Why some older people are likely to be more economically vulnerable than others?48

In Chapter 1, I highlighted the criticisms against the advocacy literature on older Africans, which tends to underplay the diversity of vulnerable older groups. This diversity of older groups can help to explain why some urban elderly Nigerians may be more vulnerable than others. Some examples of demographic factors include: age, and gender. These socio-demographic factors may manifest themselves at the individual and household level. Besides income, some socio-economic characteristics are likely to be important in explaining economic vulnerability differences among older people. In Sociology, the main socio-economic characteristics are often viewed to as ‘occupation, education, and income’ (De Vos, 2005, p.88).

In the next section, I briefly review studies within economics and sociology which provide supporting evidence for the inclusion of these factors as possible determinants of economic vulnerability. According to these studies, older people as a demographic group exhibit certain disparities across socio-economic classifications.

2.2.1 Old-Age and Economic Vulnerability

Age is an important variable in understanding the welfare differences among older people.

Earlier, I discussed Grundy’s (2006) study on older Europeans, which identified vulnerable elderly based on those that are very old. Theoretically, household welfare increases with age due to asset accumulation and experience of the individual. Income begins to decline due to withdrawal from the labour force and declining productivity at older ages (Modigliani and

49 Brumberg, 1954). This relation gives the ‘hump’ often explained in the literature (Deaton, 1992;Börsch-Supan, 1992;Alessie and De Ree, 2009). Based on this accepted theory, it has become quite orthodox in the empirical literature to control for age in a household welfare model and as an important determinant of elderly household welfare in developing countries (Deaton and Paxson, 1995;Deaton and Paxson, 1998b;Duflo, 2003;Maitra and Ray, 2003;Van de Walle, 2013;Woolard and Klasen, 2005).

Age effects are important in understanding the economic situations of elderly people. On a societal level, It can determine how much support is given to older people (Harris, 2007) and how much access some may have to income generating opportunities (Maharaj, 2012).

Barrientos et al. (2003), in their review of old-age poverty studies in developing countries, found evidence of a decline in economic opportunity with age. The authors use household surveys pulled from different sources to show that that poverty increases with age. Using a survey of 503 people aged 60 years and over in Thailand, Lloyd-Sherlock (2006) found age differences in economic vulnerability among the elderly.

A key question here is when old age starts. This definition is bound to vary based on the context. I examine this old-age starting point debate in the next section.

2.2.1.1 Who is an older person in an African context?

The World Population Ageing Report posits that ‘50 years’ to be the lowest retirement age in Nigeria, Kuwait, Kiribati, Swaziland, and Solomon Islands (UN, 2013), p. 55). While the key stakeholders in the WHO’s minimum data set project (WHO-SAGE) on older people (1995-2003) strongly advocate for the development of a separate criterion for Africa based on 50 or 55 years (WHO, 2010). Lower life expectancy in many African countries is the key reason cited for a lower age-cut off point for re-defining the classification of older people. This WHO communiqué continues to influence the research studies based on the SAGE dataset in Africa.

Unfortunately, the data has not been collected on Nigeria to warrant its use in this study. The WHO report further identifies two sides of the old-age cut-off point debate in the literature - those who argue that age should be contextualised because information on elderly people could be lost for countries with low life expectancies, and on the other hand, those that argue that doing so will impair international comparisons or comparisons with other body of work (ibid).

There are merits and demerits of using a context-specific approach. However, the merits far outweigh an age-cut of point that is not representative of the ageing context. As I will find, there are indeed difficulties in making comparisons with official statistics in Nigeria. In fact, in some cases I had to increase the age cut-off to the official retirement age of 60 years to ensure

50 that the analysis was comparing ‘like-with-like’ in Chapter 4. Nevertheless given Nigeria’s low life expectancy of 51 years¹⁸ reported by the World Bank in 2010, and the body of evidence suggesting that old age begins much earlier in Nigeria, there is a stronger basis for applying a context-specific age criterion for majority of our analysis.

For instance, one study that addresses the definitions of old-age in applied work is Ezeh et al.’s study on elderly Kenyans in (Cohen and Menken, 2006). Using focus groups and interviews, the authors asked elderly people themselves to identify the meanings that older people assign to being old. They found that older people viewed ‘old age’ based on social definitions, and in the authors’ words “as a process and a stage” characteristic of an end of reproductive capabilities.

Physical characteristics were described as important as well as functionality and increasing financial independence. Although, the authors argued for a lower age starting point based on their findings, they chose to still use the convention of 60 years and over, in the quantitative part of their study. Although, they do not elaborate on this change of approach, it may be simply down to editorial preference as all the other articles in the Cohen and Menken’s book utilised the age of 60 years and above to refer to the elderly.

A recent study by Hunter and May in (Maharaj, 2012) found that those aged 50-59 years old (a group they call “near-old) in South Africa share characteristics which differed from younger age groups. Elderly South Africans regardless of their background are entitled to the State’s old age pension (OAP), payable to elderly from the age of 60 years. It is within this context that they examined the economic status of the near-old before they become eligible for the OAP.

Using a life-course framework and the National Income Dynamics Study, they investigated the employment, health status, and income of near-old South Africans. The authors asserted that including the near-old in any analysis of the economic situation of elderly in Africa provides a better opportunity to mitigate old-age poverty. In all indications, context matters in applying definitions of old age. From a contextual standpoint, most of these studies on African elderly suggest that, perhaps the most appropriate method in studying older people in Africa is to use a lower starting age for older people. Therefore, this thesis will further consider the suitability of the starting point of 50 years for old age for urban elderly Nigerians in Chapter 4.

