calculating the annual escalation adjustment for...

Calculating the Annual Escalation Adjustment for Municipal Infrastructure

REPORT NUMBER: 8237

VERSION 2.0

19 JULY 2013

Prepared by

Aurecon (Pty) Ltd PO Box 74381 Lynnwood Ridge 0040 South Africa

Contact Person: Dr HMS Belmonte

Tel: 012 427 2560 Fax: 086 723 1845

Calculating the Annual Escalation Adjustment for Municipal Infrastructure 2

15 November 2012 Dr H.M.S. Belmonte

APPROVAL PAGE

Name

Designation Signature Date

Compiled by: Name: Dr H.M.S. Belmonte

Technical Lead

19 Jul 2013

Approved by: Name: Mr Chris Schmidt

Technical Director

19 Jul 2013

AMENDMENT HISTORY

Version Date Amendment Section / Chapter / Page CR

Number

Checked by:

(Name and Initial)

1.0 16 Nov 2012 Final draft for comment. N/A HB, CS

2.0 19 Jul 2013 Updated for 2012/13 financial year 2 HB, CS



TABLE OF CONTENTS

List of Figures ................................... ................................................................................................................ 4

List of Tables .................................... ................................................................................................................. 4

List of Abbreviations ............................. ........................................................................................................... 5

1. Introduction ...................................... ................................................................................................. 6

2. Approach .......................................... .................................................................................................. 7

2.1 Introduction .......................................................................................................................................... 7

2.2 The Formula ........................................................................................................................................ 7

3. Methodology ....................................... ............................................................................................... 9

3.1 Introduction .......................................................................................................................................... 9

3.2 The Indices .......................................................................................................................................... 9 3.2.1 Introduction ............................................................................................................................. 9 3.2.2 CPI - Labour Index ............................................................................................................... 11 3.2.3 PPI - Plant Index, Material Index and Fuel Index ................................................................. 12

3.3 The Coefficients ................................................................................................................................ 13

3.4 Calculating the Contract Price Adjustment........................................................................................ 15

4. Comparison of %CPA to CPI and PPI ................. .......................................................................... 17

4.1 Introduction ........................................................................................................................................ 17

4.2 CPI..................................................................................................................................................... 17

4.3 PPI ..................................................................................................................................................... 18

4.4 Comparison of Inflation Indices ......................................................................................................... 18

5. Concluding Remarks ................................ ...................................................................................... 20

References ........................................ .............................................................................................................. 21

Appendix A – Labour, Plant, Material and Fuel Indic es .............................................................................. 22

Appendix B – Headline CPI and PPI ................. ............................................................................................ 29



List of Figures

Figure 4-1 Calculated %CPA, Headline CPI and PPI form the 2001/02 to 2012/13 Municipal Financial Years. 19

List of Tables

Table 3-1 Conversion Factor for Determining the CPI Indices from the 2012 and 2008 Base Years to the 2000 Base Year 9 Table 3-2 Using the Conversion Factor for Determining the CPI Indices 10 Table 3-3 Conversion Factor for Determining the PPI Indices from the 2012 Base Year to the 2000 Base Year 10 Table 3-4 Labour Index Values per Province for each Financial Year (Base Year = 2000) 11 Table 3-5 Plant Index, Material Index and Fuel Index Values for each Municipal Financial Year 12 Table 3-6 Guidelines for the Coefficients for the Contract Price Adjustment as published by the CIDB 13 Table 3-7 Statistical Analysis of Coefficient Values in CIDB Guideline 13 Table 3-8 Weighting of Coefficients to Represent Typical Composition of Municipal Infrastructure 14 Table 3-9 Final Recommended Coefficients for Municipal Infrastructure 14 Table 3-10 Contract Price Adjustment Factor Calculated from the 2001/2 to the 2012/13 Municipal Financial Year 15 Table 4-1 Annual Municipal Financial Year %CPI from 2001/02 to 2012/13 17 Table 4-2 Annual Municipal Financial Year %PPI from 2001/02 to 2012/13 18 Table 4-3 Comparison between Calculated Annual %CPA, CPI and PPI, based on Municipal Financial Years 19 Table A-0-1 Labour Index values as obtained from Stats SA CPI Index per Province 22 Table A-0-2 Plant Index, Material Index and Fuel Index values as obtained from Stats SA PPI 25 Table B-0-1 Headline Consumer Price Index: Index numbers and Annual Percentage Change on a Monthly Basis 29 Table B-0-2 Headline Producer Price Index: Index numbers and Annual Percentage Change on a Monthly Basis 30



List of Abbreviations

%CPA - Percentage Contract Price Adjustment

fCPA - Contract Price Adjustment Factor

CIDB - Construction Industry Development Board

CPA - Construction Price Adjustment

CPAP - Contract Price Adjustment Provisions Work Group Indices

CPI - Consumer Price Index

FIDIC - Fédération Internationale Des Ingénieurs-Conseils, French for the International Federation of Consulting Engineers

PPI - Producer Price Index

SAFCEC - South African Federation of Engineering Contractors

SAICE - South African Institution of Civil Engineering

SEIFSA - Steel and Engineering Industries Federation of South Africa

Stats SA - Statistics South Africa



1. Introduction

Under the Public Finance Management Act No.1 of 1999 and the Municipal Finance Management Act of 1999

No.56 of 2003, municipalities are required to account for their assets in compliance with GRAP (Generally

Recognised Accounting Practice). Most municipalities provide services to their communities through their

infrastructure assets that account for the largest portion of the value of all their assets that are captured within

their asset register. The asset registers are prepared as part of the annual financial statements that are audited

by the Auditor General.

The challenge with valuing infrastructure assets lies in availability, or more accurately in the lack of availability of

accurate costing data for the broad spectrum of infrastructure assets that are typically owned by municipalities.

Ideally first principal modelling should be utilised to determine the valuation of infrastructure assets on an annual

basis, but the time and data requirements for implementing this approach are onerous which tends to make the

costs associated with this approach prohibitive. Unfortunately there is no national system in place that can

assist with the provision of accurate infrastructure asset valuations on an annual basis. In many cases

infrastructure asset valuation data or the unit rates derived from pre-exiting infrastructure costing data that is

available tends be historic. This presents a challenge in terms of the alignment between the age of the

valuation data and the age of the infrastructure being evaluated, due to the effect of inflation on the buying

power of money.

There are several measures or inflation rates that can be utilised to reflect this erosion in the purchasing power

of money. The most commonly used measure for price inflation is the Consumer Price Index (CPI) which is

usually calculated as a measure of the average change over time in the prices paid by urban consumers for a

market based basket of consumer goods and services. Another measure is the Producer Price Index (PPI)

which measures the average change in prices received by domestic producers for their output. However since

municipal infrastructure is created through civil engineering works, the infrastructure will be not representative of

the typical goods and services that an average ‘urban consumer’ uses nor the average price of the national

produce output. Thus using the CPI or PPI as measures for determining the value of municipal infrastructure is

not ideal as these indices will not be representative of the civil engineering construction industry.

This paper outlines an approach for utilising the Contract Price Adjustment (CPA) formula, that is used in the

construction industry and in particular in civil engineering construction to compensate contractors for the

escalation in costs over time, for escalating and de-escalating the value of municipal infrastructure assets. As

the Contract Price Adjustment is widely accepted in the civil engineering construction industry and is an effective

measure of cost escalation (i.e. inflation), it would thus provide a more representative measure of the expected

escalation and de-escalation in costs of municipal infrastructure.

This document details the methodology, assumption and results of this approach for determining a CPA based

‘inflation’ rate for municipal infrastructure.



2. Approach

2.1 Introduction

Most engineering construction based contracts contain provisions for adjustments to changes in cost (i.e. price

escalation) utilising a price adjustment formula to take into account the increases or decreases in the costs of

labour, equipment, plant, material and fuel over the period of the contract. It is the general practice that the

client of the works specifies the exact formula that is used for the contract; however standard formulae for

determining the escalation have been developed, in South Africa by: the South African Institution of Civil

Engineering (SAICE) ), South African Federation of Engineering Contractors (SAFCEC) and the Steel and

Engineering Industries Federation of South Africa (SEIFSA), and internationally by the Fédération Internationale

Des Ingénieurs-Conseils (FIDIC), French for the International Federation of Consulting Engineers.

The approach followed in this paper utilises the formula developed by the South African Institution of Civil

Engineering for determining the price escalation for construction works.

2.2 The Formula

The formula accepted and approved for inclusion in the General Conditions of Contract for Construction Works

(Second Edition, 2010), by the South African Institution of Civil Engineering (SAICE), is based on the Haylett

Formula for escalation, which has been adopted in the industry as it has been accepted by the SIACE,

Construction Industry Development Board (CIDB) and the South African Federation of Engineering Contractors

(SAFCEC). The expression utilised by the SAICE to calculate the Contract Price Adjustment Factor, fCPA, is

presented in Equation 1.

