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Introduction
The production account is compiled for fourteen industries according to the International
Standard Industrial Classification (ISIC Revision 3) adopted by the Zimbabwean economy. Under
normal circumstances main sources of data are economic censuses carried out yearly for
agriculture, manufacturing, mining and quarrying, construction, and, water and electricity; annual
surveys for services industries (used to determine cost structures); central and local government
accounts; sales taxes; and employment statistics on numbers of employees and earnings as well as
annual reports of public enterprises. Of late, due to inadequate funding of statistics, major
economic surveys were carried until 2005. Due to this and many other challenges that were being
experienced in the economy, alternative methods based on using some proxy indicators have been
adopted.
2.0 The Calculation of Gross Domestic Product 2000- 2005
2.1 Derivation of a weighted exchange rate
For 2005 the amount of goods imported using the official exchange rates and imported using
parallel market exchange rate were used as weights for deriving unitary exchange rate. This rate
was used to convert the 2005 current price GDP in the Zimbabwean Dollar terms to GDP in US
dollar terms for that year.
2.2 Calculation of Gross Domestic Product
The detailed formula is described below:

A weighted exchange rate was found using the following formula: 0.4* Official exchange
rate + 0.6 * parallel exchange rate. The formula is adopted following the assumption that
40% of the transactions were done on the formal market and 60% were done on the
parallel market.

2005 was used as a benchmark, so the weighted exchange rate for the year was used to
divide the nominal GDP for the same year to come up with the GDP in US dollars

To project backwards the following formula was used:
USDGDPyto * ZIM $GDPkyt  1 ZIM $GDPkyto
Where y stands for the year, and k stands for constant.
This was done for all the years backwards

