Search

Am 1. September 2018 veröffentlichte die Frankfurter Allgemeine Zeitung ihr neues Ökonomenranking. Der vorliegende Artikel macht einige Anmerkungen zur Methodik und Interpretation. Zudem werden kritische Punkte diskutiert. Abschließend wird ein Vergleich zum Ökonomenranking der RePEc-Website gezogen.

Im September 2014 veröffentlichte die Frankfurter Allgemeine Zeitung zum zweiten Mal nach 2013 ihr neues Ökonomenranking. Es fand eine deutliche methodische Weiterentwicklung zur Erstausgabe statt. Das Ranking berücksichtigt neben der Forschungsleistung auch noch zwei weitere Aspekte: Medienpräsenz und Politikberatung. In diesem Artikel wird das Ranking erneut einer kritischen Betrachtung unterworfen und mit dem Handelsblatt- und RePEc-Ranking verglichen.

Rankings von wissenschaftlichen Fachzeitschriften spielen eine wichtige Rolle sowohl für das Prestige der Zeitschriften als auch für die Reputation der Autoren, die in diesen Zeitschriften veröffentlichen. Der vorliegende Artikel stellt ein Meta-Ranking von 277 ökonomischen Fachzeitschriften vor. Es basiert auf 22 individuellen Rankings, die Daten aus vier verschiedenen bibliometrischen Datenbanken nutzen.

Im September 2013 veröffentlichte die Frankfurter Allgemeine Zeitung ein neues Ökonomenranking. Dieses berücksichtigt neben der Forschungsleistung auch noch zwei weitere Aspekte: Medienpräsenz und Politikberatung. In diesem Artikel wurde das FAZ-Ranking einer kritischen Analyse unterworfen, die zeigte, dass das FAZ-Ranking viele Schwachpunkte hat. Neben dem Aggregationsproblem ist vor allem die unvollständige Erfassung der Zitierungen im Forschungsranking hervorzuheben. Auf Grundlage dieser Kritik wird hier eine alternative Aggregationsmethode für die Einzelrankings vorgeschlagen.

This study examines the question of whether the journal ranking VHB-JOURQUAL 2 can be considered as a good measure for the construct ”scientific quality„. Various rankings in business research provide the database for the analysis. The correlations between theses rankings are used to assess the validity of VHBJOURQUAL 2 along various validity criteria. The correlations with rankings that measure the same construct based on different methods show that VHB-JOURQUAL 2 has acceptable, but moderate convergent validity. The validity varies considerably across disciplines, showing that the heterogeneity of business administration is not sufficiently represented by this overall ranking. The variability is related to the variation in members per discipline represented by the German Association for Business Research. Furthermore, the measure shows a weak correlation with acceptance rates as an indicator of nomological validity in some disciplines.

VHB-JOURQUAL represents the official journal ranking of the German Academic Association for Business Research. Since its introduction in 2003, the ranking has become the most influential journal evaluation approach in German-speaking countries, impacting several key managerial decisions of German, Austrian, and Swiss business schools. This article reports the methodological approach of the ranking’s second edition. It also presents the main results and additional analyses on the validity of the rating and the underlying decision processes of the respondents. Selected implications for researchers and higher-education institutions are discussed.

Erneuerbare Energien tragen wesentlich zum Klimaschutz, zur Schonung erschöpfbarer Ressourcen und zur Energieversorgungssicherheit bei. Ziel der Europäischen Union ist es, den Anteil erneuerbarer Energien bis 2020 auf mindestens 20 Prozent des Energieverbrauchs zu erhöhen. Deutschlands Anteil soll dabei von 8,6 Prozent im Jahr 2007 auf 18 Prozent steigen. Im Juni 2008 hat der Deutsche Bundestag beschlossen, bis 2020 den Anteil erneuerbarer Energien am Stromverbrauch auf mindestens 30 Prozent und den Anteil an der Wärmebereitstellung auf mindestens 14 Prozent zu verdoppeln. Um diese Ziele zu erreichen wurden auf Bundesebene insbesondere das Erneuerbare-Energien-Gesetz novelliert, ein spezielles Wärmegesetz eingeführt und die Ausgaben für Forschung und Entwicklung aufgestockt. Neben dem Bund spielen auch die Bundesländer eine wichtige Rolle bei der Förderung erneuerbarer Energien. Sie setzen eigene Ausbauziele, führen Förderprogramme durch und beeinflussen die Entwicklung maßgeblich durch die Gestaltung von rechtlichen und administrativen Rahmenbedingungen. Zum Vergleich der Anstrengungen und Erfolge der Bundesländer in diesem Bereich hat das DIW Berlin im Auftrag der Agentur für Erneuerbare Energien e. V. ein umfangreiches Indikatorensystem entwickelt. Es zeigt sich, dass sich die Bundesländer unterschiedlich stark für erneuerbare Energien engagieren und dabei verschiedene Schwerpunkte setzen. Auf der Grundlage dieser Studie ist im November der Preis "Leitstern 2008" in der Gesamtbewertung dem Land Brandenburg verliehen worden. Künftig müssen allerdings alle Bundesländer ihre Anstrengungen im Bereich der erneuerbaren Energien verstärken, damit die längerfristigen Ausbauziele erreicht werden können.

