WORKING PAPER
PRICE SETTING BEHAVIOUR IN SOUTH AFRICA –
STYLISED FACTS USING CONSUMER PRICE MICRODATA
Kenneth Creamer and Dr Neil Rankin
SCHOOL OF ECONOMIC AND BUSINESS SCIENCES,
UNIVERSITY OF THE WITWATERSRAND
September 2007
1
Abstract
An empirical analysis of the large microdata sample at the unit level of
South Africa’s Consumer Price Index (CPI) is undertaken for the period
2001m12 to 2006m2. This study will allow for findings to be made on the
following issues: the frequency of price changes and the related duration of
price spells, the frequency of price increases and price decreases, as well
findings on the magnitude of price changes, price increases and price
decreases. Results are presented at both an aggregate and a disaggregated
level, based on the CPI’s major product sub-categories. A brief comparison
of results for the South African economy with the results for other countries,
where such micro level price data analysis has been undertaken, will also be
made. The study is part of a broader research effort into the implications of
price setting behaviour for the conduct of monetary policy in South Africa,
including an analysis of factors influencing the frequency and magnitude of
price changes.
JEL Codes:
E31, E52
2
Price Setting Behaviour in South Africa – Stylised
facts using Consumer Price Microdata
By Kenneth Creamer and Neil Rankin1
Introduction
An empirical analysis of the large microdata sample at the unit level of South Africa’s
Consumer Price Index (CPI) has been undertaken for the period 2001m12 to 2006m2,
This allows for findings to be made for the sample on the following issues: the frequency
of price changes and the related duration of price spells, the frequency of price increases
and the frequency of price decreases, as well as findings on the magnitude of price
changes, the magnitude of price increases and the magnitude of price decreases. Results
are presented at both an aggregate and a disaggregated level based on the CPI’s 18 major
product sub-categories.
The analysis of unit level CPI microdata facilitates an understanding of actual price
setting behaviour at the level of individual firms. As such, it adds value in understanding
price setting conduct in the economy, particularly as it is the first time that such a study
has been undertaken in the South African context. A basic example of a two-product
economy with inflation running at 5%, illustrates this point. If the products are equally
weighted in the CPI then an inflation rate of 5% could be the result of one price always
changing by 10% and the other price never changing, or by both price changing by 5%,
or various other combinations. Such an improved micro-level understanding of price
setting behaviour will assist in providing a solid foundation for the formulation and
conduct of macro-economic policy.
1
Kenneth Creamer and Dr Neil Rankin lecture in economics at the School of Economic and Business
Sciences at the University of Witwatersrand. This paper reflects an aspect of Kenneth Creamer’s PhD
research on “Price Setting and Monetary Policy in South Africa”. Thanks are owed to PhD Supervisor
Greg Farrell, and Statistics South Africa’s Patrick Kelly and Jenny Caldecott for facilitating access to
unpublished unit level CPI data for purposes of this research.
3
This working paper is part of a broader research effort into the implications of price
setting behaviour for the conduct of monetary policy in South Africa. In future research,
an analysis of factors influencing the frequency and size of price changes is proposed,
including such factors as seasonality, the prevailing rate of inflation, preference for round
prices, interest rate developments and exchange rate developments. It may then be
possible to conduct an analysis of the extent to which price setting in the period can be
shown to be state dependant or time dependant and to conduct a comparison of results for
the South African economy with the results for other countries where similar micro level
price data analyses have been undertaken.
An analysis of the policy implications of the findings of the study into price setting
behaviour would include discussion on the following dialectic. Firstly, an assessment of
how interest rate changes influence price setting behaviour by South African firms, which
would bring into discussion the relative significance of cost channel effect (as rising
interest rates put upward pressure on prices) and negative demand effects (as rising
interest rates put downward pressure on prices). Secondly, a discussion on how an
understanding of price setting behaviour influences the conduct of monetary policy, such
as, the role which adjustments in the frequency and magnitude of price changes have in
leading to interest rate changes. Furthermore, the existence of such price rigidities means
that monetary policy decisions are non-neutral and impact on short to medium term
output and employment levels. As such, an understanding of pricing behaviour and price
rigidities would improve the understanding of the manner in which monetary policy
decisions impact on real economic outcomes.
For example, in a model such as that developed by Altissimo et al (2006) would assist in
the analysis of monetary policy in the context of varying degrees of price rigidity.
Altissimo et al’s model is based on a Phillips Curve, IS curve and Taylor rule and is used
to show that in comparing situations of high and low degrees of price rigidity, monetary
policy should be less aggressive in the face of cost push shocks in order to achieve
preferable output, real interest rate and inflation outcomes. This is because if prices are
relatively sticky there will be greater short-run real effects due to interest rate changes.
4
Data issues
Defining the data set
The current study is based on the large data sets at unit level of South Africa’s CPI data
(comprising 3 710 573 items of pricing information for the 51 month period from
2001m12 to 2006m2)2 and the utilization of techniques for analyzing the frequency and
size of price changes using this data.3
In terms of this approach, each individual price record corresponds to a precisely defined
item sold in a particular outlet at given point in time, therefore the pricing of individual
items can be followed over time within the same outlet. Along with each individual price
quote the following additional information was provided: the year and month of the
record; the item code (indicating the type of product), a unit code (indicating the specific
variety of the product), a capture code (indicating the capture status of the item), and a
numeric outlet code (which in terms of relevant legal confidentiality requirements does
not enable the name of the outlet to be identified, but which enables the tracking of
pricing activity at specific anonymous outlets). Furthermore, a complimentary data-set
was integrated into the main data-set which enabled the identification of whether specific
items where classified as goods or services.
Before using the 3 710 573 price records provided over the period, it is necessary to
analyse the data and where necessary exclude price records for which the capture code
indicated that the price information has not been properly received and captured.
2
This selection of the period was determined by data availability, as a full historical record of unit level
price data is not stored by Statistics South Africa, only the most recent 4 years or so worth of data is
available. Fortuitously, the period under study constitutes an important period shortly post the introduction
of an Inflation Targeting monetary policy framework in South Africa.
3
The approach is broadly based on the methodology adopted by Alvarez and Hernando (2004) in their
study of price setting conduct in the Spanish economy. See also the “Stata Methodology” Appendix
outlining the methods used to calculate price change frequencies and magnitudes.
5
Code
0
1
2
3
Status
Questionnaire still outstanding
Questionnaire received and captured
Estimated price
Prices that fall outside the allowed range
and could not be confirmed with respondent
– Outliers
4
Price confirmed by respondent but quality
and/or unit of product changed and so price
is not comparable. Also used for items that
were out of stock when prices are given
again.
Price provided for first time on this product
by an existing respondent
New respondent
Currently not used
Respondent is out of stock or no longer sells
product
Shop closed
5
6
7
8
9
Total
Number of
observations
524513
2310395
13
% of total
observations
14.14%
62.27%
0.00%
8611
0.23%
62483
1.68%
5839
8320
1
0.16%
0.22%
0.00%
790398
0
21.30%
0.00%
3710573
The bulk of the price records, 2 310 395 or about 62%, are described as being correctly
received and captured (code 1) and there is no question that these should be included in
the study. Similarly, there appears to be no reason to exclude the 5 839 prices which have
been provided for the first time by an existing respondent (code 5) or the 8 320 prices
from new respondents (code 6). The 62 483 code 4 prices are also included in the study,
as even though there is same ambiguity as to whether the code indicates a change in the
quality of the product, the code has also been used when prices are given for previously
out of stock items.
With regard to the 524 513 (code 0) price records that are classified as having a
questionnaire outstanding (14,1% of the total sample), the convention of the statistical
authorities (in all but 120 instances or 0,023% of the relevant records) has been to assume
6
that the price from the most recently recorded previous period has remained unchanged
until up to date price information is acquired.
Such price records have been included in the study, as although based on an imperfect
assumption, these records serve to provide an approximate account of the frequency and
size of price changes, although they do not provide a precise account of the timing of
price changes. For example, if no price change is recorded for some time due to the non
submission of information, then any price change which did occur during the nonsubmission period will be reflected when submissions are resumed. If more than one
price increase takes place during the period of non-reporting, then this assumption may
lead to an underestimation of the frequency of price changes and an overestimation of the
magnitude of price changes, but the alternative of following a strict approach which
excludes all non-submitted price records would lead to a significant overestimation of the
frequency of price changes. A question remains as to whether the distortion of the timing
of price changes is significant, an issue which may need to be resolved when the study of
the time series regressions of the influence of various factors on the frequency and
magnitude of price setting is undertaken.
The prevalence of questionnaire’s outstanding may be due in part to the historic
collection methodology employed by Statistics South Africa (“Stats SA”).
It is
understood that, during the period under study, Stats SA enumerators collected price data
by telephonic surveys and mailing questionnaires.
This collection methodology is
currently in the process of being changed to include site visits and collections, so perhaps
it is to be expected that there will be a reduction in the 0 capture code and an increase in
the capture code (code 4) indicating changes in the quality or unit of the product as a
result of on-site visits.
About 21,3% of the price records are recorded as being out of stock or no longer stocked
(code 8) and these are recorded as having R0,00 price. As such, it is necessary to exclude
these 790 382 price records from the study. The exclusion of these price records is
necessary, as the inclusion of such price records, for which a captured price of R0,00 was
7
entered into the data base, would have a significant distorting impact on studies of the
frequency and magnitude of price changes. In essence, the inclusion of such null entry
price record in the study would result in the underestimation of the frequency of price
changes as well as an overestimating bias in the absolute value of the size of price
decreases, retarding estimations of the overall size of price changes.
The 8 611 prices classified as pricing outliers that could not be confirmed with the price
setter (code 3) have been excluded from the data set to be studied. Similarly, the 13
prices classified as price estimates (code 2), and the single price with classification not
currently in use (code 7), have been excluded from the data set under study. Code 9, was
also not in use over the period of the study.
In summary, a total of 2 911 550 prices have been included in the data set to be studied,
that is, prices classified with codes 0, 1, 4, 5 and 6. Whereas a total of 799 023 price
records have been excluded from the study, that is, prices classified with codes 2, 3, 7 and
8.
