Work
Background
Article 27 of the CRPD “recognizes the right of persons with disabilities to work, on an equal basis with others; this includes the opportunity to gain a living by work freely chosen or accepted in a labor market and work environment that is open, inclusive and accessible to persons with disabilities”. It also prohibits all forms of employment discrimination, calls for reasonable accommodation in the workplace, promotes access to vocational training and self-employment opportunities. This section describes and discusses the main results on work indicators. The entire set of results is available in the Work Results Tables.
The term “work” is broad and includes both paid and unpaid work. Unpaid work can be, for instance, working in a family enterprise. Meanwhile, paid work means being employed by another person or organization whether in the formal or informal economy. This report uses five work indicators for adults. The first one is the employment population ratio, also called the employment rate. It captures the share of the adult population who is employed, i.e. working for pay or those who are self-employed.
The youth idle rate measures the share of youth aged 15-24 years who are not enrolled in school and are not employed (SDG indicator 8.6.1). We measure the share of the employed in the manufacturing sector (SDG 9.2.2) and the share of women who hold managerial positions (SDG 5.5.2). Finally, the informal work indicator[12] captures the share of the adult population who do informal work, i.e. who are self-employed, those who work for a microenterprise of five or few employees or in a firm that is unregistered and those who have no written contract with their employers. It also includes persons who work unpaid, including for a family business.
Except for the youth idle rate which focuses on adults ages 15 to 24, the work indicators are generally reported for all adults ages 15 and older. For seven countries for which the Demographic and Health Survey (DHS) females and males modules were used (Cambodia, Colombia, Haiti, Maldives, Mali, Pakistan, Timor Leste), the work information in DHS covers ages 15 to 49 and ages 15 to 54 for women and men respectively.
Results
Adults with any functional difficulty have significantly lower employment population ratios in 30 out of 40 countries. For adults with at least a lot of difficulty, this is the case for 29 out of 35 countries. The disability gap in the employment population ratio ranges from a low of 2 percentage points in Malawi to a high of 48 percentage points in Mauritius. The median stands at eight percentage points.
For 15 of the 35 countries, there is a gradient in the employment population ratio, with persons with some difficulty having lower employment population ratios than persons with no difficulty but higher ones than persons with at least a lot of difficulty.
As shown in Tables 7.1 and 7.2, while women consistently have lower employment population ratios than men, the disability gap in the employment population ratio tends to be larger for men than for women with a median gap of 10 and five percentage points respectively. It is also often larger for older age groups.
Four countries have a reverse gap, i.e. a larger employment population ratio for persons with any difficulty compared to persons with no difficulty (disaggregation a: Colombia, Papua New Guinea, Timor Leste, Vanuatu). However, for all of them except Colombia, this result only holds for persons with some difficulty and not persons with at least a lot of difficulty with disaggregation b.
The youth idle rate shows a similar pattern as the employment population ratio across countries with a disability gap in 22 out of 38 countries. The disability gap in the youth idle rate is larger in rural areas compared to urban areas. In most countries, the share of persons in manufacturing and the share of women in managerial positions are similar across functional status but are significantly lower for persons with functional difficulty in 12 and eight countries respectively.
Adults with any functional difficulty are significantly more likely to do informal work in 26 out of 37 countries. Persons with some and at least a lot of difficulty have a higher rate of informal work in respectively 17 and 20 out of 29 countries.
Discussion
Overall, employment population ratios are lower for persons with functional difficulties compared to persons with no difficulty in most countries.
The significance and magnitude of the gap varies considerably across contexts. This may come from the variety of survey questions that capture work. It is noteworthy that most of the countries that do not have a disability gap are countries with DHS datasets, where work questions are only asked among a subsample of adults who are young or middle aged and do not capture older adults.
There are also contextual variations in the accessibility of the work environment, the availability of workplace accommodations, and the presence of discrimination. The cultural and social context also matters in so far as negative attitudes toward the employment potential of persons with disabilities in society at large or within the household might limit access to work. The policy context is also relevant: for instance, are there vocational rehabilitation programs available? Are there disability cash transfer programs? Such programs, depending on how they are designed and put into practice, might facilitate or limit access to work for persons with disabilities.
In addition, the results in this report point out that work differences across functional difficulty status are more pronounced among males than females. For women, barriers to work may well be primarily gender-related.
This paper finds a significantly higher proportion of adults with functional difficulties who do informal work in a majority of countries. Other studies do find a higher share of workers with disabilities in self-employment compared to workers without disabilities in several countries (e.g., Eide and Kamaleri, 2009; Mitra and Mizunoya 2013). The data used in this study does not help us determine if they are constrained into informal work due to barriers to the formal sector, which should be the subject of further research.
