Composite Leading Indicators for Major OECD Non-Member Economies: Brazil, China, India, Indonesia, Russian Federation, South Africa
The OECD developed a System of Composite Leading indicators for its Member countries in the early 1980's based on the 'growth cycle' approach. Today the OECD compiles composite leading indicators (CLIs) for 23 of its 30 Member countries and it is envisaged to expand country coverage t...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2006
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| Schriftenreihe: | OECD Statistics Working Papers
no.2006/01 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | The OECD developed a System of Composite Leading indicators for its Member countries in the early 1980's based on the 'growth cycle' approach. Today the OECD compiles composite leading indicators (CLIs) for 23 of its 30 Member countries and it is envisaged to expand country coverage to include all Member countries and the major six OECD non-member economies (NMEs) monitored by the organization in the OECD System of Composite Leading Indicators. The importance of the six major NMEs was considered the first priority and a workshop with participants from the six major NMEs was held at the OECD in Paris in April 2005 to discuss an initial OECD selection of potential leading indicators for the six major NMEs and national suggestions for alternative and/or additional potential leading indicators for calculation of country specific composite leading indicators. The outcomes of this meeting and followup activities undertaken by the OECD in co-operation with the participating national agencies are reflected in the results presented in this final version of the document. The OECD indicator system uses univariate analysis to estimate trend and cycles individually for each component series and then a composite indicator is obtained by aggregation of the resulting de-trended components. Today, statistical techniques based on alternative univariate methods and multivariate analysis are increasingly used in cyclical analysis and some of these techniques are used in this study to supplement the current OECD approach in the selection of leading components and the construction of composite indicators. |
| Beschreibung: | 1 Online-Ressource (59 p.) 21 x 29.7cm. |
| DOI: | 10.1787/834716666802 |
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| spelling | Nilsson, Ronny VerfasserIn aut Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa Ronny, Nilsson and Olivier, Brunet Paris OECD Publishing 2006 1 Online-Ressource (59 p.) 21 x 29.7cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OECD Statistics Working Papers no.2006/01 The OECD developed a System of Composite Leading indicators for its Member countries in the early 1980's based on the 'growth cycle' approach. Today the OECD compiles composite leading indicators (CLIs) for 23 of its 30 Member countries and it is envisaged to expand country coverage to include all Member countries and the major six OECD non-member economies (NMEs) monitored by the organization in the OECD System of Composite Leading Indicators. The importance of the six major NMEs was considered the first priority and a workshop with participants from the six major NMEs was held at the OECD in Paris in April 2005 to discuss an initial OECD selection of potential leading indicators for the six major NMEs and national suggestions for alternative and/or additional potential leading indicators for calculation of country specific composite leading indicators. The outcomes of this meeting and followup activities undertaken by the OECD in co-operation with the participating national agencies are reflected in the results presented in this final version of the document. The OECD indicator system uses univariate analysis to estimate trend and cycles individually for each component series and then a composite indicator is obtained by aggregation of the resulting de-trended components. Today, statistical techniques based on alternative univariate methods and multivariate analysis are increasingly used in cyclical analysis and some of these techniques are used in this study to supplement the current OECD approach in the selection of leading components and the construction of composite indicators. Economics Brazil China, People's Republic India Indonesia Russian Federation South Africa Brunet, Olivier MitwirkendeR ctb FWS01 ZDB-13-SOC FWS_PDA_SOC https://doi.org/10.1787/834716666802 Volltext |
| spellingShingle | Nilsson, Ronny Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa Economics Brazil China, People's Republic India Indonesia Russian Federation South Africa |
| title | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa |
| title_auth | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa |
| title_exact_search | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa |
| title_full | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa Ronny, Nilsson and Olivier, Brunet |
| title_fullStr | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa Ronny, Nilsson and Olivier, Brunet |
| title_full_unstemmed | Composite Leading Indicators for Major OECD Non-Member Economies Brazil, China, India, Indonesia, Russian Federation, South Africa Ronny, Nilsson and Olivier, Brunet |
| title_short | Composite Leading Indicators for Major OECD Non-Member Economies |
| title_sort | composite leading indicators for major oecd non member economies brazil china india indonesia russian federation south africa |
| title_sub | Brazil, China, India, Indonesia, Russian Federation, South Africa |
| topic | Economics Brazil China, People's Republic India Indonesia Russian Federation South Africa |
| topic_facet | Economics Brazil China, People's Republic India Indonesia Russian Federation South Africa |
| url | https://doi.org/10.1787/834716666802 |
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