Abstract
This paper looks behind the standard, publicly available labor force statistics relied upon in most studies of transition economy labor markets. We analyse microdata on detailed labor force survey (LFS) responses in Russia, Romania, and Estonia to measure nonstandard, boundary forms and alternative definitions of employment and unemployment. Our calculations show that measured rates are quite sensitive to definition, particularly in the treatment of household production (subsistence agriculture), unpaid family helpers, and discouraged workers, while the categories of part-time work and other forms of marginal attachment are still relatively unimportant. We find that tweaking the official definitions in apparently minor ways can produce alternative employment rates that are sharply higher in Russia but much lower in Romania and slightly lower in Estonia, and alternative unemployment rates that are sharply higher in Romania and moderately higher in Estonia and Russia.
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Notes
See, for example, Layard and Richter (1995) on employment and wage adjustment, and Boeri and Terrell (2002) on the effects of alternative levels of unemployment benefits.
This definition follows Kalleberg et al. (2000), who discuss the characteristics of standard and nonstandard employment relations in the United States.
Earle and Sakova (2000) study the self-employed in six transition economies, differentiating own-account workers from employers.
Results for other years are available on request.
The methodological issues are discussed at length in CEU Labor Project (2003), which provides a detailed comparison of the Romanian questionnaire design with ILO recommendations and with the labor force survey in the United States, the Current Population Survey.
There is some question whether the sample weights became increasingly biased between the decennial censuses of 1992 and 2002. It is possible that the officially reported labor force figures, as well as the 2001 numbers reported in this paper, will be – or should be – revised on the basis of the 2002 census.
For a description of the RLFS, see Goskomstat (2002).
Persons serving in the military are also included in reported employment, as are persons who performed various kinds of occasional or exceptional work for at least 1 h.
In the United States, the issue is trivial, as unpaid family workers account for only about 0.1 per cent of all employment. In Romania, as we shall show, the share of this group is much larger.
The GKS changed the wording of the relevant RLFS question (see GKS, 2002), which may have contributed to the increase in reported temporary employment. For a thorough analysis of temporary employment in Russia, see Gimpelson (2003).
An additional category that could be considered underemployed consists of workers with wage arrears, which were quite prevalent at least in Russia during the time period we study. See, for instance, Lehmann et al. (1999), Gimpelson and Lippoldt (2001) and Earle and Sabirianova (2002). We cannot measure these with our labor force survey data in the three countries, however.
One problem with this measurement could be seasonal fluctuations. Part-time work is likely to be more common in the summer months, making it difficult to compare first-quarter figures in Romania and fourth-quarter figures in Russia to second-quarter figures in Estonia.
We do not consider this category in our computations of alternative unemployment rates below, but clearly if we did so, for instance adding half of them to the unemployed pool, the rate would rise by about 1.5 percentage points.
These two categories are closely related because of the problem of classifying multiple family members working without pay (ie, not receiving a regular wage) in a family business; one practice would be to designate them all as own-account, and another would be to designate one member of the family as own-account and the rest as unpaid helpers (eg, ILO, 1990, 171). How this is applied in practice depends on specific family situations and interviewers’ interpretations.
The relevant Estonian LFS questions are worded in such a way that agricultural own-account workers and unpaid family helper categories are likely to include only those involved in production for sale.
For regulatory quality in 2000, Estonia received a score of 1.33, Romania −0.27 and Russia −1.58. The same order applies for rule of law (0.71, −0.22, and −0.87) and for control of corruption (0.78, −0.45, and −1.02) (Kaufmann et al., 2005).
Indeed, as the ILO database for 2001 documents, agriculture accounted for 6.5 per cent of employment in Estonia, 10.6 per cent in Russia, and 42 per cent in Romania.
The exception to use of ILO criteria is Estonia in 1994, where information on availability was not requested on the retrospective survey in 1995. The ‘partially relaxed’ measure is not available in Estonia in either year.
The evidence is less clear in Eastern Europe; see Lehmann et al. (2005) for Estonia.
These numbers are not available for Estonia and Russia for 1994.
These figures exclude job losers not searching but expecting recall in Estonia in both years and in Russia in 2001, because this information is unavailable.
See Earle (1997) for an initial analysis of these questions using Romanian data from the mid-1990s.
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Acknowledgements
This research was supported by a grant from the US Agency for International Development's SEGIR EP Contract No. PCE-I-00-00-00014-00, reference Russia, task order no. 803, ‘Improvement of Economic Policy Through Think Tank Partnership Project.’ We thank Randy Filer, Ted Gerber, Tatyana Gorbacheva, Susan Houseman, Jeff Miller, Catalin Pauna, Zinaida Ryzhikova, Nina Vishnevskaya, Valery Yakubovich, and participants at workshops in Bucharest, Kalamazoo, and Moscow for valuable advice, help, and comments. They are particularly grateful to Ben Jones and Joanne Lowery for careful editing and to Joanne also for organizing the Partnership Workshop in August 2003.
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Brown, J., Earle, J., Gimpelson, V. et al. Nonstandard Forms and Measures of Employment and Unemployment in Transition: A Comparative Study of Estonia, Romania, and Russia. Comp Econ Stud 48, 435–457 (2006). https://doi.org/10.1057/palgrave.ces.8100181
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DOI: https://doi.org/10.1057/palgrave.ces.8100181