Internationale Standortrankings sind in jungerer Zeit zunehmend in die wissenschaftliche Kritik geraten. Sebastian Gundel und Ulrich van Suntum analysieren im Folgenden, inwieweit eine kritische Studie zum Landerranking von Ullrich Heilemann, Harald Lehmann und Joachim Ragnitz 1 ihrem wissenschaftlichen Anspruch selbst gerecht wird. Daran anschliesend eine Erwiderung von Ullrich Heilemann, Harald Lehmann und Joachim Ragnitz.

Discovery-Systeme lösen auch in Deutschland in immer mehr wissenschaftlichen Bibliotheken die in die Jahre gekommenen Onlinekataloge (Opacs) ab. Diese Arbeit befasst sich deshalb mit der Frage, ob Discovery Systeme eine Lösung, ein One-Stop Shop, für alle Wissenschaftsdisziplinen sein können (und sollen) oder ob sie, so meine These, je nachdem wie sie konfiguriert sind, die eine oder andere Disziplin bevorzugen bzw. von sich aus einer der Wissenschaftstaxonomien eher entsprechen. Um dies zu überprüfen, wurden zunächst auf Grundlage einer wissenschaftshistorischen Analyse der Fachkulturen wissenschaftstheoretische Taxonomien erstellt. Diese Taxonomien bildeten die Basis für die empirischen Erhebungen zur Anwendung und zum Nutzen von Discovery-Lösungen im deutschsprachigen Raum. Eine Erhebung befragte elf Bibliotheken hinsichtlich ihrer fachspezifischen Beachtung dieser Taxonomien beim Einsatz und der Konfigurierung ihrer spezifischen Discovery-Systeme, die andere zwölf Wissenschaftler/innen mit unterschiedlichem fachkulturellen Background. Als Ergebnis zeigte sich relativ deutlich, dass Discovery-Tools eher die Bedürfnisse der Naturwissenschaftler/innen bedienen und dass es teilweise erhebliche Desiderate im Erkennen und Berücksichtigen der Bedarfe der Geisteswissenschaftler/innen gibt. Um diesen Zustand abzumildern, werden einige Vorschläge präsentiert, die insbesondere die Themen bessere inhaltliche Erschließung (Semantic Web), Trennung von Indices und Katalog und transparentes Ranking aufgreifen. Ein wissenschaftsphilosophisches Fazit über die möglichen Folgen der Discovery-Systeme für Forschung und Wissenschaft beschließt die Arbeit.

Im Januar 2014 wurde das aktuelle »Global Go-To Think Tank«-Ranking veröffentlicht. Eine erneute Prüfung der Qualität des Rankings zeigte, dass die bereits 2010 und 2012 erhobene Kritik an dem Rankingverfahren nach wie vor Gültigkeit hat. Die Ergebnisse sind nur mit höchster Vorsicht zu genießen.

Objective Rank county health using a Bayesian factor analysis model. Data Sources Secondary county data from the National Center for Health Statistics (through 2007) and Behavioral Risk Factor Surveillance System (through 2009). Study Design Our model builds on the existing county health rankings (CHRs) by using data-derived weights to compute ranks from mortality and morbidity variables, and by quantifying uncertainty based on population, spatial correlation, and missing data. We apply our model to Wisconsin, which has comprehensive data, and Texas, which has substantial missing information. Data Collection Methods The data were downloaded from www.countyhealthrankings.org. Principal Findings Our estimated rankings are more similar to the CHRs for Wisconsin than Texas, as the data-derived factor weights are closer to the assigned weights for Wisconsin. The correlations between the CHRs and our ranks are 0.89 for Wisconsin and 0.65 for Texas. Uncertainty is especially severe for Texas given the state's substantial missing data. Conclusions The reliability of comprehensive CHRs varies from state to state. We advise focusing on the counties that remain among the least healthy after incorporating alternate weighting methods and accounting for uncertainty. Our results also highlight the need for broader geographic coverage in health data.