For the years after 2005, the following formula was used:
USDGDPyto * ZIM $GDPkyti  n ZIM $GDPkyto
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This method assumes that the movement in the GDP deflator is the same as those in the unitary
exchange rate. This in turn implies that the GDP deflation for the GDP in US dollar is one each
year i.e. there is no GDP inflation in US dollars.
If the movements in CPI were equal to the movement to the GDP deflator then all the movements
will be the same as movements in unitary exchange rates
If such a scenario arises where CPI movement is the same as movement of the GDP deflator and
movement in unitary exchange rates, then there is no inflation in US dollar terms
3.0 Compilation GDP for 2009
3.1 Value added Tax Method
Value Added tax (VAT) is a fraction deductible from value addition. In Zimbabwe VAT
constitute 15% of the taxable industries’ value addition. The total VAT collected for 2009 is
equal to $370, 443,408.65
Therefore the total value addition for the industries is $370, 443,408.65*
100
= 2,469,622,720
15
This figure was allocated proportionally to the contribution of each industry to VAT
Non taxable industries estimates were derived from recent surveys and production accounts as
given in the account overleaf:
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INDUSTRY
1.
Agriculture,
Hunting and
Forestry
Normal Source of Data
a) Production Account of Agriculture, forestry
and Fishing
b) Crop production on large scale commercial
farms, c)Agricultural production on small
scale commercial farms,
PROPOSED SOLUTION
Recent Crop assessment data were used. This
data was complimented with data from Tobacco
marketing institutions. VAT data on agriculture
services, forestry hunting and fishing was added
to come up with the value addition for the whole
industry.
d)Agriculture and livestock on communal
lands
c) Agricultural services,
d) Changes in herds communal and
commercial, e)Net additions to capital stock in
large scale commercial farms,
f) Production by Agricultural Estates,
g) Volume and value of livestock slaughtering
and milk and butter fat prodn ,
h)Public Corporations GFCF (From Finance
parastatal bodies summary) Central Govt.
GFCF (From Finance GFS)
3
2.
Mining and
Quarrying
a) Census of Industrial Production tables (final
tables),
b) Mineral production volume index (1990 =
100),
c) Value of mineral production,
d) Central Govt. GFCF (From Finance GFS)
In Zimbabwe almost all the minerals that are
produced are exported the value addition should
be close to the value of mineral exports. The
value addition is 246,083,507 and the value of
exports is 345,406,196 the difference between
being intermediate consumption, 29% of gross
output
3.
Manufacturing
a) Census of Industrial Production tables (final
tables),
b) Index of volume of production of the
manufacturing industries(1990=100)
Value added tax was used. Value addition
was 496,936,835 plus around 20% informal
sector
4.
Electricity and
Water
Production accounts from ZESA holdings and
Zimbabwe National water authority were used.
5.
Construction
a) Census of Industrial Production tables
(final), b) Electrical energy produced in
Zimbabwe,
c) Central Govt. GFCF (From Finance GFS),
ZESA report for GFCF (Finance section)
a) Census of Industrial Production tables
(Prodn section)
b) Construction work done by the public and
private sectors (prodn sect)
c) B roll earnings ( from company returns)
employment section,
d) Construction earnings (from employment
section), e) Central Govt. GFCF ( From
Finance GFS)
6.
Distribution,
hotels and
Restaurants
a) Turnover figures from the taxes department
(Prodn Section),
b) Retail trade value index (Prodn Section),
c) Hotel bed occupancy ( migration statistics),
d) National Accounts questionnaire analysis(
Output and GFCF),
e) Classification of functions of govt. (other
economic activities, central, local),
f) Parastatal bodies Summary (Finance
Section),
g) Central Govt. GFCF (From Finance GFS),
h) Census of Distribution (preliminary figures)
Tax data was used . Data for hotel occupants was
readily available from ZTA be readily available
7.
Transport and
Communication
a) NRZ, PTC, AZ, figures (finance section
parastatals summary), Load tonne Km NRZ
for the above from Production section, Load
tonne Km flown AZ for the above from
Production section,
b) CMED & Civil Aviation ( Finance section),
c) Consumer price index ( Code 17500),
d) Number of vehicles registered (production
Section/Min. of transport), NRZ own account
production ( Production Section),
e) PTC own production ( production Section),
PTC earnings code 7200 (employment
section), PTC revenue annual report ( Finance
section),
f) National Accounts Questionnaire Analysis
both output and GFCF,
g) Parastatal bodies Summary (Finance
Section),
h) Central Govt GFCF ( From Finance GFS)
Percentage change in Imports for building and
construction Material was used to project 2008
figure. The taxation data was very minimal
Taxation data was used.
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Taxation data was used
8.
Finance and
Insurance
a) Report of the Commissioner of Insurance
and Provident Funds(Min of Fin),
b) Finance statistics report (Finance Section),
c) Imputed banking charges
9.
Real Estate
a) Number of electricity connections from
ZESA annual report,
b) Rental income (estimated by national
accounts),
c) Earnings from the employment section
Number of employees (all industries) from
Employment section,
Electricity new connections data was used
a) Classification of Functions of Government
figures from finance section,
b) Public Administration a) Earnings figures
from Employment section,
b) Numbers employed in public
administration,
c) Gross fixed capital formation (GFS Finance
Section)
a) Classification of Functions of Government
figures from finance section,
b) Education Earnings figures from
Employment section,
c) Numbers employed in Education,
d) Gross fixed capital formation (GFS Finance
Section),
e) GFCF non profit making bodies ( Finance
Section)
a) Classification of Functions of Government
figures from finance section,
b) Earnings figures from Employment section,
c) Numbers employed in Health, Gross fixed
