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Behind Closed Doors: how traditional measures of poverty mask inequality inside the household and a new look at possible solutions

Caren Grown's picture

During the days coming up to, and after October 17, when many stories, numbers, and calls for action will mark the International Day for the Eradication of Poverty, we want to invite you to think for a second on what you imagine a poor household to be like. Is this a husband, wife, and children, or maybe an elderly couple? Are the children girls or boys? And more importantly, do all experience the same deprivations and challenges from the situation they live in?  In a recent blog post and paper, we showed that looking at who lives in poor homes—from gender differences to household composition more broadly—matters  to better understand and tackle poverty.

Globally, female and male poverty rates—defined as the share of women and men who live in poor households—are very similar (12.8 and 12.3 percent, respectively, based on 2013 data). Even in the two regions with the largest number of poor people (and highest poverty rates)—South Asia and Sub-Saharan Africa—gender differences in poverty rates are quite small. This is true for the regions, but also for individual countries, irrespective of their share of poor people. Why is that the case? As Chapter 5 of the 2018 Poverty and Shared Prosperity Report explains, our standard monetary poverty indicator is measured by household, not by individual. So, a person is classified as either poor or nonpoor according to the poverty status of the household in which she or he lives. This approach critically assumes everyone in the household shares equally in household consumption—be they a father, a young child, or a daughter-in-law.  By design, it thus masks differences in individual poverty within a household.

Notwithstanding this shortcoming, when we look a bit deeper the information we have today still shows visible gender differences in poverty rates. Take age, for example. We know that there are more poor children than poor adults, and while we do not find that poverty rates differ much between girls and boys at the early stages of life, stark differences appear between men and women during the peak productive and reproductive years.

The poverty rate of women aged 25-34 in Sub-Saharan Africa and South Asia is, on average, 5.5 percentage points higher than that of men (27.8 percent versus 22.3 percent). What could explain this striking difference?

Factors such as age of marriage and childbearing, the presence of young children in the household, and the related higher likelihood for women to leave (or not engage in) economic activities as a result of the time they allocate to unpaid care and domestic work, can be linked to the gender gap in poverty rates for individuals in this age group. Moreover, these factors relate to an unequal distribution of power inside a household, which tends to favor men in many countries. Even when we take into account age differences between husbands and wives (as a proxy for women’s bargaining power), the gender difference in poverty remains.

The picture changes when looking at older ages. In most countries, later in life—that is, for men and women 60 years and older (which represent only 5 percent of the total poor women and poor men in South Asia and Sub-Saharan Africa)—gender differences in poverty rates shrink sharply and re-emerge in a different direction. The poverty rate of older men is higher than the poverty rate for older women in more than half of the countries. On average, men ages 60 and older in Sub-Saharan Africa and South Asia are 3.1 percentage points poorer than their female counterparts (24.2 percent versus 21.1 percent), but there is wide variation across countries.

While the current approach to measuring poverty can provide insights into the gender and age dimensions of poverty, it falls short of accurately measuring welfare inequality within households. More work is needed to deepen our understanding. And while Chapter 5 of the Poverty and Shared Prosperity report takes some initial steps towards documenting and exploring new methods to address this shortcoming, to drill down to individual poverty measures, complementary poverty estimates are needed. However, this is not an easy challenge to address due to both data and methodological constraints.

Data deprivation[1] remains a critical problem in many countries—particularly low-income fragile and conflict affected states. Improving the availability, quality, and frequency of poverty data at the household level, particularly in Africa, is a first step to increase the availability of individual level data within households (and thus being able to assess differences by gender, age, or other characteristics).

In addition, a renewed focus on intra-household individual-level data collection and methodological research in nonmonetary dimensions, such as time use, violence, access to services and assets, and some socioemotional aspects is needed, and can be started in those countries where household level data is already available.

Learning more about the needs and constraints of poor people would facilitate a better understanding of the characteristics of poverty, and its intergenerational transmission, and help identify the interventions most appropriate for different types of households, and more importantly, for those individuals who live in them. This, in turn, can support more effective targeting of social protection and broader development programs.

-By Caren Grown and Carolina Sanchez-Paramo with Eliana Rubiano-Matulevich, Miriam Müller and Ana Maria Munoz-Boudet.


[1] Data deprivation occurs if a country conducts fewer than two household surveys in a 10-year period. According to the PSPR, the World Bank considered that 83 economies exhibited moderate or extreme data deprivation as of August 8, 2018. The World Bank pledged in 2015 to help the poorest countries improve the frequency of data collection to one household survey every three years. See http://www.worldbank.org/en/news/press-release/2015/10/15/world-bank-new-end-poverty-tool-surveys-in-poorest-countries

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