Gender unemployment gaps in the EU: blame the family
1 While the latter paper explores predominantly the gender employment gaps, it also shows that unionization raises the female relative to the male unemployment rate.
2 There is also Albanesi and Sahin (2013), who focus primarily on the USA but also include a short section on international evidence from 19 OECD countries (including a series of the West European countries). They suggest that convergence in the labor force participation of women and men played a key role in the reduction of gender unemployment gaps over time.
3 We provide evidence about 21 EU countries for the period of 2003–2007, compared with only 14 West European countries and the USA in the second half of the 1990s in AGM. As a collection of standardized national labor force surveys, the EU LFS data is superior to ECHP in terms of the sample size and representativeness. Section Replication of Azmat et al. 2006
in the Appendix provides information about our replication of the AGM results.
4 AGM conjecture that this may be one of the reasons for the lack of research interest in gender unemployment gaps as the majority of the international research had been carried out on data from Anglo-Saxon countries.
5 While gender unemployment gaps have decreased in some of the Benelux and Mediterranean countries, their ranking in the EU have remained stable over the last 10 years. See Fig. 13 in the Appendix.
6 The correlation between the gender unemployment gaps in the 21 EU countries in 2007 and 2013 is 0.85; the correlation between countries’ respective ranks when ordered by the size of the gap is 0.79. The absolute value of the change in the rank in 16 of the 21 countries is at most 4; the average absolute value of the change in the rank was 3.2.
7 The exact source of the data, the definition of the sample, and the data description is in Section EU LFS data in the Appendix.
8 The correlation between gender unemployment gaps (averaged over 2003–2007) among prime age individuals and among all individuals in the population in the 21 countries is 0.98, suggesting that our main conclusions should be robust to the choice of the sample.
9 As the data only permit us to construct participation profiles from cross-sectional data, the observed permanent withdrawal could be also driven by inter-cohort changes, namely, by the increase in female labor force participation. A simple version of a cohort analysis in Appendix Cohort analysis shows that while the profiles shift upward over time, their shape remains the same across cohorts.
10 A term coined by Altonji and Blank (1999).
11 We use standard but rather limited measures of human capital. The lack of more detailed information in the data is a cost of using a rich dataset in terms of the number of countries and the size and representativeness of the samples.
12 In other words, when comparing individuals, we condition on what is known as the potential work experience. This approach also allows us to control for potential cohort differences in the quality of education, which is likely to be important, in particular in the New-EU member states, where the analyzed workforce still contains those educated under the Communist regime and those educated after the transition to the market economy.
13 This is the most detailed categorization we can achieve given the information available in the data and given the need to ensure that each cell is sufficiently populated.
14 In Germany, the two gaps are not statistically significantly different from zero.
15 The coefficient of variation of the pre-market human capital-adjusted gender unemployment gaps is 1, compared to the corresponding measure of 1.3 for the unadjusted gaps.
16 We cannot distinguish between individuals who never had children and those whose children have already grown up. There are certainly both ex ante (Group 0) and ex post (Group 4) differences between career paths of individuals who plan to have children and those who do not, which we are forced to ignore and to interpret the results for the two endpoints of family life as averaged over the two types of individuals.
17 The almost zero gender differences in unemployment in these two groups may underestimate the gender unemployment gaps among the individuals who plan to have children and among those whose children are grown up, as they are combined with individuals who do not plan to have children (Group 0) and with individuals who never had children (Group 4), respectively. This would, however, require substantial gender unemployment gaps in favor of women among truly childless individuals (who form less than one third of the sample, according to demographic trends), which is unlikely.
18 Some countries such as Greece or Italy, however, struggle with high unemployment rates among the young (Group 0), irrespective of gender, which somewhat alters the typical shape of the female and male unemployment profiles.
19 The fact that men with families have better labor market outcomes than the ones without is well established. Previous research has focused primarily on the question whether this so-called family gap is driven by a selection of above-average-productivity men to marry or by the fact that family increases men’s effort at work and reduces their reservation wage (see, for example, Korenman and Neumark (1991); Ginther and Zavodny (2001)).
20 Unemployment rate is defined as the ratio of the number of the unemployed divided by the number of individuals in the labor force.
21 Consistent with the “family gap” phenomenon mentioned earlier, male labor force participation is always the highest in families with young children.
22 Formally, (frac {left (text {FLFP}_{3}-text {FLFP}_{1}right)}{left (text {FLFP}_{0}-text {FLFP}_{1}right)}0.50), where FLFPj
is the female labor force participation in group j.
23 Aggregate development in female and male labor force participation rates between 2000 and 2007 are depicted in Fig. 14 in the Appendix.
24 See Section Cohort analysis in the Appendix. Moreover, note that the inter-cohort changes also affect gender unemployment gaps as the behavior of the previous cohorts of women form a basis for the anticipated future labor force participation behavior of the current cohorts of young women, thus affecting both individual decisions and employers’ incentives to statistically discriminate against young women.
25 AGM mention only in a footnote the possibility of a positive selection effect on gender unemployment gaps as an analogy to the gender wage gap case emphasized in Olivetti and Petrongolo (2008). Bicakova (2014) formalizes the effect of selection on gender unemployment gaps and derives the corresponding Manski bounds.
26 These seven countries suffer from a high unemployment of youth, which is followed by a decline in both female and male measures of unemployment between the first two stages of family life. The two female unemployment measures, however, diverge from each other and from those of men in a similar way as in the rest of the sample.