�� 1 � ��

��

��

�� 1� Equation 1

Where:

• “x” is the proportion of the contract value that is not subject to adjustment (i.e. the fixed portion), and unless

stated otherwise in the contract the fixed proportion will be 0.10 or 10%. Thus the portion that will be

subject to adjustment is 0.9 or 90% of the contract/claim value.

• “a”, “b”, “c” and “d” are the coefficients contained in the contract which are deemed, irrespective of the

actual constituents of the work, to be representative of the proportionate value of labour, contractor’s

equipment, materials (excluding specialist materials which must be separately stipulated in the contract)

and fuel respectively. The arithmetical sum of “a”, “b”, “c” and “d” must be equal to unity. Thus these

coefficients are effectively weighting factors that account for the proportion of the labour, plant, material and

fuel values of the construction works being carried out.

• “L” is the Labour Index, the value for which is taken as the Consumer Price Index for the Province where

the work is/was carried out as published by Stats SA in their monthly statistical news release P0141

(Consumer Price Index) (Table 14).

• “P” is the Plant Index, the value for which is taken as the Producer Price Index for Civil Engineering Plant

as published by Stats SA in their monthly statistical news release P0151 (Contract Price Adjustment

Provisions Work Group Indices (CPAP)) (Table 4).

• “M” is the Materials Index, the value for which is taken as the Producer Price Index for Civil Engineering

materials as published by Stats SA in their monthly statistical news release P0151 (Table 3).

• “F” is the Fuel Index, the value for which will be taken as the Producer Price Index for Diesel at wholesale

level for the area where the contract is being carried out as published by Stats SA monthly statistical news

release P0151 (Table 4).



• For “L”, “P”, “M” and “F” the suffix “o” denotes the base indices applicable to the base time frame (month or

year) that will be utilised in the determination of the Contract Price Adjustment Factor and the suffix “t”

denotes the current indices applicable to the future time frame (month or year) that will be utilised in the

determination of the Contract Price Adjustment Factor.

The price adjustment amount is determined by multiplying the original applicable/relevant amount by the

Contract Price Adjustment Factor (fCPA). In summary the expression in Equation 1 provides a multiplication

factor to adjust what the contractor is paid for to reasonably account for the effects of inflation that occur within

in the civil engineering construction industry over the period of the contract. Hence the formula in Equation 1

provides an effective inflation adjustment mechanism for the civil engineering construction industry that can be

calculated based on published CPI and PPI indices that are germane to the civil engineering construction

industry.

Considering that the current replacement cost value of any given municipal asset needs to be representative of

the cost that would be incurred if that same asset had to be constructed in the same location to provide the

same service, utilising the Construction Price Adjustment to determine the escalation in value of municipal

assets due to inflation would provide a more representative measure than simply scaling the municipal asset

value by CPI or PPI rate. Utilising the Construction Price Adjustment formula in Equation 1 it is thus possible to

determine the multiplication factor (i.e. the percentage change) for adjusting the value of municipal infrastructure

to accommodate for inflation.



3. Methodology

3.1 Introduction

In the proposed methodology the Haylett Formula as adopted by the SAICE for determining the Construction

Price Adjustment will be calculated for the municipal financial year from 2001/02 to 2012/13. However in order

to use the expression in Equation 1, the required indices data for the Labour Index, the Plant Index, the

Materials Index, the Fuel Index along with the weighting coefficients (for labour, contractor’s equipment,

materials and fuel) must first be determined. This section details how each of the required indices and

coefficients are determined, then utilised to calculate the Construction Price Adjustment.

3.2 The Indices

3.2.1 Introduction

The indices for the Labour Index, Plant Index, Materials Index and Fuel Index are taken from the Statistical

News Releases P0141 and P0151, which published by Stats SA on a monthly basis.

The first consideration that needs to be taken into account is that Stats SA calculates the CPI and PPI on a base

year and every few years they change the base year. The current base year for the CPI is 2012, previously it

was 2008 and before that it was 2000 and 1995. Stats SA provided a conversion factor to change the indices

from the 2008 base year to the equivalent indices for the previous base year (2000). In order to determine the

inflationary changes from 2000/1 municipal financial year onwards it was decided that the base year that would

be utilised for this study for the CPI and PPI indices would be 2000 base year.

This means that for the CPI we would need to utilise the conversion factor to convert the newer CPI indices from

the 2012 base year (where 2012 = 100) to the 2008 base year (where 2008 = 100) and to then convert from the

2008 base year (where 2008 = 100) to the 2000 base year (where 2000 = 100).

Presented in Table 3-2 is the conversion factor for determining CPI Indices for the nine provinces from the 2000

base year to the 2008 base year, from the 2008 base year to the 2012 base year and the derived conversion

factor for determining CPI Indices from the 2012 base year to 2000 base year. In Table 3-1 the provinces are

listed by their initials.

Table 3-1 Conversion Factor for Determining the CPI Indices from the 2012 and 2008 Base Years to the 2000 Base Year

2000 : 2008 2008 : 2000 2008 : 2012 2012 : 2008 200 0 : 2012 2012 : 2000

WC 0.6085 1.6433 0.7893 1.2670 0.4803 2.0821

EC 0.6067 1.6483 0.7776 1.2860 0.4718 2.1197

NC 0.5895 1.6965 0.7788 1.2840 0.4591 2.1783

FS 0.6478 1.5438 0.7788 1.2840 0.5045 1.9822

KZN 0.6157 1.6242 0.7924 1.2620 0.4879 2.0497

NW 0.6147 1.6269 0.7849 1.2740 0.4825 2.0727

GP 0.6176 1.6191 0.7937 1.2600 0.4902 2.0401

MP 0.5917 1.6899 0.7776 1.2860 0.4601 2.1732

LP 0.6257 1.5983 0.7899 1.2660 0.4942 2.0234



Presented in Table 3-2 is an example of how the conversion factor for determining CPI Indices from one base

year to another base year, for the: 2000 base year to the 2008 base year (and visa-versa), the 2008 base year

to the 2012 base year (and visa-versa) and the derived conversion factor for the 2000 base year to 2012 base

year (and visa-versa). In effect to covert a CPI index from the 2008 base year (where 2008 = 100) to the 2000

base year (where 2000 = 100), simply multiply the CPI indices for 2008 base year by the Conversion factor

(1.6191) to get the equivalent indices as per the 2000 base year.

Table 3-2 Using the Conversion Factor for Determining the CPI Indices

Base Year A : Base Year B Conversion Factor Effective Index Base Year A

Effective Index Base Year B

2000 : 2008 0.6176 100 61.76

2008 : 2000 1.6191 100 161.91

2008 : 2012 0.7937 100 79.37

2012 : 2008 1.2600 100 126.00

2000 : 2012 0.4902 100 49.02

2012 : 2000 2.0401 100 204.01

The current base year for the PPI is 2012, which means that there for all PPI indices published after 2012 will

need to converted from the 2012 base year to the 2000 base year. However there will be no need to convert

any of the indices data from one base year to another for the indices between 2001 and 2012.

Presented in Table 3-3 is the conversion factor for determining PPI Indices for the Plant (Civil Engineering

Plant), Materials (Civil Engineering) and Fuel (Diesel Oil – Coast and Witwatersrand) from the 2012 base year to

the 2000 base year.

Table 3-3 Conversion Factor for Determining the PPI Indices from the 2012 Base Year to the 2000 Base Year

PPI Index 2000 : 2012 2012 : 2000

Plant (Civil) 0.523386 1.910636

Material (Civil) 0.440352 2.270909

Fuel (Diesel Oil – Coast and WW Rand) 0.241392 4.142636



3.2.2 CPI - Labour Index

The Labour Index is taken as the Consumer Price Index according to urban area that is published by Stats SA in

their monthly Statistical release P0141 Consumer Price Index publication. The CPI index values are published

for each province in the Consumer Price Index and Percentage Change According to Urban Area Table in

publication P0141 is taken as the Labour Index for each province (as required by the expression in Equation 1).

It should be noted that the format of Stats SA, Statistical release P0141 Consumer Price Index has changed

over the years. This means that the Table in Stats SA, Statistical release P0141.1 Consumer Price Index for

determining the Labour Index values changed. Between January 2001 to December 2006 the data for the

Labour Index could be found in Table 21, titled “Consumer Price Index and percentage change according to

urban area”; then between January 2007 to December 2008 the data for the Labour Index could be found in

Table 7.1, also titled “Consumer Price Index and percentage change according to area”; and then in January

2009 to December 2012 the data for the Labour Index can be found under Geographic Indices and CPI per

Province in Table A, titled “Consumer Price Index: Indices and percentage changes”. Current the CPI data for

the Labour Index can be found under Table 14 titled “CPI - all items, according to area”.

It should be noted that in 2001 the CPI provincial data for the Limpopo Province was presented under Northern

Province. An average of the provincial indices was calculated to provide an indicative Labour Index for the

whole of South Africa. The Labour Index data was collected from Stats SA from January 2001 to June 2013,

this data can be found in Table A–0–1 in Appendix A.