Trends within the data set
The overall trend in data collection has been a decline with a sharp drop from over 92
000 monthly price records in the initial 9 month period, to a monthly average of 68 538
price records for the following 42 month period, with some increase over the second
period to a maximum of 73 689 in 2005m10. A sharp reduction took place in 2002m9
and a similar but smaller reduction in 2005m11.4
4
The statistical authorities explain that the sharp reduction in price records is due to changes in collection
methodology. Instead of collecting certain identical price information from a wide range of retail outlets,
centralised price information was received from retail head offices.
8
Number of monthly price records
100000
90000
80000
70000
60000
Number of monthly
price records
Linear (Number of
monthly price records)
50000
20
01
m
20 12
0
20 2m5
02
m
20 10
03
20 m3
03
20 m8
04
20 m1
0
20 4m6
04
m
20 11
05
20 m4
05
20 m9
06
m
2
40000
This reduction does not indicate a cleaning-out of out of stock items, as the proportion of
code 8 out of stock items in 2002m9 increased from 18,46% in 2002m8 to 21,3% in
2002m9. The reduction in about 26 000 monthly price records took place mainly in the
largest sub-category of foodstuffs with a reduction of over 18 000 items, household
operations with over 2 500 items removed and smaller reduction in personal care (about 1
400), furniture and equipment (about 750), non-alcoholic beverages (about 700), and
cigarettes, cigars and tobacco products (about 500).
It is noticeable that in the selected sample, with capture codes 0, 1, 4, 5 and 6, the
tendency remains for there to be sharp a reduction in data in 2002 m9 and a smaller
reduction in 2005 m11. Overall the selected sample shows a reduction in the total
number of observations each month, as compared to the number of monthly observations
in the full data set.
9
Selected sample of price data
90000
80000
70000
60000
50000
Selected sample of
price data
20
01
m
20 12
02
20 m5
02
m
20 10
03
m
20 3
03
m
20 8
04
m
20 1
04
20 m6
04
m
20 11
05
m
20 4
05
m
20 9
06
m
2
40000
30000
20000
10000
0
With regards to the three major capture codes, the following trends are discernable.
Code 0 (Questionnaire outstanding) – In the initial period until 2003m11 there was a
strong cyclical pattern in the collection of price questionnaires with the proportion of
non-returns consistently dropping to between 10% and 12% in months in months 3, 6, 9
and 12 (with non returns rising to around 22% and 25% in months 2, 5, 8 and 11). From
the beginning of 2004, this cyclical pattern falls away, as the number of non-returns falls
to an average of 9,17%, ending of a low of 4,72% at the end of the period. This indicates
a shift from quarterly to monthly collection price data collections for a range of items, as
well as a general improvement in the collection of questionnaire’s by Statistics South
Africa.
10
Code 0 - Proportion of Questionnaires Outstanding
30
25
20
Proportion of
Questionnaires
Outstanding
15
10
5
20
01
m
20 12
02 |
20 m4
0
|
20 2m
02 8 |
m
20 12
03 |
20 m4
0
|
20 3m
03 8 |
m
20 12
04 |
20 m4
0
|
20 4m
8
04
m |
20 12
05 |
20 m4
0
|
20 5m
05 8 |
m
12
|
0
Code 1 (Questionnaire received and captured) – In negative correlation with the code 0
non-returns, the pattern of code 1 returns received and captured, shows a cyclical pattern
over the period to the end of 2003. During this period, the proportion of received and
captured returns is generally high at between 63% and 70% during months 3, 6, 9 and 12
(when non-returns are low), and low between 50% and 55% in months 2, 5, 8 and 11
(when non-returns are high).
This pattern correlates with the quarterly price data
collection utilized for certain product categories, including motor vehicle insurance and
public transport tariffs, where price information is collected in months 3, 6 9 and 12. See
Appendix outlining price collection frequencies.
From the beginning of 2004, the
cyclical pattern falls away as the average number of received and captured returns rises to
an average of about 66,59%, peaking at 71,96% in 2006m1.
Again indicating an
improvement in the collection of questionnaire’s by Statistics South Africa.
11
Code 1 - Proportion Received and Captured
75
70
65
60
Proportion Received
and Captured
55
50
45
2005m12 |
2005m8 |
2005m4 |
2004m12 |
2004m8 |
2004m4 |
2003m12 |
2003m8 |
2003m4 |
2002m12 |
2002m8 |
2002m4 |
2001m12 |
40
Code 8 (Out of stock or no longer stocked) – Over the 51 month period under study, the
proportion of price records which indicate that the item tracked is out of stock or not
stocked is 21,56%, with a high of 23,74% in 2004m8 and a low of 16,11% in the first
month included in the data 2001m12. The sharp increase in the proportion of code 8
returns in 2002m9 could probably be explained by the overall reduction of the number of
items tracked at that time and the disproportionate continuation of the surveying of items
that were giving out of stock returns.
Code 8 - Proportion out of stock or not stocked
Proportion out of stock
or not stocked
20
01
m
20 12
02 |
20 m
02 5 |
m
20 10
03 |
20 m3
03 |
20 m8
04 |
20 m1
0
|
20 4m
6
04
m |
20 11
05 |
20 m4
05 |
20 m9
06 |
m
2
|
30
28
26
24
22
20
18
16
14
12
10
12
Also, the data indicates that the inclusion of out of stock items continues for prolonged
periods, that is, items once out of stock are not removed from the collection basket and
thus the proportion of code 8 returns tends to stay steady or even accumulate.
Illustration of price data at the unit level
In order to facilitate a clearer understanding of the pricing data at the unit level, an
example of monthly collected price data of 700g loafs of white bread at 15 selected
outlets, over the period under study, is outlined in the table below.
Store
11
52
127
143
239
253
302
307
476
489
499
523
555
611
633
price
price
price
price
price
price
price
price
price
price
Price
price
price
price
price
2001/12/01
4.20
3.80
3.99
3.75
3.40
2.90
3.85
2002/01/01
4.20
3.80
3.99
3.25
3.40
2.90
3.85
2002/02/01
4.20
3.80
3.99
3.25
3.40
2.90
3.85
2002/03/01
4.50
4.10
2.95
3.99
3.40
2.90
3.89
4.49
2002/04/01
4.50
4.10
2.95
3.99
4.20
4.59
3.89
4.49
2002/05/01
4.50
4.10
2.95
3.99
4.20
3.30
4.19
4.49
2002/06/01
4.50
4.10
2.95
3.99
4.20
3.30
4.19
4.49
2002/07/01
4.50
4.10
2.95
3.99
4.20
3.30
3.79
4.49
2002/08/01
4.60
4.10
2.95
3.99
4.20
3.30
4.19
4.49
2002/09/01
4.60
4.10
4.45
4.20
3.30
4.69
4.99
2002/10/01
4.60
4.10
4.45
4.50
3.70
4.69
4.99
2002/11/01
4.60
4.10
4.45
4.50
3.70
4.69
4.99
2002/12/01
4.60
4.60
4.45
4.50
3.70
3.97
4.99
2003/01/01
4.60
4.60
4.45
4.50
3.70
4.59
4.99
2003/02/01
4.60
4.60
4.45
4.50
3.70
4.59
4.99
2003/03/01
4.60
4.60
4.45
4.90
4.50
3.70
4.59
4.99
2003/04/01
4.60
4.60
4.45
4.90
4.50
3.70
4.69
4.99
2003/05/01
4.60
4.60
4.45
4.90
4.50
3.70
4.69
4.99
2003/06/01
4.60
4.60
4.45
4.90
4.50
3.00
4.99
4.99
2003/07/01
4.60
4.60
4.45
5.00
4.50
3.00
4.49
4.99
2003/08/01
4.60
4.80
4.65
5.00
4.50
3.00
4.49
4.99
2003/09/01
4.60
4.80
4.65
5.00
4.50
3.00
4.99
5.67
2003/10/01
4.60
4.80
4.65
5.00
4.50
3.00
4.99
5.49
2003/11/01
4.60
4.80
4.65
5.00
4.50
3.00
4.69
5.49
2003/12/01
4.60
4.80
4.65
5.00
4.50
3.00
4.69
5.49
2004/01/01
4.60
4.80
4.65
5.00
4.50
3.00
4.69
5.49
2004/02/01
4.60
4.80
4.65
5.00
4.50
4.50
0.00
4.69
5.49
2004/03/01
4.60
4.80
5.55
4.65
5.00
4.50
4.50
0.00
3.99
5.49
2004/04/01
4.60
4.80
5.55
4.65
5.00
4.50
4.50
4.99
4.69
5.49
Date
13
2004/05/01
4.60
4.80
5.55
4.65
5.00
4.50
4.50
4.99
4.69
5.49
2004/06/01
4.60
4.80
5.55
4.65
5.00
4.50
4.50
4.99
4.69
5.49
2004/07/01
4.60
4.80
5.55
4.65
5.00
4.19
4.50
4.50
4.99
4.15
5.49
2004/08/01
4.60
4.80
5.55
4.65
5.00
4.19
4.50
4.50
4.99
4.69
5.49
2004/09/01
4.60
4.80
5.55
4.65
5.00
4.19
4.50
4.50
4.99
4.69
5.49
2004/10/01
4.60
4.80
5.55
4.65
5.00
4.99
4.50
4.50
4.99
5.19
5.49
2004/11/01
4.60
4.80
5.55
4.65
5.00
4.69
4.50
4.50
4.65
5.19
5.19
5.49
2004/12/01
4.60
4.80
5.55
4.65
5.00
4.69
4.50
4.50
4.65
5.19
5.19
5.49
2005/01/01
4.60
4.80
5.55
4.65
5.00
4.29
4.69
4.50
4.50
4.65
5.19
5.19
0.00
2005/02/01
4.60
4.80
5.55
4.65
5.00
4.29
4.69
4.50
4.50
4.99
5.19
5.19
5.79
2005/03/01
4.60
4.80
5.55
4.65
5.00
4.29
4.69
4.50
4.50
4.99
5.19
4.29
5.75
2005/04/01
5.00
5.00
4.59
5.55
4.65
5.00
4.29
4.69
4.50
4.70
4.99
5.19
4.29
5.95
2005/05/01
5.00
5.00
3.99
5.79
4.65
5.00
4.29
4.69
4.50
4.70
4.99
5.19
5.19
5.95
2005/06/01
5.00
5.00
4.59
5.79
4.65
5.00
4.29
4.69
4.50
4.70
4.99
5.19
4.89
5.95
2005/07/01
5.00
5.00
4.59
5.79
4.65
5.00
4.29
4.69
4.50
4.70
4.99
5.19
4.89
5.95
2005/08/01
5.50
5.00
3.99
5.79
4.65
5.00
4.29
4.69
4.70
4.70
4.99
5.19
4.99
5.95
2005/09/01
5.50
5.00
3.99
5.79
4.65
5.00
4.29
5.49
4.70
4.70
4.99
5.49
4.99
5.95
2005/10/01
5.50
5.00
3.99
5.79
4.65
5.00
4.29
5.49
4.70
4.70
4.99
5.49
4.79
5.95
2005/11/01
5.50
5.00
3.99
5.79
4.65
5.00
3.99
3.99
4.70
4.70
4.99
5.49
4.79
5.95
2005/12/01
5.50
5.00
3.99
5.79
4.65
5.50
3.99
3.99
4.70
4.70
4.99
5.49
4.79
5.95
2006/01/01
5.50
5.00
3.99
5.79
4.65
5.50
3.99
4.70
4.70
4.99
5.49
4.79
5.95
2006/02/01
5.50
5.00
3.99
5.79
4.65
5.50
4.70
4.70
4.99
5.49
4.99
5.95
Graphing of price of white bread (750 g) at 15 selected outlets, including all capture
codes. The distorting effect of the inclusion of capture code 8 (where out of stock items
are recorded as having a R0,00 price) is noteworthy.
