Jobs for Immigrants (Vol. 2)

Abstract

The OECD is a unique forum where the governments of 30 democracies work together to address the economic, social and environmental challenges of globalisation. The OECD is also at the forefront of efforts to understand and to help governments respond to new developments and concerns, such as corporate governance, the information economy and the challenges of an ageing population. The Organisation provides a setting where governments can compare policy experiences, seek answers to common problems, identify good practice and work to co-ordinate domestic and international policies.

Labor Force Participation of Immigrant Women in the Netherlands: Do Traditional Partners Hold Them Back?

“…As the dependent variable FLFP is binary and the interest of this study is in comparing coefficients across groups and models, the statistical analysis has to account for the scaling problem (cf. Mood 2010). The scaling problem refers to the fact that logistic regression estimates are implicitly rescaled based on a fixed residual variance of 3.29.…”

“…Hence, unless all factors that might cause differences in unobserved heterogeneity in the dependent variable between respondents are accounted for, coefficients may not be comparable across groups and models (Karlson, Holm, and Breen 2012). 5 We therefore followed Mood's (2010) suggestion and, using the margins command in stata, estimated AME, which are calculated by averaging effects 5 Potential sources of scaling bias in our analysis are differences in the residual variance across ethnic groups. It is possible that including mediating variables between ethnicity and FLFP, such as gender role attitudes, affects the residual variance differently across ethnic groups.…”

“…over all observations based on an initially estimated equation (in our case logit regressions). This makes them relatively unaffected by unaccounted explanatory factors unrelated to the already included independent variables (Mood 2010). Moreover, AME are intuitive to interpret as they express the change in the expected value (or the expected probability) of the dependent variable as an explanatory variable increases by one unit.…”

“…To test H3 and H4 about the moderating role of women's and men's gender role attitudes on the effect of the partner's labor market resources, we included two-way interaction effects between all indicators of men's labor market resources (male partner higher educated, male partner lower educated, male partner unemployed, male partner disabled, student, or retired, income of male partner) and women's and men's gender role attitudes. To get a direct test for the interaction coefficients, we estimate an OLS regression, as linear models come usually relatively close to the estimates of AME (Mood 2010). 6 The results of this estimation, not shown here, support H3 that the effect of a higher educated male partner on FLFP is more negative the more traditional gender role attitudes women endorse (b = À0.077; SE = 0.04; p two-sided = 0.064).…”