Time-Distance as a Dynamic Measure of Disparities in Social and Economic Development

The Information Society

Hüsing

et al. 2006

Self Cite

158

The term "digital divide" has been used for almost a decade and typically relates to sociodemographic differences in the use of information and communication technology. However, the corresponding measurement is still relatively imprecise. Very often it is simply reduced to comparisons of Internet penetration rates. This article extends the measurements above the usual bivariate comparisons. Within this context, three essential approaches are presented and critically evaluated. First, loglinear modeling is used to address the interactions among the factors affecting the digital divide. Second, compound measures (i.e., the Digital Divide Index) that integrate a number of variables into a single indicator are discussed. Third, time-distance methodology is applied to analyze changes in the digital divide. The article argues that these approaches often yield entirely different conclusions compared to simple bivariate analysis. The examples are presented as a general warning against an oversimplified methodological approach to digital divide studies.

Section: Time-distance Methodologymentioning

confidence: 99%

Methodological Challenges of Digital Divide Measurements

Vehovar

The Information Society

Hüsing

et al. 2006

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158

“…Time distance concept and S-time-distance measure are directly connected to the pillar 3 of the proclamation of the OECD initiative on key indicators and the proposed project to measure and assess the overall ''position'' and ''progress'' (OECD, 2005, p. 9): ''research work to develop innovative approaches to make statistical information accessible and usable to the public at large: to compare existing tools and develop new approaches to statistical data dissemination and presentation to Table 1 Time matrix from the inverse relations: time when a specified level of the variable was achieved in each compared unit Sicherl (1973Sicherl ( , 1993 proposes ... observed time distance is a dynamic measure of temporal disparity between the two series intuitively clear, readily measurable, and in transparent units ... It is suggested that one should complement conventional vertical measures with horizontal measures'.…”

Section: Policy Implications Of the Broader Perspectivementioning

confidence: 99%

The inter-temporal aspect of well-being and societal progress

2007

Soc Indic Res

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“…The years in bold refer to the latest available observation available for each country. Japan 196019621963196619701971197519761979198319861991199620002005Switzerland 1964197019731976198119851992199620002004Iceland 196119691974197519831995199720002004Italy 196219661971197619801984198619901994199820032005Australia 19701974197619791982198619901995199920022006…”

Section: Box 2 a Graphical Illustration Of How To Compare Two Time-smentioning

confidence: 99%

“…5 Japan 19621976198419901994199820012005200820122014201720232031203620392044Korea 19831996200220132017202120232025202720302032203520372039204320462050Spain 19571973198519911997201320202025202820322035203820412044Italy 1965197519881993199920152022…”

Section: 2mentioning

confidence: 99%

See 1 more Smart Citation

New Understanding and Insights from Time-Series Data Based on Two Generic Measures

OECD Statistics Working Papers

2011

JT03311863 OECD STATISTICS WORKING PAPER SERIESThe OECD Statistics Working Paper Series -managed by the OECD Statistics Directorate -is designed to make available in a timely fashion and to a wider readership selected studies prepared by OECD staff or by outside consultants working on OECD projects. The papers included are of a technical, methodological or statistical policy nature and relate to statistical work relevant to the Organisation.The Working Papers are generally available only in their original language -English or French -with a summary in the other. Comments on the papers are welcome and should be communicated to the authors or to the OECD Statistics Directorate, 2 rue André Pascal, 75775 Paris Cedex 16, France.The opinions expressed in these papers are the sole responsibility of the authors and do not necessarily reflect those of the OECD or of the governments of its Member countries.This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. ABSTRACTTime distance is an innovative approach for looking at time-series data. Expressed in time units, the approach is easy to understand and provides a useful complement to existing methods. The time distance approach compares time series in the horizontal dimension, i.e. for a given level of the variable, based on two generic statistical measures: S-time-distance and S-time-step. These measures are based on a time matrix that summarises information over many units and years and that provides a first-level visualization tool. The paper also introduces the concept of the 'overall degree of disparity', defined as proximity in the indicator space as well as in time, arguing that this concept has the potential to bring new understanding in economics, management, research and statistics. RÉSUMÉLa distance temporelle est une approche novatrice pour analyser des séries temporelles. Exprimé en unités de temps, l'approche est facile à comprendre et fournit un complément utile aux méthodes existantes. Cette approche compare les séries chronologiques dans la dimension horizontale, c'est-à-dire pour un niveau donné de la variable, basé sur deux mesures statistiques génériques: S-time distance et S-time step. Ces mesures sont basées sur une matrice de temps qui résume l'information sur de nombreuses unités et années, et qui fournit un outil de visualisation de première lecture. Le document introduit aussi le concept de «degré total de disparité», défini comme la proximité dans l'espace ainsi que dans le temps, arguant que ce concept a le potentiel pour apporter une nouvelle compréhension en économie, gestion, et statistiques.