27 The compositional effect describes the mechanical relationship between the size of the labor force and unemployment, given by the fact that unemployment rate is defined as a ratio of the unemployed and those in the labor force. See Bicakova (2014) for details.
28 This is not surprising, as only previously employed women (in contrast with their unemployed counterparts) meet the conditions for enjoying the benefits of a statutory family leave, both in terms of pay and job security.
29 A pattern analogous to the temporary leave participation profiles at the third stage of family life (Group 2) can be detected also among those permanent withdrawal countries, where some women come back to the labor force after their family leaves, but it is almost negligible.
30 The exact formula for the imputed length of the actual leave is the difference between the female labor force participation rates in Group 2 and Group 1 times 5 (times 60 when expressed in months).
31 Note that the compositional effect of the increase in the female labor force at the third stage of family life still corresponds to the case of negative selection as the increased average risk of unemployment of women returning to the labor force is still between zero and the unemployment rate among women who have stayed in the labor force. The change in the labor force due to the return of women from family leaves therefore increases the share of the unemployed among women but reduces the female unemployment rate.
32 Note that this rate is below 65% in all the Mediterranean permanent withdrawal countries except for Portugal, where a relatively high female participation rate is a consequence of a series of external shocks after WW2: colonial war, male emigration in the 1960s, and the 1976 revolution.
33 The correlation between female participation rates and gender unemployment gaps in Group 4 is ?0.66 and the correlation between female participation rates in Group 4 and the aggregate gender unemployment gaps is ?0.64, both statistically significant at the 10% significance level.
34 As the data only permit us to construct participation profiles from cross-sectional data, the observed permanent withdrawal could be also driven by inter-cohort changes, namely, by the increase in female labor force participation. A simple version of a cohort analysis in the Appendix Cohort analysis shows that while the profiles shift upward over time, their shape remains the same across cohorts.
35 See Sections Duration of the statutory family leaves and Discrimination and prejudice measures in the Appendix for the exact definitions and sources.
36 Note that we do not propose any explanatory factor for the variation in gender unemployment gaps among individuals without children younger than 15 in the temporary leave countries as there are almost no gaps in favor of men and not much variation to explain.
37 The gender discrimination indicator is missing for Hungary, leaving 40 data points for 20 countries.
38 Regression with full interactions among the two binary indicators (for the type of country and for the presence of children) and with the two explanatory factors (statutory duration of paid family leave and the perceived prevalence of gender discrimination) renders Adjusted R
2=0.75. Statistically insignificant variables are dropped in the preferred specification in the text.
39 Results for the unadjusted gaps are fairly similar: Identical specification explains 68% of the variation in unadjusted gender unemployment gaps. See Fig. 12 in the Appendix.
40 The gender unemployment gaps for individuals 25–54 years old were calculated from unemployment rates of 25–54 year olds with any level of education, extracted from Eurostat website http://ec.europa.eu/eurostat/web/lfs/data/database
on November 14, 2016, as part of the series “Unemployment rates by sex, age and educational attainment level (%).” The longest possible duration of statutory paid family leave (in weeks) available to mothers in a given country in a given year was extracted from the OECD Family Database Indicators web site at http://www.oecd.org/els/family/database.htm
on November 14, 2016, as part of the xls file “PF2.5 Trends in leave entitlements around childbirth.” Due to missing values, the data is an unbalanced panel of 17 EU countries (Austria, Belgium, Czech Republic, Denmark, Finland, Greece, Hungary, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Spain, Sweden, UK) for which more than 2 years of data are available over the period 1990–2015, with 402 country-year observations in total.
41 The full regression output is available from the author upon request.
42 The R
2 from a regression of the actual family leave duration on a constant and the duration of the statutory paid family leave of 0.60.
43 The actual family leaves in permanent withdrawal countries are short by construction as only very few women who leave the labor force after childbirth in Group 1 come back in Group 2.
44 See the Appendix for the additional data source and the exact definition of prejudice.
45 Note that gender differences in the incidence of permanent contracts among working prime age individuals exceed 3.5 p.p. in three of the Mediterranean countries as well as in Belgium.
46 It is interesting that the overrepresentation of women in the small share of part-time jobs that exist in Southern Europe is also involuntary in contrast to the other EU countries (Petrongolo 2004). In contrast with countries like the Netherlands where the widespread use of part-time jobs helps women combine work and family, the scarce part-time jobs in the Mediterranean countries seem to serve employers as tools for gender discrimination.
47 The exact reference is as follows: European Commission, Eurostat, the 2008 release of the anonymized European Union Labor Force Survey datasets for the reference years 2001–2007. We use the Spring data (from Quarter 2) only to ensure comparability across years. The Eurostat has no responsibility for the results and conclusions presented in this paper.
48 Children cannot be linked to their parents for all the countries and years in the data, but the presence of individuals younger than 15 years old in the typical family with only one or two prime age household members makes parenthood very likely. Note that information about children and their age is incomplete or missing in Ireland in the years 2003–2005 and in Italy for 2004. Whenever we disaggregate the data by the five stages of family life, these country-years are omitted from the analysis.
49 The statutory length as well as actual duration and occurrence of family leaves taken by fathers is negligible relative to the career breaks taken by women and has little relevance for the present analysis.
50 Namely, there are three cases in which we deviate from Figure 13 of The Council of Europe Family Policy Database: First, we take the duration of 36 months instead of 24 in France and Poland, where the earlier is for the second and subsequent child. Note also that the paid family leave in Poland is means-tested. Second, we take the duration of 24 months in Germany instead of 12 as the 12-month paid parental leave there can be increased to 24 months with proportional reduction of the amount paid.