Experts possess knowledge and information that are not publicly available. The paper is concerned with forecasting academic journal quality and research impact using a survey of international experts from a national project on ranking academic finance journals in Taiwan. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance (hereafter Finance) category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. The harmonic mean of the ranks of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A linear regression model is used to forecast expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal. The robustness of the rankings is also analysed.

The paper focuses on the robustness of rankings of academic journal quality and research impact in general, and in Economics, in particular, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). The paper analyses 299 leading international journals in Economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. All existing RAMs to date have been static, so two new dynamic RAMs are developed to capture changes in impact factor over time and escalating journal self citations. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, and PI-BETA (Papers Ignored - By Even The Authors). As all existing RAMs to date have been static, two new dynamic RAMs are developed to capture changes in impact factor over time (5YD2 = 5YIF/2YIF) and Escalating Self Citations. We highlight robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal quality, impact and influence relative to the harmonic mean of the ranks.

We project the medal number and medal ranking for the Olympic Games in London in 2012. The largest relative increase is predicted for Brazil (80% more medals) and the UK (+28%). UK will continue to rank 4th. The largest decreases in medal numbers are predicted for Australia (-13%, but remains in 5th place) and the USA (-13%, remains No. 1). Germany should retain a rank of 6th and will win 38 medals (compared to 41 in 2008).

This paper proposes a new tool to assess sustainability and make the concept of sustainable development operational. It considers its multi-dimensional structure combining the information deriving from a selection of relevant sustainability indicators belonging to economic, social and environmental pillars. It reproduces the dynamics of these indicators over time and countries. Then, it aggregates these indicators using a new approach based on Choquet's integrals. The main novelties of this approach are indeed: (i) the modelling framework, a recursive-dynamic computable general equilibrium used to calculate the evolution of all indicators over time throughout the world, and (ii) the aggregation methodology to reconcile them in one aggregate index to measure overall sustainability. The former allows capturing the sector and regional interactions and higher-order effects driven by background assumptions on relevant variables to depict future scenarios. The latter makes it possible to compare sustainability performances, under alternative scenarios, across countries and over time. Main results show that the current sustainability at world level differs from what the traditional measure of well-being, the GDP, depicts, highlighting the trade-offs among different components of sustainability. Moreover, in the next decade a slight decrease in world sustainability may occur, in spite of an expected increase in world domestic product. Finally, dedicated policies increase overall sustainability, showing that social and environmental benefits may be greater than the correlated economic costs.

The evaluation of scientific output has a key role in the allocation of research funds and academic positions. Decisions are often based on quality indicators for academic journals and over the years a handful of scoring methods have been proposed for this purpose. Discussing the most prominent methods (de facto standards) we show that they do not distinguish quality from quantity at article level. The systematic bias we find is analytically tractable and implies that the methods are manipulable. We introduce modified methods that correct for this bias, and use them to provide rankings of economic journals. Our methodology is transparent; our results are replicable.

