Waste pickers in informal self-employment: Over-worked and on the breadline

Figures & data

Table 1. Dimensions of underemployment.

Dimension	Description
First	Individuals whose formal education is higher than the requirements of their job.
Second	Individuals employed in a field which does not fall within their formal educational field.
Third	Individuals whose work experience and work skills are higher than the requirements of their job.
Fourth	Individuals that are engaged in involuntary part-time work.
Fifth	Individuals that are earning 20% less in their current job than their previous employment.

Source: Feldman (1996:388).

Table 2. Demographic and educational attainment characteristics of the waste pickers (%).

Gender
Male	64.0
Female	36.0
Race
African	8.0
Coloured	92.0
Indian	0.0
White	0.0
Home language
Afrikaans	92.0
English	2.0
African language	6.0
Marital status
Not married	78.0
Married or living with a partner	14.0
Divorced or Widowed	8.0
Age
0–17 years	0.0
18–24 years	12.0
25–34 years	48.0
35–44 years	26.0
45–54 years	12.0
55–64 years	2.0
65 years or above	0.0
Highest educational attainment
None	0.0
Grade 1–3	0.0
Grade 4–7	34.0
Grade 8–9	36.0
Grade 10–11	14.0
Grade 12 (Matric)	16.0

Figure 1. Reason why the waste pickers left their last job, if they ever worked in a job that involved the receipt of a pay slip.

Figure 2. Reason why the waste pickers decided to collect recyclable waste.

Photo 1. Examples of adapted supermarket trolleys.

Photo 2. Example of a homemade trolley.

Table 3. Work activities of the waste pickers (%).

What they like about their work
Bring income	78.0
Flexible work hours	6.0
Other	6.0
Don’t really like their work	8.0
Unspecified	2.0
What they don’t like about their work
Scratching in bins	20.0
Treated rudely by people	18.0
Bad weather	14.0
Dirty	12.0
Safety concerns	8.0
Tiring job	6.0
Other	6.0
There is nothing they don’t like	14.0
Unspecified	2.0
How to make things better for their work
Given a trolley	48.0
Given a better or bigger trolley	30.0
A firm to collect waste	6.0
Help from the government	4.0
Other	12.0
What is needed to grow the business
Given a trolley	36.0
Given a better or bigger trolley	22.0
Storage space to keep the trolley or waste	8.0
Other	12.0
Nothing is needed	4.0
Unspecified	18.0
Duration of working as a waste picker
Less than 1 year	28.0
1–3 years	28.0
3–5 years	18.0
More than 5 years	26.0
Mean (years)	4.13
Median (years)	2.00
Daily work hours
1–4 h	12.0
5–7 h	20.0
8–10 h	32.0
More than 10 h	36.0
Mean (hours)	9.05
Median (hour)	9.00
Collection of goods for personal use
Yes	62.0
No	38.0
Collection of food for personal consumption
Yes	56.0
No	44.0
Frequency of selling collected waste
Daily	98.0
Weekly	2.0
Reason for selling waste to the BBC (more than one option can be chosen)
Convenient location	60.0
Paid well	42.0
The only place I know	14.0

Figure 3. Where the waste pickers found the waste (more than one option could be declared).

Figure 4. Type of recyclable waste collected by the waste pickers (more than one option could be declared).

Table 4. Use of trolleys by waste pickers (%).

Use of a trolley to collect waste
Yes	54.0
No	46.0
How to collect waste, if a trolley is not used
Bags	82.6
Own dustbin	4.4
By hand	4.4
Ask others for help	4.4
Unspecified	4.4
Would like to have a trolley, if a trolley is not used
Yes	91.3
No	8.7
How to obtain the trolley, if a trolley is used
Stole it at Pick’n Pay / Shoprite	37.0
Made by family / friends	14.8
Made by myself	11.1
Bought it	11.1
Borrowed it	7.4
Got it freely from someone	7.4
Unspecified	11.1
Ideal type of trolley, if a trolley is used
Bigger trolley	50.0
Flatter trolley	11.5
Pick’n Pay / Shoprite type trolley	11.5
Other	27.0

Figure 5. (a) Distribution of usual daily income of waste pickers (2016 December prices). (b) Distribution of log usual daily income of waste pickers (2016 December prices).