Considering that municipal infrastructure valuations tend to coincide with the municipal financial year, an

average Labour Index for the municipal financial year was determined by averaging the Labour Index values for

each month of the municipal financial year (i.e. July to June). This was calculated for the municipal financial

year from 2001/02 to 2012/13, the result of which are presented in Table 3-4.

Table 3-4 Labour Index Values per Province for each Financial Year (Base Year = 2000)

Municipal Financial Year WC EC NC FS KZN NW GP MP LP ZA

2001/02 110.4 109.8 110.7 107.8 109.6 108.9 108.9 109.9 109.2 109.5

2002/03 122.8 123.1 123.3 116.9 121.8 120.6 121.3 122.5 120.2 121.4

2003/04 123.9 124.8 125.1 119.1 123.8 123.0 122.2 125.1 120.4 123.1

2004/05 127.0 128.3 129.0 122.2 126.3 125.8 125.7 128.8 123.2 126.3

2005/06 131.5 133.6 135.0 127.3 130.6 131.9 130.4 134.4 127.3 131.3

2006/07 140.2 142.2 144.1 134.2 139.7 138.6 139.1 143.9 136.3 139.8

2007/08 154.6 154.9 157.2 145.2 153.5 153.0 153.3 159.2 151.0 153.5

2008/09 171.3 172.9 176.4 160.9 170.6 170.3 168.6 177.7 167.3 170.7

2009/10 180.9 181.2 185.4 169.3 178.0 178.3 177.6 186.9 173.9 179.1

2010/11 187.9 189.0 192.2 176.9 183.7 184.7 184.3 193.9 180.4 185.9

2011/12 198.5 202.0 206.3 188.3 194.7 196.2 194.7 206.0 191.4 197.5

2012/13 208.9 212.5 218.3 198.6 205.6 208.0 205.5 218.0 202.7 208.7

In Table 3-4 the provinces are listed by their initials and the ZA refers to the average value calculated for the

whole of South Africa.



3.2.3 PPI - Plant Index, Material Index and Fuel Index

The Plant, Material and Fuel Indices used in Equation 1 are specific Producer Price Index values that are

currently published by Stats SA in their monthly Statistical release P0151 the Contract Price Adjustment

Provisions Work Group Indices, previously they were published by Stats SA in Statistical News Release

P0142.1.

The Plant Index is taken as the “Civil Engineering Plant” index as published in Table 4, titled “Producer Price

Index for Selected Materials’, of the Statistical News Release P0151, previously it was published in Table 12,

titled “Producer Price Index for Selected Materials’, of the Statistical News Release P0142.1.

The Material Index is taken as the “Civil Engineering” index as published under Building and Construction in

Table 3, titled “Producer Price Index for Selected Materials’, of the Statistical News Release P0151, previously it

was published in Table 11, titled “Producer Price Index for Materials used in Certain Industries”, of the Statistical

News Release P0142.1.

The Fuel Index is taken as the “Coast and Witwatersrand” index as published under Diesel Fuel in Table 4, titled

“Producer Price Index for Selected Materials’, of the Statistical News Release P0151, previously it was

published in Table 12, titled “Producer Price Index for Selected Materials”, of the Statistical News Release

P0142.1.

The Plant Index, Material Index and Fuel Index data was collected from Stats SA from January 2001 to June

2013; this data can be found in Table A–0–2 in Appendix A.

Similarly to the Labour Index an average Plant Index, Material Index and Fuel Index for each municipal financial

year was determined by averaging the Labour Index values for each month of the municipal financial year (i.e.

July to June). This was calculated for each municipal financial year, from 2001/02 to 2012/13, the result of

which are presented in Table 3-5.

Table 3-5 Plant Index, Material Index and Fuel Index Values for each Municipal Financial Year

Municipal Financial Year Plant Index Material Index Fuel Index

2001/02 125.8 112.4 121.5

2002/03 145.2 126.3 127.3

2003/04 135.8 137.2 111.1

2004/05 133.0 153.4 144.5

2005/06 135.6 160.3 190.5

2006/07 145.9 170.6 232.5

2007/08 157.4 185.8 336.0

2008/09 183.9 214.7 323.7

2009/10 188.9 212.0 277.0

2010/11 186.9 214.6 333.0

2011/12 188.9 224.0 404.2

2012/13 195.2 231.1 423.2



3.3 The Coefficients

The coefficients used in Equation 1 are generally pre-defined and stated in the contract for the civil engineering

works. The sum of the four coefficients are required to add up to unity. The Construction Industry Development

Board and the South African Federation of Engineering Contractors (SAFCEC) publish guidelines for the

coefficients. The coefficients recommended in the February 2009 guidelines obtained from the SAFCEC

website, as published by the CIDB under the “Compiler Guidance Note - Component document: C1.2 - Contract

Data” (CIDB 2009) are presented in Table 3-6.

Table 3-6 Guidelines for the Coefficients for the Contract Price Adjustment as published by the CIDB

No. Work Category Labour Plant Materials Fuel

1 Bulk Earthworks 0.1 0.65 0.05 0.2

2 Earthworks (with culverts and drainage) 0.15 0.5 0.2 0.15

3a New Road Construction: National Provincial Roads 0.15 0.35 0.35 0.15

3b New Road Construction: Urban Roads 0.25 0.15 0.55 0.05

4 Township Roads and Services 0.2 0.25 0.45 0.1

5 Rehabilitation/Resurfacing Works 0.15 0.25 0.5 0.1

6 Routine Maintenance Works 0.45 0.3 0.15 0.1

7 Concrete Works (major structures) 0.3 0.2 0.45 0.05

8 Concrete Works (reservoirs and other general civil engineering works) 0.25 0.15 0.55 0.05

9 Water and Sewer Reticulation 0.15 0.2 0.55 0.1

A simple statistical analysis of the figures presented in Table 3-6 is presented in Table 3-7.

Table 3-7 Statistical Analysis of Coefficient Values in CIDB Guideline

Coefficient Average Median Mode Std. Deviation Min Max

Labour 0.215 0.175 0.15 0.103 0.1 0.45

Plant 0.3 0.25 0.15 0.162 0.15 0.65

Materials 0.38 0.45 0.55 0.184 0.05 0.55

Fuel 0.105 0.1 0.1 0.050 0.05 0.2

From Table 3-6 it can be seen that majority of the work categories (1, 2, 3a, 3b, 4, 5 and 6) can be associated

with Roads and Stormwater infrastructure, although work categories 1 and 6 can also be found in other service

sectors of municipal infrastructure (such as Water, Sanitation, Solid Waste and Operational Building etc.). Work

categories 8 and 9 are readily associated with Water and Sanitation, and work category 7 would be associated

with buildings.

Although the work categories provided by the CIDB coefficients table seem to be dominated by the construction

of roads, which tends to account for only a part of the total municipal infrastructure value, it is possible to identify

work categories that could be grouped into broad classes of municipal infrastructure. In a typical municipality,

the value of the Roads and Stormwater assets generally accounts for around 30% of the total value of the

municipal assets and Water and Sanitation infrastructure assets together can typically account for up to 30% of

the total value of municipal assets. This leaves about 40% of the total value of municipal assets that would be

comprised of Operational Buildings, Community Facilities, Public Amenities, Solid Waste and Electrical

infrastructure assets. Using these guidelines based on the authors experience and understanding of municipal



infrastructure and in particularly the typical composition municipal infrastructure in terms of value, a weighting

factor can be assigned to each work category, as shown in Table 3-6, in order to provide a more representative

measure of the value of infrastructure associated with municipalities.

The weighting factor is then applied to each work category and the resultant sum for coefficient components are

then added to determine a suggested labour, plant, materials and fuel coefficient, these results are presented in

Table 3-8.

Table 3-8 Weighting of Coefficients to Represent Typical Composition of Municipal Infrastructure

No. Suggested Weighting Labour Plant Materials Fuel

1 0.07 0.007 0.046 0.004 0.014

2 0.06 0.009 0.030 0.012 0.009

3a 0.06 0.009 0.021 0.021 0.009

3b 0.06 0.015 0.009 0.033 0.003

4 0.05 0.010 0.013 0.023 0.005

5 0.05 0.008 0.013 0.025 0.005

6 0.05 0.023 0.015 0.008 0.005

7 0.26 0.078 0.052 0.117 0.013

8 0.14 0.035 0.021 0.077 0.007

9 0.20 0.030 0.040 0.110 0.020

Total 1 0.223 0.259 0.429 0.090

The coefficients suggested in Table 3-8 were then rounded up and down, based on the statistical trends

presented in Table 3-7, to provide the overall recommended coefficients that will be used to calculate the

Contract Price Adjustment factor, which should be more representative of municipal infrastructure than the

figures provided in the CIDB guideline, the results are presented in Table 3-9.

