Document Title | Documents | Presentations | |||||||
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ENG | FRE | RUS | |||||||
Programme of the meeting | |||||||||
Report of the meeting | |||||||||
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ENG | FRE | RUS | |||||||
Workshops 26 May | |||||||||
Workshop 1. Elementary price indices | |||||||||
Consumer Price Statistics in the UK, by W. Erwin Diewert | |||||||||
Background papers: | |||||||||
Answers to Questions Arising from the RPI Consultation, by W. Erwin Diewert | |||||||||
Is the Carli index flawed?: assessing the case for the new retail price index RPIJ, by Peter Levell | |||||||||
Workshop 2. Core inflation measurement | |||||||||
Core inflation measurement - Agenda | |||||||||
Core Inflation Measurement, by Mick Silver (IMF) | ENG RUS | ||||||||
Core Inflation: Measurement and Statistical Issues in Choosing Among Alternative Measures, by Mick Silver (IMF) | |||||||||
Reconsidering the Role of Food Prices in Inflation, by James P. Walsh (IMF) |
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Methodological approaches to measuring core inflation in the CIS countries, CISStat | |||||||||
Methodology for Core Inflation Calculation, by Olga Kalabukha (Ukraine) | ENG RUS | ||||||||
Core inflation measurement in Norway, by Ragnhild Nygaard (Norway) | ENG | ||||||||
Workshop 3. Quality Management | |||||||||
Quality Management Workshop - Agenda | |||||||||
Managing the CPI and PPI processes under ISO 9000, Mexico | ENG | ||||||||
Quality Management in Finnish CPI, Finland | ENG | ||||||||
A holistic approach to quality management in consumer price statistics, UNECE | ENG | ||||||||
ISO 9001: Supporting Statistical Systems, UK | ENG | ||||||||
Workshop 4. Scanner data | |||||||||
The Revolution of Scanner Data and the Challenges Ahead | |||||||||
Questionnaire forms: Steps for ensuring data quality – scanner data Challenges ahead – next step |
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GS1 and scanner data, Sweden | |||||||||
Scanner Data; Optimal Preservation Policy for Identifiable Datasets, Iceland | |||||||||
One size fits all? The need to cope with different levels of Scanner Data quality for CPI computation, Australia | |||||||||
Implementing scanner data in the Danish CPI, Denmark | |||||||||
Scanner data in the CPI/HICP, Denmark | |||||||||
Room documents: Transactions Data: From Theory to Practice, Australia | |||||||||
Relevant papers: | |||||||||
Past, present and future of scanner data with focus on Statistics Sweden | |||||||||
Austrian Scanner Data Project - Report “Multipurpose Consumer Price Statistics: The use of scanner data”, Australia |
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The use of scanner data in the Luxembourg CPI: first lessons learned, Luxembourg | |||||||||
Issues on the use of scanner data in the CPI, Sweden | |||||||||
Chapter on scanner data (retail transaction data) from the discussion paper for the New Zealand CPI revision advisory committee 2013, New Zealand | |||||||||
Statistics and Science, Handbook on the application of quality adjustment methods in the Harmonised Index of Consumer Prices, Volume 13, Germany | |||||||||
Questions regarding scanner data | |||||||||
Workshop 5. Higher-level price indices | |||||||||
High-level indices: Agenda | |||||||||
Higher-level indices: a practical guide | |||||||||
The calculation of higher-level indices in the CPI – a practical guide, Australia | |||||||||
Why ‘Lowe’ when ‘Young’ and ‘Laspeyres’ are available?, Australia | |||||||||
ABS’ HFCE-Weighted Price Index, Australia | |||||||||
Workshop 6. Quality adjustment: A general framework and the role of Hedonics | |||||||||
Quality adjustment: A general framework and the role of Hedonics, Agenda | |||||||||
Quality Adjustment and Hedonic Regressions, IMF | |||||||||
Limitations and impact of hedonic adjustment for the rent index, Switzerland | |||||||||
Limitations and impact of hedonic adjustment for the Swiss rent index | |||||||||
Quality adjustment in the New Zealand Consumers Price Index, New Zealand | |||||||||