Die Erstellung qualitativ hochwertiger Benchmarkings für die Forschung betriebswirtschaftlicher Fachbereiche ist von hoher praktischer Relevanz. Den Studierenden, aber auch dem wissenschaftlichen Personal und der Hochschulpolitik, wird auf diese Weise ermöglicht, die Leistungen von Fachbereichen zu vergleichen und besonders forschungsstarke Standorte zu identifizieren. Den Fachbereichen wird die Möglichkeit geboten, Verbesserungspotenziale zu identifizieren und gegebenenfalls von leistungsstärkeren Fachbereichen zu lernen. Das Centrum für Hochschulentwicklung (CHE) veröffentlicht alle drei Jahre Rankings von Hochschulen zu einzelnen Studienfächern. Hierbei werden verschiedene Leistungsindikatoren, beispielsweise zu der Anzahl und Qualität von Publikationen, den Promotionen und Habilitationen sowie den Forschungsgeldern herangezogen. Basierend auf den Daten des CHE aus dem Jahr 2008 sowie einem kürzlich veröffentlichten neuen CHE-Ranking (2011) wird in dem vorliegenden Aufsatz ein auf die Forschung der individuellen Fachbereiche bezogenes und auf die quantitativen Daten des CHE gestütztes relatives Effizienz-Benchmarking der Fachbereiche erstellt. Im Gegensatz zu einem rein Output-bezogenen Effektivitätsranking analysiert die vorliegende Effizienzanalyse die Leistungsfähigkeit der Fachbereiche bei der Transformation und Gewichtung von Forschungsinput (z.B. Professoren, Forschungsgelder und Promotionen) in Forschungsoutput (Publikationen). Je mehr Forschungsoutput mit dem gegebenen Forschungsinput erzielt wird (und vice versa), desto leistungsfähiger ist der jeweilige Fachbereich und desto höher ist sein Effizienzwert. Ein für eine solche Analyse geeignetes und in dem vorliegenden Aufsatz verwendetes Verfahren ist die Data Envelopment Analysis (DEA). Es zeigt sich, dass zwischen den Effizienzrankings der Fachbereiche keine erheblichen Unterschiede zwischen den Jahren 2008 und 2011 bestehen. Deutliche Unterschiede ergeben sich jedoch bei einem Wechsel der Leistungsindikatoren (Outputfaktoren) von nationalen zu internationalen Publikationen, die mit den Forschungsgeldern, den Promotionen und Habilitationen als Inputfaktoren erzeugt werden. Für einen Großteil der untersuchten Fachbereiche ergibt sich ferner ein erhebliches Potenzial für Steigerungen der Forschungseffizienz. Um diese zu realisieren, werden für jeden ineffizienten Fachbereich operationale individuelle Output-Ziele (Publikationsziele) und effiziente Benchmark-Fachbereiche als Orientierung vorgegeben.

This paper contributes to the axiomatization of additive rules for ranking sets of objects under the psychological principle of categorization. Firstly we proceed with the case where the elements in the sets are categorized into at most three groups, namely good (with value 1), neutral (with value 0), and bad (with value−1). Secondly, we solve the case where there are only good and neutral elements. In both instances the evaluation of the sets is purely additive. Lastly, we show that dropping one of the axioms in our general characterization produces an axiomatization of the more general class of evaluations where good and bad elements are weighted differently. Areas of research in Economics such as committee selection problems, hedonic games and matching are among the ranking sets models where our results could potentially be applied. José C. R. Alcantud acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (Project ECO2009-07682), and from Junta de Castilla y León (Project SA024A08 and GR-99 Funding). R. Arlegi (corresponding author) acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (Projects SEJ2006-11510 and ECO2009-12836), and from Junta de Castilla y León (Project VA040A05).

We introduce a procedurally fair rule to study a situation where people disagree about the value of three alternatives in the way captured by the voting paradox. The rule allows people to select a final collective ranking by submitting a bid vector with six components (the six possible rankings of the three alternatives). In a laboratory experiment we test the robustness of the rule to the introduction of subsidies and taxes. We have two main results. First, in all treatments, the most frequently chosen ranking is the socially efficient one. Second, subsidies slightly enhance overbidding. Furthermore, an analysis of individual bid vectors reveals interesting behavioral regularities.

We propose a simple network–based methodology for ranking systemically important financial institutions. We view the risks of firms –including both the financial sector and the real economy– as a network with nodes representing the volatility shocks. The metric for the connections of the nodes is the correlation between these shocks. Daily dynamic centrality measures allow us to rank firms in terms of risk connectedness and firm characteristics. We present a general systemic risk index for the financial sector. Results from applying this approach to all firms in the S&P500 for 2003–2011 are twofold. First, Bank of America, JP Morgan and Wells Fargo are consistently in the top 10 throughout the sample. Citigroup and Lehman Brothers also were consistently in the top 10 up to late 2008. At the end of the sample, insurance firms emerge as systemic. Second, the systemic risk in the financial sector built–up from early 2005, peaked in September 2008, and greatly reduced after the introduction of TARP and the rescue of AIG. Anxiety about European debt markets saw the systemic risk begin to rise again from April 2010. We further decompose these results to find that the systemic risk of insurance and deposit–taking institutions differs importantly, the latter experienced a decline from late 2007, inline with the burst of the housing price bubble, while the former continued to climb up to the rescue of AIG.

