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ABSTRACT
Despite the high prevalence of disabilities and evidence that persons with disabilities are marginalised in rural areas of developing countries, little is known about their economic lives. The literature is limited to studying how disability affects participation in labour markets and hours worked. This paper extends the current literature by exploring the extent to which disability is associated with participation in, and income generated from, different types of rural activities, such as agriculture, non-agriculture, and wage labour, in three of the most populous Sub-Saharan African countries (Ethiopia, Nigeria, Tanzania). Findings based on panel data and a split first-difference model demonstrate that correlations between changes in disability and changes in economic activities and outcomes are highly contextual. A disaggregated look at various rural economic activities provides a more nuanced understanding of ways in which households cope with changing disability status within a given context. Analyses of disability severity and physical disabilities provide consistent results.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. For more information on the Washington Short Set of questions, see Washington Group on Disability Statistics (2021).
2. Only Mani et al. (Citation2018) establishes causality using panel data and instrumental variable. Schultz and Tansel (Citation1997) and (Schultz, Citation2008) use instrumental variables and find the same results, but they use cross-sectional data.
3. Attrition between waves is not systematic, i.e. having a person with disability in the household is not correlated with attrition. Results are presented in Table A2.
4. (Altman, Citation2016) discusses the disability measure in detail.
5. In Ethiopia’s second and third waves and Tanzania’s second wave, the disability questionnaire is asked to individuals who are five and older. But these questions are answered by all individuals in Nigeria, Ethiopia’s first wave, and Tanzania’s first wave.
6. There are around nine percent, six percent, and seven percent of persons with disabilities in the panel data for Ethiopia, Nigeria, and Tanzania, respectively. Although these rates are similar, they are smaller in comparisons to the prevalence rates from Indonesia (around 16% in the panel used) presented in Mani et al. (Citation2018). Mitra (Citation2018b) reports that variation in prevalence rate is to be expected and are consistent with the findings from WHO-World Bank (Citation2011) and Mitra and Sambamoorthi (Citation2014). The statistics are different from Mitra (Citation2018b) because it uses cross-sectional data and restricts by age. It is not clear why there is a sharp increase in prevalence rate between 2008 and 2010 in Tanzania. However, one possibility is people feeling more comfortable reporting their disability because of Tanzania’s public commitment to the rights of persons with disability through national policies such as the Persons with Disabilities Act of 2010.
7. The data does not provide information on the source of the transfer.
8. Please refer to Mitra and Jones (Citation2017) for more detail.
9. As an alternative, we conducted the same analyses by dividing individuals into three categories – those that experience onset, those that experience recovery from disability, and those that experience persistence disability. Reference group for each category was individuals with no disability in both waves. Results were consistent between the two different identification strategies. Results available upon request.
10. In the interest of space, results for recovery from disability are available upon request from the authors. Results do not provide additional insights beyond those found in the analysis of onset.
11. Mani et al. (Citation2018) presents both fixed effect model and fixed effect model with instrumental variable. We are comparing our results to the results from the fixed effect model.