The Effect of Preschool Attendance on Secondary School Track Choice in Germany - Evidence from Siblings

We study the effect of preschool attendance on secondary school track choice in Germany which is a crucial outcome that largely predicts educational pathways of children. Using data from the German Socio-Economic Panel, multivariate models show a significant positive association between years of preschool attendance and a child’s probability of attending the highest school track, that is, German Gymnasium. Including family fixed effects in a sibling model, our estimates become considerablysmaller and are no longer significant, indicating an upward bias in multivariate models. Accounting for several sibling-specific covariates, such as measures of innate abilityand social skills, does not change this result. The low intensity of Germany’s centerbased preschool system might be a reason for the zero effects.Preschool education, sibling models, GSOEP

Campaign Management under Approval-Driven Voting Rules

Approval-like voting rules, such as Sincere-Strategy Preference-Based Approval voting (SP-AV), the Bucklin rule (an adaptive variant of $k$-Approval voting), and the Fallback rule (an adaptive variant of SP-AV) have many desirable properties: for example, they are easy to understand and encourage the candidates to choose electoral platforms that have a broad appeal. In this paper, we investigate both classic and parameterized computational complexity of electoral campaign management under such rules. We focus on two methods that can be used to promote a given candidate: asking voters to move this candidate upwards in their preference order or asking them to change the number of candidates they approve of. We show that finding an optimal campaign management strategy of the first type is easy for both Bucklin and Fallback. In contrast, the second method is computationally hard even if the degree to which we need to affect the votes is small. Nevertheless, we identify a large class of scenarios that admit fixed-parameter tractable algorithms.Comment: 34 pages, 1 figur

Regional Origins of Employment Volatility: Evidence from German States

Openness for trade can have positive welfare effects in terms of higher growth. But increased openness may also increase uncertainty through a higher volatility of employment. We use regional data from Germany to test whether openness for trade has an impact on volatility. We find a downward trend in the unconditional volatility of employment, which has been interrupted by the re-unification period. Patterns are similar to those for output volatility. The conditional volatility of employment, measuring idiosyncratic developments across states, in contrast, has remained fairly unchanged. In contrast to evidence for the US, we do not find evidence for a significant link between employment volatility and trade openness.employment volatility, trade openness, regional labour markets

Econometric Methods for Causal Evaluation of Education Policies and Practices: A Non-Technical Guide

Education policy-makers and practitioners want to know which policies and practices can best achieve their goals. But research that can inform evidence-based policy often requires complex methods to distinguish causation from accidental association. Avoiding econometric jargon and technical detail, this paper explains the main idea and intuition of leading empirical strategies devised to identify causal impacts and illustrates their use with real-world examples. It covers six evaluation methods: controlled experiments, lotteries of oversubscribed programs, instrumental variables, regression discontinuities, differences-indifferences, and panel-data techniques. Illustrating applications include evaluations of early-childhood interventions, voucher lotteries, funding programs for disadvantaged, and compulsory-school and tracking reforms.causal effects, education, policy evaluation, non-technical guide

Econometric Methods for Causal Evaluation of Education Policies and Practices: A Non-Technical Guide

Education policy-makers and practitioners want to know which policies and practices can best achieve their goals. But research that can inform evidence-based policy often requires complex methods to distinguish causation from accidental association. Avoiding econometric jargon and technical detail, this paper explains the main idea and intuition of leading empirical strategies devised to identify causal impacts and illustrates their use with real-world examples. It covers six evaluation methods: controlled experiments, lotteries of oversubscribed programs, instrumental variables, regression discontinuities, differences-in-differences, and panel-data techniques. Illustrating applications include evaluations of early-childhood interventions, voucher lotteries, funding programs for disadvantaged, and compulsory-school and tracking reforms.policy evaluation, education, causal effects, non-technical guide

Recognizing when a preference system is close to admitting a master list

A preference system $\mathcal{I}$ is an undirected graph where vertices have preferences over their neighbors, and $\mathcal{I}$ admits a master list if all preferences can be derived from a single ordering over all vertices. We study the problem of deciding whether a given preference system $\mathcal{I}$ is close to admitting a master list based on three different distance measures. We determine the computational complexity of the following questions: can $\mathcal{I}$ be modified by (i) $k$ swaps in the preferences, (ii) $k$ edge deletions, or (iii) $k$ vertex deletions so that the resulting instance admits a master list? We investigate these problems in detail from the viewpoint of parameterized complexity and of approximation. We also present two applications related to stable and popular matchings.Comment: 30 pages, 1 figure. Reason for update: additional discussion on the Kemeny Score problem, and correction of some typo

Age at Preschool Entrance and Noncognitive Skills before School - An Instrumental Variable Approach

We estimate the effect of age at preschool entrance on crucial noncognitive skills in theyear before school starts. Using an instrumental variable approach and exploiting cut-offdates for the time at preschool entrance we find that children entering preschool earlierin life have better noncognitive skills in terms of being more assertive and being moreable to form friendships. Hence, our results offer general empirical evidence for thenon-linearity in the skill formation process. Moreover they show that entering preschoolat an early age is an important prerequisite for the development of social schoolreadiness.Preschool; noncognitive skills; instrumental variables; entrance effects