7.00
Outlet 1
Outlet 2
6.00
5.00
Outlet 3
Outlet 4
Outlet 5
4.00
Outlet 6
Outlet 7
3.00
2.00
Outlet 8
Outlet 9
Outlet 10
1.00
Outlet 11
Outlet 12
De
c0
Ap 1
r- 0
Au 2
g0
De 2
c0
Ap 2
r- 0
Au 3
g0
De 3
c0
Ap 3
r- 0
Au 4
g0
De 4
c0
Ap 4
r- 0
Au 5
g0
De 5
c05
0.00
Outlet 13
Outlet 14
Outlet 15
14
Graphing of price of white bread (750 g) at 15 selected outlets, including capture codes,
utilized in study, that is, capture codes 0, 1, 4, 5 and 6. The distorting effect of the out of
stock R0,00 price capture code is hereby excluded.
7.00
Outlet 1
Outlet 2
6.00
5.00
4.00
Outlet 3
Outlet 4
Outlet 5
Outlet 6
Outlet 7
3.00
2.00
1.00
Outlet 8
Outlet 9
Outlet 10
Outlet 11
Outlet 12
De
c0
Ap 1
r- 0
Au 2
g0
De 2
c0
Ap 2
r- 0
Au 3
g0
De 3
c0
Ap 3
r- 0
Au 4
g0
De 4
c0
Ap 4
r- 0
Au 5
g0
De 5
c05
0.00
Outlet 13
Outlet 14
Outlet 15
For example, the frequency and size of price changes at three of the outlets occurred as
follows:
Outlet 1 (Store 11): The price of a 700g loaf of white bread rose 4 times over the 51
month period from an initial price of R4,20, to R4,50, to R4,60, to R5,00, to R5,50.
Outlet 2 (Store 52): The price of a 700g loaf of white bread rose 4 times from the 51
month period from an initial price of R3,80, to R4,10, to R4,60, to R4,80, to R5,00.
Outlet 3 (Store 127): The price of a 700g loaf of white bread fell, rose and fell again over
an 11 months period from an initial price of R4,59, to R3,99, to R4,59, to R3,99.
Frequency of data collection
Most price data is collected monthly, but price information on certain items is collected
quarterly, and on other items price information is collected once, twice or three times per
15
year.5 For purposes of the aggregate price study the various longer than monthly data
collection frequencies have some impact on the findings of the average frequency of
price changes (possibly causing estimates of the frequency to be smaller) and the
magnitude of price changes (possibly causing estimates to be larger than they should be).
This is because it is generally assumed that prices do not change over the months until the
next collection takes place.
It would not be correct to exclude price information that is collected quarterly or annually
as such data provides important information on the overall frequency and magnitude of
price changes for the economy as a whole. This is also justified by the fact that the price
collection frequencies are linked to the likely actual frequency of price changes, for
example, school fees are only set once per year. With regard to disaggregated studies of
price changes, the collection frequency of price data will have more of an impact on the
analysis.
Items which are collected quarterly include motor vehicle insurance and public transport
tariffs. This is represented in the graph of four instances of municipal bus ticket prices
over the period.6
5
See Appendix attached which outlines the frequency of data collection by Stats SA.
Even though the rental of dwellings and air ticket prices are categorized as being collected quarterly, the
data seems to indicate that such price data is in fact collected monthly.
6
16
160
140
120
100
80
60
Firm 1
Firm 2
Firm 3
Firm 4
40
20
De
c0
Ap 1
r- 0
Au 2
g0
De 2
c0
Ap 2
r- 0
Au 3
g0
De 3
c0
Ap 3
r- 0
Au 4
g0
De 4
c0
Ap 4
r- 0
Au 5
g0
De 5
c05
0
Items which are collected annually include doctors and dentists fees, motor vehicles
license, registration fees, telephone (land lines), toll-fees at toll-gates, school fees,
university boarding and class fees. This is representated in the graphing of school fees
over the period at four separate schools.
250
200
150
100
School 1
School 2
School 3
School 4
50
De
c0
Ap 1
r- 0
Au 2
g0
De 2
c0
Ap 2
r- 0
Au 3
g0
De 3
c0
Ap 3
r- 0
Au 4
g0
De 4
c0
Ap 4
r- 0
Au 5
g0
De 5
c05
0
17
Product categories
There are approximately 1 200 goods and services in current CPI basket. The CPI data
set contains pricing information on consumer products divided into 18 subcategories with
the following weightings, both for the data set of total observations and for the selected
sample based on the relevant capture codes.
Product Group
FOOD
NON ALCOHOLIC
BEVERAGES
ALCOHOLIC
BEVERAGES
CIGARETTES
TOBACCO AND
CIGARS
CLOTHING
FOOTWEAR
HOUSING
FUEL AND POWER
FURNITURE AND
EQUIPMENT
HOUSEHOLD
OPERATION
MEDICAL CARE AND
HEALTH EXPENSES
TRANSPORT
COMMUNICATION
RECREATION AND
ENTERTAINMENT
READING MATTER
EDUCATION
PERSONAL CARE
OTHER GOODS AND
SERVICES
Total
observations
Proportion
sample to
% of Observations % of
total
total
in sample
total observations
1663606 44.83
1348805 46.33
0.81
69104
1.86
57244
1.97
0.83
126326
57280
3.40
1.54
108261
43950
3.72
1.51
0.86
0.77
161137
69119
19074
16061
4.34
1.86
0.51
0.43
122894
42126
19073
13252
4.22
1.45
0.66
0.46
0.76
0.61
1.00
0.83
322389
8.69
202412
6.95
0.63
244058
6.58
206562
7.09
0.85
101036
291882
12936
2.72
7.87
0.35
86516
229190
12936
2.97
7.87
0.44
0.86
0.79
1.00
150391
21742
4488
346079
4.05
0.59
0.12
9.33
105135
16196
4487
266509
3.61
0.56
0.15
9.15
0.70
0.74
1.00
0.77
26002
0.89
2911550 100.00
0.77
0.78
33865
0.91
3710573 100.00
The table compares the number of observations per product category for the total data set
as well as for the sample data set based on the selected relevant capture codes. Certain
18
product sub-categories, such as, housing, communication and education, were unaffected
by the inclusion only of relevant product codes.
Whereas other subcategories
experienced a reduction of data records included in the sample, due to a high relative
preponderance of excluded capture codes, such as, footwear (39% reduction), furniture
and equipment (37% reduction) and recreation and entertainment (30% reduction). The
largest sub-category, food, experienced a reduction of 19%.
Limitations of sample
The findings on the frequency and magnitude of price changes are based on the specific
sample of 2 911 550 prices included in the study and do not purport to represent every
price movement which took place in South African over the period. Furthermore, even
though the same basic price information is used to construct the various inflation indices
published by Stats SA, there are important differences between the sample data set and
the constructed indices. As per the table below, it can be seen that there is not a one-toone mapping between the price data sample and proportion of product sub-categories in
the widely publicized Consumer Price Index (CPI) for historical metropolitan areas and
the Consumer Price Index, excluding interest rates on mortgage bonds, (CPIX) for
historical metropolitan and other urban areas.
In comparison to the weighting of product sub-categories in the CPI, the specific sample
of price data used in the current study, contains a high proportion of price information on
furniture and equipment, alcoholic beverages, personal care, food, clothing.
The
proportion of the sample size of all these product sub-categories is more than double their
weighting in the CPI. A similar pattern exists in the comparison of the sample data with
the weighting of product sub-categories in the CPIX.
Conversely, in comparison to the weighting of product sub-categories in the CPI, the
sample contains a low proportion of price information on housing, fuel and power,
medical care and health expenses, communication, education and other goods and
19
services. The proportion of the sample size of all these product sub-categories is less than
half their weighting in the CPI. A similar pattern exists in the comparison of the sample
data with the weighting of product sub-categories in the CPIX.
Product Group
FOOD
NON ALCOHOLIC
BEVERAGES
ALCOHOLIC
BEVERAGES
CIGARETTES
TOBACCO AND
CIGARS
CLOTHING
FOOTWEAR
HOUSING
FUEL AND
POWER
FURNITURE AND
EQUIPMENT
HOUSEHOLD
OPERATION
MEDICAL CARE
AND HEALTH
EXPENSES
TRANSPORT
COMMUNICATION
RECREATION
AND
ENTERTAINMENT
READING
MATTER
EDUCATION
PERSONAL CARE
OTHER GOODS
AND SERVICES
Ratio
of
sample
to CPI
2.21
Weighting in
CPIX for
historical
metropolitan
and other
urban areas
25.66
Ratio
of
sample
to
CPIX
1.81
Observations
in sample
1348805
% of
total
46.33
Weighting in
CPI for
historical
metropolitan
areas
20.99
57244
1.97
1.1
1.79
1.26
1.56
108261
43950
3.72
1.51
1.4
1.14
2.66
1.32
1.7
1.35
2.19
1.12
122894
42126
19073
4.22
1.45
0.66
2.04
1.21
22.14
2.07
1.20
0.03
2.53
1.53
11.57
1.67
0.95
0.06
13252
0.46
3.49
0.13
4.28
0.11
202412
6.95
2.53
2.75
3.15
2.21
206562
7.09
4.82
1.47
5.22
1.36
86516
229190
12936
2.97
7.87
0.44
7.15
14.84
2.98
0.42
0.53
0.15
7.7
15.3
3.19
0.39
0.51
0.14
105135
3.61
3.31
1.09
3.39
1.07
16196
4487
266509
0.56
0.15
9.15
0.39
3.48
3.67
1.43
0.04
2.49
0.4
3.77
4.37
1.39
0.04
2.09
26002
2911550
0.89
100.00
3.32
100.00
0.27
3.63
100.00
0.25
Due to these significant differences in weighting, it is clear the frequency and magnitudes
of price changes found in the sample under study can not simply be related back to
20
changes in the rate of inflation. Indeed, the emphasis of the current paper is not a study
of inflation, but rather a study of price setting behaviour using CPI micro-data.
