Links with Poverty

Not all informal workers are poor and not all working poor are engaged in the informal economy — but there is significant overlap between informality and poverty. This page details what is known about the relationship between working in the informal economy and being poor, based on analyses of official national data commissioned by WIEGO.

The links between informality and poverty can be analyzed at the country, household and individual levels. The first-ever global estimates of informal employment, published by the International Labour Organization (ILO) in 2018, reveal the relationship between informality and poverty at the country and household levels.

Global estimates show that 61 per cent of all workers worldwide are informally employed – a total of 2 billion workers. They also indicate that the rate of informal employment is:

• highest in developing (low-income) countries (90%)
• lowest in developed (high-income) countries (18%)
• quite significant in emerging (middle-income) countries (67%).

(Source: ILO 2018 and Bonnet et al 2019)

They confirm a significant overlap between working informally and being from a poor household:

• a higher per cent of informal workers, than formal workers, are from poor households
• a higher per cent of all workers in poor households, than in non-poor households, are informally employed.

(Source: ILO 2018 and Bonnet et al 2019)

Not all informal workers are poor and not all working poor are engaged in the informal economy. Some informal operators — especially those who hire others — are not poor, while some formal wage workers are poor. But there is a significant overlap between working in the informal economy and being poor. This section details what is known about the relationship between working in the informal economy and being poor. It summarizes findings of several recent studies that used different measurement approaches: average earnings of the various types of formal and informal employment; the earnings/expenditures of households; and the risk for informal workers of being in a poor household.

In the late 1990s, the WIEGO Network commissioned two reviews of the links between informality, poverty, and gender: one of available literature (Sethuraman 1998); the other of available statistics (Charmes 1998). Both reviews found a similar hierarchy of earnings and segmentation by employment status (see Box 1) and sex. These common findings provided the basis for the WIEGO multi-segmented model depicted in Figure 1 below.

In 2004, WIEGO commissioned data analysts to test this model in five developing countries — Costa Rica, Egypt, El Salvador, Ghana, and South Africa — by analyzing national data in those countries (Chen et al. 2005). Data for casual day laborers and industrial outworkers were not available in these countries. The available data allowed for a comparison of status in employment (measured at the individual level) and income poverty (measured at the household level), making it possible to estimate the percentage of workers in specific employment statuses who were from poor households (what WIEGO calls “poverty risk”).

In all countries, average earnings went down and the risk of being from a poor household went up as workers moved down the employment statuses in the WIEGO model.

WIEGO Multi-Segmented Model of Informal Employment: Hierarchy of Earnings & Poverty Risk by Status in Employment & Sex

Source: Chen et al. 2005

• Related WIEGO Blog: How a pyramid sketch redefined the informal economy — and the new data that is putting that 20-year-old idea to the test by Michael Rogan (2018)

For more information, see  Links with Poverty: Data Sources.

For earlier data on earnings in the informal economy, see Links with Poverty: Earlier Findings.

What follows is a summary of the findings of the analysis of data from five countries for the 2005 UNIFEM publication Progress of the World’s Women and of two recent analyses of data from India and South Africa.

Average Earnings

The links between employment, gender, and poverty can be seen by comparing a) average earnings in formal, and informal employment and b) average earnings of different categories of informal employment.

Average Earnings in Formal and Informal Employment

A first comparison is the contrast between average earnings in formal and informal employment, taken as a whole. In all five UNIFEM-WIEGO study countries, average earnings in most forms of informal employment, particularly in agriculture, are well below earnings for formal employment. In Costa Rica and El Salvador, however, average earnings for informal employers are equal to or higher than earnings in formal employment; and in Ghana and South Africa, average earnings of informal public wage workers are higher than those of formal private-sector employment. In general, wage employment in the public sector, both formal and informal, has higher average earnings than wage employment in the private sector. Read Chapter 3 of Chen et al., Progress of the World’s Women 2005 for more details.

Comparative Earnings within Informal Employment

A second comparison is the difference in average earnings within informal employment. As noted earlier, the informal workforce is diverse and segmented. The different segments are associated with different earning potentials that are concealed by the average for the informal economy as a whole.

The five UNIFEM-WIEGO country analyses found a similar hierarchy of average earnings across the different segments of the informal economy. To begin with, average earnings in agricultural informal employment were lower than average earnings in non-agriculture informal employment. Among non-agricultural informal employment, in the five countries with available data, informal employers had the highest average earnings followed by their employees and other “regular” (as opposed to casual) informal wage workers, then own account workers, and then casual wage workers and domestic workers (ibid.; Chen et al. 2005). This set of country studies did not separate out industrial outworkers who tend to have the lowest average earnings of all.

In most of these country cases, separate data on employees of informal enterprises or informal employees more generally were not available. In Egypt, such data are available from an enterprise survey but these cannot be linked to the broader labour-force analysis. In South Africa, such data was available from the labour force survey. Wage employees in informal (unincorporated or unregistered) enterprises earn somewhat less than own account workers, while informal employees in formal (incorporated or registered) enterprises earn more than own account workers. Therefore, in South Africa, informal employees in unregistered enterprises would be considered more closely linked with “casual wage workers” than with “regular wage workers” (Casale et al. 2005, cited in Chen et al. 2005).

