I’d like to take a moment to give a brief report on some research that my colleagues Ajit Zacharias, Rania Antonopoulous, and I have been working on as a result of collaboration between the Levy Economics Institute and United Nations Development Programme (UNDP) Regional Service Centre for Latin America and the Caribbean (RSCLAC), particularly the Gender Practice, Poverty, and Millennium Development Goals (MDG) Areas. It addresses an identified need to expand our understanding of the links between income poverty and the time allocation of households, and between paid and unpaid work. Policies to combat poverty and promote equality require a deeper and more detailed understanding of the linkages between conditions of employment, unpaid household production, and existing arrangements of social provisioning—including social care provisioning.

Income poverty is customarily judged by the ability of individuals and households to gain access to some level of minimum income based on the premise that such access ensures the fulfilment of basic material needs.  However, this approach neglects to take into account the necessary (unpaid) household production requirements, without which basic needs cannot be fulfilled. Households differ in terms of their household production requirements and also in terms of the time their members have available to meet the requirements, so it should not be assumed that all households can meet these requirements. In order to promote gender equality, it is imperative to understand how labor force participation and earnings interact with household production responsibilities, as it is already well established that women contribute their time disproportionately to unpaid work.

We provide an analytical and empirical framework that includes unpaid household production work in the concept and measurement of poverty. Our approach shows that awareness of gender differences (especially in unpaid work) can bring to the forefront a ‘missing’ but key analytical category that allows for an improved measurement of poverty, and a deeper and more precise poverty classification of households and individuals. Future posts will delve more into policy ramifications of this work. In this post, I want to report on two of the headline results of our research.

Our alternative measure is a two-dimensional measure of income and time poverty, which we refer to as the Levy Institute Measure of Time and Income Poverty (LIMTIP). Time poverty, especially when coupled with income poverty, imposes hardships on the adults who are time-poor as well as their dependents, particularly the children, elderly, and sick. Income poverty alone does not convey enough useful information about their deprivation. Our measure can shed light on this phenomenon. My colleague Ajit Zacharias has published a working paper that lays out the theoretical underpinnings of the measure, and I have a working paper that outlines the methods used to construct the data sets we used to create the measure for Argentina, Chile, and Mexico.

The first important result of our project is that the size of the hidden poor, namely those with incomes above the official threshold but below the LIMTIP poverty line, is considerable in all three countries (Table 1). The LIMTIP income poverty rate for Argentina is 11.1 percent, compared to 6.2 percent for the official poverty line. For Chile, adjusting for time deficits increases the poverty rate to 17.8 percent from 10.9 percent for the official line. And in Mexico, the poverty rate increases to 50 percent from an already-high 41 percent. This implies that the households in hidden poverty in Argentina, Chile, and Mexico comprise, respectively, 5, 7, and 9 percent of all households.

The second important result of taking time deficits into account is that it dramatically alters our understanding of the depth of income poverty. The average LIMTIP income deficit (the time-adjusted poverty line minus household income) for poor households was 1.5 times higher than the official income deficit in Argentina and Chile and 1.3 times higher in Mexico. Thus, official poverty measures grossly understate the unmet income needs of the poor population. From a practical standpoint, this suggests that taking time deficits into account while formulating poverty alleviation programs will significantly shift both the coverage (including the ‘hidden poor’ in the target population) and the benefit levels (including the time-adjusted income deficits where appropriate).

Table 1 Official, LIMTIP, and ‘Hidden’ Poverty Rates and Number of Poor (thousands)