1 GULAB SINGH UN Statistics Division DIAGNOSTIC FRAMEWORK: National Accounts and Supporting Statistics SELF ASSESSMENT TOOL Workshop on the Implementation.

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DIAGNOSTIC FRAMEWORK: National Accounts and Supporting Statistics
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Presentation transcript:

1 GULAB SINGH UN Statistics Division DIAGNOSTIC FRAMEWORK: National Accounts and Supporting Statistics SELF ASSESSMENT TOOL Workshop on the Implementation of the 2008 SNA, Kiev, 29 November – 2 December 2011 Agenda item 4b

Outline of Presentation  ISWGNA Strategic Framework : shared steps ◦ for National Accounts and Supporting Economic Statistics - From Diagnosis, Vision to Programme  Diagnostic Framework (DF): proposed tool ◦ for National Accounts and Supporting Economic Statistics (DF-NA&ES) 2

ISWGNA Strategic Framework: Implementation of 2008 SNA Programme  Three distinct stages irrespective of level of statistical development of country ◦ Stage I - Review of strategic framework and detailing of national and regional implementation programmes; ◦ Stage II - Adaptation of classification frameworks, business registers and frames, surveys, administrative data sources and information technology infrastructure; ◦ Stage III - Application of adapted frameworks and source data, backcasting and changeover to 2008 SNA. 3

ISWGNA Strategic Framework: From Diagnosis, Vision to Programme  Need to focus on system wide approach for improving National Accounts and Supporting Statistics  One element of Regional Programme is the assessment of capacity constraints in the region  Proposed diagnostic tool to help countries to assess adequacy or otherwise of their national statistical production process to support implementation of the 2008 SNA  This tool will help countries to make self assessment of statistical prerequisites outlined in Stages I and II of the 2008 SNA implementation strategy 4

ISWGNA Strategic Framework: From Diagnosis, Vision to Programme  Diagnosis and vision document /statistical agenda ◦ For improving the availability and quality of the basic economic statistics and institutional arrangements ◦ Through system-wide consultation with stakeholders, policy planners and other users including the academia and business community ◦ Through a vision document for minimum core set of short-term and structural indicators ◦ With agreed human and financial resources and donor/external coordination  Implementation programme ◦ Based on vision document/statistical agenda with agreed coordination and monitoring indicators 5

Diagnostic Framework Approach  System-wide approach: ◦ for basic economic statistics and related institutional environment  Diagnostic approach: ◦ for structured assessment of current strengths and weaknesses of statistical production process  Self assessment approach: ◦ for national ownership of the global/regional initiative for the 2008 SNA implementation strategy  Global and regional coordination approach: ◦ for sharing self assessment for coordination and monitoring of the regional and global program 6

Diagnostic Framework El ements  Information structure ◦ For planning, monitoring and evaluating the implementation of the SNA with other partners of ISWGNA  Taxonomies based on UN Classification of International Statistical Activities ◦ Listing of domains that provide structured presentation of statistical activities ◦ Classifies statistical activities aimed at collecting, producing and disseminating data, developing standards, harmonisation and implementation approaches in official statistics 7

Diagnostic Framework Classification of International Statistical Activities Domain 1: Demographic and social statistics 1.2 Labour 1.5 Income and consumption Domain 2: Economic statistics 2.1 Macroeconomic statistics 2.2 Economic accounts 2.3 Business statistics 2.4 Sectoral statistics Agriculture, forestry, fisheries Energy Mining, manufacturing, construction Transport Tourism Banking, insurance, financial statistics 2.5 Government finance, fiscal and public sector statistics 2.6 International trade and balance of payments 2.7 Prices 2.8 Labour cost 8

Diagnostic Framework International Classification of Statistical Activities Domain 4: Methodology of data collection, processing, dissemination and analysis 4.1 Metadata 4.2 Classifications 4.3 Data sources Population and housing censuses; registers of population, dwellings and buildings Business and agricultural censuses and registers Household surveys Business and agricultural surveys Other administrative sources 4.4 Data editing and data linkage 4.5 Dissemination, data warehousing 4.6 Statistical confidentiality and disclosure protection 4.7 Data analysis 9

Diagnostic Framework I nternational Classification of Statistical Activities Domain 5: Strategic and managerial issues of official statistics 5.1 Institutional frameworks and principles; role and organisation of official statistics 5.2 Statistical programmes; coordination within statistical systems 5.3 Quality frameworks and measurement of performance of statistical systems and offices 5.4 Management and development of human resources 5.5 Management and development of technological resources (including standards for electronic data exchange and data sharing) 5.6 Coordination of international statistical work 5.7 Technical cooperation and capacity building 10

Diagnostic Framework Statistical production process  Statistical production process – Outputs ◦ Domain 1: Income and expenditure of households and labor statistics ◦ Domain 2: Economic statistics  Statistical production process – Inputs: ◦ methodology for data collection, processing, dissemination and analysis Domain 4.1 Metadata Domain 4.2 Classifications Domain 4.3 Data sources Domain 4.4 Data integration, editing and data linking Domain 4.5 Dissemination and communication Domain 4.6 Statistical confidentiality and disclosure protection Domain 4.7 Data analysis 11

