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Introduction Composite indicators (or indices) are of increasing interest for benchmarking institutions’ performance. Organizations such as the United Nations, the European Commission and others have developed and used

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Scientometrics
Authors: Fiorenzo Franceschini and Domenico Maisano

the considerations about hg can be extended to other composite indicators, which are based on the mathematical composition of other 1st level indicators—for instance the q 2 -index, suggested by Cabrerizo et al. ( 2010 ). Basic

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Spillovers from foreign direct investment in Central and Eastern Europe

An index for measuring a country’s potential to benefit from technology spillovers

Society and Economy
Authors: Balázs Szent-Iványi and Gábor Vigvári

): Handbook on Constructing Composite Indicators. Methodology and User Guide . Paris: OECD. Handbook on Constructing Composite Indicators. Methodology and User Guide 2008

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.0001) denoted by s . 19 Then we normalise this composite indicator by taking away its mean and dividing this result by the standard deviation of the series. Therefore, the Resilience indicator is as follows: R e s i l i e n c e   ( R ) = ln ( r a t i o − m e

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Summary  

Both quantitative and qualitative evaluation of publications of research teams or institutes requires several scientometric indicators. In this paper a new composite indicator is introduced for the assessment of publications of research institutes working in different fields of science. The composite indicator consists of three part-indicators (Journal Paper Productivity, Relative Publication Strategy and Relative Paper Citedness). The different methods of calculating the composite index have only a slight effect on the value, whereas application of diverse weights for the individual part-indicators results in significant changes.

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Scientometrics
Authors: Anthony Nasir, Tariq Mahmood Ali, Sheikh Shahdin, and Tariq Ur Rahman

Abstract

Ranking of 91 countries based on the Technology Achievement Index 2009 (TAI-09) (2009 refers to the year in which most of data collection was carried out.) is reported. Originally proposed in 2002, the TAI is a composite indicator which aggregates national technological capabilities and performance in terms of creation/diffusion of new technologies, diffusion of old technologies and development of human skills. In addition to the overall ranking of 91 countries, rankings in each sub-dimension of the Index are also reported. Comparative analysis of TAI ranking of 56 countries, common to the present and previous study of 2002 under similar conditions, is quite instructive and indicates shifts in technological scenario of these countries even over a relatively short period of 5–6 years. A simple concept based on Standard Deviation approach, as an indication of the technological spread or otherwise, is proposed for the first time. Application of this concept to 56 common countries is reported.

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Payment systems make a significant contribution to the flow of transactions and financial stability. In this paper, we start by applying the principles of the gravity model to explain the TARGET flows of banking transactions between Portugal and other eurozone countries. The main explanatory variables tested are a composite indicator of economic and financial activities, distance, membership of the Eurozone (EZ), and country risk measured by treasury bond yields. The results indicate that Portugal has a high level of integration in the European banking market as distance is not statistically significant, and that the membership of the EZ facilitates the financing of the economy. The economic size of the partner country becomes non-significant after controlling for country fixed effects. The increase in the Portuguese country risk during the European sovereign debt crisis led to a marked decline in external financing, indicating that this is an important channel of transmission of crises.

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Acta Oeconomica
Authors: Mirjana Gligorić Matić, Biljana Jovanović Gavrilović, and Nenad Stanišić

Abstract

After Second World War (WWII) a true evolution in understanding of economic development happened, which affected the ways of measuring prosperity, i.e. perceiving changes in people’s welfare. Numerous indicators have been created, which go ‘beyond GDP’ and cover different aspects of development and well-being. The aim of this paper is to analyse prosperity convergence in 32 European countries with a composite indicator – Legatum Prosperity Index (LPI). LPI is more complete than other indicators used in convergence analysis and reflects multidimensional nature of modern development and prosperity. Our research of absolute beta convergence is based on cross-sectional and panel data. Results indicate the existence of convergence in the overall index and its constitutive parts – dimensions and pillars, with different convergence speed regarding LPI and its segments for the total sample of countries, as well as for the countries of Eastern and Western Europe.

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Abstract  

This paper presents a methodology to aggregate multidimensional research output. Using a tailored version of the non-parametric Data Envelopment Analysis model, we account for the large heterogeneity in research output and the individual researcher preferences by endogenously weighting the various output dimensions. The approach offers three important advantages compared to the traditional approaches: (1) flexibility in the aggregation of different research outputs into an overall evaluation score; (2) a reduction of the impact of measurement errors and a-typical observations; and (3) a correction for the influences of a wide variety of factors outside the evaluated researcher’s control. As a result, research evaluations are more effective representations of actual research performance. The methodology is illustrated on a data set of all faculty members at a large polytechnic university in Belgium. The sample includes questionnaire items on the motivation and perception of the researcher. This allows us to explore whether motivation and background characteristics (such as age, gender, retention, etc.,) of the researchers explain variations in measured research performance.

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hospodářského cyklu pro českou ekonomiku (Methodology of the Composite Indicators Construction of the Czech Republic Business Cycle) . Statistika, 1 :21 Economic Cycle Research Institute ( 2011 ): Turning Points & Leading

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