.4201***
member	–0.0191	–0.1550***	–0.1798***
children	0.0143***	0.0278***	0.0142***
elderly	–0.0146	0.0030	–0.0572*
sample size	15 786	15 898	16 849
Pseudo-R^2	0.0550	0.0695	0.0542
Probability > chi-squared	0.0000	0.0000	0.0000

Notes: ***significant at 1%; **significant at 5%; *significant at 10%. Reference variables: province: wc; race: black; education: none; labour status: inactive; health: poor; importance of religious activities: not important at all or unimportant.

Source: Authors' own calculations using NIDS 2010/11 data.

Table A1: Profile of the poor by race, gender and area type of residence, using various relative income poverty lines

	All	Race				Gender		Area type
		Black	Coloured	Indian	White	Male	Female	Urban	Rural
[A]	0.2000	0.2448	0.0752	0.0006	0.0000	0.1633	0.2320	0.1125	0.3222
[B]	0.3992	0.4778	0.2064	0.0854	0.0112	0.3430	0.4471	0.2698	0.5818
[C]	0.2716	0.3287	0.1163	0.0285	0.0062	0.2221	0.3137	0.1650	0.4220
[D]	0.6953	0.7984	0.5695	0.2721	0.0789	0.6514	0.7328	0.5781	0.8608

Note: [A], poorest 20% (R344 per month, 2013 prices); [B], poorest 40% (R647 per month, 2013 prices); [C], one-half of median per capita income (R439 per month, 2013 prices); [D], one-half of mean per capita income (R1 751 per month, 2013 prices).

Table A2: Descriptive statistics of explanatory variables

Variable	Mean	Standard deviation	Minimum	Maximum
wc	0.0993	0.2991	0	1
ec	0.1220	0.3273	0	1
nc	0.0634	0.2436	0	1
fs	0.0554	0.2287	0	1
kzn	0.2990	0.4578	0	1
nw	0.0878	0.2831	0	1
gau	0.0965	0.2953	0	1
mpu	0.0740	0.2617	0	1
lim	0.1025	0.3034	0	1
urban	0.4359	0.4959	0	1
rural	0.5641	0.4959	0	1
index1	–0.2902	1.0580	–2.8824	1.0793
index2	–0.2146	0.8766	–1.5767	2.7996
crime	0.4431	0.4968	0	1
negative	0.2375	0.4255	0	1
head	0.3579	0.4794	0	1
black	0.8358	0.3705	0	1
coloured	0.1257	0.3316	0	1
indian	0.0104	0.1016	0	1
white	0.0280	0.1650	0	1
male	0.4135	0.4925	0	1
female	0.5865	0.4925	0	1
age	36.9851	17.8249	15	104
age2	1 685.6040	1 589.5720	225	10 816
married	0.3141	0.4642	0	1
none	0.1349	0.3417	0	1
primary	0.1552	0.3621	0	1
secondary	0.4830	0.4997	0	1
matric	0.1764	0.3812	0	1
certdip	0.0388	0.1931	0	1
degree	0.0117	0.1074	0	1
inactive	0.5709	0.4950	0	1
discouraged	0.0497	0.2173	0	1
unemployed	0.0917	0.2887	0	1
employer	0.0341	0.1815	0	1
nonperm	0.1405	0.3475	0	1
perm	0.1143	0.3182	0	1
h_excellent	0.3803	0.4855	0	1
h_vgood	0.2956	0.4563	0	1
h_good	0.2045	0.4034	0	1
h_fair	0.0801	0.2714	0	1
h_poor	0.0394	0.1947	0	1
medical	0.0828	0.2756	0	1
r_important	0.4165	0.4930	0	1
r_vimportant	0.4815	0.4997	0	1
member	0.3225	0.4674	0	1
children	0.1967	1.9762	0	20
elderly	0.4737	0.6869	0	3

Source: Authors' own calculations using NIDS 2010/11 data.