21
Findings on frequency of price changes
With regard to the frequency of price changes, the headline finding of the study of unit
level CPI prices over the period 2001 m12 to 2006 m2, is that an average of 15,97% of
prices change each month.
Based on the assumptions of stationarity and homogeneity of price change behaviour, it
has been shown that the inverse of the frequency of the price changes converges, in a
large sample, to the mean duration of prices, that is: T F 
1
, where T F represents the
F
average duration of price spells and F represents the frequency of price changes.7
On this basis an average frequency of price change of 15,97%, accords with an average
price duration of 6,26 months (or between 6 and 6,5 months) over the period 2001 m12 to
2006 m2.
It is interesting to note that over the 51 month period under consideration there was a
significant degree of differentiation in the frequency of price changes with the highest
frequency of price changes occurring in 2003m6 at 23,88% (which would convert to an
average price duration of 4,2 months and the lowest frequency of price changes occurring
in 2004m12 at 11,77% (which would convert to an average price duration of 8,5 months).
The diagram below also indicates a downward trend in the frequency of price changes
during the period under study.
7
In Baudry et al (2004), there is discussion on various methodologies for moving from findings of the
frequency of price changes to the estimation of the duration of price spells. For purposes of the current
study the average implied duration of prices is derived from the property that “the average of observed
durations is equivalent to the inverse of the average frequency” (p.20).
22
Aggregate Frequency of Price Changes
0.3
0.25
0.2
0.15
0.1
Aggregate Frequency of
Price changes
Linear (Aggregate
Frequency of Price
changes)
0.05
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
0
Aggregate Frequency of price increases and price decreases
Price increases occurred with an average monthly frequency of 10,50% and price
decreases with a frequency of 5,47%. Indicating, a significant degree of asymmetry in
price setting in favour of price increases over price decreases.
There was a downward trend in the frequency of price increases over the period. The
month recorded with the highest frequency of price increases was 2002m3, with 19,00%
of prices increasing in that month, and the month with lowest frequency of price
increases was 2005m6 with 6,52% of prices increasing in that month.
23
Aggregate Frequency of Price Increases
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Aggregate Frequency of
Price Increases
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
Linear (Aggregate
Frequency of Price
Increases)
With regard to the frequency of price decreases, there is a slight upward trend over the
period. The monthly frequency of price decreases has tended to increase with the highest
frequency of price decreases recorded in 2003 m6 (9,60%) and the lowest frequency of
price decreases in 2002 m10 (3,75%).
Aggregate Frequency of Price Decreases
0.12
0.1
0.08
0.06
0.04
Aggregate Frequency of
Price Decreases
Linear (Aggregate
Frequency of Price
Decreases)
0.02
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
0
24
There is a trend towards increasing upward and downward symmetry in the frequency of
price changes. The ‘asymmetry gap’ reduces over time as there is increasing equivalence
in the likelihood of price increases and decreases. This finding is also consistent with the
period’s initial high level of inflation followed by disinflation.8 Furthermore, the finding
is not inconsistent with hypothesis that inflation targeting framework introduced at the
beginning of the period has gained credibility with price-setters over the period.
An interesting finding is that over the period from 2001m12 to 2005m6, there has been a
declining proportion of price increases and an increasing proportion of price decreases.
Proportion of price increases and price decreases
when price change
90.00
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Share of price
increases when price
change
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
Share of price
decreases when price
change
8
CPI - 2001m12 to 2006m2
14
12
10
8
6
4
2
2006/02
2005/12
2005/10
2005/08
2005/06
2005/04
2005/02
2004/12
2004/10
2004/08
2004/06
2004/04
2004/02
2003/12
2003/10
2003/08
2003/06
2003/04
2003/02
2002/12
0
25
As can be seen from the previous diagram, in 2005m6, the proportion of price increases
(51,97%) to price decreases (48,03%) approaches parity. Thereafter, the proportion of
price increases to price decreases diverge once more with price increases (65,02%)
assuming dominance over price decreases (34,98%) by 2006m1.
26
Comparison between goods and services
Average frequency of price changes for goods and services
Goods
Services
Frequency of price change
16,03%
16,39%
Frequency of price increase
10,42%
12,53%
Frequency of price decrease
5,61%
3,86%
In South Africa, in the period under review, the prices of services (16,39%) tended to
change more frequently than the prices of goods (16,03%). The findings for goods and
services do not tie up with the findings for the aggregate data set, which reflects a price
change frequency of 15,97%. This is due to an anomaly that when the data base which
classifies items as either a product or a service is integrated with the full price data base
for the period certain price records are lost for each period – from 2 772 854 price records
to 2 738 093 price records, or a decrease of 1,25%. On average, within the goods and
services data set, the proportion of goods price records is 94,5% to 5,5% of price records
classified as services.
Despite this limitation, the study does offer some evidence of sharper asymmetry
between the frequency of price increases and price decreases for services than for goods
in the South African economy over the period. Whereas goods prices tend to increase
with a frequency of 10,42% and decrease with a frequency of 5,61% (comparable with
the finding for the aggregate data set of an average monthly frequency for price increases
of 10,50% and price decreases with a frequency of 5,47%), services prices tend to
increase with a frequency of 12,53% and decrease with a frequency of 3,86%.
27
Comparison of frequency of price changes of different product categories
The findings on the frequency of price changes by product sub-category are tabulated to
show the overall frequency of price changes, the mean duration of prices in months, the
average frequency of price increase and the average frequency of price decreases.
Frequency
of Mean
price change
Frequency
duration
of
of Frequency
price increase
of
price decrease
prices
(months)9
FOOD
NON
0.19
5.22
0.12
0.07
0.11
9.38
0.08
0.02
0.12
8.29
0.10
0.02
0.17
0.10
0.07
0.42
0.14
5.83
7.23
0.16
0.06
0.04
0.34
0.10
0.02
0.03
0.03
0.09
0.04
0.11
8.88
0.07
0.04
0.13
7.52
0.09
0.04
0.16
0.16
0.08
6.38
12.26
0.10
0.11
0.07
0.06
0.05
0.01
0.12
8.02
0.07
0.06
ALCOHOLIC
BEVERAGES
ALCOHOLIC
BEVERAGES
CIGARETTES
TOBACCO
AND
CIGARS
CLOTHING
FOOTWEAR
HOUSING
FUEL AND POWER
FURNITURE
10.41
15.32
2.36
AND
EQUIPMENT
HOUSEHOLD
OPERATION
MEDICAL
AND
CARE
HEALTH
EXPENSES
TRANSPORT
COMMUNICATION
6.12
RECREATION AND
ENTERTAINMENT
9
Calculated using basic methodology outlined in Baudry et al (2004).
28
READING MATTER
EDUCATION
PERSONAL CARE
OTHER
0.16
0.06
0.11
8.70
0.15
0.06
0.08
0.01
0.00
0.04
16.79
0.26
3.82
0.18
0.08
6.31
GOODS
AND SERVICES
Analysis of frequency of price changes by product sub-category
The table below lists product sub-categories from those with the least frequently changed
prices, to those with the most frequently changed prices.
Product Sub-category
EDUCATION
FOOTWEAR
COMMUNICATION
CLOTHING
NON ALCOHOLIC BEVERAGES
FURNITURE AND EQUIPMENT
PERSONAL CARE
ALCOHOLIC BEVERAGES
RECREATION AND ENTERTAINMENT
HOUSEHOLD OPERATION
FUEL AND POWER
MEDICAL CARE AND HEALTH
EXPENSES
READING MATTER
TRANSPORT
CIGARETTES TOBACCO AND CIGARS
FOOD
OTHER GOODS AND SERVICES
HOUSING
Frequency of
price change
0.06
0.07
0.08
0.10
0.11
0.11
0.11
0.12
0.12
0.13
0.14
Mean Duration of
prices (months)
16.79
15.32
12.26
10.41
9.38
8.88
8.70
8.29
8.02
7.52
7.23
0.16
0.16
0.16
0.17
0.19
0.26
0.42
6.38
6.31
6.12
5.83
5.22
3.82
2.36
It is important to note that education prices are gathered annually, which clearly
influences the finding of price stickiness in this sector, where prices are found to change
at a low frequency of 0,06, that is, prices change every 16,79 months. Footwear and
communication prices also change at low frequency 0,07 (15,32 months) and 0,08 (12,26
months) respectively.
The most flexible prices are housing prices changing at a
29
frequency of 0,42 (2,36 months). Prices of other goods and services 10 (3,82 months),
food (5,22 months), cigarettes, tobacco and cigars (5,83 months), transport (6,12 months),
reading matter (6,31 months), and medical care and health expenses (6,38 months) all
change relatively frequently.
In order to facilitate, a closer analysis of the month to month variations in the frequency
of price changes by product sub-category, an appendix of such results has been included
at the end of this paper.
Analysis of frequency of price increases by product sub-category
The most frequent price increases have occurred in housing (0.34), other goods and
services (0.18) and cigarettes, tobacco and cigars (0.16).
The least frequent price
increases occurred in footwear (0.04), fuel and power (0.04), education (0.06) and
clothing (0.06).