Table 3-9 Final Recommended Coefficients for Municipal Infrastructure

Weighting Results Statistical Trend Final

Labour 0.223 Lower values 0.20

Plant 0.259 Similar values 0.25

Materials 0.429 Higher values 0.45

Fuel 0.090 Higher values 0.10



3.4 Calculating the Contract Price Adjustment

Utilising the values in Table 3-4 for the Labour indices, Table 3-5 for the Plant, Material and Fuel indices, Table

3-9 for the coefficients, and taking the non-adjustment portion to be 0.1 (10%) as per the SAICE guidelines, the

Contract Price Adjustment factor can be determined using the formula in Equation 1. It should be noted that the

baseline year for the calculations will be the municipal financial year of 2000/1. The results of these calculations

are presented in Table 3-10.

Table 3-10 Contract Price Adjustment Factor Calculated from the 2001/2 to the 2012/13 Municipal Financial Year

fCPA, Effective Value

CPA Value

Base Year % Change

Base Year Multiplication Factor

Year to Year % Change

Year to Year Multiplication Factor

2001/2 0.1446 1144.61 144.61 14.5% 1.1446 14.5% 1.1446

2002/3 0.2714 1271.41 271.41 27.1% 1.2714 11.1% 1.1108

2003/4 0.2826 1282.56 282.56 28.3% 1.2826 0.9% 1.0088

2004/5 0.3778 1377.82 377.82 37.8% 1.3778 7.4% 1.0743

2005/6 0.4622 1462.22 462.22 46.2% 1.4622 6.1% 1.0613

2006/7 0.5798 1579.78 579.78 58.0% 1.5798 8.0% 1.0804

2007/8 0.7854 1785.39 785.39 78.5% 1.7854 13.0% 1.1302

2008/9 0.9819 1981.86 981.86 98.2% 1.9819 11.0% 1.11

2009/10 0.9551 1955.14 955.14 95.5% 1.9551 -1.4% 0.9865

2010/11 1.024 2023.98 1023.98 102.4% 2.024 3.5% 1.0352

2011/12 1.1518 2151.76 1151.76 115.2% 2.1518 6.3% 1.0631

2012/13 1.2317 2231.70 1231.70 123.2% 2.2317 3.7% 1.0372

In Table 3-10 the Contract Price Adjustment Factor (fCPA) was calculated using the expression in Equation 1; the

Effective Value is the nominal value for the asset based on the value of the asset in the base municipal financial

year (2000/1), which for this study was taken as a nominal value of 1000; the CPA Value represents the

difference between in the asset value from the previous year (municipal financial year) to the current year

(municipal financial year), taking the value in the base municipal financial year (2000/1) to be 1000; the Base

Year % Change is the percentage difference between the value in the municipal financial year from the baseline

municipal financial year (2000/1); the Base Year Multiplication Factor represents the figure that needs to be

multiplied to an asset value in the baseline municipal financial year (2000/1) in order to determine its value in the

municipal financial year in question; the Year to Year % Change is the percentage change in asset value from

the previous municipal financial year to the current municipal financial year; and the Year to Year Multiplication

Factor represents the figure that needs to be multiplied to an asset value in the previous municipal financial year

to determine it value in the current municipal financial year.

It should be noted that the values provided for the Base Year % Change and the Base Year Multiplication Factor

always refer from the current municipal financial year to the baseline municipal financial year (2000/1). This

means that in order to determine the escalation in value of an asset from the baseline municipal financial year

(2000/1) to the 2009/10 municipal financial year, the value of the asset in the base municipal financial year is

multiplied by the Base Year Multiplication Factor of the 2009/10 municipal financial year to provide the value of

the asset in the 2009/10 municipal financial year. Similarly to de-escalate from the 2007/08 municipal financial

year asset value to the baseline municipal financial year (2000/1), the value of the asset in the 2007/08

municipal financial year is divided by the Base Year Multiplication Factor of the 2007/08 municipal financial year



to determine the value of the asset in the baseline municipal financial year (2000/1). This also means that in

order to determine the escalation/de-escalation from one non baseline year to another non baseline year, the

value of the asset must first be determined for the baseline year by dividing the first years asset value by that

years Base Year Multiplication Factor, then the value of the asset in the baseline year must be multiplied by the

Base Year Multiplication Factor of the second year to determine the assets value in the second year.

Alternatively the Year to Year % Change and the Year to Year Multiplication Factor provides the step change

between municipal financial years. Thus in order to determine the escalation from the 2004/05 municipal

financial year to the 2005/06 municipal financial year, the value of the asset in the 2004/05 municipal financial

year is multiplied by the Year to Year Multiplication Factor of the 2005/06 municipal financial year to provide

value of the asset in the 2005/06 municipal financial year. Similarly to de-escalate from the 2010/11 municipal

financial year asset value to the 2009/10 municipal financial year asset value, the value of the asset in the

2010/11 municipal financial year is divided by the Year to Year Multiplication Factor of the 2010/11 municipal

financial year to provide value of the asset in the 2009/10 municipal financial year. This also means that in

order to determine the escalation/de-escalation from one year to several years before or after, the value of the

asset will have to first be escalated/de-escalated each year successively for every year in between the two

years.

Overall the Year to Year % Change best shows how the asset value changes over the municipal financial years,

thus the Year to Year % Change value will be used as the CPA based ‘inflation’ rate for municipal infrastructure,

designated the percentage Contract Price Adjustment (%CPA).



4. Comparison of %CPA to CPI and PPI

4.1 Introduction

In order to understand the significance of the value of the %CPA it is best considered in comparison to the

headline inflation rates for the Consumer Price Index (CPI for all items in all urban area in South Africa) and

Producer Price Index (PPI for domestic output of all industry groups in South Africa).

This section details how the CPI and PPI values are determined for each municipal financial year and then a

comparison between the %CPA, CPI and PPI is presented.

4.2 CPI

The headline Consumer Price Index is the CPI determined for all items in all urban area in South Africa, and this

is the figure that is widely reported in the media as the % CPI. The headline Consumer Price Index is published

monthly by Stats SA (in their Statistical release P0141), but historical records are also available from the Stats

SA website (Stats SA 2012).

The headline CPI figures (both the index and the % change) from January 2000 to June 2013 were obtained

from the Stats SA Website. The headline CPI index values obtained were based on the 2008 base year (where

2008 = 100) and these values can be found in Table B–0–1 of Appendix B.

Similarly to the Labour Index, Plant Index, Material Index and Fuel Index that was calculated for each municipal

financial year, the Headline CPI was determined by averaging the %CPI values for each month of the municipal

financial year (i.e. July to June). Thus an annual municipal financial year %CPI was calculated for the municipal

financial years from 2001/2 to 2011/12 along with a multiplication factor and the results are presented in Table

4-1.

Table 4-1 Annual Municipal Financial Year %CPI from 2001/02 to 2012/13

Year Annual %CPI Multiplication Factor

2001/2 5.58% 1.0558

2002/3 10.41% 1.1041

2003/4 1.65% 1.0165

2004/5 2.63% 1.0263

2005/6 3.82% 1.0382

2006/7 5.93% 1.0593

2007/8 9.24% 1.0924

2008/9 10.18% 1.1018

2009/10 5.65% 1.0565

2010/11 3.85% 1.0385

2011/12 5.85% 1.0585

2012/13 5.54% 1.0554



4.3 PPI

The headline Producer Price Index is the PPI determined for domestic output of South African industry groups,

and this is the figure that is widely reported in the media as the % PPI. The headline Producer Price Index is

published monthly by Stats SA (in their Statistical release P0151), but historical records are also available from

the Stats SA website (Stats SA 2012).

The headline PPI figures (both the index and the % change) from January 2000 to June 2013 were obtained

from the Stats SA Website. The headline PPI index values obtained were based on the 2000 base year (where

2000 = 100) and these values can be found in Table B–0–2 of Appendix B.

Similarly to the Labour Index, Plant Index, Material Index and Fuel Index that was calculated for each municipal

financial year, the Headline PPI was determined by averaging the %PPI values for each month of the municipal

financial year (i.e. July to June). Thus an annual municipal financial year %PPI was calculated for the municipal

financial years from 2001/02 to 2011/12 along with a multiplication factor and the results are presented in Table

4-2.

Table 4-2 Annual Municipal Financial Year %PPI from 2001/02 to 2012/13

Annual %PPI Multiplication Factor

2001/2 10.53% 1.1053

2002/3 9.01% 1.0901

2003/4 0.75% 1.0075

2004/5 3.16% 1.0316

2005/6 4.84% 1.0484

2006/7 11.09% 1.1109

2007/8 11.47% 1.1147

2008/9 9.14% 1.0914

2009/10 1.36% 1.0136

2010/11 6.76% 1.0676

2011/12 8.64% 1.0864

2012/13 5.28% 1.0528

4.4 Comparison of Inflation Indices

In Section 3.4 the annual (based on the municipal financial year) %CPA was calculated, in Section 4.2 the

annual (based on the municipal financial year) % headline CPI was determined and in Section 4.3 the annual

(based on the municipal financial year) % headline PPI was determined for the 2001/2 to 2012/13 municipal

financial years. These figures are presented in Table 3-1Table 4-3 and provide allow a comparison to be made

of the %CPA against the two headline inflation indices the CPI and PPI.



