SlideShare a Scribd company logo
1 of 36
Download to read offline
1
• On the economic and business front many concepts
  can be measured directly
• When it is not possible, need to introduce an
  associated quantity to represent it
• Referred to as an index number
• Examples of index numbers
  –   Production Price Index
  –   Consumer Price Index
  –   JSE Mining, Industrial, Gold, All Share, Bond indices
  –   Business Confidence Index                               2
What is an index number?
• A measure that summarises the change in the level of
  activity, price or quantity, of a single item or a basket of
  related items from one time period to another
• Expressing the value of an item in the period for which the
  index is calculated as a ratio of its value in the base period
• Index is a percentage value

                                     Period of reference
                                     relative to which an
                                      index is calculated          3
What is an index number?
• Index number = Value in period of interest × 100
                     Value in base period
• When the value exceeds 100, indicates an increase in the
  level of activity
• When the value is less than 100, indicates a decrease in
  the level of activity
                                         Say: Index = 108.4
• Activity can indicate a change in price or quantity
                                           Say: Index = 98.6
                                         There was a:
   – Price index                           There was a:
                                         108.4 – 100 = 8.4%
   – Quantity index                        100 – 98.6 = 1.4%
                                         increase
                                           decrease        4
What is an index number?
• Price indices - P
   – Price of the item in the period of interest – pn
   – Price of the item in the base period – p0

• Quantity indices - Q
   – Quantity of the item in the period of interest – qn
   – Quantity of the item in the base period – q0

                                                           5
Simple index numbers
• Simple price index indicates the change in price of a
  single item from the base period to the period under
  consideration
                     pn
                 P     100
                     p0
• Simple quantity index indicates the change in quantity of a
  single item from the base period to the period under
  consideration
                      qn
                 Q  100
                      q0                                        6
Simple index numbers - example
• The following table indicates the prices, in rand, and
  quantities (in 100) sold at a small supermarket for three years
                        2007               2008               2009
                    Price   Quantity   Price   Quantity   Price   Quantity

     Coffee (500g) 10.49     13.1      15.99    12.8      17.99    14.2
     Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
       Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2


                                                                             7
Simple index numbers - example
• Simple price index for sugar in 2008 with 2007 as base year
                      2007               2008               2009
                  Price   Quantity   Price   Quantity   Price   Quantity

  Coffee (500g) 10.49      13.1      15.99    12.8      17.99    14.2
   Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
     Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2

     pn        5.29
  P    100       100  106.01 6.01 % increase
     p0        4.99                                                        8
Simple index numbers - example
• Simple quantity index for milk in 2009 with 2007 as base year
                      2007               2008               2009
                  Price   Quantity   Price   Quantity   Price   Quantity

  Coffee (500g) 10.49      13.1      15.99    12.8      17.99    14.2
   Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
     Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2

     qn      59.2
  Q  100       100  121.06  21.06 % increase
     q0      48.9                                                          9
Simple index numbers - example
• Simple quantity index for sugar in 2009 with 2008 as base year
                        2007               2008               2009
                    Price   Quantity   Price   Quantity   Price   Quantity

    Coffee (500g) 10.49      13.1      15.99    12.8      17.99    14.2
     Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
       Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2

       qn      18.2
    Q  100       100  97.3 2.7 % decrease
       q0      18.7                                                          10
Concept Questions
• 1 – 6, p418, textbook




                             11
Composite index numbers
• Composite index reflect the average change in activity of
  a basket of items from the base period to the period
  under consideration
   – Unweighted composite indices – all items in the
     basket is considered to be of the same importance
   – Weighted composite indices – each item in the basket
     is weighted according to its relative importance


                                                              12
Unweighted composite index numbers
• Simple composite price index

   P
      p    n
                100
      p    0



• Simple composite quantity index

   Q
      q    n
                100
      q    0

                                      13
Unweighted composite index numbers - example
• Simple composite quantity index for 2009 with 2007 as base year
                         2007               2008               2009
                     Price   Quantity   Price   Quantity   Price   Quantity