Frequency of price increases (ascending)
FOOTWEAR
0.04
EDUCATION
0.06
CLOTHING
0.06
COMMUNICATION
0.07
RECREATION AND ENTERTAINMENT
0.07
FURNITURE AND EQUIPMENT
0.07
PERSONAL CARE
NON ALCOHOLIC BEVERAGES
HOUSEHOLD OPERATION
0.08
0.08
0.09
ALCOHOLIC BEVERAGES
MEDICAL CARE AND HEALTH
EXPENSES
0.10
FUEL AND POWER
0.10
TRANSPORT
0.11
FOOD
0.12
READING MATTER
0.15
0.10
10
Items include in Other Goods and Services include: watches, sunglasses, envelopes, pens and pencils,
professional fees, legal fees, cost of funeral, insurance, take away meals, contributions to pension funds,
swimming pool equipment and repairs, lobola/dowry payments, religious and traditional ceremonies and
fines.
30
CIGARETTES TOBACCO AND CIGARS
0.16
OTHER GOODS AND SERVICES
0.18
HOUSING
0.34
In order to facilitate, a closer analysis of the month to month variations in the frequency
of price increases by product sub-category, an appendix of such results has been included
at the end of this paper.
Analysis of frequency of price decreases by product sub-category
The most frequent price decreases have been in housing (0.09), other goods and services
(0.08) and food (0.07)%. The least frequent price decreases have been in education
(0.00), reading matter (0.01) and communication (0.01).
Frequency of price decreases (ascending)
EDUCATION
0.00
READING MATTER
0.01
COMMUNICATION
0.01
CIGARETTES TOBACCO AND CIGARS
NON ALCOHOLIC BEVERAGES
0.02
0.02
ALCOHOLIC BEVERAGES
0.02
FOOTWEAR
0.03
CLOTHING
0.03
PERSONAL CARE
0.04
FUEL AND POWER
0.04
FURNITURE AND EQUIPMENT
0.04
HOUSEHOLD OPERATION
0.04
TRANSPORT
0.05
RECREATION AND ENTERTAINMENT
MEDICAL CARE AND HEALTH
EXPENSES
0.06
FOOD
0.07
OTHER GOODS AND SERVICES
0.08
HOUSING
0.09
0.06
31
In order to facilitate, a closer analysis of the month to month variations in the frequency
of price decreases by product sub-category, an appendix of such results has been included
at the end of this paper.
32
Findings on magnitudes of price changes
With regard to the magnitude of price changes, the headline findings for the monthly data
over the period 2001m12 to 2006m2, is that, conditional on the occurrence of a price
change, the weighted average magnitude of price change was 2,91%. For those prices
that rose, the average magnitude of price increases was 12,26%. For those prices that
declined, the average magnitude of price decreases was -15,05%. The comparative
medians were:
a 3,58% magnitude of price changes, a 8,05% magnitude of price
increases, and a -9,85% magnitude of price decreases, as median levels exclude the
impact of extreme price increases and decreases.
It should be noted that, such findings record the monthly average size of price change of
those prices that did change in the period. This is distinct from the more familiar
inflation-type measure of the monthly average size of price change, taking into account
all recorded prices, that is, including both those price that have changed and those prices
that have not changed.
Over the period the maximum overall average size of price change (including both prices
that increased and decreased) was 6,42% in 2002m3 and the minimum overall average
size of price change was -0,01% in 2005m6. The month with the highest median price
change of 7,15% was 2002m6, and with the lowest median price change of 0,19% was
2005m6. Overall there was a downward trend in the average and median size of price
changes.
33
Aggregate Size of Price Changes
0.08
0.07
0.06
Weighted average size
of price change
0.05
0.04
Median size of price
change
0.03
Linear (Median size of
price change)
0.02
0.01
0
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
-0.01
The month with the largest average price increase was 2003m10 at 14,26% and the
month with the smallest average price increase was 2004m3 at 10,81%. Monthly median
price increases were considerably lower peaking in 2006m6 at 10,10%, with a low
median of 6,45% in 2005m5.
Aggregegate Size of Price Increases
0.16
0.14
0.12
0.1
0.08
0.06
Aggregate Average Size
of Price Increases
Aggregate Median size
of price increases
0.04
0.02
20
02
20 m1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
20 m2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
0
34
The month with the largest absolute value average price decrease was 2002m2 at
-16,65% and the month with the smallest absolute value average price decrease was
2003m10 at -13,25%.
Aggregate Size of Price Decreases
0
20
02
m
20 1
02
20 m6
02
m
20 11
03
m
20 4
03
m
20 9
04
m
20 2
04
20 m7
04
m
20 12
05
20 m5
05
m
10
-0.02
-0.04
-0.06
-0.08
-0.1
-0.12
Aggregate average size
of price decreases
Aggregate median size
of price decreases
-0.14
-0.16
-0.18
Monthly median price decreases have been considerably less in absolute value terms
peaking in 2004m6 at -11,53%, with a low absolute value median of -7,80% in 2003m10.
35
Comparison of the magnitude of price changes between goods and services
Average size of price changes for goods and services
Goods
Services
Size of price changes
2,90%
2,84%
Size of price increases
12,77%
5,05%
Size of price decreases
-15,45%
-4,33%
It is notable that while for goods and services the overall monthly size of price changes is
comparable, the average size of price increases and price decreases is much larger for
goods than for services, as services experience more moderate price changes.
The
average size of price increases for goods is 12,77%, whereas for services it is 5,05%. The
average size of price decreases for goods is -15,45%, whereas for services it is -4,33%.
Due to the large proportion of goods prices in the sample, the size of goods price changes
are broadly similar to the aggregate size of price increases, which average 12,26% per
month and the size of price decreases which average -15,05% per month.
36
Analyses of magnitude of price changes by product sub-category
The findings on the size of price changes by product sub-category are tabulated to show
the overall average size of price changes where price change, the average size of price
increases where prices rose and the average size of price decreases where prices declined.
Size of price Size of price Size of price
changes
FOOD
NON
increases
decrease
0.03
0.14
-0.16
0.06
0.11
-0.12
0.05
0.08
-0.08
0.05
0.02
0.03
0.01
0.04
0.06
0.11
0.21
0.02
0.10
-0.07
-0.17
-0.21
-0.02
-0.11
0.03
0.14
-0.19
0.04
0.11
-0.13
0.03
0.03
0.03
0.11
0.09
0.04
-0.09
0.00
0.03
0.09
0.04
0.15
0.06
0.09
0.13
-0.18
-0.23
0.00
-0.14
0.01
0.03
-0.04
ALCOHOLIC
BEVERAGES
ALCOHOLIC
BEVERAGES
CIGARETTES
TOBACCO
AND
CIGARS
CLOTHING
FOOTWEAR
HOUSING
FUEL AND POWER
FURNITURE
AND
EQUIPMENT
HOUSEHOLD
OPERATION
MEDICAL
AND
CARE
HEALTH
EXPENSES
TRANSPORT
COMMUNICATION
-0.11
-0.02
RECREATION AND
ENTERTAINMENT
READING MATTER
EDUCATION
PERSONAL CARE
OTHER
GOODS
AND SERVICES
37
In order to facilitate, a closer analysis of the month to month variations in the size of
price changes by product sub-category, an appendix of such results has been included at
the end of this paper.
Analysis of magnitude of price increases by product sub-category
The largest average price increases have been in footwear (21%), recreation and
entertainment (15%), furniture and equipment (14%) and food (14%). The smallest
average price increases have been in housing (2%), other good and services (3%) and
communication (4%).
Mean size of price increases (descending)
FOOTWEAR
0.21
RECREATION AND ENTERTAINMENT
0.15
FURNITURE AND EQUIPMENT
0.14
FOOD
0.14
PERSONAL CARE
0.13
HOUSEHOLD OPERATION
0.11
CLOTHING
MEDICAL CARE AND HEALTH
EXPENSES
0.11
NON ALCOHOLIC BEVERAGES
0.11
FUEL AND POWER
0.10
TRANSPORT
0.09
EDUCATION
0.09
ALCOHOLIC BEVERAGES
0.08
READING MATTER
0.06
CIGARETTES TOBACCO AND CIGARS
0.06
COMMUNICATION
0.04
OTHER GOODS AND SERVICES
0.03
HOUSING
0.02
0.11
38
In order to facilitate, a closer analysis of the month to month variations in the size of
price increases by product sub-category, an appendix of such results has been included at
the end of this paper.
Analysis of magnitude of price decreases by product subcategory
The largest average price decreases have been in reading matter (-23%), footwear (-21%),
and furniture and equipment (-19%). The smallest average price decreases have been in
education (0%), communication (-2%) and housing (-2%).
Mean size of price decreases (ascending)
READING MATTER
-0.23
FOOTWEAR
-0.21
FURNITURE AND EQUIPMENT
-0.19
RECREATION AND ENTERTAINMENT
-0.18
CLOTHING
-0.17
FOOD
-0.16
PERSONAL CARE
-0.14
HOUSEHOLD OPERATION
NON ALCOHOLIC BEVERAGES
-0.13
-0.12
TRANSPORT
-0.11
FUEL AND POWER
MEDICAL CARE AND HEALTH
EXPENSES
-0.11
ALCOHOLIC BEVERAGES
-0.08
CIGARETTES TOBACCO AND CIGARS
-0.07
OTHER GOODS AND SERVICES
-0.04
HOUSING
-0.02
COMMUNICATION
-0.02
EDUCATION
-0.09
0.00
In order to facilitate, a closer analysis of the month to month variations in the size of
price decreases by product sub-category, an appendix of such results has been included at
the end of this paper.
39
Comparative Analysis
A brief summary of similar studies of unit level price data enables a comparison with the
findings for South Africa.11
Comparison of findings of CPI Micro-Data Analysis
South
Africa
Euro Area
US
Spain
France
Sierra
Leone
Frequency
of price
change
Frequency
of price
increases
Frequency
of price
decreases
Average
size of
price
increase
Average
size of
price
decrease
16
15.1
24.8
15
18.9
10.5
8.3
16.1
9
9.7
5.5
5.9
13.2
6
6.5
12.3
8.2
12.7
8.2
12.5
-15.1
-10
-14.1
-10.3
-10
51
Findings on the Euro area and the United States are reported in Alvarez (et al) (2005).
For the Euro area these draw on studies by Dhyne et al (2005) and Bils and Klenow
(2004). For the United States results are drawn from Klenow et al (2005). Findings on
Spain are reported from Alvarez et al (2004). Findings on France are drawn from Baudry
(2004). Findings on Sierra Leone are reported from Kovanen (2006). In the case of
Sierra Leone the frequency of price changes declined from 90% in 1999 to about 40% in
2003, resulting in the highest comparable average monthly price change frequency of
51%.
