The unece organizes with the financial support of the World Bank

Comparison of Series – Cumulative Data

Comparison of Series – Monthly Data

Time Series Methodology

• Problems with cumulative data

• International comparison and analysis not possible

• Slow identification of turning points

• Change from the previous period in seasonally adjusted data provides faster indications of turning points

• User cannot derive a correct monthly time series

• Revisions to the earlier periods cannot be matched to the correct periods of time
• Time series from cumulative data have incorrect seasonality

From Cumulative to Monthly

Time Series Methodology

• Fixed base indices and/or absolute values for discrete periods are recommended

• Time series to be linked or calculated back when base year is changed

• Not to shorten the series or to leave breaks (the series should not start from its b.y.)

• Previous periods need to be revised to come up with reliable time series

• Currently 10 countries publish time series of more than 24 observations

Where is the Economy Going?

Seasonal Adjustment

• SA data calculated by 11/17 countries

• Need for training, materials/guidelines and support on methodological and practical issues

• Expansion of number and length of seasonally adjusted series

• More metadata on SA needed for the users

• Development of release practices of SA

• Standardization of compilation and release practices would enhance quality of SA

Conclusions of the Assessment

• Need for longer time series

• Historical time series to be build and maintained
• Backcalculation or linking in base year changes

• Improve international comparability

• Seasonally adjusted data would enable comparison
• More comparable information on the service sector

• Review data collection techniques

• Introduce sampling (and allow revisions)
• Use administrative sources

• Publication policy

• New release practices (SA, time series, revisions)
• More detailed metadata

General Recommendations on STS

• Carsten Boldsen Hansen

• Economic Statistics Section, UNECE

Overview

• General guidelines and quality

• Sources for methodology guidelines

• Response burden

• STS vs. SBS

• Time series

• Release Practices

• Metadata

• User consultation

“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 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

General Guidelines

• The Fundamental Principles of Official Statistics (UN) http://unstats.un.org/unsd/dnss/gp/fundprinciples.aspx

• Quality of Statistics

• Data Quality Assessment Framework (IMF) http://www.imf.org/external/np/sta/dsbb/2003/eng/dqaf.htm
• ESS quality framework (EC) http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/introduction
• OECD quality framework (OECD) http://www.oecd.org/document/43/0,3343,en_2649_33715_21571947_1_1_1_1,00.html

• Handbook of Statistical Organization, The Operation and Organization of a Statistical Agency, 2003

• http://unstats.un.org/unsd/dnss/hb/default.aspx

The Fundamental Principles

• indispensable for a democratic society

• statistical agencies decide methods and procedures

• present data according to scientific standards

• comment on erroneous interpretation

• statistical agencies choose the data sources with regard to quality, timeliness, costs and burden

The Fundamental Principles

• strictly confidentiality of individual data and use exclusively for statistical purposes

• statistical laws, regulations and measures to be made public

• coordination among statistical agencies within countries

• use of international concepts, classifications and methods

• bilateral and multilateral cooperation

Respondent Burden

• Minimizing respondent burden should be an important objective vs. cut-off sampling

•