      Coffee (500g) 10.49     13.1      15.99    12.8      17.99    14.2
      Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
        Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2


 Q
    q     n
             100 
                    14.2  18.2  59.2
                                       100  115.5 15.5 % inc
    q     0        13.1  17.3  48.9                      14
Unweighted composite index numbers - example
• Simple composite price index for 2008 with 2007 as base year
                       2007               2008               2009
                   Price   Quantity   Price   Quantity   Price   Quantity

    Coffee (500g) 10.49     13.1      15.99    12.8      17.99    14.2
    Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
      Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2


P
   p    n
           100 
                  15.99  5.29  8.99
                                      100  132.4  32.4 % inc
   p    0        10.49  4.99  7.39                     15
Weighted composite index numbers
• Weighted composite price index

   P
       p w 100
               n

      p w     0

• Weighted composite quantity index

   Q
       q w 100
           n

      q w 0



Where: w = weight assigned to each item in the basket
                                                        16
Weighted composite index numbers - example
• Weighted composite price index for 2008 with 2007 as base
  year using the profit for each item as weight
                       2007             2008             2009
                   Price   Profit   Price   Profit   Price   Profit

    Coffee (500g) 10.49    70%      15.99   70%      17.99   70%
    Sugar (500g)   4.99    30%      5.29    30%      7.49    30%
      Milk (1 l)   7.39    20%      8.99    20%      9.39    20%


P
    p w 100
          n

   p w   0

    15.99(.7)  5.29(.3)  8.99(.2)
                                   100  141.3 41.3 % inc
    10.49(.7)  4.99(.3)  7.39(.2)                       17
Weighted composite index numbers
- Laspeyres approach
• The base period values will be assigned as weights to
  the items in the basket
                                           Price index:
• Laspeyres price index                    weight is the quantity

    PL 
            pn q0     100
                                              in the base period

           p q0 0

• Laspeyres quantity index                    Quantity index:
                                              weight is the price
    QL   
           q pn   0
                       100                   in the base period
           q p0   0                                                18
Weighted composite index numbers
- Laspeyres approach
• Advantage is that indices calculated for different period
  using the same basket of items may be compared
  directly as long as the base period remains unchanged
• Disadvantage is that it over estimates increases in the
  prices as times goes by – it is necessary to adjust the
  base period from time to time


                                                              19
Weighted composite index numbers - example
• Laspeyres price index for 2009 with 2007 as base year
                         2007               2008               2009
                     Price   Quantity   Price   Quantity   Price   Quantity

      Coffee (500g) 10.49     13.1      15.99    12.8      17.99    14.2
      Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
        Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2


PL   
       p qn 0
                 100 
                        17.99(13.1)  7.49(17.3)  9.39(48.9)
                                                              100
       p q0   0        10.49(13.1)  4.99(17.3)  7.39(48.9)
                       140.9  40.9 % inc
                                                                              20
Weighted composite index numbers
- Paasche approach
• The consumed current period values will be assigned as
  weights to the items in the basket
• Paasche price index                     Price index:
                                         weight is the quantity
    PP   
           p q
             n n
                      100               in the current period
           p q
             0 n

• Paasche quantity index                   Quantity index:
                                           weight is the price
   QP    
           q p
             n    n
                      100                 in the current period
           q p
             0    n                                          21
Weighted composite index numbers
- Paasche approach
• Advantage is that indices calculated for different period
  using the same basket of items may be compared
  directly as long as the base period remains unchanged
• Disadvantage is that it over estimates increases in the
  prices as times goes by – it is necessary to adjust the
  base period from time to time


                                                              22
Weighted composite index numbers - example
 • Paasche quantity index for 2009 with 2007 as base year
                          2007               2008               2009
                      Price   Quantity   Price   Quantity   Price   Quantity

