Unfortunately, there are important concerns about the coverage and accuracy of earnings data. Fewer countries collect earnings data than employment data, and some countries only collect earnings data for salaried workers. The profits of self-employed workers are notoriously difficult to measure accurately, and inaccurate measures of inflation can also introduce additional noise into earnings data.<sup>16</sup>

# **3.2 Methodology**

_Workers are divided into 16 cells, based on their gender, age, education and location of residence._ Only workers between age 15 and 64 are included in the sample. Age is broken into youth (age 15-24) and adults (age of 25-64), and education is grouped into the least educated (those that completed elementary or junior high) and more educated (secondary level and above). Average indicators are taken for each cell, country, and survey, weighted according to their sample weights. With the exception of education groups in the European countries, the dataset is defined consistently for all 17 countries.<sup>17</sup> _Labor market activity and type of job indicators are considered both as a ratio of the population and of the labor force._ Indicators of interest include the labor market activities over population (employment, unemployment, nonparticipation ratios), sector and status over labor force (share of each sector and status among labor force), and earnings and hours information for workers (earnings, wages, and hours). First we look at trends in employment, unemployment, and non-participation rates as a share of the population. Population trends may be relevant for policies, such as universal transfers, that are delivered outside the labor market. To better understand changes among potential workers and to inform the design of labor market programs, we then examine labor market outcomes for the active labor force. The focus is on shifts in sectors, employment status, and unemployment. Finally, in countries where the data are available, we report changes in average earnings, wages, and hours of work.

_The focus is on how disruptions in labor market trends during the crisis varied for different group of workers._ A simple way of looking at the crisis impact on various groups of workers is to compare pre and post outcomes for each group. However, this comparison may be misleading if baseline trends and initial labor market performance vary across groups. Even before the crisis, socioeconomic changes in each country were affecting different groups in different ways. For example, in many countries, employment rates were growing faster for women than men, due to trends in educational achievement and cultural norms that encourage greater female employment. To take this into account, the analysis examines how each group’s trend changed, relative to their pre-crisis trend. In other words, the key indicator is the rate at which changes in each indicator slowed down or sped up, compared across groups.

> 16 Comparing changes in urban and rural earnings is also problematic in countries that only collect price indices in urban areas.

> 17 In ECA countries, the least educated group is those with secondary education or below, as their education level is higher than other regions.

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