Training Session on
National Accounts
ICP Global Office
September 2011
2
 ICP requirement:
•detailed data needed
•only once every several years
Disaggregating GDP into the detailed basic headings is
the core part of the national accounts data needed for the
ICP
Countries will experience some difficulties in providing
estimates of final expenditure for all the basic headings
required
Participating countries should assign weights to all basic
headings
3
National accounts data for 2011 need to be available by
July 2012 (some cases based on preliminary data)
Many basic heading details might have to be estimated
by using data relating to years earlier than 2011 to split
the major aggregates for 2011
4
1
Direct estimation
The preferred method, if data sources exist
Extrapolation
Update an earlier expenditure breakdown using assumptions on
population growth, price changes etc
“Borrowing” a
per capita
quantity or
volume
Multiply the per capita quantity or volume by
the population of the “borrowing country” and
the price level index between the two countries
2
3
4
“Borrowing” a
structure
5
Using expert
opinion
Requires
clustering
countries for
each BH or
group of
BHs
Adjust the “borrowed” structure by a vector of
the price level indexes between the two
countries
Consult retailers, manufacturers, marketing experts, chambers of
commerce and other sources
5
Direct estimation
Estimation techniques used in compiling national
accounts can assist in obtaining the detailed data required
for the ICP:
commodity-flow method
supply-use tables (SUTs)
6
Extrapolation
Common cases
i) country to regularly compile annual production-based
measures of GDP but expenditure-based estimates
are available infrequently
2011 level of expenditure GDP can be assumed to be equal to that measured
from the production side of the accounts
The Global Office encourages countries to develop improved procedures to
allocate expenditures to basic headings: Commodity-flow techniques and
supply-use tables
the experience and knowledge of the national accountants, can be invaluable
in calculating the detailed splits required for the ICP
Last resort procedure: prorate the level of GDP according to the basic
heading distribution from the 2005 ICP, if available
7
Extrapolation
ii) Expenditure-based estimates of GDP are available on a
regular basis but there is a considerable lag in producing
them and they have not yet been updated to 2011
statistical surveys
Administrative records (Custom data for Exports and imports of goods,
building approvals for gross fixed capital formation on buildings ,
credit cards for household final consumption expenditure, VAT data )
Other sources of information (publications of regulatory bodies and trade
associations)
8
Extrapolation
ii) Expenditure-based estimates of GDP are available on a
regular basis but there is a considerable lag in producing
them and they have not yet been updated to 2011
statistical surveys
Administrative records (Custom data for Exports and imports of goods,
building approvals for gross fixed capital formation on buildings ,
credit cards for household final consumption expenditure, VAT data )
Other sources of information (publications of regulatory bodies and trade
associations)
9
Consider a
Basic Heading
Yes
Use Direct
Approach
No
1
Use
Extrapolation
Is there data for the
BH for a previous
year?
Yes
Borrow per
capita value
3
No
Yes
No
Yes
2
Is there country
with similar percapita value?
Is there data for the
BH for the year?
Can you obtain
data from expert?
Use Expert
Opinion
5
No
4
Borrow from
country with
similar
structure
10
11
The Model Report on Expenditure
Statistics (MORES)
The MORES aims to assist countries to compile
Detailed
expenditure
values for each
basic heading of
the ICP
classification.
Information on the
splitting
approach
Information on the
indicators that
were used/or are
going to be used
to estimate the
expenditure
values
12
MORES’s Structure
NA data information for the latest year
available
NA data information for 2011
Parameters used in previous tabs
13
Expanded Form 1
Sheets 1 and 4 include initial expenditure values, estimated expenditure
values and the discrepancies between those two values.
GDP Classification
Code
Heading
Initial
Expenditure
Value
1
2
3
100000
Individual Consumption
Expenditure by Households
110100
Food and non-alcoholic
beverages
110111
Discrepanci
es
4
5
Gross Domestic Product
110000
110110
Estimated
Expenditure
Value
Food
Bread and cereals
110111.1
Rice
[...]
[…]
14
Estimation of BH Expenditures
Sheets 2 and 5 compile, for each BH, the detailed information of the
splitting approach and for all indicators used to collect data related to
National Accounts and reveals the estimated expenditure values.
MORES Template
Code
Name
1
2
100000
#
Indicator
name
Sour
ce
name
Year
Value
Unit
3
4
5
6
7
8
Rice
Splitting Approach
2
Extrapolation
Estimated Expenditure for
Code
15
Final Expenditure Values
Sheets 3 and 6 summarize the final expenditure values for the latest year
available or for 2011 respectively and it will be automatically filled with the
discrepancy information of the initial and estimated expenditures values.
GDP Classification
Code
Heading
1
2
100000
Individual Consumption
Expenditure by Households
110100
Food and non-alcoholic
beverages
110111
3
Gross Domestic Product
110000
110110
Expenditure
Value
Food
Bread and cereals
110111.1
Rice
[...]