A more detailed comparison of findings on South Africa’s price setting conduct and
findings on price setting in other countries could be undertaken in further studies. In
particular it would be important to include a full discussion on inflationary, monetary and
11
Data on South Africa based on results of the current study. Data on Euro Area and US from Alvarez (et
al) (2005), drawing on studies by Dhyne et al (2005) and Bils and Klenow (2004). Data on size of price
change in US from Klenow et al (2005). Data on Spain from Alvarez et al (2004). Data on Sierra Leone
from Kovanen (2006), with frequency of price changes declining from 90% in 1999 to about 40% in 2003.
Data on France from Baudry (2004).
40
exchange rate conditions in each of the countries during the period under consideration.
Nonetheless, on the basis of the current limited comparison, it is possible to comment at
the aggregate level that, with regard to the frequency of price changes, that the findings
for South Africa (0,16) would appear to be most similar to findings for Spain (0,15) and
the Euro Area (0,15). The United States economy would appear to have a significantly
greater frequency of price changes, including higher frequencies both of price increases
and price decreases.
With regard to magnitude of price changes, the findings for South Africa are more similar
to those of the United States.
The average size of price increases in South Africa is
12,3% and in the United States the average size of price increases is 12,7%. This is
greater than the average size of price increases in the Euro Area (8,2%). The average size
of price decreases in South Africa at -15,1% is also more similar to the average size of
price decreases in the United States at -14,1%, than in the Euro Area (-10%).
Fortunately, price setting conduct in South Africa bears no resemblance to very high
inflation countries, such as, the finding for Sierra Leone where the frequency of price
change averages over 0,51 in the period between 1999 and 2003.
41
Discussion of Findings
The primary focus of this paper has been to work through a sizeable data set and to begin
to process basic findings from this data set on price setting conduct. While the study has
not yet matured to a point where a comprehensive discussion on findings can be
undertaken, there are a number of noteworthy issues which should be highlighted even at
this initial stage of the study.
Firstly, while the study found there to be an overall average price duration of 6,26
months, the average duration of prices tended to rise over the period including a low of
4,2 months (2003m6) and a high of 8,5 months (2004m12). This tendency for the
duration of prices to increase over the period could be regarded as consistent with a
learning phase during an important 4 year period commencing two years after South
Africa formally adopted an inflation targeting monetary policy framework. Increasing
average duration of prices may be interpreted as indicative of increased credibility with
price setters of the inflation targeting framework. Furthermore, reduced frequency of
price changes, or longer price duration, over the period would be consistent with the
experience of the disinflation that took place as South Africa’s currency appreciated
sharply after the currency crisis of late-2001 and early-2002. In this sense, the decreasing
frequency of price changes over time may also be indicative of state dependent rather
than time dependent pricing conduct in the South African economy over the period.
Secondly, potentially significant from a policy perspective is that the study establishes an
empirical basis for the fact that price setting conduct is not constant and indeed that such
conduct may be influenced by monetary policy actions (particularly interest rate
decisions) and may be indicative of the degree of credibility of such actions and the
overall policy stance.
Understanding the relationship between the monetary policy
environment and price setting conduct has important implications for the optimal design
of short-run monetary policy interventions. Also, the possibility exists to use the findings
on price setting conduct to analyse how changes in such conduct may lead changes in the
stance of the monetary authorities. For example, a study on the extent to which the
42
monetary authority’s interest rate decisions are influenced by changes in the frequency
and size of price changes at an aggregate level and at the level of product sub-sectors.
Thirdly, the fact that the highest frequency of price increases occurred in 2002m3 in the
immediate aftermath of the sharp currency depreciation, with 19% of prices recorded in
the sample increasing in that month (compared to a low of 6,52% of prices increasing in
2005m6), would seem to indicate that price setting conduct is closely effected by
exchange rate developments. An analysis of the effect, and lagged effect, of exchange
rate movements on price setting conduct would assist in understanding this relationship.
Fourthly, over the period under study there is greater symmetry in the frequency of price
increases and price decreases. Initially there was a higher frequency of price increases
(about 80%) than price decreases (about 20%), but by 2005m6, the proportion of price
increases (51,97%) to price decreases (48,03%) approached parity, only for the
proportion of price increases to price decreases to diverge once again with price increases
(65,02%) assuming dominance over price decreases (34,98%) by 2006m1.
Such a
finding for the initial period in which greater upward and downward price symmetry was
indicated, may not be inconsistent with the earlier suggested learning phase after the
introduction of South Africa’s inflation targeting monetary policy framework.
Furthermore, the more recent tendency for greater asymmetry in favour of price increases
may offer an early indicator of the build up of underlying inflationary pressures in the
economy.
Fifthly, although the data sample under study is strongly weighted in favour of goods
(94,5%) over services (5,5%), there evidence of some distinction between pricing
conduct of goods and services. When prices rise, services prices (5.05%) increase by less
than goods prices (12,77%) and when prices fall, services prices (-4,33%) fall by less
than goods prices (-15,45%). Although by a smaller magnitude, services prices (12,54%)
tend to rise more frequently than goods prices (10,42%). And in addition to falling by a
smaller magnitude, services prices (3,86%) decline less frequently than goods prices
(5,61%).
43
Sixthly, certain findings on pricing conduct in various specific product sub-sectors
require discussion:
Housing: The results for price setting behaviour in the housing sub-sector would seem to
indicate that housing price-setting is most volatile with housing prices reporting the most
frequent changes, the most frequent increases and the most frequent decreases of all subsectors (albeit with all such price changes being of small magnitude). This result is
misleading and appears to be based on the technical manner in which housing prices are
tracked by the statistical authorities rather than based on any substantive reasons. Certain
housing sub-sector price information – including the prices of rental stock of housing,
flats and townhouses (with a reported price change frequency of 0,88) – is based on a
frequently updated price index rather than on actual pricing conduct. Hence, there is a
tendency for small, but frequent changes in prices.12
The interest on mortgage bonds component of the housing prices sub-sector is also based
on changes to an index, but these changes show the expected pattern with all relevant
records increasing when the monetary authority’s key policy rate, the repo rate, increases
(for example four times in 2002), and decreasing when the repo rate decreases (on five
occasions during 2003). Overall, there is an average frequency of price changes of 0,22
for housing interest rate changes. Other components of the housing sub-sector, including
administered prices, such as, rates, sanitation and refuge services (0,07) as well as water
boarding and hostels (0,08) do not have frequent price changes and never experience
price reductions.
Footwear and clothing: It is important to attempt to reconcile the study’s findings on
price setting conduct in the clothing and footwear sub-sectors with the fact that, as an
aspect of the general disinflation over the period under study, these product sub-sectors
experienced the greatest disinflation and at times even experienced falling prices, as
12
This is as a result of a practice by the statistical authorities during the period under review, but
subsequently discontinued, that any observed price change over a quarter was distributed over the three
months of the following quarter.
44
indicated by the following graph of indices of CPI components. In the South African,
context it is understood that this is mainly due to the fact that the clothing and footwear
industries experienced intense competitive pressures mainly as a result of increased trade
liberalization preceding and during the period under review.
Commodities
CPI - COMPONENTS
Services
190
All items (The "general" index)
METROPOLITAN
Food
Cigarettes, cigars and tobacc o
170
Clothing and footwear
Housing
2000 = 100
150
Housing, gas, electricity and other fuels
COICOP
Fuel and power
Furniture and equipment
130
Household operation
Medical care and health expenses
110
Transport
Petrol
Communication
90
Recreation and entertainment
Leisure, entertainment and culture COICOP
MO042006
MO012006
MO102005
MO072005
MO042005
MO012005
MO102004
MO072004
MO042004
MO012004
MO102003
MO072003
MO042003
MO012003
MO102002
MO072002
MO042002
MO012002
MO102001
MO072001
MO042001
MO012001
MO102000
MO072000
MO042000
MO012000
70
Reading matter
Education
Personal care
Findings on price setting conduct for clothing and footwear are not inconsistent with the
disinflation-deflation experience of the sub-sector as the average magnitude of price
reductions in footwear (-21%) and clothing (-17%) are both at the upper end of the price
reduction scale in absolute value terms. On the other hand, both product sub-categories
score only moderately high average frequencies for price reductions (0.03).
The
disinflation-deflation context is also consistent with the finding that footwear (0,04) has
the lowest frequency for price increases compared to all other product sub-categories and
that clothing (0,06) is also a low scorer with regard to the frequency of price increases.
It may be somewhat counterintuitive that even in the context of disinflation-deflation for
the sub-sector, both clothing and footwear have marginally higher frequencies of price
increases than price decreases. This may be explained by the fact that, even though the
45
average magnitude of price decreases and increases are the same for footwear (-21% and
21%), the magnitude of price decreases for clothing (-17%) are higher than the magnitude
of increases for clothing (11%). The importance for this result is reinforced by the fact
that the number of price records in the clothing data set is about three times greater than
the number of price records in the footwear data set, hence the tendency for the larger
magnitude of clothing price reductions to be dominant for the sub-sector as a whole.
In conclusion, this discussion points to a complex relationship between reported inflation
rates for particular CPI component sub-sectors and findings on price setting conduct with
regard to the frequency and magnitude of price changes in each of these sub-sectors.
46
Conclusion
This working paper represents an important first attempt to use unit level pricing data to
describe pricing conduct in the South African economy.
The findings on pricing
behaviour show that during the period significant changes have taken place in aggregate
and disaggregated pricing conduct.
This is significant as the period under review
constitutes an important period shortly post the introduction of an Inflation Targeting
monetary policy framework in South Africa. During this period, there is evidence of a
general trend for a decreasing frequency of price changes, a reduced frequency of price
increases and an increased frequency of price decreases, the average sizes of price
changes, increases and decreases have not shown any such discernable pattern of change
over time, although there is evidence of increasing parity in the proportion of price
increases and price decreases over most of the period.
Working through the considerable data set and coming to some basic findings, provides a
basis for further research and analysis along a range of line of enquiry including analysis
of the degree of seasonality in price setting in the South African context and the
relationship between pricing conduct and a range of macroeconomic factors, such as,
interest rate changes, exchange rate movements, tax changes, money stock changes and
prevailing and anticipated rates of inflation. The consistency of the findings on pricing
conduct with a learning phase of the inflation targeting monetary policy framework is
also a matter for further consideration.
