General Recommendations on STS Carsten Boldsen Hansen Economic Statistics Section, UNECE UNECE Workshop on Short-Term Statistics (STS) and Seasonal Adjustment 14 – 17 March 2011, Astana, Kazakhstan

UNECE Statistical Division Slide 2March 2011 Overview  General guidelines and quality  Sources for methodology guidelines  Response burden  STS vs. SBS  Time series  Release Practices  Metadata  User consultation

UNECE Statistical Division Slide 3March 2011 “The use by statistical agencies in each country of international concepts, classifications and methods promotes the consistency and efficiency of statistical systems at all official levels.” The ninth principle of The Fundamental Principles of Official Statistics in the Region of the Economic Commission for Europe, UNECE

UNECE Statistical Division Slide 4March 2011 General Guidelines  The Fundamental Principles of Official Statistics (UN)  Quality of Statistics Data Quality Assessment Framework (IMF) ESS quality framework (EC) OECD quality framework (OECD)  Handbook of Statistical Organization, The Operation and Organization of a Statistical Agency,

UNECE Statistical Division Slide 5March 2011 The Fundamental Principles 1.indispensable for a democratic society 2.statistical agencies decide methods and procedures 3.present data according to scientific standards 4.comment on erroneous interpretation 5.statistical agencies choose the data sources with regard to quality, timeliness, costs and burden

UNECE Statistical Division Slide 6March 2011 The Fundamental Principles 6.strictly confidentiality of individual data and use exclusively for statistical purposes 7.statistical laws, regulations and measures to be made public 8.coordination among statistical agencies within countries 9.use of international concepts, classifications and methods 10.bilateral and multilateral cooperation

UNECE Statistical Division Slide 7March 2011 Respondent Burden  Minimizing respondent burden should be an important objective vs. cut-off sampling  Coordination of data collections would help reducing response burden and to divide it more evenly among respondents  Existing sources of information should be used to the largest extent possible Administrative registers Commercial datasets Data collected by other organizations

UNECE Statistical Division Slide 8March 2011 Coherence = Degree to which data is logically connected and mutually consistent Coherence within a data set Coherence across data sets  common concepts, definitions, valuation principles, classifications and co-operation Coherence over time Coherence across countries  Extent to which the recommendations have been adopted  Link to national accounts important

UNECE Statistical Division Slide 9March 2011 STS vs Structural Statistics (SBS) STS = measures economic developments SBS = a snapshot describing structure & detail  STS and SBS have different data sources, definitions, statistical methods, timing and coverage (fiscal/calendar)  Treatment of changes in the population SBS: the population in the reference year as it is STS: makes different time periods comparable (by correcting for mergers and splits etc)  Further improvement of coherence needed!

UNECE Statistical Division Slide 10March 2011 List of Methodology Guidelines  Methodology of Short-Term Business Statistics (EC),  International Recommendations for the Index of Industrial Production (UN),  Use of Administrative Sources for Business Statistics Purposes (EC),  International Recommendations for Distributive Trade Statistics (UN),  Methodological guide for Producer Price Indices for Services, (EC)  Evolution of Service Statistics, proceedings of a seminar, (EC)  Consumer Price Index Manual, Theory and Practice, 2004 (ILO)  Practical Guide to Producing Consumer Price Indices, 2009 (UNECE/ILO)  Producer Price Index Manual, Theory and Practice, 2004 (IMF)  Export and Import Price Manual, 2008 (IMF)

UNECE Statistical Division Slide 11March 2011 Time Series Recommendations  Fixed base indices and/or absolute values for discrete periods to be provided  New series should be linked to the old series to produce continuous series  Cumulative statistics should be published only as additional information  If seasonality influences the indicator, seasonally adjusted and trend series to be published  Reference period should be a year and be updated when the weights are updated

UNECE Statistical Division Slide 12March 2011 Importance of Long Time Series (1)  Long and consistent time series important for International comparison Analysis Appraisal of business cycles  Current practices of countries vary significantly  Currently no international standards on: Length of time series Methods for backcasting Implementing changes of classifications

UNECE Statistical Division Slide 13March 2011 Importance of Long Time Series (2)  STS regulation (EC) requires time series from 2000, Eurostat recommends much longer series  Methodology of Short-Term Business Statistics: “To carry out statistical analysis such as seasonal adjustment it is generally considered necessary to have observations for a minimum of 5 years… …for example, in the search for turning points it is important to be able to have data available for several complete cycles.”

UNECE Statistical Division Slide 14March 2011 Dissemination  Data should be released as soon as possible Trade off between timeliness and quality  Data to be released according to a set timetable  Confidentiality to be secured  Data made available to all users at the same time  Data to be revised as new information is available  Data to be accompanied by explanations  Contact details of relevant statisticians to be given Source: Index of Industrial Production (UN)

UNECE Statistical Division Slide 15March 2011 Reference Period  Some guidelines by IMF and Eurostat: Prices, output and sales  Monthly (GDP), labour variables at least  Quarterly (un/employment monthly)

UNECE Statistical Division Slide 16March 2011 Timeliness Guidelines  Some guidelines by IMF and Eurostat

UNECE Statistical Division Slide 17March 2011 Metadata and Dissemination Guides  UN The Common Metadata Framework Making Data Meaningful 1 and 2 Guidelines for Statistical Metadata on the Internet Terminology on Statistical Metadata  OECD Data and Metadata Reporting and Presentation Glossary of Statistical Terms Publishing Standards for Datasets and Data Tables  IMF Guide to the Data Dissemination Standards

UNECE Statistical Division Slide 18March 2011 Metadata Management “data about data”  Identify users and provide only valuable metadata  Ensure metadata is easily available  Reuse metadata for integration and efficiency  Preserve history (old versions) of metadata  Document variations from standards  Make metadata work an integral part of production  Create a coherent system for metadata  Ensure that the metadata for users reflects the real production process

UNECE Statistical Division Slide 19March 2011 Contents of Metadata  Purpose and main uses of the statistics  Definitions of the underlying economic concepts  Reference to the respective legislation  Data coverage, periodicity and timeliness  Self assessment of data quality revision history and accuracy of concepts availability, comparability and coherence limitations in the use of statistics  Descriptions of the methodologies used Index formula, weighting and frequency of revising Frequency of re-basing and linking methods Treatment of changes in commodities or quality Source: Index of industrial production (UN) & some NSO’s recommendations

UNECE Statistical Division Slide 20March 2011 User Consultation  Create mechanisms to obtain users’ views on regular basis in order to identify priority areas for improvement ensure responding to user needs provide users with advice on the strengths and weaknesses of your statistics  Important with key indicators (CPI, IPI, GDP...)  Engaging users should be an integral part of the work in the NSO Mutual understanding and exchange of information (=transparency) builds trust Decisions will be made independently by the NSO Source: Practical Guide to Producing CPI (UN)