      Coffee (500g) 10.49      13.1      15.99    12.8      17.99    14.2
       Sugar (500g)   4.99     17.3      5.29     18.7      7.49     18.2
         Milk (1 l)   7.39     48.9      8.99     53.6      9.39     59.2


QP   
       q pn   n
                 100 
                        14.2(17.99)  18.2(7.49)  59.2(9.39)
                                                              100
       q p
          0    n
                        13.1(17.99)  17.3(7.49)  48.9(9.39)
                       114.9 14.9 % inc
                                                                               23
Weighted composite index numbers
- Fischer approach
• Fischer price index

     PF  PL  PP
• Fischer quantity index

     QF  QL  QP
• May only be used if the indices for Laspeyres and Paasche
  have the same base period                               24
Example
The price of bread (rands/bread), meat (rands/kg), Cabbage (rands/cabbage) and wine
(rands/bottle), as well as the quantities (in millions) consumed during 2006, 2007 & 2008
are given in the following table:-
                             Price                               Quantity
                2006         2007         2008         2006         2007        2008
 Bread           7.0          6.6          8.4         900          1000         900
 Meat            44.0         46.0        59.0         600          600          700
 Cabbage         7.0          7.3          9.6           5            6          5.5
 Wine            30.4         30.4        32.1          90           90          100
Calculate the:-
1. Simple quantity index for meat in 2008 with 2006 as base year
2. Simple composite price index for 2007, with 2006 as base year
3. Lapeyres price index for 2008 with 2007 as base year
4. Paasche price index for 2008 with 2007 as base year
5. Fischer price index for 2008 with 2007 as base year
6. Simple composite quantity index for 2008 with 2007 as base year
7. Fischer quantity index for 2007 with 2006 as base year                               25
EXAMPLE ANSWER
1.   1) Q =
                q  100 = 700  100 = 116.67
                     n

               q    0     600

     2)   P=
                p  100 = 90.3  100 = 102.15
                     n

               p    0     88.4


     3)   PL =
                p q  100 = 46146.6  100 = 124.79
                         n   0

               p q      0   036979.8

     4)   PP =
                p q  100 = 52122.8  100 = 126.45
                         n    n

               p q      0    41220.15
                              n


     5) PF =    PL  PP = (124.79)(126.45) = 125.62

     6) Q =
                q  100 = 1705.5  100 = 100.56
                     n

               q    0      1696


     7)   QL =
                q p  100 = 36178  100 = 101.99
                         n    0

               q p      0    35471
                              0



              QP =
                    q p  100 = 36979.8  100 = 101.84
                                  n   n

                   q p           036312.5
                                      n

                                                                   26
              QF =           QL  QP = (101.99)(101.84) = 101.92
The index series
• Collection of indices for the same item or basket of items
  constructed for a number of consecutive periods using
  the same base period
• The base period will be the period = 100




                                                               27
The index series - example
 • Construct an index series for the monthly electricity
   usage for a household – use June as base month

    Month          April May June July              August
 Useage (kw)       680 754          820 835           798
                   82.9 92.0        100 101.8         97.3

   qnn
   q 100  680 100  82.9  17.1% dec
             754
Q
Q  100        100  92.0  8 % dec
   q00
   q        820
            820
                                                             28
Important indices – Consumer price index
• Composite price index of a representative basket of consumer goods
  and services
• Serves as a measure of relative change in the prices of services and
  goods consumed in SA
• Stats SA publish the CPI monthly
• Price information in the index refers to the first 7 days of that month
• Published in the second half of the next month
• Info used to determine the CPI is obtained from a survey in each of
  12 urban areas for each of 3 income groups and contains almost 600
  items in 17 categories
                                                                      29
Important indices – Consumer price index
• A weight is assigned to each item in the basket according to their
  relative importance

               p0 q0
           w
               p0 q0
                   w  pn
                         p0
           CPI 
                  w
                                                                       30
Important indices – Consumer price index
• CPI is used to determine the inflation rate
• Deflate other value series
• Adjust prices, wages, salaries and other variables for changes in the
  inflation rate
• It is available quickly
• A disadvantage is that it is based on a household with on average 1.6
  children, takes only certain good and services into account, includes
  indirect taxes but excluded direct taxes
• Can use consecutive CPI’s as a time series to make forecasts on
  future values and trends
                                                                   31
EXAMPLES OF IMPORTANT INDICES