Table 4-3 Comparison between Calculated Annual %CPA, CPI and PPI, based on Municipal Financial Years

Inflation Index CPI PPI %CPA

2001/2 5.58% 10.53% 14.46%

2002/3 10.41% 9.01% 11.08%

2003/4 1.65% 0.75% 0.88%

2004/5 2.63% 3.16% 7.43%

2005/6 3.82% 4.84% 6.13%

2006/7 5.93% 11.09% 8.04%

2007/8 9.24% 11.47% 13.02%

2008/9 10.18% 9.14% 11.00%

2009/10 5.65% 1.36% -1.35%

2010/11 3.85% 6.76% 3.52%

2011/12 5.85% 8.64% 6.31%

2012/13 5.54% 5.28% 3.72%

In general it can be seen in Table 4-3 that the %CPA follows a similar trend to the headline CPI and PPI figures,

although the %CPA is often an extreme value (either above or below) both the CPI and PPI and this is

presented graphically in Figure 4-1. This suggests that there is a sound basis for using the %CPA value rather

than the CPI or PPI values usually used to account for inflation in the value of infrastructure as the %CPA tends

to provide significant variances against the other two measures of inflation.

Figure 4-1 Calculated %CPA, Headline CPI and PPI form the 2001/02 to 2012/13 Municipal Financial Years.



5. Concluding Remarks

In this report the formula for calculating the price escalation for civil engineering construction works developed

by the South African Institution of Civil Engineering (SAICE) was utilised to calculate an annual percentage

inflation based on the municipal financial year, the %CPA, for municipal infrastructure that is based on the more

representative inflation in the civil engineering construction industry from 2001/2 to 2012/13.

The %CPA has been compared against the headline CPI and PPI figures (also based on the municipal financial year) and these results are presented in Table 4-3 and Figure 4-1.

It is recommended that when determining the escalation or de-escalation in the value of municipal infrastructure

over the municipal financial years that the %CPA figure is used, rather than the CPI or the PPI, as it will provide

a more representative estimate of the inflation incurred by municipal infrastructure as it is based on the inflation

that would have been experienced in the civil engineering construction industry from which municipal

infrastructure is created.



References

CIDB 2009, Compiler Guidance Note - Component document: C1.2 - Contract Data, Construction Industry

Development Board, accessed October 2012, < http://www.cidb.org.za/documents/pdm/toolbox/>

SAICE 2010, General Conditions of Contract for Construction Works, South African Institution of Civil

Engineering, Second Edition 2010

Stats SA 2012, StatsOnline, Statistics South Africa, accessed July 2013, <http://www.statssa.gov.za/>



