LABOUR MARKET PARTICIPATION AND INCOME DISTRIBUTION OF THE AGED IN NIGERIA By Osunde Omoruyi (PhD) and Augustine Dokpesi (PhD) Presented in the Inaugural Ceremony and International Conference of African Society for Ageing Research and Development (ASARD), ABUJA NIGERIA 13th – 14TH October, 2015

Outline of presentation Introduction Ageing as a policy issue in Nigeria Objectives of the Study Labour Market Issues Methodology for Labour Market Analysis for the Aged Data Results Policy Implications/Recommendations

Introduction More than 2 million people, representing 70 percent of the older population, lived in the rural areas and they contributed mostly to agricultural production (NPC, 2006) Virtually all the people in the rural areas lack access to social and economic amenities. Studies have shown that the income situation and welfare of the elderly persons in Nigeria are deplorable. However, the rate of labour market participation in Nigeria is higher among elderly males than females, and a significant proportion of them participate in the formal wage sector well beyond their retirement age (NPC,2004) The reason for their continuous participation in the labour market is that social security policies for the seniors are weak if any and the lack of social security system increases their level of poverty and inequality

Introduction continue Apart from the level of education and place of residence as factors that influence the distribution of income of the older persons, a social security policy for the aged is another factor that could influence the distributional pattern of income for the aged. The support for old age result to high fertility in Africa. Parents do invest in their children with the hope that such investment will yield dividends in old age. Having a disabled children are viewed as “poor investment”. Increasingly, the care of older family members is falling due to the process modernization and industrialization.

Ageing as a policy issue in Nigeria Recently, ageing has become a policy issue receiving some attention by government and other stakeholders like ASARD. United Nations (2010) report on current status of the social situation of older people stated that the issue of ageing represents economic and social development strategy. While it is expected that Nigeria in the next 40 years will experience a rapid increase in the number of older people, like other African countries, sees this emerging issue as a serious future challenge. Inability of government to cope with the regular payment of pensions to the retired workforce, inadequate social and health services to cater for the needs of an ageing population and a predominately rural agrarian population all these pose new threats to sustainable development in Nigeria.

Labour Market Issues Labour Force Participation Features of the labour market . Formal . Informal Location Rural – largely informal Urban – mix of formal and informal Labour Force Participation Income Inequality and Determinants

Methodology In this study, income generation model were designed to described the structure of the labour market income The method of Bourguignon et al, (2002) was adopted based on the decomposition of wage differences on the socio-demographic structure of the Nigerian population for the elderly. This methodological approach provides information regarding the impact of demographic patterns on labour force participation and income inequality for older people. Earnings are a function of education, experience and other demographic characteristics such as gender, martial status and number of children

Methodology continue The logit model is specified for labour market participation. This model is used to predict the probability of each individual (minimum 65 years of age participate in the labour market for both males and females). For the estimation of earnings, a logarithm of the yearly wage is estimated using the Ordinary Least Square (OLS) method. On the decomposition side, the Half Square Coefficient (commonly referred to as the General Entropy Class of Inequality measure were employed). This method were employed because it places more weight on the income trend of high income households.

Data National Living Standard Survey. 2004- Conducted by the national Bureau of Statistics Comprises of: 19158 Households 92610 Individuals Only individuals 65 years and above were used in this study. (3290)

RESULTS

Descriptive Statistics Table 1: Average Age of Household Head and Number of persons In each Household Group Source: estimated by the authors Table 1 describe the average age of household head and number of persons in each household group. These are likely going to offer some clues as to the likely sources of changes in the income distribution among household heads. Household group Number of persons Age Married old persons with more than 2 other adults 4 80 Unmarried old persons without children 2 72 Married old persons with children 71 Total 8

Table 2: Percentage share of sources of Household Income of the elderly persons by Education, Sex, Region and Occupation Source: Estimated by the authors Demographic variables Employed income Self-employed income Farm income Capital Benefit Male 10.6 27.2 54.7 2.8 4.6 Female 1.7 43.3 50.8 2.5 Urban 13.9 52.1 25.8 2.6 5.7 Rural 5.2 9.3 79.9 3.0 2.9 No education 4.1 14.5 78.7 2.3 0.4 Primary 13.4 30.2 52.3 3.7 0.5 Lower secondary 12.8 42.1 41.1 1.4 Upper secondary 23.1 64.3 7.9 University 18.2 30.0 28.1 18.5