2.2.2 Gender and Economic Vulnerability

With respect to gender, feminist theories of ageing prioritise gender as a factor that can affect the experience of ageing (Calasanti, 2010b, a). These theorists take the position that gender relations can identify differential ageing experiences between men and women; and women's differential access to material resources (Giddens, 2009;Johnson et al., 2005a). Other examples

18 http://data.worldbank.org/indicator/SP.DYN.LE00.IN

51 can be found in sociological studies where household decision-making status is inferred from gender-based assignments of domestic labour (Giddens, 2009, citing Stroller, 1993; Oppong, 2006).

Gender is now widely recognised as a variable that can influence economic welfare outcomes, and as such it has become common practice to control for gender in applied work. In particular, the role of female household headship has been well-debated over the years.

In one study by Okojie (2002), the author also found that female-headed households are more likely to be poor compared to MHHs in all four survey periods. Mberu (2007), drawing on data from a Demographic Health Survey in Nigeria, found a similar result. The gender variable is a dummy that could highlight any gender disparities that may exist between female headed elderly households compared their male elderly counterparts. Anyanwu (2011) also found a similar result. Conversely, some researchers have found contrary evidence in other SSA countries— many of these studies are somewhat dated. These authors surmise that FHHs are not in the majority among poor households in Africa. Appleton (1996), using the 1992 Integrated Household Survey in Uganda, found contrary evidence. The author did not find any significant gender differences in consumption or income levels in Uganda, although, in urban areas, it was found that female-headed households and households headed by widows had lower economic welfare.

In Malawi, one study by Mukherjee and Benson (2003) on the determinants of poverty found inconclusive gender differences. The study draws data from the 1997/98 Malawi Integrated Household Survey. They also use model simulations to analyses effects of poverty changes on certain household characteristics such as education and labour employment.

As thesis is not primarily focused on providing a gendered perspective on economic vulnerability, the review of the relevant studies above is rather brief. However, it cannot be disputed that although the feminist economics literature has generated mixed evidence in many African settings, there is no disputing the importance of gender differences in economic welfare outcomes. Therefore, it has become good practice to control for gender in any household welfare model. This thesis does not depart from this approach, and in developing the models in Chapter 6 and 7, gender will be controlled for, as the exclusion of the variable may cause significant omitted variable bias.

52 2.2.3 Education, Occupation and Economic Vulnerability

In this section, I review studies that have been able to identify unique socioeconomic factors including owning a home, that are associated with old-age economic vulnerability. Although these studies do not categorically examine economic vulnerability, they relate to welfare outcomes which affect older people.

Educational Achievement and Economic Vulnerability

There is a clear consensus about the importance of education in any economic welfare study on individuals or households. The human capital theory surmises that education is a key determinant of household income (Becker, 1964). According to Becker, there is a positive relationship between educational acquisition and wage earnings. Using Consumption Expenditure Surveys in Nigeria over four periods (1980, 1985, 1992, and 1996), Okojie (2002) found that education reduced the likelihood of household poverty in Nigeria. Elsewhere in Africa, Mukherjee and Benson (2003), using data from the 1997–98 Malawi Integrated Household Survey found that educational attainment would be poverty-reducing in Malawi.

Similarly, education has been found to improve household economic welfare in Cote D’Ivoire (Grootaert, 1997). Citing an earlier study, Appleton (2000) presented evidence to show that there are positive returns on household welfare in Sub-Saharan African countries from receiving secondary education schooling.

Himaz and Aturupane (2011) examined the impact of education on household economic welfare in Sri Lanka using household surveys from 1985 to 2006. The authors applied quantile regression techniques and found that there is an incremental value in household welfare with an extra year of education, suggesting that educational acquisition is important in the labour market.

Occupation and Economic Vulnerability

As an older person, what one is doing or did in the labour market is also important. Some occupations have been found to command higher earnings than others based on the level of skills demanded by labour market forces. For instance, in much of Africa, farm income has been found to be lower than non-farm income (Fox, 2015;Zimmer and Das, 2013). In Nigeria, Appleton et al. (2008) found significant income differences between those in agricultural occupations and those in professional occupations.

53 According to Alem and Söderbom (2012) labour market status affects consumption levels. In their study of urban Ugandans by using household surveys in 2004, 2004, and 2008 and OLS regression analysis, they found that those in the labour force had higher consumption growth rates compared to those out of the labour force. In addition, public sector workers and casual workers where most affected by food price shocks. This evidence suggests that what one does in the labour market is likely to be important in understanding old-age economic vulnerability.

The evidence on education and occupation on economic welfare in African contexts is conclusive, and it would be problematic to exclude these variables as potential determinants of economic vulnerability. In the following chapters of the thesis, I further examine their importance empirically. In addition, some of the studies in this review have noted that, economically inactive individuals may have alternative sources of income which may be important. One alternative source of income is household rental income. In Chapter 4 and 5, I also examine rental income, which may not be influenced by education and occupation. By doing so, and as these studies have done, I can control for omitted variable bias. In addition, some of the studies in this review have highlighted the problem of measurement errors in using income measures. I further examine the completeness of the income data in Chapter 4. In later empirical chapters, identifying potential basic and underlying determinants of economic vulnerability will enable a more robust model in confirming their function as determinants of economic vulnerability.