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

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