Diagnostic Framework Statistical production process  Statistical production process – Strategic managerial issues ◦ activities which are applicable to all statistical activities under domain 2 and some selected activities under domain 1 Domain 5.1 Institutional framework and principles Domain 5.2 Statistical programmes; coordination within national statistical systems Domain 5.3 Quality framework and management of performance Domain 5.4 Management and development of human resources Domain 5.5: Management and development of technological resources (including standards for exchange and data sharing) 12

Diagnostic Framework Structure  Structure ◦ Domain ◦ Data Category ◦ Data Indicator(s): each indicator under these blocks has 2-6 quality questions to assess its adequacy or otherwise as it exists in the system.  Data category by economic activity (GDP by production) ◦ Metadata and data reporting ◦ Statistical registers and censuses ◦ Surveys and administrative sources ◦ Technical cooperation and capacity building, priorities and plans for improvements 13

Diagnostic Framework Structure  Data category by final expenditures (GDP by expenditure – broken down by ICP categories) ◦ Metadata and data reporting ◦ Statistical registers and censuses ◦ Surveys and administrative sources ◦ Technical cooperation and capacity building, priorities and plans for improvements  Data category by institutional sector ◦ Metadata and data reporting ◦ Technical cooperation and capacity building, priorities and plans for improvements 14

Diagnostic Framework Quality variables Metadata and data reporting: ◦ SNA version followed (53/68/93/2008 SNA) ◦ Activity classification (ISIC 3/3.1/4/other) ◦ Product classification (CPC 1/1.1/2/other) ◦ Periodicity (A/Q/M) ◦ Timeliness ◦ Latest reference (base year) ◦ Revision cycle 15

Metadata and data reporting  Annual (Structural) statistics – ◦ Structural analysis of the economy and annual growth rate  Short-term (high frequency) statistics – quarterly and monthly ◦ Early signal of changes of vulnerabilities and business cycle  Recent crises ◦ High frequency statistics for real sector in addition to external, fiscal, financial and monetary sector  GDP, value added  Commodity production  Production index  Production price index  Turnover index  New order index  Employment Diagnostic Framework Quality variables-Periodicity and timeliness 16

Diagnostic Framework Quality variables-Periodicity and timeliness Metadata and data reporting Timeliness  Timely release of information is important to retain the relevancy of data.  Long time lag between collection of data and release of results – makes it ‘stale ’  Failure of providing timely data by NSOs – private players ◦ Annual – 18 months after the close of the reference year ◦ Quarterly – 3 months after the close of the quarter ◦ Monthly – 45 days after close of the month 17

Diagnostic Framework Quality variables- Statistical registers and censuses Statistical registers and censuses  List of all productive units in the economy  Sampling frame for drawing samples for the purpose of conducting sample surveys  Regularly updated to account for the births and deaths of businesses 18

Diagnostic Framework Quality variables-Statistical registers and censuses Statistical registers and censuses Population and Housing Census  Population, labour force  Housing stock Economic Census  List of establishments/enterprises  Limited characteristics of establishments  Useful for drawing up area frame for covering small and informal sector enterprise Agricultural Census  List of agricultural holdings  Limited characteristics of establishments  Useful for drawing up area frame for covering small and informal sector enterprise 19

Diagnostic Framework Quality variables: Use of Administrative Sources Administrative sources  Administrative sources are sources containing information that is not primarily collected for statistical purposes  There is pressure to reduce expenditure, cut costs and improve efficiency Benefits of administrative sources  Less costly – surveys are generally expensive  Reduce the response burden  Good coverage of the target population – eliminate survey errors  Timeliness of statistics – surveys take time to plan, design and pilot questionnaires 20

Diagnostic Framework Quality variables: Use of Administrative Sources Issues in Using Administrative Sources  Units used in those sources do not correspond directly to the definition of the required statistical units (legal units to statistical units – profiling).  The data in administrative sources have generally been collected for a specific administrative purpose (turnover for value added tax (VAT) purposes may not include turnover related to the sales of VAT exempt goods and services)  Classification systems used within administrative sources may be different  Timeliness (different time schedule than that of the NSO advance release calendar) 21

Diagnostic Framework Quality variables: Use of Administrative Sources Issues in Using Administrative Sources  Data from several administrative sources – matching problem  Data from one source may appear to contradict those from another source - may be due to different definitions, classifications or differences in timing, or simply to an error in one source – priority rule)  There are usually a number of problems to overcome when using an administrative source, but these problems can be grouped into categories, for which other countries have usually found solutions 22

Points for consideration Periodicity  Need for review through user consultation – identify some statistical output to be released with greater periodicity  Review the list of high frequency indicators (HFI) compiled by the country - how does it compare with the list developed under the global initiative?  If HFI not compiled – plans for its compilation?  Creation and maintenance of business register 23

Points for consideration – contd.  Need for establishing dialogue with administrative data source agencies for alignment to statistical concepts and definitions?  Countries should take initiatives to use progressively more administrative data  Need for external technical assistance? 24

Thank you 25