income inequality. Section III focuses on the dynamics of poverty and its correlates, with emphasis on the distribution of welfare across geographical regions and socioeconomic groups. Section IV investigates the determinants of poverty using probit analysis. Section V provides concluding remarks and policy implications.

# **II. Dynamics of Income Inequality in Latvia**

This Section provides a trend analysis of income inequality and poverty using two Household Budget Surveys carried out by the Latvian Central Statistics Bureau in 1997 and 2000. These surveys are very similar in the scope of data collection, sampling design and coverage. They are nationally representative and the sample selection uses a multi-stage stratified random sampling in both designs. The questionnaires are standardized and collect individual and household level information on a relatively large sample: 7,881 households in the first round, and about 3,846 in the second. This relatively large coverage allows a spatial analysis of welfare and income inequality, which reflects the country’s five main geographic regions and key socioeconomic groups.<sup>4</sup> The similarity in the sampling and standardized questionnaire design also facilitates welfare inferences over time.

The Latvian Household Budget Survey data is of excellent quality, a necessary attribute for robust estimation and welfare inference over time. In particular, these surveys collect exhaustive information on non money metric and money metric variables, and especially household expenditures and income, including state and local transfers, income from own property (real estate, interests and dividends), and unemployment benefits and compensation.<sup>5</sup> The quality of the data is partly illustrated by the consistency in the trend of welfare estimates from income and expenditure aggregates.<sup>6</sup> Table 1 provides point estimates for measures of central tendency, variance and income inequality over the two reference periods. These statistics are based on the monthly household per capita expenditures estimated at the national and regional levels. Table 1 in annex 1 provides similar estimates for measures of central tendency, variance and income inequality over the same reference periods, based on the monthly household per capita income.

At 74 lats, the mean per capita expenditure is slightly above the nationally accepted minimum wage established at 70 lats. This measure of central tendency, along with the median per capita household expenditure aggregate, is consistently higher than the incomebased estimates, reflecting the relatively low nonsampling errors.<sup>7</sup> Though these surveys

> 4 The main geographic regions include the Riga region, Kurzeme (Western region), Vidzeme (Central region), Zemgale (Northern region), and Latgale (Eastern region). Similarly, there are 5 key socioeconomic groups, including Wage and Salary Earners, Entrepreneurs and Self-employed, Farmers, Pensioners, and Other Households.

> 5 The good quality of the data is also tributary of the nature of the survey: aggregate distributions of household expenditure from more comprehensive surveys such as Household Budget Surveys, are also subject to low bias and non sampling errors because the relatively high frequency of visits to households increases recall and reduces underreporting.

> 6 The quality of income data is reminiscent of the socialist era, where most income sources were under the direct control of the state, and data collection agencies could verify reported income at the sources. The implicit control system limited the prospects for under-reporting, which is likely to grow with the rise of private sector income.

> 7 Historically, this bias has been considerably higher in Sub-Saharan African countries, particularly when income data is collected on a single visit to households in the context of the implementation of Household Priority Surveys,  for instance.

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