capital formation (GFS Finance Section),
GFCF non profit making bodies ( Finance
Section),
Data on industry employees and earnings from
SSB was used, and also data on Governments
Accounts
a)Classification of Functions of Government
figures from finance section,
b) Earnings figures from Employment section,
c) Numbers employed in other services,
d) Gross fixed capital formation (GFS Finance
Section),
e) GFCF non profit making bodies ( Finance
Section), Parastatal bodies Summary (Finance
Section),
f)National accounts Questionnaire analysis
(GFCF)
Vat data was used.
10. Domestic
Services
11. Public
Administration
12. Education
13. Health
14. Other Services
VAT data was used
Government accounts data was used. VAT data
was also used for private education institutions
Government accounts data was used. For private
health institutions VAT data was used.
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3.2 Rough Check on the validity of the GDP figure
Under normal circumstance the taxable industries constitute 53 % of GDP at factor cost
GDP at factor cost is therefore equal to 2,469,622,720 *
100
= 4,659,665,509
53
If we add net the value of net tax which is 758,540,227
The figure comes to $ 5,366,048,433
3.3 Expenditure Tables
The figures are still very preliminary:
15. Private
Expenditure
16. Consumption
Expenditure by
Non Profit
Making Bodies
17. General
Government
consumption
expenditure
18. GCF
Income and Expenditure survey (ICES) and
As a residual
Calculated as a residual
Boosted Output figures from the survey results (Finance
Section)
Data for the survey was used
a) Central Government intermediate consumption by
commodity,
b) Local Government intermediate consumption total,
c) Fees sales and recoveries for both central and local
government,
ICES data, Agriculture Production Account, CIP, COFOG
COFOG data was used
COFOG data was used for
government.
Imports
of
Building and construction
materials will be used, car
parts and plant and machinery
as well
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ICES data, Agriculture Production Account, CIP, COFOG
19. GFCF
20. Changes in stock
21. Exports and
Imports
GMB, oil refinery company, sugar refinery, tobacco sales
floors, agriculture production account
Customs and Exercise data
Reserve Bank BOP data
Reserve Bank BOP data
Imports of Building and
construction materials will be
used, car parts and plant and
machinery as well
Data was obtained from
GMB, GMB, oil refinery
company, sugar refinery,
tobacco sales floors and
changes in lives stocks were
imputed
Customs and exercise data was
used, BOP data was used
BOP data was used
22. Property income
paid and received
from abroad
4.0 Calculation of CPI in United States Dollars
4.1 Introduction
The Central Statistical Office of Zimbabwe produces a consumer price index (CPI) and the month
on month and year on year rates of inflation for the whole country once every month. The CPI is
based on price observations from across the country covering both urban and rural outlets and
weights obtained from the latest Income Consumption and Expenditure Survey (ICES)
As the economic situation characterized by hyperinflation deteriorated in 2007 and 2008 many
products became scarce or unavailable in the country. The number of observations per month of
the prices of the products used for computing the CPI similarly decreased. Under normal
circumstances on average, close to 1500 observations of prices of all products were made every
month. However, less than 500 observations per month were being made in the last half of 2008.
The period was also characterized by an increase in the number of domestic transactions that
were conducted in foreign currency. This began unofficially, as parallel or black market
activities, then there was a mixture of both official (some shops were licensed to sell in foreign
currency) and unofficial domestic transactions in foreign currency, until early in 2009 all
transactions were permitted to be conducted in foreign currency.
It thus became necessary to construct a CPI of transactions in foreign currency. Although the
office had begun observing prices both in foreign and local currency from the middle of 2008,
there were very few recorded observations of prices in foreign currency until December 2008
when a total of 283 observations were recorded.
This paper describes how the challenges of constructing a new foreign currency based CPI,
without conducting an ICES and faced with having to start with a few products that were
available and accommodating an increasing number of products as they reappeared in the market,
were handled. The techniques employed were similar to those used when the number of products
available in the market was decreasing.
The normal method of calculating the CPI and rates of inflation in Zimbabwe
7
(i)
Index
Every month prices of about 385 products are observed from outlets across the country in both
rural and urban areas. The work is organized by province and for each province a geometric mean
price for each item is calculated every month. The mean price is calculated for those items for
which there are matching observations of prices, outlet by outlet in the current and previous
month. A geometric mean price ratio of current to previous month prices is also calculated for
each item, each province. National weighted mean prices and weighted mean price ratios are
calculated from the provincial mean prices and mean price ratios, respectively, using expenditure
weights obtained from the ICES.
The Laspeyres formula is used for calculating the price index. The month on month rate of
inflation is obtained by dividing the current by the previous month’s index and expressing the
change as a percentage while the year on year rate of inflation is obtained by similarly comparing
the figures for the current month with those of the same month in the previous year.
The calculation of the index is done at the lowest subclass level of aggregation. The class index
is then obtained as a weighted mean of its subclass indices. The weight of the sub class is equal
to the sum of the weights of the individual elementary aggregate items that comprise the subclass.
We have
It
=
p q
p q
t
0
0
0
p