[…]
16
Sheets
Complete column 3 of sheet 1 with whatever aggregate
estimates are available
1
1
GDP
Classification
Codes
1
Classification
Headings Names
2
Initial
Expenditures
Values (GDP and
main uses)
3
Basic heading
values estimated
using the
proposed 5
approaches
4
Discrepancies
(3)-(4)
5
2
2
3
From 2
to 1
Column 4 of sheet 1 receives expenditures values from sheet 2
4
1
Discrepancies between columns 3 and 4 appear under column 5
5
1 or 2
6
3
Apply 5 approaches
Make adjustments to resolve discrepancies
Read results if discrepancies solved
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18
Completing MORES - Example
Step 1
ICP Code
Heading
Initial
Estimated11
Expenditure Value Expenditure Values
Discrepancies
100000
GROSS DOMESTIC PRODUCT
168527.54
168527.54
0
110000
INDIVIDUAL CONSUMPTION EXPENDITURE BY
HOUSEHOLDS
117081.29
117081.29
0
110100
FOOD AND NON-ALCOHOLIC BEVERAGES
59812.66
59812.66
0.002396
0.00
51634.63
0.00
19335.26
110110
110111
FOOD
Bread and cereals
1101111
Rice
6370.77
1101112
Other cereals, flour and other products
3874.10
1101113
Bread
3435.03
1101114
Other bakery products
1907.83
1101115
Pasta products
3747.53
Complete Table1 with whatever aggregate estimates are available.
19
Completing MORES - Example
Step 2
Name
Rice
Please indicate all the approaches
used in calculation of expenditure for
this basic heading. Enter a number (15).
2 Extrapolation
#Indicator Name
1Sales of Rice
Source Name
Retail Census
Year
2007
Value
5364
2Population increase from 2007 to 2011
3CPI price increase
Population Census
CPI
2011
2011
5.30%
12.1%
2011
6331.74
2011
19216.79
Household
Expenditure Survey
2009
17965.00
Population Census
CPI
2011
2011
2.60%
4.90%
2011
19335.26
1101111
6370.77
4Adjusted expenditure for rice (1,2,3)
Summation of adjusted basic heading
5 values under "bread and cereals"
Expenditure for "bread and cereals"
6 subgroup
7Population increase from 2009 to 2011
8CPI increase for this subgroup
Adjusted expenditure for "bread and
9 cereals" (6,7,8)
Estimated
expenditure for
Complete Table 2 for each basic heading using five splitting approaches.
20
Completing MORES - Example
Step 3
ICP Code
Heading
100000
110000
GROSS DOMESTIC PRODUCT
INDIVIDUAL CONSUMPTION EXPENDITURE BY
HOUSEHOLDS
110100
110110
110111
1101111
1101112
1101113
1101114
1101115
FOOD AND NON-ALCOHOLIC BEVERAGES
FOOD
Bread and cereals
Rice
Other cereals, flour and other products
Bread
Other bakery products
Pasta products
Expenditure Value
168527.54
117081.29
59812.66
51634.63
19335.26
6370.77
3874.10
3435.03
1907.83
3747.53
Table 3 will be automatically filled once discrepancies between
aggregate figures and summation of BHs have been resolved.
21
Approach
Count
1
Direct estimation
108
2
Extrapolation
20
3
Borrow per capita value
8
4
Borrow structure
13
5
Expert opinion
40
total
189
Indicator
Count
1
CPI
45
2
Government final accounts
34
3
Population Census
30
4
Expert opinion
29
5
Household Expenditure Survey
24
Summation of frequency of major indicators
162
48 indicators were used and five major indicators account for 46% (162 out of 351).
22
Fictitious country case statistics
Number of
sources
Case study
counts
Individual consumption expenditure by households
20
13
Individual consumption expenditure by NPISHs
1
1
Individual consumption expenditure by government
8
1
Collective consumption expenditure by government
1
1
Gross fixed capital formation
8
5
Changes in inventories & net acquisitions of valuables
4
3
Balance of exports and imports
3
1
23
Multiple Approach Examples
Name
Actual and imputed rentals for
housing
2 Extrapolation
4 Borrowing structure
Name
Out-patient paramedical services
1 Direct estimation
5 Expert opinion
Indicator Name
Source Name
Year
Value
1Expenditure value for 2008
Rental survey
2008
450.45
2Rents increase
3Actual rents
Number of dwellings (no change in the
4 number of dwellings since 1996)
Ratio of average rent to household
5 income
CPI
Own-estimation
2011
2011
11%
500.00
Population Census
Structure of a
neighboring country
Government
statistics
Own-estimation
Estimated
expenditure for
1996
1
2011
22%
2011
2011
15000.00
3300.00
1104111
3800.00
6Annual household income
7Imputed rents
Indicator Name
1Total outpatient services
2Proportion of paramedical services
5
6
Source Name
Government final
accounts
Year
Value
2011
218
Expert opinion
2011
25%
Estimated
expenditure for
1302123
54.50
24
Issues
Lack of sources
Lack of overall resources, heavy dependence on
expert opinions
Iterative process
Iterative process occurs when borrowing a
structure from another country
Distribution of
specific BHs
Distribution of specific basic headings such net
expenditures abroad
Limited adoption of
imputing methods
Limited adoption of imputing methods including
the user cost method (housing)
25
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