52. As we pointed out above, we will consider these mechanisms as a guide for the empirical analysis. The next couple of sections explain how the transition from these hypothetical examples to the real data will work, and what are the different strategies that we have in mind in order to test the 'predictions' generated by such examples.

# E. **DATA**

53. The empirical analysis combines two different data sources, the Unemployment Registry (National Labor Office) and the Labor Force Survey (Slovak Statistical Office). The first data source contains very detailed information on unemployment duration and unemployment insurance payments and will therefore be used to assess the effect that such payments may have on the behavior of unemployed workers. However, there are certain drawbacks associated with the use of these data. First, a registered worker is not necessarily an unemployed worker according to ILO standards (i.e. did not perform paid work for more than an hour during the week prior to the interview, is looking for a job, and is able to start working within the next two weeks), and it is impossible to determine who is actually 'unemployed' using such criteria because no information is collected neither on search behavior nor on availability. Second, the Unemployment Registry contains no information on social assistance/support payments or on household-level variables, although both are potentially very relevant for out analysis. Fortunately, the Labor Force Survey provides fairly rich _information_ on _both_ issues, so we will this data both to expand the scope _of_ the analysis, and to check on the robustness of the results obtained when using the Unemployment Registry.

# **Unemployment Registry data**

54. We use administrative data from the Unemployment Registry covering all districts in the Slovak Republic for 1990-2000. These data contain information on the beginning and the ending dates of the unemployment spell, as well as on the quantity and duration of unemployment insurance benefits when received. Since information is organized by individual rather than by spell, the records only contain complete demographic information on the last unemployment spell of each unemployed individual. However, we are able to construct individual histories using archival data on past unemployment spells, and adjusting the necessary demographic variables accordingly.

_55._ The sample contains 30,714 spells corresponding to 18,141 individuals. The number of spells per individual ranges from 1 to 5, although more than 50 percent of all individuals in the sample experience only one unemployment spell (Table VI). The duration of such spells also varies substantially, with 36 percent lasting less than 3 months and 25 percent lasting for more than a year (Table VII).

56. Individuals in the sample are fairly young, with 60 percent (35 percent) of them under 35 (25) at the beginning of the corresponding spell"<sup>4</sup> (Table VIII). As a consequence, almost a third of the sample has no previous work experience. Almost half of the workers possess

> 14 All summary statistics are reported at the beginning of the corresponding unemployment spell. Gender, marital status and education do not vary across spells for the same individual, while age, region and work experience (or the lack of) do.

15