Table 2 shows the percentage share of household income type for sex, region of residence and education. It was observed that household income between male and female varies substantially with the income types. Overall, the income of elderly male is higher than that for elderly female in all income types except for self-employment As expected, income is also higher in urban areas than in rural areas except for farm income in the rural areas Considering how education significantly enhances the earnings potential of the elderly, it should come as no surprise that the elderly persons with no university degrees have lower proportion of earnings in the formal wage sector. Elderly persons with upper secondary education have a higher share of income in the self-employed sector, while the share of income is higher in the farming sector with elders with no education. Interestingly, elders in the household received more benefits with those with university degrees.

Table 3 Inequality by Gender and Rural- Urban Dimensions Sector/Gender/Inequality Indices GE(0) GE(1) GE(2) Gini Coefficient Income share Population share Aggregate 0.661 0.537 0.759 0.551 Male Female Within Inequality Between Inequality 0.607 0.520 0.580 (86.0) 0.081 (14.0) 0.486 0.373 0.469 (85.5) 0.068 (14.8) 0.639 6.414 0.699 (91.5 0.059 (8.5) 0.529 0.472 0.848 0.151 0.688 0.311 Urban Rural 0.584 0.843 0.656 (99.2 0.005 (3.8) 0.685 0.532 (99.2) 0.004 (0.8) 0.634 1.214 0.754 (99.3) (0.7) 0.531 0.598 0.765 0.234 0.722 0.277

Inequality by Gender and Rural- Urban Dimensions Inequality is about 5 percentage points different between males and females (male 0.529, female 0.472) using Gini coefficient. Within group inequality accounts for 86% of inequality by sex. While between gender inequality accounts for only 14%. Urban-rural inequality is slightly higher in rural areas than urban based on Gini coefficient (urban 0.531 and rural 0.598). Within group inequality dominates at 99% as against between group at about 1%

Table 5: Labour market participation equations using Logit method for in-work, employed, self-employed, farmer, has-capital and benefit received Inwork Employed Self-employed Farm Capital Benefit Mal e Female Male Univ -1.431* (0.265) -4.145* (0.683) -0.130 (0.744) 0.570 (0.488) 2.427 (1.532) -0.326 (0.519) -2.079 (1.529) 0.710* (0.199) -0.437 (0.735) 2.377* (0.403) 1.791** (0.859) Upsec -1.060* (0.600) -2.316** (0.888) 0.906 (0.636) -0.919* (1.567) 1.450* (0.485) -1.551* (0.527) -0.069* (0.483) 1.919* (0.624) 3.331** (1.224) Losec -0.568* (0.165) -0.440 (0.311) 1.063** (0.391) 0.401*** (0.279) 1.199** (0.596) -0.667*** (0.288) -1.212* (0.598) -0.328 (0.256) -0.466* (0.736) 1.826* (0.426) Primed -0.494*** -0.364 (0.278) 1.126*** (0.439) 0.611** (0.337) -0.029*** (0.536) -0.626*** (0.360) 0.047 (0.542) 0.076 (0.296) 0.134 (0.410) 0.705 (0.779) 1.389 (1.109) Rural 0.728* (0.113) 0.035 (0.129) -1.013* (0.254) -1.347*** (0.587) -2.481* (0.176) -2.929* (0.262) 2.756* (0.185) 3.105* (0.281) 0.542** (0.202) -0.697** (0.264) -0.622* (0.309) -0.044 (0.761) Married 0.955* (0.134) -0.409* -0.214 (0.425) -0.229 (0.284) -0.058 (0.245) 0.316 (0.304) 0.084** (0.250) Illness -0.261*** (0.115) 0.105 (0.125) -0.081* (0.314) 0.329 (0.632) 0.380** (0.213) -0.378* (0.241) -0.233 (0.226) 0.405*** (0.045) -0.082 (0.183) 0.165 (0.277) Experience 0.029 (0.048) -0.200 -0.351* (0.122) -0.796*** (0.474) -0.081 (0.091) (0.996) -0.186 (0.249) Experience2 -0.001** (0.000 ) 0.001 (0.000) -0.003* (0.001) 0.005** (0.003) -0.002 -0.001* -0.001 Worky - 5.286* (0.615) -2.194*** (0.885) 3.300* (9.111) 4.011* (3.688) 4.633 (1.833) --0.000 Constant 0.741 (1.671) 9.592*** (3.954) 9.265*** (4.160) -2.863* (0.242) 2.366 (3.075) -9.355* (8.939) -5.700** (3.375) 5.433 (8.649) -2.888* (0.208) -2.686* (0.231) -4.521* (0.395) -5.100* (0.722) Pseudo R2 0.082 0.075 0.119 0.355 0.236 0.256 0.408 0.282 0.025 0.016 0.123 Obs. 2234 1464 1548 546 580 1455 1403