Research rankings based on publications and citations today dominate governance of academia. Yet they have unintended side effects on individual scholars and academic institutions and can be counterproductive. They induce a substitution of the “taste for science” by a “taste for publication”. We suggest as alternatives careful selection and socialization of scholars, supplemented by periodic self-evaluations and awards. Neither should rankings be a basis for the distributions of funds within universities. Rather, qualified individual scholars should be supported by basic funds to be able to engage in new and unconventional research topics and methods.

Am 5. September 2011 veröffentlichte das Handelsblatt das VWL-Ranking 2011. Der vorliegende Beitrag unterwirft die Methodik des Handelsblatts einer kurzen Kritik und vergleicht anschließend das Ranking mit demjenigen von RePEc.

We develop a composite indicator measuring the performance of national innovation systems. The indicator takes into account both hard factors that are quantifiable (such as R&D spending, number of patents) and soft factors like the assessment of preconditions for innovation by managers. We apply the methodology to a set of 17 industrialized countries on a yearly basis between 2007 and 2009. The indicator combines results from public opinion surveys on the process of change, social capital, trust and science and technology to achieve an assessment of a country's social climate for innovation. After calculating and ranking the innovation indictor scores for the 17 countries, we group them into three classes: innovation leader, middle group and end section. Using multiple sensitivity analysis approaches, we show that the indicator reacts robustly to different weights within these country groups. While leading countries like Switzerland, the USA and the Nordic countries have an innovation system with high scores and ranks in every sub indicator, the middle group consisting among others of Germany Japan, the UK and France, can be characterized by higher variation within ranks. In the end section, countries like Italy and Spain have bad scores for almost all indicators.

We develop a composite indicator measuring the performance of national innovation systems. The indicator takes into account both 'hard' factors that are quantifiable (such as R&D spending, number of patents) and 'soft' factors like the assessment of preconditions for innovation by managers. We apply the methodology to a set of 17 industrialized countries on a yearly basis between 2007 and 2009. The indicator combines results from public opinion surveys on the process of change, social capital, trust and science and technology to achieve an assessment of a country's social climate for innovation. After calculating and ranking the innovation indictor scores for the 17 countries, we group them into three classes: innovation leader, middle group and end section. Using multiple sensitivity analysis approaches, weshow that the indicator reacts robustly to different weights within these country groups. While leading countries like Switzerland, the USA and the Nordic countries have an innovation system with high scores and ranks in every sub indicator, the middle group consisting among others of Germany Japan, the UK and France, can be characterized by higher variation within ranks. In the end section, countries like Italy and Spain have bad scores for almost all indicators.

Die Analyse und der Vergleich des Outputs wirtschaftswissenschaftlicher Fachbereiche erfahren eine anhaltend hohe Aufmerksamkeit. Evaluationen und Rankings schaffen für die Hochschule als Anbieter von Forschungs- und Lehrleistungen mehr Klarheit über den eigenen Output und verringern die Informationsasymmetrien auf den Märkten, auf denen die Hochschule mit potentiellen Studierenden oder den Nachfragern von Forschungsergebnissen interagiert. Das bekannteste Forschungsleistungsranking betriebswirtschaftlicher Fachbereiche ist 2009 vom Handelsblatt vorgelegt worden. Dessen Methodologie erweist sich allerdings sowohl hinsichtlich der Datenbasis als auch der verwendeten Aggregationsmethode als nicht unproblematisch. Bezugnehmend auf diese Kritik wird ein zitationsbasiertes Ranking mit Google Scholar entworfen. Es soll den aktuellen Output der betriebswirtschaftlichen Fachbereiche in Deutschland, Österreich und der Schweiz abbilden. Für die Rangfolgebildung werden drei alternative Kriterien vorgeschlagen. Im Anschluss sollen mittels einer ökonometrischen Schätzung mögliche Einflussfaktoren auf die Platzierungen identifiziert werden. Abschließend werden die Daten zudem auf der Ebene der (Bundes-)Länder aggregiert, um auch diese hinsichtlich der in ihnen erbrachten betriebswirtschaftlichen Forschungsleistungen miteinander zu vergleichen. The analysis and comparison of the academic output of business departments receive a sustained high attention. For universities as producers of services in research and teaching, evaluations and rankings provide more clarity about their own output. Furthermore, they reduce information asymmetries in the markets on which the university interacts with prospective students and users of research. The best-known research ranking of business departments has been published by the newspaper Handelsblatt in 2009. Its methodology, however, is problematic in regard of the underlying data base and the methods of aggregation. Referring to this critique our paper outlines a citation based approach with Google Scholar. Its purpose is to reflect the current research output of business departments in Germany, Austria and Switzerland, and we propose three alternative aggregation methods. Furthermore, we identify possible influencing factors. Finally, the data gets aggregated at the level of (federal) states in order to compare the different jurisdictions according to the business research produced within.