Appendix A – Labour, Plant, Material and Fuel Indices

Table A-0-1 Labour Index values as obtained from Stats SA CPI Index per Province

WC EC NC FS

Province KZN NW GP MP LP ZA

Jan-01 103.4 102.7 104.3 103.2 104.1 103.3 103.6 103.3 103.6 103.5

Feb-01 103.6 102.9 104.5 103.1 104.3 103.6 103.9 103.8 104.0 103.7

Mar-01 104.4 103.8 105.1 103.7 105.1 104.4 104.5 104.5 104.8 104.5

Apr-01 105.0 104.3 105.6 103.9 105.2 104.9 105.1 105.2 105.3 104.9

May-01 105.4 104.8 106.1 104.5 105.6 105.3 105.4 105.7 105.3 105.3

Jun-01 105.8 105.4 106.7 104.9 106.1 105.5 105.8 106.0 106.0 105.8

Jul-01 107.0 105.9 107.4 105.9 106.2 105.9 105.7 106.0 105.9 106.2

Aug-01 106.8 105.8 107.3 105.6 105.9 105.9 105.6 106.1 105.9 106.1

Sep-01 107.1 106.2 107.5 105.6 106.2 106.2 105.7 106.3 106.1 106.3

Oct-01 107.2 106.3 107.6 105.5 106.4 106.5 105.6 106.3 106.0 106.4

Nov-01 107.7 106.7 108.0 106.2 107.0 106.7 106.0 106.8 106.5 106.8

Dec-01 108.3 107.8 108.8 106.2 107.8 107.0 106.6 107.5 106.9 107.4

Jan-02 109.9 109.3 110.7 107.5 109.4 108.2 108.5 109.7 108.5 109.1

Feb-02 111.3 110.6 112.0 108.5 110.8 109.9 109.8 111.1 110.0 110.4

Mar-02 112.8 112.2 113.0 109.3 112.1 111.0 111.0 112.4 111.4 111.7

Apr-02 114.6 114.5 114.7 110.6 113.7 112.5 113.1 114.6 113.7 113.6

May-02 115.4 115.5 115.3 111.1 114.3 113.1 114.1 115.3 114.3 114.3

Jun-02 116.4 116.5 116.5 111.8 115.3 113.7 115.2 116.5 115.3 115.2

Jul-02 118.7 118.5 118.4 113.5 117.1 115.9 116.9 117.9 116.5 117.0

Aug-02 119.5 119.5 119.7 114.4 118.2 117.0 117.7 118.7 117.2 118.0

Sep-02 120.7 121.0 121.1 114.8 119.5 117.6 119.1 119.5 117.9 119.0

Oct-02 122.6 122.6 123.0 116.2 121.1 119.4 121.2 121.0 119.9 120.8

Nov-02 123.3 123.2 123.6 116.7 121.8 119.7 121.9 122.2 120.1 121.4

Dec-02 123.9 123.4 123.9 116.6 122.1 119.4 122.4 122.5 120.3 121.6

Jan-03 125.3 124.7 125.4 117.8 123.4 120.9 123.6 123.3 121.5 122.9

Feb-03 125.2 124.5 125.5 117.7 123.2 120.8 124.3 123.4 121.7 122.9

Mar-03 123.9 124.7 124.5 118.8 123.7 123.4 122.1 125.1 121.8 123.1

Apr-03 123.2 125.0 124.8 119.1 123.9 124.1 122.5 125.9 122.3 123.4

May-03 124.1 124.9 124.8 118.7 124.1 124.3 122.2 125.5 122.0 123.4

Jun-03 123.7 125.0 124.4 118.7 123.8 124.8 121.7 124.9 121.6 123.2

Jul-03 123.7 124.5 124.9 118.8 124.0 124.3 121.9 125.3 121.5 123.2

Aug-03 124.0 124.6 125.4 119.2 124.3 124.5 122.5 126.2 121.7 123.6

Sep-03 123.8 124.3 125.1 118.7 123.4 123.9 122.2 125.4 120.8 123.1

Oct-03 123.1 123.6 124.6 118.4 122.8 122.7 121.5 124.2 119.7 122.3

Nov-03 122.3 122.6 123.6 117.7 122.4 121.5 120.7 122.9 118.4 121.3

Dec-03 122.5 123.1 123.6 117.5 122.3 121.5 120.8 122.8 118.5 121.4

Jan-04 123.7 124.3 124.8 118.5 123.1 121.9 121.6 124.0 119.2 122.3

Feb-04 124.3 125.1 124.8 119.1 123.5 122.0 122.2 124.7 119.8 122.8

Mar-04 125.1 126.2 125.6 119.9 124.1 123.0 123.0 125.9 121.0 123.8

Apr-04 124.9 126.1 126.2 120.4 124.7 123.5 123.3 126.5 121.4 124.1

May-04 124.8 126.4 126.5 120.5 125.1 123.7 123.2 126.7 121.5 124.3

Jun-04 125.1 126.8 126.5 120.6 125.3 123.8 123.7 127.0 121.6 124.5



Jul-04 125.5 126.9 127.1 120.8 125.1 124.3 124.3 127.6 122.2 124.9

Aug-04 125.4 126.6 127.0 120.2 124.9 123.4 124.1 127.3 121.9 124.5

Sep-04 125.2 126.6 127.2 120.3 124.8 123.7 124.2 127.0 121.8 124.5

Oct-04 126.0 127.2 127.6 121.0 125.5 124.8 124.7 127.4 122.0 125.1

Nov-04 126.5 128.1 128.4 122.0 126.3 125.8 125.3 128.0 122.5 125.9

Dec-04 126.2 128.2 128.6 121.7 125.7 125.3 125.1 127.8 122.6 125.7

Jan-05 127.0 128.5 129.4 122.5 126.4 125.7 125.5 128.5 123.1 126.3

Feb-05 127.2 128.7 129.5 122.6 126.4 125.7 125.6 128.5 123.2 126.4

Mar-05 128.3 129.3 130.5 123.4 127.6 126.9 127.0 130.0 124.5 127.5

Apr-05 129.1 129.9 131.1 124.1 128.1 128.1 127.5 130.9 125.1 128.2

May-05 129.0 130.1 131.2 124.1 127.8 128.1 127.6 130.9 124.9 128.2

Jun-05 128.8 129.4 130.6 123.3 127.4 127.7 127.4 131.2 124.8 127.8

Jul-05 130.0 130.8 133.1 124.9 128.3 129.6 128.7 132.6 125.6 129.3

Aug-05 130.6 131.3 133.6 125.3 128.4 130.3 129.2 133.1 125.8 129.7

Sep-05 130.6 131.8 133.8 125.8 129.2 130.7 129.4 133.3 126.0 130.1

Oct-05 130.8 132.1 133.6 125.7 129.5 131.1 129.6 133.6 126.1 130.2

Nov-05 130.8 132.1 133.2 125.6 129.3 130.5 129.6 133.6 125.9 130.1

Dec-05 130.8 132.1 133.4 126.2 129.6 131.5 129.6 133.7 125.8 130.3

Jan-06 131.8 133.2 135.1 127.4 130.8 132.2 130.3 134.7 126.6 131.3

Feb-06 131.4 134.7 135.3 127.9 131.5 132.4 130.3 134.2 127.9 131.7

Mar-06 132.0 135.3 136.0 128.9 131.9 133.0 130.9 135.0 128.6 132.4

Apr-06 132.4 135.8 136.5 129.0 132.3 133.0 131.7 135.5 128.8 132.8

May-06 133.0 136.2 137.5 129.6 133.0 133.7 132.5 136.5 129.7 133.5

Jun-06 134.2 137.3 138.7 130.8 133.9 134.8 133.4 137.1 130.9 134.6

Jul-06 135.5 138.6 140.0 132.1 135.2 135.6 134.8 138.4 131.7 135.8

Aug-06 136.6 140.1 140.9 133.2 136.2 136.4 135.7 139.1 132.7 136.8

Sep-06 137.1 140.2 141.7 133.4 136.7 136.6 135.9 140.8 133.5 137.3

Oct-06 137.7 140.7 142.3 133.7 137.5 137.3 136.2 141.9 133.9 137.9

Nov-06 137.7 140.7 142.3 133.8 137.5 137.0 136.0 141.9 134.2 137.9

Dec-06 138.4 141.2 142.8 133.8 137.9 137.2 136.5 142.5 134.4 138.3

Jan-07 141.3 142.7 145.0 133.2 140.9 138.0 140.3 144.8 136.3 140.3

Feb-07 141.3 142.3 144.9 133.2 140.6 137.7 140.0 144.6 136.7 140.1

Mar-07 142.5 143.5 146.1 134.6 141.8 139.3 141.3 146.2 138.3 141.5

Apr-07 143.9 144.7 146.6 135.7 142.8 142.3 143.3 147.9 140.0 143.0

May-07 144.6 145.5 147.8 136.2 143.8 142.8 144.2 149.0 141.4 143.9

Jun-07 145.7 146.5 148.9 137.1 144.9 143.5 145.3 149.7 142.1 144.9

Jul-07 147.6 147.5 150.1 138.8 146.5 145.0 146.8 150.9 143.3 146.3

Aug-07 148.5 149.0 151.1 139.6 147.3 145.7 147.6 152.3 144.2 147.3

Sep-07 149.7 150.6 152.1 140.6 148.4 147.6 148.2 153.7 145.2 148.5

Oct-07 151.0 151.8 153.5 141.7 149.6 148.7 149.8 154.9 147.1 149.8

Nov-07 151.7 152.5 154.5 142.5 150.6 149.4 150.2 156.5 147.9 150.6

Dec-07 153.0 153.0 155.1 143.3 152.2 151.1 151.4 157.6 149.3 151.8

Jan-08 154.7 155.5 157.3 145.7 153.6 153.2 153.3 159.5 151.7 153.8

Feb-08 155.4 155.5 157.8 145.9 154.4 153.9 153.9 159.9 152.8 154.4

Mar-08 157.6 157.1 160.3 147.9 156.2 156.8 156.4 162.8 155.1 156.7

Apr-08 160.3 160.1 163.0 150.5 159.3 159.8 158.7 165.3 157.5 159.4

May-08 161.7 162.2 164.8 152.1 160.8 161.3 160.4 167.8 158.0 161.0



Jun-08 163.9 164.5 166.5 153.8 162.7 163.7 162.5 169.6 160.0 163.0

Jul-08 168.0 168.4 169.9 156.5 166.6 166.3 166.1 173.5 163.7 166.6

Aug-08 169.5 170.8 173.3 158.3 168.2 168.5 167.1 175.2 164.7 168.4

Sep-08 170.0 171.8 174.5 159.1 168.6 169.1 167.1 175.4 165.4 169.0

Oct-08 170.3 171.8 175.9 159.6 169.2 169.4 167.2 176.1 166.1 169.5

Nov-08 170.5 171.7 176.4 159.7 169.4 169.3 167.7 176.1 167.2 169.8

Dec-08 169.1 170.1 174.4 158.7 168.1 167.9 165.8 174.4 165.1 168.2

Jan-09 169.3 171.4 174.7 159.5 169.7 168.1 166.3 176.1 166.1 169.0

Feb-09 170.9 173.2 176.8 161.3 171.0 170.2 168.4 178.6 167.3 170.9

Mar-09 173.5 175.4 178.8 163.3 173.0 173.3 170.8 180.7 169.6 173.1

Apr-09 174.4 176.4 180.3 164.4 173.9 173.4 171.6 181.7 170.2 174.0

May-09 174.9 176.9 180.5 164.7 174.3 174.1 172.3 182.3 170.9 174.5

Jun-09 175.5 177.4 181.4 165.3 174.8 174.2 172.9 182.3 170.9 175.0

Jul-09 177.6 178.8 183.4 167.0 176.1 176.2 175.0 184.4 171.7 176.7

Aug-09 178.1 179.3 183.9 167.5 176.2 176.8 175.7 184.9 172.3 177.2

Sep-09 179.1 180.0 184.6 167.8 176.7 177.0 176.2 185.6 172.5 177.7

Oct-09 179.3 180.2 184.6 167.7 176.9 176.8 176.2 185.9 172.3 177.7

Nov-09 179.3 180.0 184.6 167.8 176.7 176.7 176.2 185.7 173.1 177.8

Dec-09 180.3 180.3 184.7 168.3 177.2 177.0 176.3 185.9 172.9 178.1