Determinants of Labour Market Participation Labour market participation was measured by various income type for both male and female aged 65 years and above Significant determinants include education, age and marriage For female, illness and marriage affected participation in the labour market significantly though has a negative relationship Capital and Benefit recipients increases with education and decreases with rural areas.

Choice of Occupation and Labour Market Income (OLS Estimation) Employed Self-employed Farm Capital Benefit Male Female University 0.301 (1.532) 0.549 (0.105) -0.175 (0.834) 0.422** (0.231) 0.393 (0.253) -0.041 (1.305) 3.336*** (1.282) 0.394 (0.277) Upper secondary -0.754 (1.152) 0.208* (0.501) 2.274*** (0.964) 0.328* (0.366) 0.742 (0.647) 3.960** (1.788) 0.031 (0.240) Lower secondary (0.811) 3.174 (2.458) 0.436** (0.320) 0.006 (0.339) 0.369 (0.129) 0.801*** (0.348) 1.045 (1.045) 1.024 (1.264) -0.434** (0.245) Primary -0.074 (0.122) 0.038 (0.409) -0.641 (0.489) 0.131 (0.144) 1.151* (0.403) 1.290 (01.094) 2.858 (2.366) -1.185* (0.235) Rural -0.919*** (0.487) -0.604 (1.035) -0.659* (0.219) -0.395*** (0.159) -0.350** (0.119) -0.300 (0.268) -0.281 (0.488) -0.316 (1.012) -1.150* (0.107) Illness 0.768 (0.645) -1.872** (0.827) -1.153 -0.271* (0.079) Experience -0.137 (0.237) -0.767 (0.781) 0.030 (0.103) 0.168 (0.150) 0.069 (0.048) Experience2 0.001 (0.000) -0.000 -0.001 Constant 15.867** (8.108) 35.509* (29.358) 9.731* (3.462) 4.994 (5.189) 7.831* (1.641) -0.581 (0.871) -3.595 (23.355) 10.267 (78.889 7.486* (0.233) R2 . 0.149 0.692 0.077 0.081 0.018 0.056 0.058 0.319 0.183 Obs 78 13 202 220 1563 211 64 48

Earnings Education and experience significantly and positively affects income of the elderly for both males and females Being employed in rural area is significant and sign is negative Farm income reduces significantly in rural areas Capital and benefit incomes reduces for male and female in rural areas

Policy Implications/Recommendation Need for adequate social security system for the elderly in order for them not to part take or continue to participate in the labour market after retirement. There is also need to balancing the unequal distribution of income in the Nigerian labour market among the seniors There is also the need for policy makers to focus more on various development programs for the elderly to reduce unequal distribution of income between males and females

Conclusion ☻Labour market is a primary area where inequality should be addressed especially among the elderly ☻Structure of the labour market is an important factor in determining welfare ☻Inequality is more pronounced among the elderly males involves in income earning activities compared to the elderly females ☻The primary variables which explains the distribution of income and its differences among the elderly is their educational attainment, sex and location of residence ☻ Disparity in labour earnings is a specific factor, which explains inequality among Nigeria elderly people