p q
P0 q0
P0
t
0
0
=
 pt  p 0 q 0
  p  p q
 0   0 0
=
p
pt




wo
o
pt pt 1
wo
t 1 p 0
=
p
=
p
pt
t 1
x
p t 1
p
t 2
x
p t 2
p t 3
.....
p3
p2
x
p2
p1
x
p1
wo
po
8
In the above pt is the price of an item in the current month, the national weighted mean price as
described above;
p 0 is the price in the base or reference period;
q 0 is the quantity of the product consumed in the base period and generally,
p s is the price of the item in the sth month.
 p0
wo = 
 p q
0
0


 is the weight of item or its expenditure share during the period the Income,


Consumption and Expenditure Survey (ICES) was conducted.
For the above derivation the ICES period is taken as though it is also the reference period for the
prices.
The formula for It is applied at the smallest sub-class level for which prices are observed from the
outlets, for example the bread sub-class. In this instance wo refers to the share of each type of
bread in the total household expenditure as at the time of the ICES.
The index for bread for any month t is thus given by
3 
p  P
P 
I t    it  it 1 ... i  wio
Pio 
i 1  Pit 1  Pit  2
i  1 for white bread, 2 for brown bread and 3 for biscuits.
 Pit 1 Pi 
... wio is taken as a weight Wit .
 Pit 2 Pio 
For computational purposes 
Hence I t 
 p it 
Wit , in the above example.

i 1  it 1 
3
  P
The index for the next level of aggregation is obtained as a weighted arithmetic mean of the
indices of the subclasses in the class. The process is repeated in a similar manner up to the all
items index.
(ii)
Rate of Inflation
The month on month rate of inflation is obtained as It/It– 1 = Rtm.
The year on year rate of inflation is obtained as It/It–1 = Rty
Rtm and Rty are the month on month and the year on year rates of inflation, respectively.
Due to non availability of products we obtained
Rt  
pt
wo
p t 1
9
We then obtained I t  Rt I t 1 for t = 2,3,……
= R1
I1
pt
wo
p t 1
Rt  
Compare
and R 1 r  It / I t 1 for a sub-group like bread.
R1t  I t / I t 1
=
 p W /  p
=
p
=
p
it
it
/ pit 1 
it
pit
i0
x
/ pit 2 Wit 1
pit 1
p
Woo /   pii pit 2  it 2 Wi 0
p1o
pi 0
Wi 0 / 
pit
p
=
it
pit 1
Wi 0
pi 0
pi 0 qi 0
/
i0
p
/  pit 1qi0
=
p
itqio
=
p
it 
=
  p
i 0 qi 0
pi 0 q 0
pit 1
x
pi 0  pi 0 qi0
pit 1qi0
/  pit  Qi 0
pit 1
 pit  pit 1qi 0

 it 1   pit 1qi 0
The index for a subgroup for a month is calculated using the Laspeyers formula.
I t   pit qi 0 /  pi 0 qi 0

For computational purposes this is written as follows:_
p q /p
it
i0
q
i0 i0
=
p
it
/ pio qi 0 /  pi 0 qi 0  pit / pi 0
it
/ pio wi 0
i
=
p
i

wi 0  pi 0 qi 0 /  Pi 0 qi 0

10
=
p
it
/ pit 1 ..... pi 2 r / pi1  pi1 / pi 0 wi 0
it
/ pit 1 wit
i
=
p
wit   pit1 / pit .... pi1 / pi 0 wi 0 
i
The rate of inflation for the subgroup for the month is given by I t / I t 1  Rr .
Milk, cheese and eggs consists of the items sour milk, fresh milk, sterilized milk, powdered milk,
full cream and powdered milk for babies.
The formulae for Ik and Rt could not be used in Zimbabwe when the US dollar based consumer
price index was introduced with the reference December 2008 = 100 but still using the weights
derived from the 2001 Income, Consumption and Expenditure Survey (ICES). The reason was
that there were items that were not available in the market as at December 2008. Infact from a
possible 1400 observations of all items across the country only 280 odd were made in December
2008. The products became increasingly available as the months progressed in 2009.
When a product was not observed at all it was dropped, together with its corresponding weight,
from the calculation of the index for its group and the all items index. For January 2009 only
those items whose prices had been observed both in December 2008 and January 2009 were
included in the calculation of the index. Since the index had December 2008 = 100, for January
2009 the index and the month on month rate of inflation were the same.
An item whose price had not been observed in December 2008, had to have its prices observed
for at least two consecutive month before it was included in the calculation of the index and rate
of inflation.
The usual computational technique of calculating I t 
 p
it
pik  1Wit as described above,
could not be applied directly because it required knowledge or an estimate of
 pit1 pit2  pit2 pit3 ... pi1 pi 0   pit1 p20 , which did not exist because pio did not exist.
However an index with the previous month = 100 including all items whose prices had been
observed both in the current and previous month. The month indices are also the month on month
rates of inflation.
By chaining such indices, an estimate of the index for the current month with December 2008 =
100 was obtained.
Hence I 1, 0 xI 2,1 x...xIt ,t 1 .
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