• JSE all share index
• JSE gold index
• CPI- consumer price index – used to calculate
  inflation rate and cost of living
• Inflation rate
• PPI – Production price index
• Business confidence index
• New car sales index

                                                  32
Statistics SA
• Look at www.stassa.gov.za




                              33
Example
• Activity 1, p197 Module Manual




                                   34
Example
• Activity 2, p199 Module Manual




                                   35
Classwork/Homework
• Revision exercises 1,2,3 p 200 module
  manual




                                          36

More Related Content

What's hot

Standard deviationnormal distributionshow
Standard deviationnormal distributionshowStandard deviationnormal distributionshow
Standard deviationnormal distributionshow
BiologyIB
 
Introduction to Business Statistics
Introduction to Business StatisticsIntroduction to Business Statistics
Introduction to Business Statistics
Megha Mishra
 
Multiple regression presentation
Multiple regression presentationMultiple regression presentation
Multiple regression presentation
Carlo Magno
 
Factor Analysis in Research
Factor Analysis in ResearchFactor Analysis in Research
Factor Analysis in Research
Qasim Raza
 
Chapter 16
Chapter 16Chapter 16
Chapter 16
bmcfad01
 

What's hot (20)

Index number
Index numberIndex number
Index number
 
Time series
Time seriesTime series
Time series
 
Standard deviationnormal distributionshow
Standard deviationnormal distributionshowStandard deviationnormal distributionshow
Standard deviationnormal distributionshow
 
Regression and Co-Relation
Regression and Co-RelationRegression and Co-Relation
Regression and Co-Relation
 
Chapter 13
Chapter 13Chapter 13
Chapter 13
 
Weighted Moving Average Method
Weighted Moving Average MethodWeighted Moving Average Method
Weighted Moving Average Method
 
Auto Correlation Presentation
Auto Correlation PresentationAuto Correlation Presentation
Auto Correlation Presentation
 
Autocorrelation- Detection- part 1- Durbin-Watson d test
Autocorrelation- Detection- part 1- Durbin-Watson d testAutocorrelation- Detection- part 1- Durbin-Watson d test
Autocorrelation- Detection- part 1- Durbin-Watson d test
 
Forecasting Attendance at SWU Football Games
Forecasting Attendance at SWU Football GamesForecasting Attendance at SWU Football Games
Forecasting Attendance at SWU Football Games
 
Chap16 time series analysis and forecasting
Chap16 time series analysis and forecastingChap16 time series analysis and forecasting
Chap16 time series analysis and forecasting
 
Cost of Living, Linear Regression, Multiple Linear Regression
Cost of Living, Linear Regression, Multiple Linear RegressionCost of Living, Linear Regression, Multiple Linear Regression
Cost of Living, Linear Regression, Multiple Linear Regression
 
Time Series, Moving Average
Time Series, Moving AverageTime Series, Moving Average
Time Series, Moving Average
 
Introduction to Business Statistics
Introduction to Business StatisticsIntroduction to Business Statistics
Introduction to Business Statistics
 
Msb12e ppt ch11
Msb12e ppt ch11Msb12e ppt ch11
Msb12e ppt ch11
 
Multiple regression presentation
Multiple regression presentationMultiple regression presentation
Multiple regression presentation
 
Annuity
AnnuityAnnuity
Annuity
 
Factor Analysis in Research
Factor Analysis in ResearchFactor Analysis in Research
Factor Analysis in Research
 
