Better measures of informality can improve poverty reduction policy
In a recent study, my co-authors and I propose a new way to measure informality by household, rather than by individual worker. We find that such an approach —a household-level ‘depth of informality’ metric— can have important consequences for making and evaluating policies that seek to address the link between high levels of informality and levels of household welfare in developing country economies. The development of effective policy in this arena is a critical challenge to overcome to ensure wellbeing for all workers and their households in developing economies today.
Most workers in the world are employed informally, especially in the developing world. They earn lower wages and many cannot move into more lucrative activities. Also, they lack access to social insurance, such as health insurance or old age pensions, which can lead to greater precarity. Without the safety net that many formal workers enjoy, or savings for old-age, income losses when a worker falls ill, or a family member is sick and the worker stays home to care for them, leave informal workers more vulnerable to greater poverty.
This implies that social insurance or social assistance can contribute to poverty reduction. In South Africa, for example, the social pension programme reduced the poverty gap among the elderly population. Additionally, access to old-age pension by an elderly family member improved children’s nutritional status or enabled migration for work, thus benefitting the whole family. These are some reasons why informality and poverty often go hand-in-hand. At the same time, research has shown that formalization does not automatically lead to poverty reduction. One reason for this discrepancy could be how we measure informality.
Informal workers or informal families?
Poverty is usually measured based on household income or expenditure with the assumption that families share these. Thus, poverty reduction policies usually consider the whole household; for example, proxies from household data are often used to assess poverty levels for means-testing of eligibility for public benefits, and related transfers often target the whole family. But when informality is studied, most research considers either family firms, individual workers, or only the household head. Consequently, policies related to reducing the risks of informality are often designed with single individuals in mind, rather than their entire household.
If we imagine a family with two adults working, what do you think they do with their work income? They usually share it. If they both work informally, their family is probably vulnerable to poverty. If both have a formal job, they likely are not poor. If one of them has a formal job, the other one not, they still might be less vulnerable to poverty, thanks to the access to insurance of one member. Therefore, we need to consider families as an economic unit when talking about informality and poverty reduction.
In a recent study, my co-authors and I propose a new way to measure informality by household and use data from five sub-Saharan African countries to investigate the relationship between informality at the household level and household welfare. Our findings confirm that households with some formal income are as well off —or even better off— than families with only formal income. We also find that moving to full formality —meaning households begin to earn all their income from formal jobs— only translates to meaningful welfare improvements if the household income gain is sufficiently large.
What does this mean for policy?
How we measure informality matters. It matters, first, for how we help. If we want to reduce poverty by reducing informality, one pathway might be to formalize workers. Incentivizing workers to formalize only works if their family situation makes this desirable. The informal worker might already have access to social insurance through a family member with a formal job. The family would only consider this change to become fully formal if the welfare gain were sufficiently large. Depending on the policy aim, different measures of informality can lead to different policy prescriptions.
Second, how we measure informality matters for who we help. In sub-Saharan Africa, most countries only have small social insurance schemes, accessible to only few workers and primarily in urban areas. Yet, when we consider how many families indirectly benefit from social insurance because one of their members has a formal job, more people are reached. Such considerations can guide policymakers when they evaluate the cost and benefits of an expansion of social insurance under resource constraints.
Third, how we measure informality matters for how we evaluate policies. For example, when Mexico introduced health insurance for informal workers (Seguro Popular), studies found that this led to an increase in overall informality, which could be seen as a negative consequence and an argument against the policy. Maybe some Mexican families decided that a member should leave their formal job to gain a more flexible informal job, because they would still be insured. They might have added a member to the workforce who could more easily find an informal job and be insured, while also increasing family income. Considering the whole household, the policy might have helped to reduce poverty, even if informality increased. Our measure of informality could be used, for example, to answer these unanswered questions in an evaluation of the Seguro Popular policy.
Informality and poverty are closely linked. Reducing one might reduce the other. To do so, policies must account for the realities of families’ income sharing.
The views expressed in this piece are those of the author(s), and do not necessarily reflect the views of the Institute or the United Nations University, nor the programme/project donors.
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