Transcript Effective proposals for economic statistics

Effective study proposals for
economic statistics development:
“SBRs in focus”
Zeynep Orhun Girard
Statistician
UN ESCAP Statistics Division
2 December 2016
This presentation discusses…
• Why analytical studies are important for the
implementation of the Regional Programme
• How RPES supports analytical capacity
building in national statistical systems
• The criteria for effective national studies
• Dissemination and use of national studies
RPES is a framework for economic statistics capacity
building
4 outputs or “strategic
interventions…”
Advocacy
Advocacy
Coordination
...to deliver our common vision...
NSSs in Asia-Pacific have capacity to
produce & disseminate the Core Set in
line with international standards,
including in support of SDG monitoring
...and reach our key goal of RPES
Infrastructure
Infrastructure
Skills
Improved soundness of economic
analysis & decision making through
increased availability and effective
use of timely, reliable and comparable
economic statistics
RPES progress is monitored based on:
• Activities that are delivered under each
strategic intervention and their results for
capacity to produce and disseminate
economic statistics
• Milestones of the Core Set of Economic
Statistics implementation (periodicity)
Country A
Price and Costs
Demand and Output
Income and Wealth
Core Indicator
Consumer price index (CPI)
Producer price index (PPI)
Commodity price index
External merchandise trade price
indices
Wages / Earnings data
Labour costs index / Wage index
GDP (production) nominal and real
GDP (expenditure) nominal and real
External trade – merchandise
External trade – services
Short-term indicator (STI) - industry
output
STI – services output
STI – consumer demand
STI – fixed investment
STI – inventories
Economy structure statistics
Productivity
Integrated national accounts
Institutional sector accounts
Balance of payments (BOP)
International investment position (IIP)
External debt
Income distribution
Reported Freq.
Quarterly
Quarterly
Weekly
RPES recommendations
Quarterly

Quarterly

Monthly

Unavailable
Monthly
×
Annually
Annually
Annually
Annually
Annually
Annually
Quarterly
Quarterly
Quarterly
Quarterly
Monthly
Quarterly
●
●
●
●
●
●
Monthly
Quarterly

Unavailable
Annually
Unavailable
Unavailable
Every 10 years
Unavailable
Annually
Annually
Annually
Unavailable
Quarterly
Every 10 years
Quarterly
Quarterly
Quarterly
Quarterly
Every 5 years
Annually
Annually
Annually
Quarterly
Annually
Quarterly
Every 5 years
×
●
×
×
●
×


●
×

●
Periodicity alone is not sufficient to
assess quality of a statistical output
1. Integrity
2. Methodological
Soundness
3. Accuracy and
Reliability
4. Servicability
5. Accessibility
- institutional integrity
- transparency
- ethical standards
- concepts ,definitions and scope
- classification/sectorization
- basis for recording
- source data
- assessment of source data
- validation of data and statistical outputs
- periodicity and timeliness
- consistency
- revision policy and practice
- data accessibility
- metadata accessibility
- assistance to users
More analysis needed to understand
quality issues on economic statistics
• Problem: NSSs do not systematically use the
statistics they produce hampering
identification and remedy of quality gaps
• Reasons: Inadequate analytical skills in NSOs
and other agencies, lack of resources (staff
time/financial) and of institutional guidance,
e.g. quality assurance policies
• Available support: ESCAP Resource Facility &
other development partners
ESCAP Resource Facility (RF) is a pool
of funds
…that supports national statistical systems to
undertake analysis and research in the form of
national studies for developing economic statistics.
ESCAP assistance to national studies also covers:
• Expert missions in support of the national study
• Facilitation of peer-to-peer exchanges
• Research-based training, especially for countries
with special needs
Countries select study topics based on
RPES areas & national priorities
• Economic statistics topic areas (Core Set) and
linkages between economic statistics and other
domains of statistics
• Statistical infrastructure for economic statistics
• Institutional setting for economic statistics
production and dissemination
Effective proposals meet the
selection criteria
Required
• Alignment with RPES and priorities in NSDS/similar
plan
• Clear linkage between results, activities and the
resources required
Desirable
• National studies conducted in cooperation by multiple
national agencies
• National studies with gender equality focus
• National studies on economic statistics underlying
sustainable development monitoring
National studies are used to develop
economic statistics
Pilot survey of individual entrepreneurs
• Improve availability and quality of business
statistics
GVA estimation methods for livestock sector
• Improve the methodology for Gross Value Added
(GVA) estimation of total production in the
livestock sector in line with the 2008 SNA
Trade-related pilot survey
• Improve information base for national accounts
by calculating trade margins
RF opportunities for SBR development
Some ideas for SBR study areas:
Demand and output
• Institutional/stakeholder analysis for
national accounts aggregates (production),
SBRs
productivity measures, trade, informal
economy, economy structure, short-term • Develop/improve economic units
model
indicators (industry/services output,
• Review/assess quality of available
consumer demand and investment)
data sources
• Improve quality of SBR (production of
Advocacy
Coordination
business statistics) process
(GSBPM/GSIM)
• Develop/improve maintenance of
SBRs
Statistical Business Register
• Improve use of SBRs—business
demography, economic statistics, etc.
• Explore/assess possible linkages to
Infrastructure
Skills
other databases in the national
statistical system
National studies are regional
knowledge
National studies are disseminated through:
• ESCAP knowledge sharing platform on
economic statistics
• Regional seminars, e.g. as part of the AsiaPacific Economic Statistics Week and the
ESCAP Committee on Statistics
Any questions?