47
0.2
0.05
0
0.8
0.7
0.5
0.4
0.3
0.1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.25
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Appendix: Frequency of price changes by product sub-category 2001m12 to 2006m2
Alcoholic Beverages
Cigarettes Tobacco and Cigars
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
Clothing
Communication
0.7
0.6
0.15
0.5
0.4
0.1
0.3
0.2
0.1
0
Education
Food
0.3
0.6
0.25
0.2
0.15
0.2
0.1
0.05
0
48
0.04
0.1
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.06
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and Power
0.14
0.3
0.12
0.25
0.08
0.2
0.15
0.1
0.02
0.05
0
0
Furniture and Equipment
Household operation
0.3
0.25
0.25
0.2
0.2
0.15
0.15
0.1
0.05
0.05
0
0
Housing
Medical care and health expenses
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
49
0.4
0.35
0.25
0.3
0.2
0.15
0.05
0.1
0
0.3
0.25
0.2
0.15
0.1
0.05
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.2
0.15
0.1
0.05
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.45
0.4
0.35
0.3
0.25
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Non-alcoholic beverages
Other goods and services
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Personal Care
Reading Matter
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Recreation and entertainment
Transport
0.4
0.35
0.25
0.3
0.15
0.2
0.05
0.1
0
50
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.2
0.8
0.6
0.5
0.3
0.2
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.3
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
Appendix: Frequency of price increases by product sub-category 2001m12 to
2006m2
Alcoholic Beverages
Cigarettes, Tobacco & Cigars
0.6
0.7
0.5
0.6
0.4
0.5
0.4
0.3
0.1
0.2
0.1
0
0
Clothing
Communication
0.18
0.16
0.14
0.12
0.1
0.7
0.08
0.06
0.04
0.02
0
0.3
0.6
0.5
0.4
0.2
0.1
0
Education
Food
0.7
0.25
0.2
0.4
0.15
0.1
0.1
0.05
0
51
0.25
0.2
0.15
0.1
0.05
0
0.4
0.1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m5
02
20 m9
03
20 m1
03
20 m5
03
20 m9
04
20 m1
04
20 m5
04
20 m9
05
20 m1
05
20 m5
05
20 m9
06
m
1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
0.04
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and Power
0.12
0.25
0.08
0.1
0.2
0.06
0.15
0.1
Fuel and Power
0.02
0.05
0
0
Furniture and Equipment
Household Operation
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Housing
Medical Care and Health Expesnses
0.6
0.4
0.5
0.35
0.25
0.3
0.3
0.2
0.2
0.15
0.1
0.05
0
52
0.25
0.3
0.15
0.2
0.05
0.1
0
0.3
0.25
0.2
0.15
0.1
0.05
0
0.25
0.2
0.05
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.4
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.35
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Non-Alcoholic Beverages
Other goods and services
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Personal Care
Reading Matter
0.35
0.4
0.3
0.25
0.15
0.2
0.05
0.1
0
Recreation and Entertainment
Transport
0.35
0.3
0.15
0.25
0.2
0.1
0.15
0.05
0.1
0
53
0.09
0.08
0.07
0.06
0.05
0.04
Clothing
0.03
0.02
0.01
0
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
2006m1
2005m10
2005m7
2005m4
2005m1
2004m10
2004m7
2004m4
2004m1
2003m10
2003m7
2003m4
2003m1
2002m10
2002m7
2002m4
2002m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.05
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Appendix: Frequency of price decreases by product sub-category 2001m12 to
2006m2
Alcoholic Beverages
Cigarettes, Tobacco and Cigars
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
Clothing
Communication
0.3
0.25
0.2
0.15
0.1
0.05
0
Education
Food
0.14
0.12
0.08
0.1
0.06
0.04
0.02
0
54
0.06
0.35
0.3
0.25
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.07
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.08
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and Power
0.16
0.14
0.12
0.05
0.1
0.04
0.08
0.03
0.06
0.02
0.04
0.01
0.02
0
0
Furniture and Equipment
Household Operation
0.14
0.07
0.12
0.06
0.1
0.05
0.08
0.04
0.06
0.03
0.04
0.02
0.02
0.01
0
0
Housing
Medical Care and Health Expenses
0.16
0.14
0.12
0.2
0.1
0.08
0.15
0.06
0.1
0.04
0.05
0.02
0
0
55
0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.05
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Non-Alcoholic Beverages
Other Goods and Services
0.3
0.25
0.2
0.15
0.1
0.05
0
Personal Care
Reading Matter
0.035
0.04
0.025
0.03
0.015
0.02
0.005
0.01
0
Recreation and Entertainment
Transport
0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
56
0.02
-0.06
-0.08
-0.1
-0.02
Education
0.12
0.1
0.08
0.06
0.04
0.02
0
2002m1
2002m3
2003m3
2004m3
2005m3
2005m11
-0.02
2005m9
0.04
2005m10
0
2005m7
0.06
2005m4
0.08
0.04
2005m1
0.06
2004m8
0.1
2004m11
0.12
2004m5
Clothing
2004m4
-0.04
2004m1
-0.02
2003m8
0
2003m7
Alcoholic Beverages
2003m5
0.08
2003m4
0.1
2003m1
0.1
2002m5
0.12
2002m1
0.02
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.08
-0.01
-0.02
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Appendix: Size of price changes by product sub-category 2001m12 to 2006m2
Cigarettes, Tobacco and Cigars
0.06
0.06
0.04
0.04
0.02
0
-0.02
-0.04
Communication
0.12
0.08
0.1
0.02
-0.04
0
Food
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
-0.03
57
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Housing
0.05
0.25
0.04
0.2
0.03
0.15
0.02
0.1
0.01
0.05
0
0
-0.01
-0.05
-0.02
-0.1
2006m1
-0.1
2005m9
-0.05
2005m11
0.02
2005m7
0
2005m5
0.04
2005m3
0.05
2005m1
0.15
2004m9
Furniture and Equipment
2004m11
-0.3
2004m7
-0.2
2004m5
-0.1
2004m3
0
2004m1
0.1
2003m9
0.3
2003m3
0.12
2002m9
0.4
2002m12
0.14
2002m6
0.5
2002m1
0.1
-0.04
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.2
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and Power
0.08
0.06
0.04
0.02
0
-0.02
Household operation
0.1
0.1
0.08
0.06
0
-0.02
-0.04
Medical care and health expenses
58
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.15
0.1
0.05
0
-0.05
-0.1
0.18
0.16
0.14
0.12
0.04
0.02
0
-0.02
0.15
0.1
0
-0.05
-0.1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.25
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
m1
20
02
20 m6
02
m
20 10
03
m3
20
03
20 m7
03
m
20 12
04
m3
20
04
m6
20
04
20 m9
04
m
20 12
05
m3
20
05
m6
20
05
20 m9
05
m1
2
0.3
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
m1
20
02
m4
20
02
20 m7
02
m
20 10
03
m1
20
03
m4
20
03
20 m7
03
m
20 10
04
m1
20
04
m4
20
04
20 m7
04
m
20 10
05
m1
20
05
m4
Non-alcoholic beverages
Other goods and services
0.08
0.2
0.06
0.04
0.02
0
-0.02
-0.04
Personal Care
Reading matter
0.35
0.25
0.3
0.1
0.2
0.08
0.06
0.15
0.05
0.1
0
-0.05
-0.1
Recreation and entertainment
Transport
0.1
0.08
0.05
0.06
0.04
0.02
0
-0.02
59
0.12
0.08
0.1
0.06
0.04
0.02
0
0.15
0.1
0.12
0.1
0.08
0.06
0.04
0.02
0
2002m1
2002m3
2003m3
2004m3
2005m3
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.14
20
03
m
1
20
03
m
4
20
03
m
5
20
03
m
7
20
03
m
8
20
04
m
1
20
04
m
4
20
04
m
5
20
04
20 m8
04
m
20 11
05
m
1
20
05
m
4
20
05
m
7
20
05
20 m9
05
m
11
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
0.16
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m
1
Appendix: Size of price increases by product sub-category 2001m12 to 2006m2
Alcoholic beverages
Cigarettes, Tobacco and Cigars
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Clothing
Communication
0.25
0.12
0.2
0.1
0.08
0.06
0.05
0.04
0.02
0
0
Education
Food
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
60
0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.4
0.3
0.2
0.1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.9
0.8
0.7
0.6
0.5
20
03
m1
2
20
04
m2
20
04
m4
20
04
m6
20
04
m8
20
04
m1
20
0
04
m1
2
20
05
m2
20
05
m4
20
05
m6
20
05
m8
20
05
m1
20
0
05
m1
2
20
06
m2
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and power
0.25
0.2
0.15
0.1
0.05
0
Furniture and Equipment
Household Operation
0.45
0.4
0.35
0.3
0.25
0.14
0.2
0.15
0.1
0.05
0
0.06
0.12
0.08
0.1
0.04
0.02
0
Housing
Medical care and health expenses
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
61
0.1
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
0.25
0.2
0.15
0.1
0.05
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0.15
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
03
m1
2
20
04
m2
20
04
m4
20
04
m6
20
04
m8
20
04
m1
20
0
04
m1
2
20
05
m2
20
05
m4
20
05
m6
20
05
m8
20
05
m1
20
0
05
m1
2
20
06
m2
0.25
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
04
20 m7
04
m
20 10
05
20 m1
05
20 m4
05
20 m7
05
m1
0
Non-alcoholic beverages
Other goods and services
0.35
0.12
0.3
0.1
0.2
0.08
0.06
0.04
0.05
0.02
0
0
Personal Care
Reading Matter
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Recreation and entertainment
Transport
0.16
0.14
0.12
0.08
0.1
0.06
0.04
0.02
0
62
1
0
0.9
-0.02
0.8
0.7
20
02
m
20 1 |
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
