Academic journal article Journal of Economic Issues

Explaining the Gender Poverty Gap in Developed and Transitional Economies

Academic journal article Journal of Economic Issues

Explaining the Gender Poverty Gap in Developed and Transitional Economies

Article excerpt

As economies throughout the world experience large and wrenching changes, poverty has increasingly become a problem in country after country. This is true regardless of whether these changes result from globalization, the economic transition from socialism to capitalism, increasing marketization and privatization, or some other major economic transformation (Aslanbeigui, Pressman, Summerfield 1994; Funk and Mueller 1993; Moghadam 1996).

A concomitant, disturbing aspect of rising poverty throughout the world is that poverty has increasingly become feminized--women are much more likely than men to be poor. This phenomenon was first noticed in the United States (Pearce 1978, 1989; Pressman 1988), but more recently the problem of the feminization of poverty has become an international concern as well (Casper, McLanahan, and Garfinkel 1994; Pressman 1998; Wright 1995).

This article employs the Luxembourg Income Study (LIS) to compare poverty rates for female-headed households (FHHs) with poverty rates for other households in a number of developed and transitional economies. It then seeks to explain why, in some countries, female-headed households are so much more likely to be poor compared with other families.

The next two sections, respectively, describe the LIS and discuss some of the problems encountered in measuring poverty. The paper then computes poverty rates in individual countries for female-headed households and for all other households using the LIS database. Given the problems associated with measuring poverty, I present several estimates of poverty for both types of household. Two sections then look at a couple of theoretical explanations for the gender poverty gap--human capital theory and a Keynesian approach that emphasizes the importance of fiscal policy as an antipoverty tool. The last section summarizes the main findings and draws some policy conclusions.

The Luxembourg In come Study

The Luxembourg Income Study began in April 1983 when the government of Luxembourg agreed to develop, and make available to social scientists, an international microdata set containing a large number of income and socio-demographic variables. Until that time, most cross-national studies of income distribution and poverty suffered because the national data that they used would define key terms differently. Most importantly, the notion of income itself was defined and measured differently in different countries.

One goal in creating the LIS database was to employ common definitions and concepts so that variables are measured according to uniform standards across countries. As a result, researchers can be confident that the coss-national income data that they are analyzing, and the socio-economic variables that they are examining, have been made as comparable as possible.

By 2001, the LIS contained information on twenty-five nations-Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Poland, Russia, the Slovak Republic, Spain, Sweden, Switzerland, Taiwan, the United Kingdom, and the United States. Negotiations are currently under way with Japan and several other countries to have their income data added to the US. Data for each country was originally derived from national household surveys similar to the US Current Population Reports, or (in a few cases) from tax returns filed with the national revenue service.

Currently four waves of data are available for individual countries. Wave I contains datasets for countries for one particular year in the late 1970s or early 1980s. Wave II contains datasets for some year in the mid 1980s. Wave III contains datasets for the late 1980s and early 1990s. Wave IV (currently in the process of being "Lissified" and put online) contains country datasets for the mid 1990s. Finally, historical data from the late 1960s and/or early and mid 1970s are available for a few countries. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed


An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.