Selection of bin width and bin number in histograms
Selection of bin width and bin number in histogramsSelection of bin width and bin number in histograms
Selection of bin width and bin number in histograms
 
Chapter 16
Chapter 16Chapter 16
Chapter 16
 
Risk & Uncertainty in Managerial Decision Making (Managerial economics)
Risk & Uncertainty in Managerial Decision Making (Managerial economics)Risk & Uncertainty in Managerial Decision Making (Managerial economics)
Risk & Uncertainty in Managerial Decision Making (Managerial economics)
 

Viewers also liked

Chapter 11 index number
Chapter 11  index numberChapter 11  index number
Chapter 11 index number
atiqah ayie
 
Ch1 2 index number
Ch1 2 index numberCh1 2 index number
Ch1 2 index number
Jay Tanna
 
Chap19 time series-analysis_and_forecasting
Chap19 time series-analysis_and_forecastingChap19 time series-analysis_and_forecasting
Chap19 time series-analysis_and_forecasting
Vishal Kukreja
 

Viewers also liked (20)

Index Number
Index NumberIndex Number
Index Number
 
Chapter 11 index number
Chapter 11  index numberChapter 11  index number
Chapter 11 index number
 
Index Numbers
Index NumbersIndex Numbers
Index Numbers
 
Types Of Index Numbers
Types Of Index NumbersTypes Of Index Numbers
Types Of Index Numbers
 
Presentation on Index Number
Presentation on Index NumberPresentation on Index Number
Presentation on Index Number
 
Index number
Index numberIndex number
Index number
 
Index number
Index numberIndex number
Index number
 
Chap15 time series forecasting & index number
Chap15 time series forecasting & index numberChap15 time series forecasting & index number
Chap15 time series forecasting & index number
 
Index numbers
Index numbersIndex numbers
Index numbers
 
Ch1 2 index number
Ch1 2 index numberCh1 2 index number
Ch1 2 index number
 
Index number
Index numberIndex number
Index number
 
Index number
Index numberIndex number
Index number
 
I ndex no_stats
I ndex no_statsI ndex no_stats
I ndex no_stats
 
Time series, forecasting, and index numbers
Time series, forecasting, and index numbersTime series, forecasting, and index numbers
Time series, forecasting, and index numbers
 
Index numbers
Index numbersIndex numbers
Index numbers
 
Chap19 time series-analysis_and_forecasting
Chap19 time series-analysis_and_forecastingChap19 time series-analysis_and_forecasting
Chap19 time series-analysis_and_forecasting
 
Msb11e ppt ch13
Msb11e ppt ch13Msb11e ppt ch13
Msb11e ppt ch13
 
Index numbers
Index numbersIndex numbers
Index numbers
 
Chapter 20
Chapter 20Chapter 20
Chapter 20
 
Evolving role of teacher
Evolving role of teacherEvolving role of teacher
Evolving role of teacher
 

More from jillmitchell8778

Lu5 how to assess a business opportunity
Lu5   how to assess a business opportunityLu5   how to assess a business opportunity
Lu5 how to assess a business opportunity
jillmitchell8778
 
Lu4 – life cycle stages of a business
Lu4 – life cycle stages of a businessLu4 – life cycle stages of a business
Lu4 – life cycle stages of a business
jillmitchell8778
 

More from jillmitchell8778 (20)

Revision workshop 17 january 2013
Revision workshop 17 january 2013Revision workshop 17 january 2013
Revision workshop 17 january 2013
 
Statistics lecture 13 (chapter 13)
Statistics lecture 13 (chapter 13)Statistics lecture 13 (chapter 13)
Statistics lecture 13 (chapter 13)
 
Statistics lecture 11 (chapter 11)
Statistics lecture 11 (chapter 11)Statistics lecture 11 (chapter 11)
Statistics lecture 11 (chapter 11)
 