Jan-10 180.8 180.6 184.6 168.7 177.8 177.5 177.0 186.6 173.4 178.6

Feb-10 181.4 181.5 185.4 170.0 178.5 179.0 178.1 187.6 174.4 179.5

Mar-10 183.4 183.0 186.6 171.1 179.8 180.1 179.7 188.8 176.3 181.0

Apr-10 183.9 183.5 187.1 171.7 180.0 180.4 179.9 189.1 176.0 181.3

May-10 184.1 183.8 187.8 171.8 180.3 180.9 180.2 189.6 176.1 181.6

Jun-10 183.9 183.9 187.8 171.8 180.3 180.8 180.2 189.3 176.1 181.6

Jul-10 184.7 184.9 189.2 172.9 181.1 181.6 181.5 190.5 177.4 182.6

Aug-10 184.9 185.9 189.2 173.5 181.3 181.7 181.5 190.8 177.6 182.9

Sep-10 185.0 186.6 189.7 174.3 181.1 181.9 181.7 191.3 177.4 183.2

Oct-10 185.5 186.7 190.0 174.8 181.4 182.1 182.0 191.8 178.4 183.6

Nov-10 185.7 186.7 190.0 174.8 181.9 182.5 182.5 191.6 178.0 183.8

Dec-10 186.2 186.9 189.8 175.1 182.1 182.5 182.8 191.8 179.0 184.0

Jan-11 187.0 188.4 191.5 176.5 183.0 183.8 183.4 193.0 179.6 185.2

Feb-11 188.2 189.5 192.4 177.4 184.2 185.3 184.6 194.5 179.5 186.2

Mar-11 190.8 191.7 194.9 179.5 186.0 187.4 186.8 196.9 182.8 188.5

Apr-11 191.3 192.2 196.1 180.6 186.5 188.1 187.2 197.6 183.8 189.3

May-11 192.3 193.3 196.8 181.4 187.4 188.9 188.3 198.6 184.9 190.2

Jun-11 192.9 195.2 197.3 181.7 188.4 190.2 189.1 199.1 186.2 191.1

Jul-11 194.2 197.0 200.0 183.9 189.9 191.7 190.7 200.9 186.5 192.8

Aug-11 194.7 197.3 201.5 184.2 190.4 192.3 191.1 201.1 186.8 193.3

Sep-11 195.7 198.6 202.7 185.1 190.8 192.6 191.5 201.8 187.8 194.1

Oct-11 196.5 199.9 204.4 186.3 192.3 194.1 192.7 203.5 189.2 195.4

Nov-11 196.9 200.6 205.1 187.0 192.9 194.3 193.0 203.8 189.7 195.9

Dec-11 197.2 201.3 204.6 187.6 194.1 194.7 193.3 204.6 190.5 196.4

Jan-12 198.0 202.2 206.6 188.6 194.7 196.0 194.5 206.0 192.0 197.6

Feb-12 199.2 202.9 207.5 189.6 195.7 197.2 195.6 207.5 192.7 198.7

Mar-12 201.3 204.7 209.9 191.0 198.1 199.6 197.7 209.9 194.7 200.8

Apr-12 202.1 205.9 210.9 191.9 198.8 200.3 198.5 210.4 194.7 201.5



May-12 202.5 206.4 211.0 192.0 199.0 200.1 198.7 210.6 195.5 201.7

Jun-12 203.1 206.7 211.0 192.2 199.3 201.4 199.3 211.4 196.4 202.3

Jul-12 203.6 206.9 212.2 192.8 199.9 201.6 199.8 211.9 197.2 202.9

Aug-12 204.1 207.4 212.2 193.3 200.3 202.6 200.3 212.6 197.4 203.3

Sep-12 205.7 209.2 214.8 195.1 202.2 205.3 201.9 214.5 199.3 205.3

Oct-12 207.1 210.6 216.1 196.5 203.7 206.8 203.4 216.1 200.9 206.8

Nov-12 207.6 211.8 217.5 197.1 204.3 207.1 203.7 216.5 201.4 207.4

Dec-12 208.2 212.0 217.8 198.2 205.0 207.3 204.0 217.3 202.3 208.0

Jan-13 208.6 212.4 218.7 198.6 205.2 208.1 204.8 218.2 203.4 208.7

Feb-13 210.1 213.9 219.6 200.0 207.2 209.8 207.3 220.1 204.0 210.2

Mar-13 212.6 216.0 221.8 202.2 209.7 211.2 209.9 221.9 206.2 212.4

Apr-13 213.4 216.8 222.8 202.6 210.3 212.2 210.5 222.5 207.2 213.2

May-13 212.8 216.2 222.4 202.6 209.7 211.6 209.9 222.3 206.8 212.7

Jun-13 213.4 216.8 223.1 203.6 210.1 212.0 210.7 222.5 206.8 213.2

The CPI figures presented in Table A-0-1 are for the Consumer Price Index per Province in South Africa

sourced from Stats SA Consumer Price Index P0141 Publications. The Indices in Table A-0-1 are calculated

using the base year of 2000, where 2000 = 100.

Table A-0-2 Plant Index, Material Index and Fuel Index values as obtained from Stats SA PPI

Month Plant Index Material Index Fuel Index

Jan-01 104.7 103.7 117.7

Feb-01 108.2 103.6 114.1

Mar-01 108.2 103.7 111.8

Apr-01 108.2 103.7 112.1

May-01 112.2 105.1 116.7

Jun-01 112.2 105.0 116.3

Jul-01 112.2 107.9 116.1

Aug-01 114.3 108.4 116.1

Sep-01 114.3 108.6 116.0

Oct-01 114.3 108.8 118.3

Nov-01 119.8 108.7 117.9

Dec-01 119.8 108.9 115.4

Jan-02 119.8 113.2 126.9

Feb-02 135.8 113.4 124.4

Mar-02 135.8 113.5 119.1

Apr-02 136.1 118.2 128.8

May-02 143.9 119.0 128.5

Jun-02 143.9 119.9 130.3

Jul-02 144.2 120.6 128.1

Aug-02 144.9 120.7 127.0

Sep-02 144.9 120.9 131.0

Oct-02 145.5 125.2 140.4

Nov-02 146.8 125.6 144.3

Dec-02 146.5 125.5 136.1

Jan-03 146.2 128.3 121.2

Feb-03 147.2 129.6 124.3



Mar-03 146.9 129.4 133.0

Apr-03 146.9 129.8 138.5

May-03 141.4 129.7 105.8

Jun-03 141.4 130.5 97.5

Jul-03 140.8 131.7 108.0

Aug-03 138.8 132.7 103.9

Sep-03 138.5 132.7 106.4

Oct-03 138.5 132.9 103.7

Nov-03 135.7 134.7 108.4

Dec-03 135.7 134.4 106.6

Jan-04 135.7 137.3 103.4

Feb-04 133.8 137.6 117.6

Mar-04 133.8 137.6 112.1

Apr-04 133.9 142.2 115.9

May-04 132.4 147.0 117.2

Jun-04 132.1 145.1 130.1

Jul-04 132.1 146.3 122.0

Aug-04 133.1 147.6 126.6

Sep-04 133.4 147.6 139.2

Oct-04 133.1 150.8 148.0

Nov-04 133.1 153.9 158.0

Dec-04 133.1 153.6 145.4

Jan-05 133.4 155.2 128.7

Feb-05 132.2 156.7 130.2

Mar-05 132.5 156.8 143.0

Apr-05 132.5 157.2 165.9

May-05 133.8 157.5 167.7

Jun-05 133.8 157.6 158.9

Jul-05 134.1 159.1 183.3

Aug-05 134.7 159.3 188.0

Sep-05 134.7 159.3 187.2

Oct-05 134.7 159.5 193.1

Nov-05 135.5 159.5 192.9

Dec-05 135.5 160.0 178.0

Jan-06 135.5 161.0 176.9

Feb-06 135.4 161.1 176.7

Mar-06 135.4 161.0 174.8

Apr-06 135.8 161.1 194.2

May-06 137.2 161.4 212.3

Jun-06 138.5 161.6 228.5

Jul-06 138.8 165.9 247.8

Aug-06 141.4 167.3 264.2

Sep-06 141.7 167.5 254.5

Oct-06 143.3 167.6 237.7

Nov-06 146.4 167.9 234.6

Dec-06 146.4 167.9 217.6

Jan-07 146.5 171.6 211.6



Feb-07 148.3 172.5 203.9

Mar-07 148.0 172.5 209.3

Apr-07 148.9 172.8 224.2

May-07 150.3 176.4 240.3

Jun-07 150.3 176.7 243.7

Jul-07 150.3 179.7 252.0

Aug-07 152.1 178.1 255.7

Sep-07 152.1 178.7 263.8

Oct-07 152.1 179.5 277.1

Nov-07 153.7 181.3 272.5

Dec-07 153.7 181.9 301.7

Jan-08 153.7 184.1 304.1

Feb-08 161.4 186.8 321.6

Mar-08 161.4 187.8 367.6

Apr-08 161.4 191.0 424.9

May-08 168.3 199.0 471.0

Jun-08 168.3 201.8 519.9

Jul-08 168.3 203.9 511.9

Aug-08 175.4 217.3 419.9

Sep-08 175.4 218.8 394.3

Oct-08 175.4 219.6 377.4

Nov-08 184.8 219.2 336.8

Dec-08 184.8 216.6 274.3

Jan-09 184.8 219.7 286.5

Feb-09 193.0 215.7 271.3

Mar-09 193.0 214.8 253.5

Apr-09 193.0 213.3 250.2

May-09 189.2 209.0 251.1

Jun-09 189.2 208.9 256.8

Jul-09 189.2 211.3 266.2

Aug-09 190.9 210.1 262.1

Sep-09 190.9 209.8 272.6

Oct-09 190.9 209.5 257.7

Nov-09 188.1 209.8 262.2

Dec-09 188.1 209.8 275.4

Jan-10 188.1 212.5 269.1

Feb-10 188.0 213.0 276.4

Mar-10 188.9 213.0 280.4

Apr-10 188.9 212.8 296.5

May-10 187.6 215.4 304.4

Jun-10 187.4 216.7 300.5

Jul-10 187.2 214.1 296.0

Aug-10 186.7 212.6 293.1

Sep-10 186.7 212.6 290.6

Oct-10 186.8 213.7 291.3

Nov-10 187.5 212.9 299.0

Dec-10 185.8 213.1 309.4



Jan-11 184.2 215.4 321.0

Feb-11 186.6 215.9 350.9

Mar-11 187.3 217.4 374.2

Apr-11 187.5 216.0 396.8

May-11 187.5 215.7 392.3

Jun-11 188.8 216.1 380.9

Jul-11 189.2 219.0 378.3

Aug-11 189.3 219.7 377.7

Sep-11 189.1 220.2 377.7

Oct-11 187.6 221.6 392.4

Nov-11 187.7 223.2 413.1

Dec-11 188.4 223.6 419.9

Jan-12 188.6 224.5 409.3

Feb-12 189.4 226.6 409.0

Mar-12 188.2 228.2 414.2

Apr-12 188.6 227.9 422.2

May-12 190.3 226.9 426.6

Jun-12 190.8 226.8 410.3

Jul-12 191.0 227.1 378.6

Aug-12 191.5 227.9 388.0

Sep-12 192.5 227.5 412.7

Oct-12 192.5 226.8 433.0

Nov-12 193.2 227.5 439.3

Dec-12 193.7 228.2 435.9

Jan-13 195.5 231.2 426.7

Feb-13 195.8 232.1 432.1

Mar-13 197.9 234.1 449.9

Apr-13 198.1 235.9 433.7

May-13 199.7 236.6 420.5

Jun-13 201.4 238.2 427.5

The PPI figures presented in Table A-0-2 are for the Producer Price Index for “Civil Engineering Plant”, “Building

and Construction - Civil Engineering”, and “Diesel Fuel - Coast and Witwatersrand” indices sourced from Stats

SA Consumer Price Index P0142 Publications. The Indices in Table A-0-2 are calculated using the base year of

2000, where 2000 = 100.