Use of hedonic regression for quality adjustment at Statistics New Zealand | |||||||||
Workshop 7. Treatment of seasonal products | |||||||||
Agenda of the workshop | |||||||||
The treatment of products seasonality in inflation estimate. Introduction, Italy | |||||||||
Key issues concerning the treatment of seasonal products to calculate inflation from the point of view of central banks, Turkey | |||||||||
Official Journal of the European Union, Commission regulation (EC) No 330/2009 of 22 April 2009 | |||||||||
Recompiling 2010 data and the measure of impact of Regulation 330/2009 on Italian HICP, Italy | |||||||||
Treatment of seasonal products. Implementation of the commission regulation (EC) No 330/2009 of 22 April 2009, Hungary | |||||||||
The Hungarian experience in implementing European Regulation about seasonal products, Hungary | |||||||||
Report to the plenary session | |||||||||
Workshop 8. The Price Index Processor Software | |||||||||
Demonstration of PIPS CPI, by Paul Armknecht |
Document Title | Documents | Presentations | |||||||
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ENG | FRE | RUS | |||||||
Plenary sessions 27-28 May | |||||||||
Session 1. Reports from the workshops | |||||||||
Session 2. Update of the 2004 CPI Manual | |||||||||
Issues Paper on a possible update of the 2004 CPI Manual, prepared by the Intersecretariat Working Group on Price Statistics (IWGPS). Carsten Boldsen, UNECE | |||||||||
Session 3: Methodological issues I | |||||||||
Treatment of seasonal products and CPI volatility. Oguz Atuk, Mustafa Utku Ozmen, and Orhun Sevinc, Central Bank of Republic of Turkey | |||||||||
An Empirical Illustration of Index Construction using Israeli Data on Vegetables, Erwin Diewert, University of British Columbia, Canada | |||||||||
Will the real inflation rate please stand up–overlooked “quirks” of a favoured chain-linking technique. Dr Jens Mehrhoff, Deutsche Bundesbank, Germany | |||||||||
Session 4: Methodological issues II | |||||||||
The FEWS index: fixed-effects with a window-splice non-revisable quality-adjusted price indexes with no characteristic information. Frances Krsinich, Statistics New Zealand | |||||||||
Private Label Brands versus National Brands: Some Implications for the Construction of the CPI. Satoshi Imai, Statistics Bureau of Japan, and Tsutomu Watanabe, University of Tokyo | |||||||||
Estimating daily inflation using scanner data:a Progress Report.Tsutomu Watanabe, University of Tokyo, and Kota Watanabe, Chuo University and University of Tokyo, Japan | |||||||||
Room document | |||||||||
Experiences in calculating the consumer price index in Azerbaijan. The State Committee on Statistics of the Republic of Azerbaijan | |||||||||
Session 5: Price collection methods | |||||||||
Collecting clothing data from the internet. Leon Willenborg, Robert Griffioen, Jan de Haan and Karlijn Bakker, Statistics Netherlands | |||||||||
Exploiting new technologies and new data sources – the opportunities and challenges associated with scanner data. David Fenwick, International Expert, the United Kingdom | |||||||||
Sampling Selection Bias in Consumer Price Indices. Kristina Strandberg and Anders Norberg, Statistics Sweden | |||||||||
Session 6: Difficult to measure products and services | |||||||||
Mobile Phone Service Computing Methodology. Rafael Gaona Lopez, INEGI, Mexico | |||||||||
Methodological approaches to recording certain types of services in the consumer price index in Belarus. Ekaterina Grikhanova, National Statistical Committee of the Republic of Belarus | |||||||||
Alternative Approaches to Commercial Property Price Indexes for Tokyo. Erwin Diewert, University of British Columbia, Canada, and Chihiro Shimizu, Reitaku University, Japan | |||||||||
Session 7: Management | |||||||||
Statistics Canada’s Consumer Price Index Enhancement Initiative (CPI EI). Haig McCarrell, Statistics Canada | |||||||||
Quality management. Patrick Kelly, Statistics South Africa | |||||||||
High quality official statistics – benchmarking as an integral part of a quality management system. David Fenwick, International Expert, the United Kingdom |