Table 5. Daily income of the waste pickers (2016 December prices).

Income measure	Usual income for a day's waste	Best income for a day's waste	Worst income for day's waste	Income earned from last time the waste is sold
Mean
BBC 1	R 135.43	R 283.67	R 64.77	R 120.03
BBC 2	R 106.50	R 156.10	R 49.12	R 89.24
All BBCs	R 123.86	R 232.64	R 58.51	R 104.45
Median
BBC 1	R 100.00	R 175.00	R 42.50	R 105.00
BBC 2	R 100.00	R 150.00	R 37.50	R 70.00
All BBCs	R 100.00	R 150.00	R 40.00	R 100.00

Figure 6. Actual income compared to expected income.

Table 6. Other information on the waste pickers (%).

Location of sleep
Hostel / Shelter	28.0
Backyard shack	24.0
Buy-back centre	24.0
On the street	8.0
Other	16.0
Travelling from home to waste collection point
Yes, travel from home	32.0
No, stay overnight	52.0
Unspecified	16.0
Access to food and facility (more than one option can be chosen)
Drinking water	84.0
A place to wash himself/herself	68.0
Toilet	66.0
Food	64.0
Level of treatment by the public
Good	70.0
Fair	24.0
Poor	2.0
Unspecified	4.0
Work with other waste pickers to help one another
Yes	74.0
No	26.0
Seeing more waste pickers since started collecting waste
Yes	100.0
No	0.0
Health and injury risks
Yes – small cuts	28.0
Yes – get sick easily	24.0
Yes – bad smell	4.0
No	44.0

Figure 7. (a) Distribution of life satisfaction of waste pickers. (b) Distribution of life satisfaction of informal self-employed in elementary occupations, NIDS2016.

Table 7. Underemployment likelihood (%) of non-agricultural workers in each approach.

	Time-based	Over-qualification	Low-income: <125% of poverty line	Low-income: earning 20% less than previous period
Quarterly Labour Force Survey 2017 data (including self-employed only)
Formal sector	1.48	15.00	4.09	N/A
Informal sector	9.41	5.42	23.00	N/A
Authors’ data
Waste pickers	24.00	16.00	26.00	42.00

Table 8. Regression of factors associated with the usual daily income generated by the waste pickers.

Dependent variable (log of daily income)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9
Male	0.520**	0.506**	0.517**	0.500**	0.502**	0.477*	0.478*	0.489*	0.443*
	(0.246)	(0.249)	(0.241)	(0.231)	(0.243)	(0.241)	(0.243)	(0.260)	(0.252)
Married		0.285	0.414*	0.544**	0.542**	0.561**	0.561**	0.397	0.549**
		(0.237)	(0.231)	(0.227)	(0.232)	(0.228)	(0.232)	(0.271)	(0.260)
Age			0.034	0.060	0.060	0.054	0.055	0.033	0.061
			(0.065)	(0.061)	(0.061)	(0.062)	(0.067)	(0.074)	(0.069)
Age squared			−0.001	−0.001	−0.001	−0.001	−0.001	−0.001	−0.001
			(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Buy back Centre				0.412*	0.409*	0.424*	0.428*		0.438*
				(0.232)	(0.230)	(0.233)	(0.242)		(0.233)
Education					0.002	−0.011	−0.010	0.013	−0.012
					(0.040)	(0.045)	(0.047)	(0.053)	(0.048)
Previous formal work experience						0.121	0.115	0.036	0.082
						(0.216)	(0.218)	(0.240)	(0.240)
Hours							0.005	−0.003	0.008
							(0.034)	(0.038)	(0.034)
Trolley								0.201	0.218
								(0.243)	(0.236)
Constant	4.094***	4.061***	3.949***	3.233***	3.218***	3.393***	3.308**	3.765**	3.111**
	(0.211)	(0.213)	(1.158)	(1.125)	(1.184)	(1.196)	(1.461)	(1.619)	(1.471)
Observations	47	47	47	47	47	47	47	47	47
R-squared	0.101	0.118	0.262	0.320	0.320	0.324	0.324	0.282	0.342
Specification test (P-value)		0.732	0.632	0.909	0.906	0.968	0.962	0.100	0.579

Note: Robust standard errors in parentheses.