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different indicators for more than 30,000 economists. Based on this bibliographic information RePEc calculates well-known rankings for authors and academic institutions. We provide some cautionary remarks concerning the interpretation of some provided bibliometric measures in RePEc. Moreover, we show how individual and aggregated rankings can be biased due to the employed ranking methodology. In order to select key in-dicators describing and assessing research performance of scientist, we propose to apply principal component analysis in this data-rich environment. This approach allows us to assign weights to each indicator prior to aggregation. We illustrate the approach by providing a new overall ranking of economists based on RePEc data.

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source both for the spread of existing and new economic research. Furthermore the calculation of rankings for authors and academic institutions play a central role. We provide some cautionary remarks on the ranking methodology employed by RePEc and show how the aggregated rankings maybe biased. Furthermore we offer anew ranking approach, based on standardization of scores, which allows interpersonal comparisons and is less sensitive to outliers. We illustrate our new approach with a large data set provided by RePEc based on 24,500 authors.

Pflegebedürfnisse werden zum erheblichen Teil durch professionelle Dienste befriedigt. Ein wichtiger Eckpfeiler in der pflegerischen Versorgung stellen darüber hinausfamiliäre Beziehungen wie Partner und Kinder, sowie Freundes- und Nachbarschaftsnetzwerke dar. Diese Ressourcen stehen aber nicht allen Personen gleichermaßen zur Verfügung, sondern sind in der Bevölkerung ungleich verteilt. Wir beschäftigen uns mit der Reihenfolge von genannten Unterstützungspersonen, bei der Befragte Personengruppen – überwiegend aus dem Kreis informeller Beziehungen – im Hinblick auf die Versorgung im Rahmen einer hypothetischen Pflegebedürftigkeit nennen sollten. Es handelt sich um eine Frage, die u.a. den Befragten des Sozio-ökonomischen Panels regelmäßig gestellt wird. Die Besonderheit der Situation einer pflegerischen Bedürftigkeit aufgrund der Notlage und der Intimität des Ereignisses setzt eher vertrauensvolle Personen als Ansprechpartner voraus. Inhaltlich können somit durch diese Personenangaben Hinweise auf die Ausgestaltung individuell differenzierter Teilnetzwerke gefunden werden. Ähnliche Fragen nach Präferenzen finden sich aber auch in vielen anderen Bereichen der Sozialstatistik, in denen Befragte gebeten werden, ihre Präferenzen für bestimmte Alternativen zu äußern. Die besonderen Eigenschaften solcher Daten erfordern geeignete Methoden, die den Besonderheiten der erzeugten Daten Rechnung tragen. Die vorliegende Arbeit soll einen Beitrag zur Darstellung und Analyse solcher Rangdaten leisten. Dabei werden zwei Ziele verfolgt: Einerseits wird ein Verfahren zur Visualisierung von Rangdaten dargestellt, das bislang in der sozialwissenschaftlichen Forschung wenig Beachtung gefunden hat und hier im konkreten Fall für die Darstellung von Teilnetzwerken angewendet wird. Es handelt sich um die Darstellung von Rangdaten mit Hilfe von Polytopen, durch die sich die Komplexität in den Präferenzäußerungen explorativ grafisch veranschaulichen lässt. Andererseits soll anhand dieses Verfahrens die inhaltliche und methodische Problematik einer Fragebogenkonstruktion diskutiert werden, in der Personen gebeten werden, Aussagen über hypothetische Zustände oder Meinungen zu leisten, um ihren Präferenzen Ausdruck zu verleihen. Demands for care are met not only by professional care services but as well by family members and friends, especially by partners and children. These personal resources are not equally available to everyone. Moreover, there may be differences in preferences when choosing between alternative care arrangements. In particular, the often intimate situations arising in nursing care will lead many to prefer close relatives or friends over professional care services. We consider preference orderings between potentially supporting persons or professional care services. The orderings were obtained by asking respondents to name the most preferred groups of persons they would ask for support in a hypothetical case of being in the need of care. This question is part of the standard panel questionnaire program of the Socio-Economic Panel Study (SOEP) and is thus regularly posed. Similar questions to state preferences among a given set of potential alternatives can be found in many social surveys. The analysis of such data requires suitable methods that take their special features into account. We present a method to visualize partial rankings. The method is then used to present rankings over partial preferences, where the set of alternatives depends on the availability of networks of relatives, partners and friends. The method visualizes rank data using the skeleton of polytopes, by which the complexity of given preferences can faithfully be represented . Using the method for responses to the question about nursing care clearly demonstrates a shortcoming of this type of questions in general survey questionnaires.

