- b) The “other urban areas” have poverty indicators equivalent to, or worse than, those of rural areas, including in terms of access and quality (reliability) of infrastructure.

- c) Although formal access to infrastructure and energy (e.g. utility connections) remains higher in urban areas than rural in most cases, many households, especially in secondary cities, are “infrastructure-poor” because of unreliable and deteriorated services, and these households are hidden by studies that do not examine actual quality.  To fully appreciate the welfare implications of inadequate infrastructure services, it is important to take account of the different housing circumstances and options available to urban as compared to rural households.

- d) Income and infrastructure inequality are generally higher in urban than in rural areas, and highest in capital cities.  Inequality may have significance for social perceptions of welfare.

It must be stressed, however, that there is no average ECA country and that the economies vary widely across all issues, although there are distinct similarities within the sub-regions (the Balkans, Caucasus, Central Asia, EU Accession, and Slavic countries).

The remainder of this report is organized as follows. Section 2 describes the data used for the empirical analysis and discusses some measurement issues. Section 3 provides an overview of the economic and demographic situation in Europe and Central Asia. The extent and nature of urban poverty in the region is then investigated in Section 4.

# **2. Measurement and Data Issues**

# **2.1. Data sources**

The sources of primary data were sample surveys of households within transition economies of the ECA Region. In most cases the surveys are administered by the statistical agencies within each country with technical assistance from donor organizations. The sophistication and usefulness of the household surveys undertaken in the Region have improved considerably during the 1989 - 2003 period. Most countries have a program of annual Household Budget Surveys (HBS). However the data available from this source were of poor quality until the sampling frameworks were improved in the mid to late 1990s. The HBS approach does not always allow for the calculation of welfare aggregates based on consumption so expenditures or income are used instead. Large flows in population within and among countries in the region in the early transition years also created sampling uncertainties. The most recent surveys have benefited from completion of new national censuses from 1999-2003.

This study used surveys from 20 countries in the ECA region (Table 2.1). The countries that were not included in the study include five of the EU candidate countries (the Czech Republic, Estonia, Latvia, Slovakia, Slovenia), as well as Croatia, Macedonia, Montenegro (although the more populous Serbia was included) and Ukraine. In the case of the first wave EU accession countries, data sets were not easily available and these countries were seen to be of lower priority in terms of future Bank-financed development work. Datasets of sufficient quality were not available for Croatia, Macedonia and Montenegro at the time the data were being assembled. Work on the Ukrainian dataset was not sufficiently advanced to determine the welfare (consumption) aggregate to be used. The final set of surveys that was used to provide the data used in this report is listed below. Annex 1 Measurement and Data Issues, provides more background and detail on the material presented in this chapter.

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