Table 7.1: Females’ Employment Population Ratio
Country | No Difficulty | Any difficulty | Difference | Statistical Significance |
---|---|---|---|---|
Afghanistan | 15 | 12 | 3 | *** |
Bangladesh | 11 | 8 | 3 | *** |
Cambodia | 76 | 71 | 4 | * |
Colombia | 55 | 61 | -6 | *** |
Djibouti | 10 | 11 | -1 | NS |
Dominican Rep. | 35 | 26 | 9 | *** |
Ethiopia | 43 | 38 | 5 | ** |
Gambia | 42 | 40 | 1 | NS |
Haiti | 43 | 53 | -11 | *** |
Indonesia | 46 | 29 | 17 | *** |
Kiribati | 33 | 31 | 3 | *** |
Liberia | 70 | 65 | 5 | ** |
Malawi | 74 | 73 | 1 | NS |
Maldives | 40 | 41 | -1 | NS |
Mali | 53 | 49 | 3 | NS |
Mauritius | 39 | 10 | 29 | *** |
Mexico | 37 | 18 | 19 | *** |
Morocco | 15 | 9 | 7 | *** |
Myanmar | 46 | 24 | 22 | *** |
Namibia | 58 | 56 | 2 | NS |
Nigeria | 53 | 49 | 5 | NS |
Pakistan | 17 | 23 | -6 | *** |
Panama | 39 | 15 | 25 | *** |
Papua New Guinea | 67 | 70 | -3 | * |
Peru | 62 | 35 | 26 | *** |
Puerto Rico | 40 | 12 | 27 | *** |
Rwanda | 50 | 34 | 16 | *** |
Senegal | 20 | 18 | 1 | *** |
South Africa | 37 | 29 | 8 | *** |
Suriname | 41 | 36 | 5 | *** |
Tajikistan | 17 | 14 | 3 | ** |
Tanzania | 83 | 76 | 6 | *** |
Timor Leste | 26 | 37 | -12 | *** |
Tonga | 39 | 27 | 12 | *** |
Uganda | 68 | 64 | 4 | NS |
Uruguay | 55 | 28 | 28 | *** |
Vanuatu | 58 | 60 | -2 | *** |
Vietnam | 73 | 34 | 39 | *** |
West Bank and Gaza | 17 | 9 | 8 | *** |
Zimbabwe | 64 | 65 | -1 | NS |
Notes: *, **, *** indicate that the difference is statistically significant at the 10%, 5% and 1% levels respectively. NS stands for not significant
Table 7.2: Males’Employment Population Ratio
Country | No Difficulty | Any difficulty | Difference | Statistical significance |
---|---|---|---|---|
Afghanistan | 69 | 55 | 14 | *** |
Bangladesh | 79 | 53 | 26 | *** |
Cambodia | 90 | 88 | 3 | NS |
Colombia | 89 | 92 | -3 | *** |
Djibouti | 34 | 30 | 4 | * |
Dominican Rep. | 60 | 44 | 16 | *** |
Ethiopia | 62 | 58 | 5 | * |
Gambia | 61 | 60 | 1 | NS |
Haiti | 71 | 79 | -8 | *** |
Indonesia | 81 | 61 | 20 | *** |
Kiribati | 49 | 45 | 4 | *** |
Liberia | 79 | 77 | 2 | NS |
Malawi | 82 | 80 | 2 | NS |
Maldives | 96 | 90 | 6 | *** |
Mali | 87 | 93 | -6 | *** |
Mauritius | 73 | 22 | 51 | *** |
Mexico | 76 | 41 | 35 | *** |
Morocco | 70 | 41 | 29 | *** |
Myanmar | 81 | 52 | 29 | *** |
Namibia | 67 | 58 | 9 | *** |
Nigeria | 66 | 53 | 13 | *** |
Pakistan | 97 | 93 | 4 | ** |
Panama | 73 | 35 | 38 | *** |
Papua New Guinea | 66 | 71 | -5 | *** |
Peru | 78 | 46 | 32 | *** |
Puerto Rico | 51 | 16 | 35 | *** |
Rwanda | 65 | 44 | 21 | *** |
Senegal | 58 | 45 | 13 | *** |
South Africa | 53 | 42 | 11 | *** |
Suriname | 71 | 61 | 10 | *** |
Tajikistan | 57 | 40 | 17 | *** |
Tanzania | 90 | 80 | 9 | *** |
Timor Leste | 62 | 79 | -17 | *** |
Tonga | 61 | 49 | 12 | *** |
Uganda | 74 | 67 | 7 | ** |
Uruguay | 76 | 45 | 30 | *** |
Vanuatu | 77 | 79 | -2 | *** |
Vietnam | 82 | 48 | 34 | *** |
West Bank and Gaza | 57 | 32 | 25 | *** |
Zimbabwe | 74 | 69 | 5 | *** |
Notes: *, **, *** indicate that the difference is statistically significant at the 10%, 5% and 1% levels respectively. NS stands for not significant
[12] It is related to, but is not exactly the same as, SDG indicator 8.3.1.