0
-0.02
-0.04
-0.06
-0.08
-0.12
-0.14
-0.18
0
-0.05
-0.1
-0.25
-0.3
-0.35
0.6
0.5
0.4
0.3
0
2001m12
2002m1
2002m3
2003m3
2004m3
2005m3
20
02
20 m2
02
20 m5
0
20 2m8
02
m
20 11
03
20 m2
03
20 m5
03
20 m8
03
m
20 11
04
20 m2
04
20 m5
0
20 4m8
04
m
20 11
05
20 m2
05
20 m5
0
20 5m8
05
m
20 11
06
m2
20
02
20 m2
02
20 m5
0
20 2m8
02
m
20 11
03
20 m2
03
20 m5
03
20 m8
03
m
20 11
04
20 m2
04
20 m5
0
20 4m8
04
m
20 11
05
20 m2
05
20 m5
0
20 5m8
05
m
20 11
06
m2
Appendix: Size of price decreases by product sub-category 2001m12 to 2006m2
Alcoholic Beverages
Cigarettes, Tobacco and Cigars
0
-0.1
-0.2
-0.1
-0.3
-0.4
-0.16
-0.5
-0.6
Clothing
Communication
0
-0.005
-0.15
-0.02
-0.2
-0.025
Education
0.2
-0.14
0.1
-0.16
2003m7
2003m8
2004m4
2005m9
2005m10
2005m11
-0.015
-0.01
-0.03
-0.035
-0.045
-0.04
Food
-0.04
-0.06
-0.08
-0.12
-0.1
-0.18
-0.2
63
20
02
20 m1
02
20 m4
02
20 m7
02
m
20 10
03
20 m1
03
20 m4
03
20 m8
03
m
20 11
04
20 m2
04
20 m5
04
20 m8
04
m
20 11
05
20 m2
05
20 m5
05
20 m8
05
m1
1
-0.05
-0.05
-0.1
-0.1
-0.15
-0.15
-0.2
-0.2
-0.25
-0.25
-0.3
-0.3
2006m2
2005m12
0
2005m8
Housing
2005m10
-0.6
2005m6
-0.5
2005m4
-0.1
2005m2
0
2004m12
Furniture and Equipment
2004m8
-0.5
2004m10
-0.45
2004m6
-0.25
2004m4
-0.3
2004m2
-0.35
2003m6
-0.2
2003m12
-0.25
2002m6
-0.2
2002m12
-0.1
2002m1
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
03
20 m7
03
m
20 10
04
20 m1
04
20 m5
0
20 4m8
04
m
20 11
05
20 m2
05
20 m5
0
20 5m8
05
m
20 11
06
m2
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
-0.05
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
Footwear
Fuel and Power
0
-0.05
-0.15
-0.1
-0.15
-0.4
-0.3
-0.35
-0.4
Household Operation
0
-0.05
-0.2
-0.3
-0.1
-0.4
-0.15
-0.2
-0.25
Medical care and health expenses
0
64
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
-0.1
-0.2
-0.1
0
-0.2
-0.3
-0.4
-0.5
-0.6
0
-0.05
-0.25
-0.3
20
02
20 m3
02
20 m7
02
m
20 11
03
20 m2
03
20 m5
03
20 m8
03
m
20 11
04
m2
20
04
20 m5
04
20 m8
04
m
20 11
05
20 m2
05
20 m5
05
20 m8
05
m
20 11
06
m2
-0.05
20
02
20 m1
02
20 m7
03
20 m1
0
20 3m7
03
m
20 10
04
20 m2
04
20 m4
04
20 m6
0
20 4m8
04
20 m10
04
m
20 12
05
20 m2
05
20 m4
05
20 m6
0
20 5m8
05
m
20 10
06
m1
20
02
20 m2
02
20 m5
0
20 2m8
02
m
20 11
03
20 m2
03
20 m5
0
20 3m8
03
m
20 11
04
20 m2
04
20 m5
0
20 4m8
04
m
20 11
05
20 m2
05
20 m5
0
20 5m8
05
m
20 11
06
m2
0
20
02
20 m1
02
20 m4
0
20 2m7
02
m
20 10
03
20 m1
03
20 m4
0
20 3m7
03
m
20 10
04
20 m1
04
20 m4
0
20 4m7
04
m
20 10
05
20 m1
05
20 m4
0
20 5m7
05
m
20 10
06
m1
20
02
m1
20
02
20 m6
02
m
20 10
03
m3
20
03
20 m7
03
m
20 12
04
m3
20
04
m6
20
04
20 m9
04
m
20 12
05
m3
20
05
m6
20
05
20 m9
05
m1
2
Non-alcoholic beverages
Other goods and services
0
-0.05
-0.1
-0.15
-0.15
-0.2
-0.25
-0.25
-0.3
-0.3
-0.35
Personal care
Reading Matter
0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.7
-0.6
-0.8
-0.7
-0.9
-0.8
Recreation and entertainment
Transport
0
-0.05
-0.1
-0.1
-0.15
-0.2
-0.15
-0.2
-0.25
65
Stata Methodology
Importation and organisation of data
set mem 930m
insheet using "C:\...CPI Unit Data\PriceData_Full_Data_Set.txt"
rename v1 store
rename v2 stccode
rename v3 productcode
/*rename v3 date*/
rename v5 price
rename v6 unitcode
rename v7 capturecode
recast double price, force
format price %9.2f
/*creating unique ids*/
gen double uniq_store=store*100000000000
gen double uniq_productcode=productcode*10000
gen double id=uniq_store+uniq_productcode+unitcode
format uniq_store uniq_productcode id %15.0f
/*now I'm going to try and split the date into date and time*/
split v4, gen(date)
drop v4 date2
gen edate=date(date1, "ymd")
split date1, gen(date1) parse(-)
gen year=date11
gen month=date12
/*converting from a string to a numeric variable*/
destring year month, replace
gen edate2=ym(year, month)
format edate2 %tm
duplicates drop id edate2, force
/*for disaggregated analysis only*/
/*select portion of CPI data base to work with*/
/* e.g. keep if productcode>3200000 & productcode<4100000
/*now put this in a panel by store*/
tsset id edate2
/*, monthly this is in monthly format*/
Analysis of frequency of price changes
gen change=price-l.price
gen changedummy=1 if change~=0 & change~=.
replace changedummy=0 if change==0
66
tabstat changedummy, stat(mean p50 n) by(edate2)
gen increasedummy=1 if change>0 & change~=.
replace increasedummy=0 if change<=0 & change~=.
tabstat increasedummy, stat(mean p50 n) by(edate2)
gen decreasedummy=1 if change<0 & change~=.
replace decreasedummy=0 if change>=0 & change~=.
tabstat decreasedummy, stat(mean p50 n) by(edate2)
Analysis of size of price change
gen lnprice=log(price)
gen changelnprice=lnprice-l.lnprice
tabstat changelnprice if changelnprice~=0 & changelnprice~=., stat(mean
p50 n) by(edate2)
tabstat changelnprice if changelnprice>0, stat(mean p50 n) by(edate2)
tabstat changelnprice if changelnprice<0, stat(mean p50 n) by(edate2)
Analysis of transitional properties (Results of this aspect are not
discussed in this paper)
/*this reports the transitional probabilities i.e. if there was a
change in the last period what is the probability of a change in the
current*/
xttrans changedummy, i(id) freq
xttrans increasedummy, i(id) freq
xttrans decreasedummy, i(id) freq
67
Price Collection Frequencies (Statistics South Africa)
Prices of goods and services collected monthly:
































Bread.
Meat.
Milk.
Vegetables and fruit.
Other groceries.
Alcoholic beverages.
Sweets, non-alcoholic beverages, ice-cream and
tobacco products.
Clothing and footwear.
Repairs of clothing, footwear and furniture.
Interest rates on mortgage bonds.
Coal and wood.
New vehicles, repairs and services.
Motor spare parts and accessories.
Petrol.
Newspapers and magazines.
Entrance fees - drive inns and bioscopes.
Air transport fees.
Cellular phone tariffs.
Furniture and equipment.
Medicine.
Garden tools.
Washing ironing and dry-cleaning.
Sport equipment.
Reading matter and stationery.
Tariffs of hairdressing services.
Ironware and crockery.
New and retread tyres.
Household textiles.
Electrical appliances and equipment.
Medical, toilet and photographic requisites and
services.
Musical instruments.
Prices of pets.
68
Prices of goods and services collected quarterly:
Good/service
Survey month
Rent of dwellings.
January, April, July and October.
Motor vehicle insurance.
March, June, September and December.
Public transport tariffs.
March, June, September and December.
Prices of goods and services collected annually.
Good/service
Survey month
Doctor's and dentist's fees. January.
Motor vehicle license and
Registration fees.
Telephone (land lines).
Toll-fees at toll-gates.
School funds.
University boarding and
class fees.
March.
Parking fees.
Postal tariffs.
April.
Property taxes.
Refuse removal.
Sanitary fees.
July.
Maintenance of graves.
October.
Prices of goods/services collected at other times of the year:
Good/service
Survey month
Contribution to medical aid. January.
Property insurance.
Hospital fees.
January and July.
Water.
Electricity.
January, July and August.
Domestic workers.
February and September.
Television licenses.
April and October.
69
Bibliography
Altissimo Filippo, Ehrmann Michael and Smets Frank, “Inflation Persistence and Price
Setting Behaviour in the Euro Area”, European Central Bank, Occasional Paper Series
No.46, June 2006
Alvarez L and Hernando I, “Price setting behaviour in Spain. Stylised facts using
consumer price microdata” , European Central Bank Working Paper No. 416, 2004
Alvarez L, Burriel P and Hernando I. “Price setting behaviour in Spain: evidence from
micro PPI data”, European Central Bank Working Paper No. 522, 2005
Alvarez L and Hernando I, “The Price setting behaviour of Spanish Firms: Evidence from
Survey Data”, European Central Bank Working Paper No.538, October 2005
Alvarez et al, “Sticky Prices in the Euro Area: A summary of new micro evidence”,
European Central Bank Working Paper Series, No.563, December 2005
Baudry L, Le Bihan H Sevestre P and Tarrieu S, “Price Rigidity in France, Some
evidence from Consumer Price Micro Data, Banque de France, mimeo, 2004
Bils M and Klenow P, “Some evidence on the importance of sticky prices”, Journal of
Political Economy 112, pp.947-985 (2004)
Dhyne E, Alvarez L, Le Bihan H, Veronese G, Dias D, Hoffman J, Jonker N,
Lunnermann P, Rumler F and Vilmunen J, “Price setting in the Euro Area: Some stylised
facts from individual consumer price data” ECB Working Paper (2005)
Klenow P and Kryvstov, “State-dependent or time-dependent pricing: Does if Matter for
Recent US Inflation?” mimeo (2005)
Kovanen A, “Why do prices in Sierra Leone Change So Often? A Case Study Using
Micro Level Price Data”, IMF Working Paper WP/06/53 (2006)
70