1. Relationship between Short-term Economic Statistics Expert Group Meeting on Short-Term Statistics 16-18 February 2016 Amman, Jordan

2. Relationship between Short-term Economic Statistics Overview 1.Background 2.What is statistical integration? 3.Situation prior to integration – What changed? 4.Main elements of statistical integration 5.Statistical integration tools 6.Relationship between priority STEIs 7.Components of early warning systems 8.Discussion issues

3. 1. Background UNSD Data Template for Short-term Economic Statistics Formulation of questionnaire for pilot countries: Egypt; Jordan; Lebanon; Oman; Palestine; Qatar; Tunisia Strengthening the Statistical Capacity of ESCWA Member Countries in Producing and Disseminating Short-term Economic Indicators for Sustainable Growth Identification of priority short-term economic indicators Preparation of Regional Guidelines on Short-term Economic Statistics Based on Selected ESCWA Member Countries publication Other frameworks Principal Global Indicators (PGIs) Principal European Economic Indicators (PEEIs) Core set of Economic Statistics (UNESCAP) Other frameworks Principal Global Indicators (PGIs) Principal European Economic Indicators (PEEIs) Core set of Economic Statistics (UNESCAP)

4. 2. What is statistical integration? Is the implementation of processes by national statistical agencies that lead to the collection, compilation of a range of economic statistics that present a consistent and coherent picture of economic activities for policy, business and other analytical uses. Key processes of statistical integration include: use of common concepts, definitions; classifications; estimation methods; and data sources for statistical reconciliation Consistency / coherence is sought within countries between different STEIs, over time and between countries

5. 3. Prior to statistical integration Statistical collections initially developed by statistical domain stovepipes Each domain used its own frames, key concepts (codelists), classifications, processing systems Resource consuming – duplication of effort across statistical agency (high overheads) Resulting outputs at national level were inconsistent International comparisons very difficult National account / BoP compilation difficult – input series required extensive adjustment

6. 3. What changed: Integration drivers Integration within national economies Globalisation Explosion of information environment – information more readily available User driven: Public Government Business User driven: Public Government Business Chicken and egg: What came first?

7. 4. Main elements of statistical integration Classifications Variable concepts Coverage Data sources Compilation methods Dissemination media Interrelated Impact on dimensions of data quality:  Relevance  Accuracy  Timeliness & punctuality  Accessibility & clarity  Comparability  Coherence Covered in international standards

8. 4. Main elements of statistical integration Classifications Variable concepts Coverage Data sources Compilation methods Dissemination media SNA integration framework

9. 5. Statistical integration tools Classifications Variable concepts Coverage Data sources Compilation methods Dissemination media International Glossaries SDMX MCV CODED (Eurostat) Metadata Glossary OECD Glossary International Glossaries SDMX MCV CODED (Eurostat) Metadata Glossary OECD Glossary Corporate registers and area frameworks Classification systems (activity, product, occupation) ISIC CPC ISCO Classification systems (activity, product, occupation) ISIC CPC ISCO Integration of systems and processes GSBPM GAMSO GSIM SDMX DDI CSPA Integration of systems and processes GSBPM GAMSO GSIM SDMX DDI CSPA International statistical standards and guidelines SNA integration framework

10. 5. Integration tools: Integration of systems and processes GSBPMGeneric Business Process Model GAMSOGeneric Activity Model for Statistical Organisations GSIMGeneric Statistical Information Model SDMXStatistical Data and Metadata Exchange DDIData Documentation Initiative CSPACommon Statistical Production Architecture

11. Common terminology is important! MCV SDMX Glossary Metadata Glossary CSPA GSBPM

12. GDP Production GDP Expenditure GDP Income GDP Production GDP Expenditure GDP Income Production index, industry Production index, construction Turnover index by major division, industry Turnover index by major division, retail Production index, industry Production index, construction Turnover index by major division, industry Turnover index by major division, retail Import price index Export price index Import price index Export price index Producer price index Residential property price index Household debt Employment by activity Consumer & business confidence indicators Identification of appropriate national data source(s) – business / household surveys, administrative data UN, Eurostat, OECD guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods UN, Eurostat, OECD guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF, Eurostat, OECD guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF, Eurostat, OECD guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF, Eurostat guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods IMF, Eurostat guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods ILO, UN guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods ILO, UN guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods ILO Resolutions Classifications Variable concepts Coverage Data sources Frequency Compilation methods ILO Resolutions Classifications Variable concepts Coverage Data sources Frequency Compilation methods UN, OECD, JRC guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods UN, OECD, JRC guidelines Classifications Variable concepts Coverage Data sources Frequency Compilation methods Flash estimates UN guidelines on Flash Estimates UN guidelines on Flash Estimates SNA 2008 integration framework 6. Relationship between priority STEIs Survey

13. Consumer tendency surveys Business tendency surveys Consumer confidence indicators Business confidence indicators Business confidence indicators Composite business cycle indicators Composite business cycle indicators Quantitative STEI component series Quantitative STEI component series Composite leading indicators Qualitative data Quantitative data 7. Components of early warning systems

14. Thank you Questions? Denis Ward teedward@gmail.com