Within informal employment, in all five countries, women’s average earnings uniformly fell below those of men with identical employment status. The gender gap in earnings was particularly pronounced among own account workers – both agricultural and non-agricultural. This gender gap in earnings was compounded by the gendered segmentation of informal employment, as women were more likely to be own account workers than regular wage workers. Read Chapter 3 of Chen et al., Progress of the World’s Women 2005 for more details.

A recent analysis of the 2015 South African Quarterly Labour Force Surveys found a similar hierarchy of average earnings and poverty risk within the South African informal workforce by status in employment. It was also able to distinguish between women and men within statuses in employment (Rogan 2019). It shows that men are more likely than women to be employers, own account workers, employees inside and outside informal enterprises while women are more likely than men to be contributing family workers and domestic workers. Among employers, employees in informal enterprises and domestic workers, women and men earn roughly the same and have roughly the same poverty risk; while men earn more and have a lower poverty risk than women among own-account workers and employees outside informal enterprises.

On average, all own account workers earn more than all informal employees, including those in both formal and informal enterprises/farms: reflecting the very low wages for South African employees. (Earlier data for South Africa analyzed for Figure 1 distinguished between informal employees — who have a known employer — and casual wage workers who do not have a regular employer.) But it should be noted that women own account workers earn just over half what men own account workers earn; and that women own account workers earn less than both types of men employees (both in formal and informal enterprises).

Poverty

Household Poverty

Among the UNIFEM-WIEGO set of country studies, the South Africa study looked at household income categories and whether the majority of household employment income was from formal or informal sources, as well the number of earners, the sex of the household head, and the sex of the primary earner (cited in Chen et al. 2005). Households that depended primarily on informal employment income had significantly higher poverty rates than households with a majority of income coming from formal employment. Female-headed households had significantly higher poverty rates than male-headed households. Similarly, households whose primary earner is female have significantly higher poverty rates than households in which the primary earner is male. However, these gender differentials were much less pronounced when households have access to formal employment (ibid).

A separate analysis of the 1999-2000 round of the labour force survey in India looked at poverty rates among urban Indian households that sustain themselves on informal employment income by broad industrial sector and employment type (Sastry 2004). (In this study, households classified as sustaining themselves on informal employment income are households with at least one person employed as an informal workers and no other household member employed outside of the informal economy.)

In marked contrast to South Africa, unemployment in India is not high, and the vast majority of workers — 92 per cent — were in informal employment (both inside and outside informal enterprises). Households that depended on “regular” (as opposed to casual) informal wage employment had lower poverty rates than households that relied on self-employment, and households that depended on casual labour as their primary source of income were the most likely to be poor. This hierarchy of poverty risk – households depending on “regular” informal wage employment having the lowest, self-employment the next highest, and casual wage employment the highest risk — was robust across industrial sectors in urban India.

A recent analysis of 2011-2012 consumption data from India found a similar hierarchy of poverty risk. The highest poverty head-count ratio — or poverty risk — is for households that depend on casual wage work as their main source of income (45), followed by households which depend primarily on self-employment (27), and lowest for households which depend primarily on regular wage work (14) (Raveendran 2019). Self-employment is the most important source of household income overall (for 50% of households), followed by casual wage work (12%) and then regular wage work (18%) (Ibid.). In sum, households which depend on causal work and self-employment as their main source of income are 3.2 and 2 times, respectively, more likely to be poor than households which depend on regular wage work (Ibid.). The households with the highest poverty head-count ratios are those which depend on casual work as the main source of income, particularly in urban areas but also in agriculture. For more details and differences by social groups (caste and religion):

Individual Poverty

Income, and thereby income poverty, is measured at the household, not the individual, level. For the country studies for the 2005 UNIFEM publication, WIEGO used an innovative technique for measuring the risk of poverty among employed persons. According to this technique, the “poverty risk” associated with different employment statuses is defined as the share of all persons employed in a given status who live in households whose incomes place them below the national poverty line. This technique connects the type of employment, measured at the individual level, to the risk of poverty, measured at the household level. As such, it is only feasible in those countries where national data on employment and household income are linked. The hierarchy of poverty risk so defined is the reverse of the hierarchy of earnings detailed above: informal agricultural workers have the highest risk of poverty and, among the non-agricultural informally employed, informal employers have the lowest risk of poverty followed by their employees and other “regular” informal wage workers; own account workers have a higher risk of poverty; while casual wage workers and domestic workers have the highest risk (Chen et al. 2005). Since the UNIFEM-WIEGO country studies were not able to separate out industrial outworkers, it was not possible to measure the poverty risk of industrial outworkers.

