Parental ethnic identity and child test scores

We examine the relationship between parental ethnic identity and the test scores of ethnic minority children. We use standard survey measures of the strength of parental identity alongside validated cognitive test scores in a rich British cohort study. We show that children whose mothers report either an adoption or an active rejection of the majority identity tend to score lower in cognitive tests at age 7, compared to those children whose mothers report neutral feelings about the majority identity. We find no consistent differences in test scores according to mothers’ minority identity. Our findings provide no support for education or citizenship policies which promote the adoption of the majority identity or discourage the maintenance of separate identities in ethnic minority communities

Convergence or Divergence? Immigrant Wage Assimilation Patterns in Germany

Using a rich German panel data set, I estimate wage assimilation patterns for immigrants in Germany. This study contributes to the literature by performing separate estimations by skill groups and controlling for a wide range of socio-economic background variables. It aims to answer the question whether Germany can be considered an attractive host country from an immigrant's perspective. Comparisons with similar natives reveal that immigrants' experience earnings profiles are flatter on average, although clear differences show up among skill groups. The effect of time spent in the host country is significantly positive for all skill groups and thus partly offsetting the diverging trend in the experience earnings profiles. Still, wage differences between natives and immigrants remain. They are particularly noticeable for highly skilled immigrants, the group needed most in Germany's skill intensive labor market. Separate estimations for immigrant subgroups confirm the general validity of the results

Identification of random resource shares in collective households without preference similarity restrictions

Resource shares, defined as the fraction of total household spending going to each person in a household, are important for assessing individual material well-being, inequality and poverty. They are difficult to identify because consumption is measured typically at the household level, and many goods are jointly consumed, so that individual-level consumption in multi-person households is not directly observed. We consider random resource shares, which vary across observationally identical households. We provide theorems that identify the distribution of random resource shares across households, including children's shares. We also provide a new method of identifying the level of fixed or random resource shares that does not require previously needed preference similarity restrictions or marriage market assumptions. Our results can be applied to data with or without price variation. We apply our results to households in Malawi, estimating the distributions of child and female poverty across households

Testing and imposing Slutsky symmetry in nonparametric demand systems

Maximization of utility implies that consumer demand systems have a Slutsky matrix which is everywhere symmetric. However, previous non- and semi-parametric approaches to the estimation of consumer demand systems do not give estimators that are restricted to satisfy this condition, nor do they offer powerful tests of this restriction. We use nonparametric modeling to test and impose Slutsky symmetry in a system of expenditure share equations over prices and expenditure. In this context, Slutsky symmetry is a set of nonlinear cross-equation restrictions on levels and derivatives of consumer demand equations. The key insight is that due to the differing convergence rates of levels and derivatives and due to the fact that the symmetry restrictions are linear in derivatives, both the test and the symmetry restricted estimator behave asymptotically as if these restrictions were (locally) linear. We establish large and finite sample properties of our methods, and show that our test has advantages over the only other comparable test. All methods we propose are implemented with Canadian micro-data. We find that our nonparametric analysis yields statistically significantly and qualitatively different results from traditional parametric estimators and tests.Demand system Slutsky symmetry Rationality Nonparametric regression Nonparametric testing