Transcript Business Sampling Frame (BSF)

South African National Accounts
benchmarking experience
Gerhardt Bouwer
1
Background
 Shared responsibility in compilation of
South African national accounts
 Stats SA responsible for production, income
 SARB responsible for expenditure
 Close liaison between two organizations
on reconciliation of their estimates
 Stats SA and SARB jointly benchmarks
South Africa’s estimates of national accounts
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South African benchmarking experience
 Previous benchmark saw a lot of changes
in data, data sources and methodology
 These changes resulted in large level
changes in data
 These changes influenced the national
accounts time series data
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Business Sampling Frame (BSF)
 Stats SA developed a new BSF, based on
Income Tax and VAT database
 Survey data used for benchmark based on
new BSF, while survey data before
benchmark was based on previous used
Business Address Register (BAR)
 The new BSF showed that SA economy
was on a much higher level
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Business Sampling Frame (BSF) cont.
Year
2000
Output at
basic prices
PreBenchmark
level
(R’million)
After
Benchmark
level
(R’million)
% change
in level
1 619 481
1 893 686
16,9
5
Business Sampling Frame (BSF) cont.
Value added (current
prices) - Year 2000
Pre-Benchmark
level (R’million)
After
Benchmark
level
(R’million)
%
change
in level
54 951
63 391
15,4
Manufacturing
150 198
159 107
5,9
Trade, hotels,
restaurants
107 299
122 702
14,4
Other personal
services
48 979
51 382
4,9
All Industries
808 461
838 218
3,7
Mining
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Business Sampling Frame (BSF) cont.
1998
1999
2000
2001
2002
2003
PreBenchmark:
GDP
(R’billion)
739
801
888
983
1 121
1 209
After
Benchmark:
GDP
(R’billion)
742
814
922
1 020
1 165
1 251
% change in
level
0,5
1,6
3,8
3,7
3,9
3,5
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Economic Activity Survey (EAS)
 Stats SA started to use EAS with benchmark
 EAS formed cornerstone of the calculation
of national accounts estimates
 Confrontation of data in SUT framework
suggested that the distribution of economic
activity between different industrial groups
was not correct
8
Economic Activity Survey (EAS) cont.
 Two main explanation for this:
 Incorrect classifications
 Enterprise vs establishment
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Supply and use tables (SUT)
 Started to use SUT to calculate annual
GDP estimates
 SUT balanced on 95-industry, 48-commodity
 Confrontation between approaches on
commodity level, previously only on
big totals
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Double-deflation
 Annual sets of SUT’s were developed
for each year, which made it possible
to introduce double-deflation
 Specific price indices could be linked to
corresponding commodity groups
 Derivation of a weighted intermediate
consumption and output for each industry
 Previously deflation by single price index
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Quarterly estimates – Denton Method
 Quarterly estimates based on annual
nominal and real estimates
 Preserve as much as possible of the short
term movements in the new series
 Quarterly ratio average to annual ratios
for each year
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Conclusion
 Large level changes in data should be worked
in over longer period than only two years
 More frequent annual data than periodical
data might influence time series
 Establishment vs enterprise will always
create problems
 Changing of methodology might also
influence time series
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End
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