In all five UNIFEM-WIEGO study countries, there is an overall gender gap in poverty risk within the informal economy as women are concentrated in forms of informal employment with high rates of poverty. However, the country case studies found that the difference in poverty rates between women and men informal workers within a particular form/segment of informal employment was not significant.

Hierarchy of Earnings and Poverty Risk

The statistical evidence from these various sets of national data analysis suggests a hierarchy of earnings and poverty risk across the various segments of the labour force; as depicted in Figure 1.

While average earnings are higher in formal employment than in informal employment, there is also a hierarchy of earnings within the informal workforce. Employers have the highest average earnings followed by their employees and other “regular” informal employees, then own account workers, followed by casual wage workers and domestic workers, and finally industrial outworkers. Within this hierarchy, women are disproportionately represented in segments of the informal labour force with low earnings. The fact that women tend to be underrepresented among informal employers and “regular” informal wage workers and over-represented among industrial outworkers leads to a gender gap in average earnings, as well as in poverty risk within the informal economy. Average earnings are lower and the risk of poverty is higher among all women workers in the informal economy compared to all men workers within the informal economy.

The hierarchy of poverty risk among households depends on whether households have some formal sources of employment income or only informal sources and also on what type of employment is the primary source of employment income. Households which rely primarily on informal sources of employment income face higher poverty risk than those that rely on formal sources. And households which depend on the most vulnerable forms of informal employment as their primary source of income are likely to have substantially higher poverty risk than those that have access to more stable and better paid forms of informal employment.

See Hierarchies of Earnings & Poverty Risk for the poverty risk of households by source of income, formal and informal.

Conclusion

As this review of available evidence suggests, average earnings are higher in the formal workforce than in the informal workforce. But there are earnings gaps within the informal workforce by status in employment: the studies cited above found a remarkably similar hierarchy of average earnings and of poverty risk across these segments. Within the informal workforce, informal employers typically have the highest average earnings followed by their employees and other “regular” informal wage workers, then own account workers, followed by casual wage workers and domestic workers, with industrial outworkers earning the least of all. A reverse hierarchy of poverty risk obtains within the informal workforce: informal employers have the lowest risk of poverty followed by their employees and other “regular” informal wage workers, own account workers have a higher poverty risk, while casual wage workers and domestic workers have the highest poverty risk. The fact that women tend to be underrepresented among informal employers and “regular” informal wage workers and over-represented among industrial outworkers leads to a gender gap in average earnings and in poverty risk within the informal economy: average earnings are lower and the risk of poverty is higher among all women workers in the informal economy, compared to all men workers within the informal economy.

It should also be noted that the poverty and other outcomes of work are a function not only of the level of earnings but also of the period over which earnings are sustained, and the arrangements through which they are achieved, including related costs and benefits. Four dimensions of work are instrumental in determining the income and other outcomes of work: status in employment, place of work, branch of industry and production system. Each status in employment is associated not only with different average earnings but also with different degrees of autonomy and risk for those who work in them. Each place of work is associated with specific risks and, thus, different degrees of security or insecurity. Each branch of industry — agriculture, manufacturing and services — is undergoing structural shifts: the associated uncertainties, costs and risks and benefits will vary by country. Informal self-employed and wage workers tend to lose market knowledge and bargaining power as they move from traditional to industrial to global systems of production. Read Chapter 4 of Progress of the World’s Women 2005.

While informal work may offer positive opportunities and benefits, such as flexibility of work hours and convenience of work location, the costs and risks are often quite high. Some of these are “out-of-pocket” direct expenses needed to run an informal business or otherwise work informally; others are indirect, reflecting the more general conditions under which the working poor live and work. For example, industrial outworkers in global supply chains often have to absorb the risks of global competition (through irregular work orders and delayed payments); and the absorb many of the non-wage costs of production (workspace, equipment, electricity). Some of these costs can be rather high over the long-term, such as when a worker does not have access to health, old-age pensions and education (or training) for herself or himself or for family members. Also, there are psychological and emotional costs — in terms of a worker’s self-esteem and dignity — associated with many forms of informal work.  For a typology of the costs of working informally and examples illustrating the typology, see Chapter 4 of Chen et al. Progress of the World’s Women 2005.

In conclusion, the quantity and quality of employment available to women, men, and households matter a great deal in determining who is poor and who is not – not only in terms of income poverty but also in terms of other dimensions of poverty. The benefits of informal employment are often not sufficient and the costs and risks are often too high for those who work informally to achieve an adequate standard of living over their life course. However, the costs and risks notwithstanding, informal employment contributes to reducing poverty in households. A recent analysis applying an econometric model to national data from South Africa found that informal workers in that country, particularly informal wage workers but also informal self-employed, contribute to reducing the poverty level of their household. The estimates suggest that “eliminating 100 informal self-employment activities, as some government policies have sought to do in order to discourage ‘illegal trading’, would drive as many individuals into extreme poverty as eliminating 63 formal jobs” and that “(i)nformal employees and domestic workers have a ‘per job’ impact on poverty reduction which is even closer to that of a formal job” (Rogan and Cichello forthcoming).