***p < .01.

**p < .05.

*p < .1.

Table 9. Logistic estimates of underemployment likelihood.

Dependent variable: Underemployment	Time-based		Low-income: <125% of poverty line		Low-income: earning 20% less than previous period		Over-qualification
	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
Male	0.135	0.153	−0.336***	−0.321***	0.069	0.074	−0.000	−0.037
	(0.107)	(0.113)	(0.087)	(0.099)	(0.141)	(0.147)	(0.131)	(0.118)
Married	−0.305	−0.306	−0.019	−0.035	−0.574***	−0.575***	0.019	0.029
	(0.200)	(0.256)	(0.142)	(0.159)	(0.207)	(0.216)	(0.174)	(0.155)
Age	0.079**	0.072**	0.014	0.021	−0.049	−0.053	0.034	0.031
	(0.039)	(0.035)	(0.034)	(0.033)	(0.038)	(0.037)	(0.035)	(0.038)
Age squared	−0.001**	−0.001**	−0.000	−0.000	0.001	0.001	−0.000	−0.000
	(0.001)	(0.000)	(0.000)	(0.000)	(0.001)	(0.001)	(0.000)	(0.000)
Buy back Centre	0.051	0.047	−0.231**	−0.233**	−0.308***	−0.308***	0.134	0.124
	(0.113)	(0.107)	(0.113)	(0.108)	(0.112)	(0.109)	(0.115)	(0.115)
education	0.061***	0.067***	0.029	0.030	−0.039	−0.036
	(0.018)	(0.020)	(0.028)	(0.029)	(0.034)	(0.035)
Previous formal work experience	−0.143	−0.179	−0.016	−0.019	0.274	0.282*
	(0.103)	(0.121)	(0.107)	(0.103)	(0.169)	(0.165)
Hours	−0.075***	−0.076***	−0.011	−0.012	0.022	0.022	0.023
	(0.010)	(0.008)	(0.016)	(0.017)	(0.024)	(0.024)	(0.021)
Trolley		−0.103		−0.101		−0.105		0.166
		(0.087)		(0.098)		(0.116)		(0.113)
Observations	50	50	50	50	50	50	50	50
Logistic Regression Chi^2(2)	25.870***	28.250***	15.370***	16.650***	15.79***	17.150***	5.160*	5.37*
Pseudo R^2	0.469	0.513	0.268	0.291	0.230	0.250	0.117	0.122
Specification test	0.324	0.189	0.831	0.489	0.864	0.455	0.243	0.389
Goodness-of-fit test	0.945	0.936	0.480	0.295	0.215	0.178	0.145	0.217

Note: Robust standard errors in parentheses.

***p < .01.

**p < .05.

*p < .1.

Table A1. Underemployment likelihood (%) of non-agricultural self-employed, QLFS 2010–2017

	Formal sector			Informal sector
	Time-based	Over-qualification	Low-income^#	Time-based	Over-qualification	Low-income^a
2010	1.41	20.23	4.48	8.47	9.72	25.83
2011	1.54	17.57	3.94	8.20	7.54	24.78
2012	1.36	19.93	6.22	9.32	2.82	25.42
2013	2.11	16.47	10.36	9.25	3.23	24.54
2014	1.28	16.34	6.45	8.88	3.54	23.58
2015	2.02	16.26	5.27	9.00	3.80	24.13
2016	1.16	14.25	5.09	9.92	4.09	22.03
2017	1.48	15.00	4.09	9.41	5.42	23.00

^aEarning 125% less than the poverty threshold.

Feldman, D, 1996. The nature antecedents and consequences of under-employment. Journal of Management 22(3), 385–407.

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