Upload
warren-moore
View
213
Download
0
Tags:
Embed Size (px)
Citation preview
Integration of Annual Economic Collections – The Australian
Experience
ICESIII, Canada, 2007Presented by Eden Brinkley
Overview of presentation
• Overview of ABS annual collections– Current collections– Client concerns
• Annual Integrated Collection (AIC)– Motivation – Understanding client needs– Basic AIC model– Design and estimation– Editing processes and systems– Developing a common culture
• Key learnings
Current annual collections
• Annually– Economic Activity Survey (economy wide)– Manufacturing Industry Survey– Mining and Utilities Survey– Selected Service Industries Surveys
• Biennially– Information and Communications Technology Survey
• Every 6-7 years– Construction Industry Survey– Retail Industry Survey– Wholesale Industry Survey
Client concerns with current collections
• Lack of coherence amongst the annual collections – Releasing statistics, nominally for the same industry, that did
not accord
• Need for operational efficiency and simplicity– Annual collections operated as individually managed projects
with different methodologies, systems and processes
• National Accounts Branch felt the annual estimates were not always ‘fit for purpose’– Lack of coherence with quarterly collections– Outputs not always aligned with National Accounts needs– Lack of sectors splits and regular product detail
Annual Integrated Collection (AIC)
• Established a project in 2003 to integrate annual collections into a single system known as the AIC– Common designs directly focussed on meeting
client needs– Common systems infrastructure– Changed culture and motivation for staff
• focus on a ‘big picture’ program
• Phased in progressively over 4 years from the 2004-05 reference year
Approach to integration
• Started with a ‘bottom up’ approach– Progressively align elements of the various
collections in the program (e.g scope, estimation methodologies, etc.)
• Moved to a ‘top down’ approach– Start with a comprehensive prioritized
assessment of client needs– Design collections to meet these needs
Key client needs
• National Accounts requirements (must have)– Financial data across economy at Supply Use
industry level annually– Financial product level data every 1 to 9 years,
depending on priority
• Other client requirements– A range of financial, structural and activity data
• By fine industry levels, business size, and broad geographic region
– Alternative views of the data across industries• e.g. satellite accounts
Broad AIC model
• A two-part integrated collection vehicle
– An annual economy-wide core collection
– A rolling program of more detailed but less frequent industry-specific collections linked to the core
• Administrative by-product data used, as much as possible, to complement the directly collected survey data– Decision criterion: “is the resulting data fit for
purpose?”
AIC collection program (example)
SU = Su p p ly U se an d IO = In p u t/O u tp u t
In du stry Y ear 1 Y ear 2 Y ear 3 Y ear 4 Y ear 5 Y ear 6 Y ear 7 Y ear 8 ...
C ore program
A ll in du stries
R oll in gprogram
S U in du stry A IO in du stry A
IO in du stry B
IO in du stry C
S U in du stry B
S U in du stry C IO in du stry DIn du stryclass A
In du stryclass B
IO in du stry E
SU = Supp ly /U se and IO = Input/O utput
Design constraints
• The sample is designed to meet the following constraints:
– Core collection to have a sample size of around 15,000 units each year
– Rolling program of collections to have a further 10,000 units each year
– Sample for the rolling program is effectively a top-up of the core sample for the relevant industries
– Industry estimates from the core and rolling program to be the same/aligned wherever possible
Scope and coverage
• Scope should ideally align with the scope of Australian National Accounts– All Australian based business activities of business entities
operating during the reference period– In practice there are some exclusions (e.g. households
institutional sector)
• Continuing to explore the inclusion of government units in core estimates for the first time
• Coverage is restricted to businesses on ABS Business Register at 30th June each year
Frame
• Drawn from the ABS Business Register
• ABS Business Register has two populations– ABS maintained complex population
• Approximately 15,000 units• Accounts for about half of total operating income, and
about a third of employment
– Australian Taxation Office maintained simple population
• Almost 2 million units• No feedback allowed
Sample design
• Stratification– Industry x sector x broad region x size
• Design variables– Industry value added, Compensation of
employees, Gross operating surplus, Gross fixed capital formation
• Reliable estimates of movement are the first priority– In practice the design is mostly based on level
estimates
Estimation
• Generalised regression (GREG) estimation used for directly collected survey data– Business Activity Statement (BAS) data used as