Anfang März hat das Handelsblatt die neueste Ausgabe seines Ökonomen-Rankings vorgestellt. In diesem Beitrag wird der Aspekt der Zeitschriftengewichtung im Handelsblatt-Ranking und deren Implikationen beleuchtet.

We conducted a global study of the long-term issuer ratings of nonfinancial firms from Standard and Poor's Ratings Services (S&P) for the period 1998-2003. Specifically, we focused on the solicited versus unsolicited ratings and sample-selection bias in the analysis. Unlike the literature, we adopted an improved method using Wooldridge's instrumental-variable approach to mitigate the concern of specification errors in Heckman's model. We found that the probability of seeking a long-term issuer rating is positively related to the size and profitability of the firm, and negatively related to the growth opportunities and debt levels of the firm. The credit rating is positively related to the sovereign rating, size, and profitability of the issuer, and negatively related to the debt ratio of the issuer. Consistent with the literature, we found sample-selection bias in credit ratings. Our findings suggest that the firms with solicited ratings seem to be more profitable, more liquid, and have lower leverage than the issuers with unsolicited ratings. After controlling for sample-selection bias and some key financial ratios, we found that unsolicited firms, on average, seem to have lower long-term issuer ratings.

This paper is concerned with the problem of ranking Lorenz curves in situations where the Lorenz curves intersect and no unambiguous ranking can be attained without introducing weaker ranking criteria than first-degree Lorenz dominance. To deal with such situations Aaberge (2009) introduced two alternative sequences of nested dominance criteria for Lorenz curves which was proved to characterize two separate systems of nested subfamilies of inequality measures. This paper uses the obtained characterization results to arrange the members of two different generalized Gini families of inequality measures into subfamilies according to their relationship to Lorenz dominance of various degrees. Since the various criteria of higher degree Lorenz dominance provide convenient computational methods, these results can be used to identify the largest subfamily of the generalized Gini families and thus the least restrictive social preferences required to reach unambiguous ranking of a set of Lorenz curves. From the weight-functions of these inequality measures we obtain intuitive interpretations of higher degree Lorenz dominance, which generally has been viewed as difficult to interpret because they involve assumptions about third and higher derivatives. To demonstrate the usefulness of these methods for empirical applications, we examine the time trend in income and earnings inequality of Norwegian males during the period 1967-2005.

In diesem Beitrag wird das RePEc-Netzwerk vorgestellt, das speziell für den Bereich der Wirtschaftswissenschaften neben der Bereitstellung von Artikeln und bibliographischen Informationen auch verschiedene Rankings für Wissenschaftler und Institutionen berechnet.

A ranking of journals is manipulable if a particular journal's position can be improved by making additional citations to other journals. We introduce a simple ranking method that is not manipulable and is invariant to citation intensities, journal scaling and article-splitting. The ranking of economics journals is presented and is compared to rankings by alternative methods in the recent years.

