MICS2 - Assessing the economic status of households

Purpose

The purpose of this note is to recommend questions that should be used in the UNICEF supported end-decade Multiple Indicator Cluster Surveys (MICS2) to assess the economic status of households.l

Background

The interest here is in deriving a measure of economic status by household, when there is an absence of income or consumption data. A measure of economic status enables comparisons to be made between poor and non-poor in terms of health and education status, access to services, knowledge of preventive measures, attitudes, practices and many other aspects of social status and functioning. With a division of survey populations into economic quintiles, a more extensive analysis can be carried out of correlations between economic status, social status and, using repeated surveys, obtain a more extensive assessment of the impact on children of programmes in the health, education and other sectors.

Many surveys attempt to tackle the challenge of assessing the economic status of households when income or consumption data are not available, usually by including questions on type of house construction, whether the household has a radio or bicycle and so on. However, practical analysis and use of these data has been sparse and generally localized to a particular survey or country. html ht ht ht 

Recent work by the World Bank and Macro International (via the Demographic and Health Surveys [DHS]), has shown what can be done for the many countries in which DHS has been implemented. The DHS survey instrument lacks questions on household income or consumption expenditures, but an asset or "wealth" index has been constructed from: whether any member owns a radio, television, refrigerator, bicycle, motorcycle or car; whether electricity is used, the source of drinking water, the type of sanitation, how many rooms, and the type of materials used in dwelling construction. html ht ht ht ht 

The DHS wealth measure

The methodology for aggregating the various asset ownerships and housing characteristics variables is based on the method of principal components. This methodology is described in more detail in the Filmer and Pritchett (1998a) article, which uses State level survey data from India. The article describes the asset index as robust, producing internally coherent results, and providing a close correspondence with State Domestic Product and poverty rate data. It also reports on how the index was validated using data from Indonesia, Pakistan and Nepal that contained both consumption expenditures and asset ownership information.

A subsequent article, Filmer and Pritchett (1999), applied the methodology to the analysis of inequalities in education. An earlier World Bank working paper version of this article may be easier to obtain (Filmer and Pritchett [1998b]).

Macro International is producing information sheets for DHS showing poor-nonpoor differences in a variety of health, nutrition and population outcomes, and in access to and use of services. A selection from these sheets showing the variation of selected demographic and health indicators by wealth index quintiles is provided here. The index is being used by the World Bank to monitor the socioeconomic impact of programmes and reforms in the health sector.

The DHS has many commonalities with the end-decade MICS, and such an index could be derived for MICS provided the appropriate questions are included. While the recent work on the wealth index is a substantial development, it has to be viewed as a work in progress. One point of note is that the index uses only the first principal component which, over the 35 DHS surveys used in the Filmer and Pritchett (1999) article, accounts for about 25% of the overall variance.

MICS recommendation

Based on the World Bank and Macro International work on the wealth index described above, the World Bank recommended to UNICEF that MICS include the following question groups. html ht ht ht ht ht ht ht

Table 1: Suggested questions to use in index

In subsequent discussions with the World Bank, under the pressure to limit additional questions, it was noted that the Filmer and Pritchett 1999 article used only question groups A to F to calculate the index across 35 countries. The Bank agreed that question groups G and H might therefore be left out of MICS.

At the same time researchers at the Bank observed that the ideal variable for the index is one that varies substantially across the population, and does so in relation to a household's economic status. In this context, the type of cooking fuel performed well in the countries where it was available from DHS, and therefore would be useful to include in MICS. A further reason for including cooking fuel is that if electricity is not available, as is common in many rural areas in poorer countries, then the households usually do not have televisions or refrigerators, thus reducing the discriminatory power of the index questions in table 1. Cooking fuel is expected to help in such cases

The Bank also suggested that a finer breakdown of the material used for the dwelling floor might yield additional insights in some countries.

Drawing primarily from these discussions, the recommended core set of questions for calculating a household wealth index in MICS are given in Table 2.

Table 2: Recommended questions to use in index

The specific questions recommended can be found in the appendix.

For those countries including these questions in their MICS, support for calculating a country specific wealth index will be provided by NYHQ.

Conclusion

Deriving a wealth index from MICS is feasible if a very few additional questions are included, as listed in table 2 above, with the specific questions documented in the appendix. To the extent possible in MICS it would be useful to allow a very little additional flexibility such that where a particular variable not included in table 2 reflects household resources particularly well in one country, it might be added to the MICS in that country in order to provide a more powerful index.

References

Filmer D. and Pritchett L., Estimating wealth effects without expenditure data -- or tears: An application to educational enrolments in States of India, World Bank Policy Research Working Paper No. 1994, Washington, 1998a.

Filmer D. and Pritchett L., The effect of household wealth on educational attainment: Evidence from 35 countries, Population and Development Review, vol.25, no.1, pages 85-120, March 1999.

Filmer D. and Pritchett L., The effect of household wealth on educational attainment around the world: Demographic and Health Survey evidence, World Bank Policy Research Working Paper No. 1980, Washington, 1998b.

DHS questionnaire - reference to be inserted