Rudolf Farys

Matched control groups for modeling events in citation data: An illustration of nobel prize effects in citation networks

Bibliometric data are frequently used to study the effects of events, such as the honoring of a scholar with an award, and to investigate changes of citation impact over time. However, the number of yearly citations depends upon time for multiple reasons: a) general time trends in citation data, b) changing coverage of databases, c) individual citation life‐cycles, and d) selection on citation impact. Hence, it is often ill‐advised to simply compare the average number of citations before and after an event to estimate its causal effect. Using a recent publication in this journal on the potential citation chain reaction of a Nobel Prize, we demonstrate that a simple pre‐post comparison can lead to biased and misleading results. We propose using matched control groups to improve causal inference and illustrate that the inclusion of a tailor‐made synthetic control group in the statistical analysis helps to avoid methodological artifacts. Our results suggest that there is neither a Nobel Prize effect as regards citation impact of the Nobel laureate under investigation nor a related chain reaction in the citation network, as suggested in the original study. Finally, we explain that these methodological recommendations extend far beyond the study of Nobel Prize effects in citation data.

Redistribution through taxes and deductions. A decomposition analysis with administrative tax data from Switzerland

This empirical analysis of administrative tax data from the Swiss Canton of Aargau (2001 to 2011), shows the potential that this type of data has to grant us a more complete picture of the redistributive effects of visible (tax rates) and hidden (tax deductions) instruments of the welfare state. In terms of methodology, Gini-based redistributive effects are decomposed into effects of mean tax rate, progression and reranking effects. The studys findings show a declined impact of direct taxes, which is attributable to reduced taxation on the community and cantonal but not the state level. At the same time, tax deductions drastically hamper the redistributive effect of taxes, primarily through deductions of wealth expenses, interest and extra-mandatory payments to the pension scheme, each of which leads to a substantial tax relief for high income earners.

Verteilung der Vermögen in der Schweiz

1. Einleitung Bedingt durch die steigende Ungleichheit und angeregt durch verschiedene Studien (u.a. Piketty 2014, OECD 2011, Bundesministerium für Arbeit und Soziales 2017) haben Verteilungsfragen wieder mehr Aufmerksamkeit in den öffentlichen Debatten erhalten. Die meisten Studien zur Ungleichheit beziehen sich auf die Einkommensungleichheit. Das Einkommen als Flussgrösse ist auf den Konsum und damit den Lebensstandard gerichtet. Vermögen begründet Eigentum und Besitz und ist damit ebenfalls eine wichtige Dimension für den gesellschaftlichen Status sowie die materielle Wohlfahrt und eine wichtige Basis für materielle Sicherheit. Ein grösseres Vermögen eröffnet zudem Handlungsund Einflussmöglichkeiten und ist eine Grundlage für ungleiche Machtverhältnisse. Bei der Betrachtung der gesellschaftlichen Schichtung bleibt das Vermögen allerdings als zentrale Ressource neben dem Einkommen, der beruflichen Position und der Bildung meist im Hintergrund. Dabei kommt dem Vermögen als materielle Ressource eine immer grössere Bedeutung zu. Im Rahmen seiner Untersuchungen hat Piketty aufgezeigt, dass in den letzten Jahrzehnten das Vermögen im Verhältnis zum Einkommen an Gewicht gewonnen hat und deshalb ein entscheidender Faktor für die zunehmende ökonomische Ungleicheit ist (Piketty & Zucman 2014). Auch in der Schweiz hat sich seit 1991 das Verhältnis des Durchschnittsvermögens zum jährlichen Durchschnittseinkommen von 2.5 auf 3.9 erhöht, wie Auswertungen von Steuerstatistiken zeigen. Ausserhalb des Schwerpunktes

Methoden-Workshop Leading House "Economics of Education"/SKBF

1 Regression Discontinuity Design (sharp RDD) 1 1.1 Daten generieren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Lineares RDD-Modell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Kubisches RDD-Modell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.4 Nichtparametrische RDD-Analyse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.5 Nichtparametrischer RDD-Schätzer mit Bootstrap-Standardfehler . . . . . . . . . . . . . . . . 4 1.6 Nichtparametrischer RDD-Schätzer von Calonico et al. . . . . . . . . . . . . . . . . . . . . . . 5

Inequality in Income and Wealth in Switzerland from 1970 to 2010

The supposed rise of inequality in income and wealth is a much-discussed issue. Since in a number of industrialized countries a trend towards more inequality was observed over the last decades, it is often assumed that Switzerland has experienced a similar development. Yet, although a variety of studies exists that provide inequality estimates for the Swiss society at different points in time, no conclusive picture of the changes in inequality can be drawn from these studies. For example, recent estimates by the Swiss Federal Statistical Office indicate that – against expectations – inequality in disposable equivalent-incomes has not risen since the end of the 1990ies, whereas other studies indicate that earnings from employment – especially top salaries – have become more unequal. The reasons for the inconclusive picture are manifold. For example, trends might have been different for different income types and results might strongly depend on the quality of the used data. To close the knowledge gap in inequality research in Switzerland a new Swiss National Science Foundation project by the University of Bern and the Bern University of Applied Sciences has been started in 2013. Individual tax data from cantons will be analyzed along with aggregate data from the Swiss Federal Tax Administration, covering a period from the early 1970ies to the present. The goal is to gain a systematic overview of the development of inequality in income and wealth in Switzerland as a whole and within cantons, and to determine how changes can be explained. In our talk we will present first results from this project.