Rankings gewinnen in der Wissenschaft an Bedeutung, stehen aber auch in der Kritik. Es kann Unterschiedliches zu verschiedenen Zwecken mit noch anderen Folgen gerankt werden. Im Folgenden werden nur Forschungsrankings betrachtet, die entweder wissenschaftliche Zeitschriften oder die darin veröffentlichten Wissenschaftler in eine Rangfolge bringen. Die Betrachtung erfolgt am Beispiel der deutschen Betriebswirtschaftslehre (BWL), kann jedoch prinzipiell in den meisten Wissenschaften entsprechend angewandt werden. Innerhalb der BWL ist das VHB-JOURQUAL 2 ein aktuelles Beispiel für ein Zeitschriftenranking, das Handelsblatt-Betriebswirte Ranking hingegen ein aktuelles Personenranking. Zu letzterem wird eine Alternative direkt über Zitationen vorgeschlagen. Grundannahme der Analyse ist, dass Anreize auch in der Wissenschaft wirken, sowohl selektierend wie auch motivierend, doch Fehlanreize entsprechend falsch wirken, weshalb eine Analyse von Rankings und ihre Verbesserung lohnt. Rankings are gaining importance in academics but are also subject to criticism. A large variety of items or persons can be ranked for different purposes and with various consequences. This article considers only research rankings that sort either academic journals or the researchers publishing therein. The study focuses on German business administration as an example, but could be applied on most other disciplines accordingly. Within business administration the VHB-JOURQUAL 2 is a recent example of a journal ranking and the Handelsblatt-Betriebswirte-Ranking is a ranking of researchers. For the latter I propose an alternative using citations directly. The basic assumption of the analysis is that incentives are effective in academia, both for selection and motivation. Hence misguided incentives function, alas in the wrong direction, such tht analysing and improving rankings is worthwile.

The ranking of colleges varies both across methods and model specifications. Still, earnings equations tend to be consistent with regard to which colleges that on average are found in the top and bottom half of the earnings distribution. Moreover, there are no systematic differences in the ranking of colleges dependent on the age of the college, i.e. old versus new colleges. Although ranking by earnings equations provide some information about the relation to earnings, endogeneity issues preclude any causal interpretation of the rankings presented here.

Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear Rank Estimator (LRE) of Tsiatis (1990) and Robins and Tsiatis (1991) to this class of models. The optimal LRE is a two-step estimator. We propose a simple first-step estimator that is close to optimal if there is no unobserved heterogeneity. The efficiency gain associated with the optimal LRE increases with the degree of unobserved heterogeneity.

Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This paper describes general methods to test for and estimate the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics literature where such methods are required. Four different methods to test the true rank of a general matrix are described, as well as one method that can handle the case of a matrix subject to parameter constraints associated with defineteness structures. The technical requirements for the implementation of the tests of rank of a general matrix differ and hence there are merits to all of them that justify their use in applied work. Nonetheless, we review available evidence of their small sample properties in the context of different modelling scenarios where all, or some, are applicable.

We use a method similar to Google's PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). Along the way we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for explaining why observed daily distributions of liquidity differ from the initial distributions, which are determined by the credit limits selected by banks., Les auteurs appliquent au système canadien de transfert de paiements de grande valeur une méthode similaire à l'algorithme PageRank de Google. Ils obtiennent ainsi une estimation de la vitesse de traitement des paiements dans chaque banque. L'analyse des différences entre banques à ce chapitre est essentielle si l'on veut comprendre pourquoi la distribution moyenne de la liquidité pour la journée diffère de la distribution observée en début de journée, qui est fonction des limites de crédit établies par les banques.

This paper reviews the governance framework of the Lisbon Strategy and discusses the specific option of increasing the role of benchmarking as a means of improving the implementation record of structural reforms in the European Union. Against this background, the paper puts forward a possible avenue for developing a strong form of quantitative benchmarking, namely ranking. The ranking methodology relies on the construction of a synthetic indicator using the “benefit of the doubt” approach, which acknowledges differences in emphasis among Member States with regard to structural reform priorities. The methodology is applied by using the structural indicators that have been commonly agreed by the governments of the Member States, but could also be used for ranking exercises on the basis of other indicators.

Billions of euros are allocated every year to university research. Increased specialisation and international integration of research and researchers has sharply raised the need for comparisons of performance across fields, institutions and individual researchers. However, there is still no consensus regarding how such rankings should be conducted and what output measures are appropriate to use. We rank all full professors in a particular discipline, economics, in one European nation using seven established, and some of them commonly used, measures of research performance. Our examination shows both that the rank order can vary greatly across measures, and that depending on the measure used the distribution of total research out-put is valued very differently. The renowned KMS measure in economics stands out among the measures analysed here. It exhibits the weakest correlation with the others used in our study. We conclude by giving advice to funding councils and others assessing research quality on how to think about the use of both quantitative and qualitative measures of performance.