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

Abstract

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.

OECD Statistics Working Papers

“…In other terms, scores were placed on a common scale running from 0 to 100, with 100 being the end-value and 0 being the value that only 10% of OECD countries failed to reach in the base year. Ratio-scale is still used in other assessments of distance to SDGs (Sachs et al, 2019 [17]; UNSD, 2020 [22]).…”

“…Alternatively, for data series whose end-values are not explicit (A-type) and when B-type end-values cannot be proposed, the best performance approach (C-type) seems to be the only alternative. A similar methodology is used in other assessment of SDGs (Sachs et al, 2019 [17]; UN-ESCAP, 2019 [18])…”