Appendix B – Headline CPI and PPI

Table B-0-1 Headline Consumer Price Index: Index numbers and Annual Percentage Change on a Monthly Basis

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2000 Index 60.6 60.4 61.0 61.8 62.1 62.4 63.0 63.3 63.6 63.8 63.9 64.1

% 2.7 2.4 3.4 4.6 5.1 5.1 6.1 6.9 7.1 7.0 7.0 7.0

2001 Index 64.9 65.1 65.5 65.8 66.1 66.4 66.3 66.2 66.4 66.3 66.6 67.0

% 7.1 7.8 7.4 6.5 6.4 6.4 5.2 4.6 4.4 3.9 4.2 4.5

2002 Index 68.1 68.9 69.6 70.7 71.2 71.7 72.7 73.1 73.8 74.9 75.2 75.3

% 4.9 5.8 6.3 7.4 7.7 8.0 9.7 10.4 11.1 13.0 12.9 12.4

2003 Index 76.0 75.9 76.7 76.9 76.8 76.5 76.5 76.8 76.6 76.1 75.5 75.6

% 11.6 10.2 10.2 8.8 7.9 6.7 5.2 5.1 3.8 1.6 0.4 0.4

2004 Index 76.1 76.5 77.0 77.1 77.2 77.4 77.7 77.6 77.6 77.9 78.3 78.1

% 0.1 0.8 0.4 0.3 0.5 1.2 1.6 1.0 1.3 2.4 3.7 3.3

2005 Index 78.4 78.5 79.3 79.8 79.8 79.6 80.3 80.6 80.9 81.0 80.9 80.9

% 3.0 2.6 3.0 3.5 3.4 2.8 3.3 3.9 4.3 4.0 3.3 3.6

2006 Index 81.5 81.6 82.0 82.4 82.9 83.5 84.3 85.0 85.2 85.4 85.3 85.6

% 4.0 3.9 3.4 3.3 3.9 4.9 5.0 5.5 5.3 5.4 5.4 5.8

2007 Index 86.4 86.3 87.0 88.1 88.6 89.4 90.3 90.7 91.3 92.1 92.5 93.3

% 6.0 5.8 6.1 6.9 6.9 7.1 7.1 6.7 7.2 7.8 8.4 9.0

2008 Index 94.4 94.7 96.2 97.9 99.0 100.3 102.4 103.1 103.3 103.3 103.4 102.2

% 9.3 9.8 10.6 11.1 11.7 12.2 13.4 13.7 13.1 12.1 11.8 9.5

2009 Index 103.1 104.3 105.7 106.2 106.6 107.0 108.2 108.5 108.9 108.9 108.9 109.2

% 8.1 8.6 8.5 8.4 8.0 6.9 6.7 6.4 6.1 5.9 5.8 6.3

2010 Index 109.5 110.2 111.1 111.3 111.5 111.5 112.2 112.3 112.4 112.6 112.8 113.0

% 6.2 5.7 5.1 4.8 4.6 4.2 3.7 3.5 3.2 3.4 3.6 3.5

2011 Index 113.5 114.3 115.7 116.0 116.6 117.1 118.1 118.3 118.8 119.4 119.7 119.9

% 3.7 3.7 4.1 4.2 4.6 5.0 5.3 5.3 5.7 6.0 6.1 6.1

2012 Index 120.6 121.3 122.6 123.1 123.2 123.5 123.9 124.2 125.3 126.1 126.4 126.7

% 6.3 6.1 6.0 6.1 5.7 5.5 4.9 5.0 5.5 5.6 5.6 5.7

2013 Index 127.1 128.3 129.9 130.4 130.0 130.4

% 5.4 5.9 5.9 5.9 5.6 5.5

The Headline CPI figures presented in Table B-0-1 are for the Consumer Price Index for all items in all urban

area in South Africa sourced from Stats SA Consumer Price Index P0141 Historic Publications. The Indices in

Table B-0-1 are calculated using the base year of 2008, where 2008 = 100.



Table B-0-2 Headline Producer Price Index: Index numbers and Annual Percentage Change on a Monthly Basis

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2000 Index 96.3 96.9 97.2 98.8 99.3 99.7 100.2 101.1 101.7 102.2 103.1 103.4

% 5.5 5.4 4.6 6.5 5.8 6.5 6.5 7.0 7.7 7.8 8.3 8.2

2001 Index 103.8 104.4 104.6 105.6 106.5 107.2 107.8 108.7 108.6 110.1 111.6 112.1

% 7.8 7.7 7.6 6.9 7.3 7.5 7.6 7.5 6.8 7.7 8.2 8.4

2002 Index 115.4 117.9 118.7 120.7 121.6 122.2 123.3 124.7 124.3 125.1 125.4 125.3

% 11.2 12.9 13.5 14.3 14.2 14.0 14.4 14.7 14.5 13.6 12.4 11.8

2003 Index 124.5 124.9 124.9 124.8 123.8 125.3 126.4 126.0 124.4 124.4 123.9 124.2

% 7.9 5.9 5.2 3.4 1.8 2.5 2.5 1.0 0.1 -0.6 -1.2 -0.9

2004 Index 124.7 125.5 125.5 126.6 126.9 129.1 129.1 129.4 128.7 129.3 129.2 128.7

% 0.2 0.5 0.5 1.4 2.5 3.0 2.1 2.7 3.5 3.9 4.3 3.6

2005 Index 128.2 128.8 129.5 130.4 131.0 133.0 134.5 135.0 134.1 134.1 134.8 134.9

% 2.8 2.6 3.2 3.0 3.2 3.0 4.2 4.3 4.2 3.7 4.3 4.8

2006 Index 134.8 134.9 135.6 136.9 138.7 142.6 145.1 148.3 147.2 148.3 149.5 149.1

% 5.1 4.7 4.7 5.0 5.9 7.2 7.9 9.9 9.8 10.6 10.9 10.5

2007 Index 149.3 150.2 152.5 154.9 157.0 160.5 161.9 162.5 160.9 162.3 162.9 163.3

% 10.8 11.3 12.5 13.1 13.2 12.6 11.6 9.6 9.3 9.4 9.0 9.5

2008 Index 164.9 167.2 170.6 174.1 182.7 187.5 192.5 193.6 186.7 185.8 183.4 181.3

% 10.4 11.3 11.9 12.4 16.4 16.8 18.9 19.1 16.0 14.5 12.6 11.0

2009 Index 180.0 179.4 179.6 179.2 177.2 179.9 185.2 185.8 179.8 179.7 181.2 182.5

% 9.2 7.3 5.3 2.9 -3.0 -4.1 -3.8 -4.0 -3.7 -3.3 -1.2 0.7

2010 Index 184.9 185.6 186.2 189.0 189.3 196.8 199.4 200.2 192.0 191.2 192.5 193.0

% 2.7 3.5 3.7 5.5 6.8 9.4 7.7 7.8 6.8 6.4 6.2 5.8

2011 Index 195.1 198.0 199.7 201.5 202.4 211.4 217.2 219.4 212.2 211.5 212.0 211.9

% 5.5 6.7 7.3 6.6 6.9 7.4 8.9 9.6 10.5 10.6 10.1 9.8

2012 Index 212.5 214.4 214.1 214.8 215.8 225.4 229.0 230.5 221.2 222.5 223.1 222.9

% 8.9 8.3 7.2 6.6 6.6 6.6 5.4 5.1 4.2 5.2 5.2 5.2

2013 Index 226.5 227.8 229.8 230.7 231.3 233.1

% 5.8 5.4 5.7 5.4 4.9 5.9

The Headline PPI figures presented in Table B-0-2, between 2000 and 2012 are for the Producer Price Index for

Domestic Output of South African industry groups (previous Headline PPI) sourced from Stats SA Producer

Price Index P0142 Historic Publications, from 2013 Final Manufactured Goods is the new headline PPI. The

Indices in Table B-0-2 are calculated using the base year of 2000, where 2000 = 100.

calculating the annual escalation adjustment for...

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