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Statistics on hours of work include: average hours actually worked, average hours paid for, and “marginal number of weekly hours” which covers persons in employment whose “usual hours of work” are below a threshold.
For more details, see notes at http://laborsta.ilo.org/applv8/data/c4e.htmland KILM (1999) p. 146. Nearly a decade ago, Behrman and Rosenzweig (1994, p. 167) examined education and employment data from around the world and reported: There is a serious problem in comparability in aggregate employment statistics that may affect inferences about the size of and trends in the labor force and its productivity . . . data gaps are systematically related to the level of a country’s development. In their article, Behrman and Rosenzweig noted that the ILO, which was (and still is) the primary source of such aggregate data had acknowledged that its aggregate data were not necessarily comparable across countries or over time (International Labour Organization, 1991, p. xi). These problems reflect the fact that the ILO did not (and still does not) collect primary data in the field. Instead, the ILO compiles global databases from data provided by various nations’ National Statistical Offices (NSOs). Although the ILO develops guidelines, provides technical assistance, and holds regular meetings with these offices, it has only limited influence on their data collection methods. At the most basic level, NSOs define “employed” or “economically active” differently, varying in the extent to which they include workers in family enterprises, the time period required to be considered employed, and the ages of workers included. Today, the lack of accurate, comparable aggregate data on wages, hours, and health and safety continues. Given these data problems, an ideal assessment of compliance with acceptable conditions of work would use country-level data sources to inform the ACW indicators. However, the assessor would need to carefully evaluate each national data source, selecting only those that used similar definitions and survey methods if the data were to be used to compare compliance across countries. The data may or may not be comparable within countries over time, and are often not comparable across countries. Although these data problems pose a challenge to accurately measuring wages, hours, and health and safety conditions in developing countries at any given time, measuring improvement or deterioration in compliance with acceptable conditions of work is even more difficult because definitions, sampling frames, and questions often change over time. Thus, an assessor who wants to determine whether a country is making progress or going backward in wages, hours, and working conditions must carefully examine the sources of data to determine whether they are comparable over time. Only a few developing countries—including Taiwan, Indonesia, Costa Rica, and Brazil— obtain data on wages and conditions of work through household surveys using consistent questions and a consistent sampling frame overtime (Fields and Bagg, 2003).
Literature cited:
Behrman, J.R., and Rosenzweig, M.R. (1994). Caveat emptor: Cross-country data on education and the labor force. Journal of Development Economics , 44.
Fields, G., and Bagg, W.S. (2003). Long-term economic mobility and the private sector in developing countries. In G.S. Fields and G.P. Pfeffermann (Eds.), Pathways out of poverty. Boston: Kluwer.
International Labour Organization. (1991). Yearbook of labour statistics. Geneva: International Labour Office.
National Research Council (2004), Chapter 8.
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