benchmarks
• BAS data also substitute for very small businesses in scope of the AIC– Substitution leads to challenges in modelling data
items not found on the tax file (e.g. employment)
• Preliminary estimates to National Accounts nine months after reference period– Publish within 12 months
AIC Estimation Framework
Complete Enumeration StreamData source: AIC surveyPopulation: 3,500 units (0.2% of total)Survey Sample: 3,500 units (55% of BAS Total sales)
Industry
Po
pu
lati
on GREG Estimation Stream
Data source: AIC survey, Benchmark Source: BASPopulation 1.2 million (63.2% of total)Survey Sample: 12,000 units (44% of BAS Total sales)
Employment* > 300
BAS Substitution Stream Data Source: BAS dataPopulation: 0.7 million units (36.6% of total)Survey Sample: 0 units (1% of BAS Total sales)
Maximum of 2.5% of Industry class turnover
Integrated outputs
Clie nt Re quire m e nts(ide ntifie d by the AIC
progra m se ttingproce ss)
Annua l'core '
re quire m e nts
Additiona l'rolling'
re quire m e nts
Estim a tion Inte gra te d suite of AIC outputs(de signe d to m e e t clie nt re quire m e nts)
Da ta Source
Adm inby-product
Dire ctlycolle cte d
surve y da ta
GREGEstim a tion
Da taSubstitution
M ode lling/synthe tic
e stim a tion
Core outputs- Broa d fina ncia ls- Broa d de m ogra phics
Rolling outputs- De ta ile d fina ncia ls- De ta ile d de m ogra phics- P roduct a nd Activity da ta- Cha ra cte ristics da ta
Instrument design
• Aiming to rationalize both data content and the different form types used across AIC collections – Understanding client requirements
• Mapping project established to map SNA concepts to questions on forms– Success in developing improved ‘Standard
Question Wording’ for 2006-07 – More rigorous process again for 2007-08
• Aiming to investigate use of tailored forms for groups of similar businesses
Integrated infrastructure
• ABS has already built the basis of an integrated end-to-end systems environment
• Main components include:– Input Data Warehouse– Intelligent forms scanning facilities– Blaise for data capture and editing– Standard estimation and imputation system– Provider management system– Central repository for storing aggregate data– Central metadata repository
• AIC is both influencing and leveraging off this integrated end-to-end environment
Editing processes and systems
• AIC core and rolling collections steadily implementing best practice– Developing detailed editing strategies and common
processes for each collection
• Aiming to deliver ‘fit for purpose’ data at minimum cost
• Editing re-engineering supported by– Editing Guide and training for AIC collection areas– Editing workshops for AIC collections– Common use of end-to-end systems developments
• Mainly focused on new micro editing tools to date
Micro editing process
1. Prepare for micro editing process
2. Clean data for selective editing
3. Identify and treat critical stream
4. Apply automatic amendments
Editing strategy and other metadata
Other data to support micro editing
Captured unit record data for current cycle
Automatic editingand imputation
Selective editing
Initial editing
Plan and prepare
Sufficient data for macro editing
No
Yes
Other enablers
• Editing strategies critically reviewed by peers• Formal senior level sign-off gives legitimacy to
new approaches being taken• Analysts focussed on validating the highest
priority outputs for key clients• Clerical attention focussed only on the
important units• Earlier system specifications meant systems
were delivered on time
Gains from improved editing
0
10
20
30
40
50
2003-042004-052005-06
Percentage of units edited
0
5
10
15
20
2003-042004-052005-06
Nominal cycle time Months after ref period
0
50
100
150
200
2003-042004-052005-06
Nominal staff months
Future editing related work
• Integrated approach to imputation and outliering
• Adoption of common macro editing processes and tools
• Integrated output and dissemination strategy• More emphasis on ensuring common
process flows across collections generally • Improved documentation (e.g. AIC quality
manual)
Common AIC culture
Common Common cultureculture
Central coordination
team
Senior management
support
Standard tools and
frameworks
Clear goals and priorities
One virtual team
Increased
communication
Key learning points
• Focus on priority client needs at each stage of the collection design and conduct to ensure outputs are ‘fit for purpose’
• From time to time take a green-fields/top down approach to collection design
• A good collection frame is the foundation for the production of quality statistics
• Work to maximize use of administrative data for design, estimation, data supplementation, etc.
• Integrated processes and systems will lead to both improved efficiency and data quality
• Build systems from the perspective of the end user
• Build a unified culture – one which involves compromise for the greater good