Statistics lecture 10(ch10)
Statistics lecture 10(ch10)Statistics lecture 10(ch10)
Statistics lecture 10(ch10)
 
Statistics lecture 9 (chapter 8)
Statistics lecture 9 (chapter 8)Statistics lecture 9 (chapter 8)
Statistics lecture 9 (chapter 8)
 
Statistics lecture 8 (chapter 7)
Statistics lecture 8 (chapter 7)Statistics lecture 8 (chapter 7)
Statistics lecture 8 (chapter 7)
 
Qr code lecture
Qr code lectureQr code lecture
Qr code lecture
 
Poisson lecture
Poisson lecturePoisson lecture
Poisson lecture
 
Statistics lecture 7 (ch6)
Statistics lecture 7 (ch6)Statistics lecture 7 (ch6)
Statistics lecture 7 (ch6)
 
Normal lecture
Normal lectureNormal lecture
Normal lecture
 
Binomial lecture
Binomial lectureBinomial lecture
Binomial lecture
 
Statistics lecture 6 (ch5)
Statistics lecture 6 (ch5)Statistics lecture 6 (ch5)
Statistics lecture 6 (ch5)
 
Project admin lu3
Project admin   lu3Project admin   lu3
Project admin lu3
 
Priject admin lu 2
Priject admin   lu 2Priject admin   lu 2
Priject admin lu 2
 
Project admin lu 1
Project admin   lu 1Project admin   lu 1
Project admin lu 1
 
Lu5 how to assess a business opportunity
Lu5   how to assess a business opportunityLu5   how to assess a business opportunity
Lu5 how to assess a business opportunity
 
Lu4 – life cycle stages of a business
Lu4 – life cycle stages of a businessLu4 – life cycle stages of a business
Lu4 – life cycle stages of a business
 
Statistics lecture 5 (ch4)
Statistics lecture 5 (ch4)Statistics lecture 5 (ch4)
Statistics lecture 5 (ch4)
 
Lu 3
Lu 3Lu 3
Lu 3
 
Learning unit 2
Learning unit 2Learning unit 2
Learning unit 2
 

Recently uploaded

Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
ZurliaSoop
 

Recently uploaded (20)

Google Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxGoogle Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptx
 
Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
 
OSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & SystemsOSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & Systems
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
How to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptxHow to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptx
 
21st_Century_Skills_Framework_Final_Presentation_2.pptx
21st_Century_Skills_Framework_Final_Presentation_2.pptx21st_Century_Skills_Framework_Final_Presentation_2.pptx
21st_Century_Skills_Framework_Final_Presentation_2.pptx
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structure
 
How to Add New Custom Addons Path in Odoo 17
How to Add New Custom Addons Path in Odoo 17How to Add New Custom Addons Path in Odoo 17
How to Add New Custom Addons Path in Odoo 17
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
latest AZ-104 Exam Questions and Answers
latest AZ-104 Exam Questions and Answerslatest AZ-104 Exam Questions and Answers
latest AZ-104 Exam Questions and Answers
 
Plant propagation: Sexual and Asexual propapagation.pptx
Plant propagation: Sexual and Asexual propapagation.pptxPlant propagation: Sexual and Asexual propapagation.pptx
Plant propagation: Sexual and Asexual propapagation.pptx
 
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptxCOMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Tatlong Kwento ni Lola basyang-1.pdf arts
Tatlong Kwento ni Lola basyang-1.pdf artsTatlong Kwento ni Lola basyang-1.pdf arts
Tatlong Kwento ni Lola basyang-1.pdf arts
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
 
Philosophy of china and it's charactistics
Philosophy of china and it's charactisticsPhilosophy of china and it's charactistics
Philosophy of china and it's charactistics
 

Statistics lecture 12 (chapter 12)

  • 1. 1
  • 2. • On the economic and business front many concepts can be measured directly • When it is not possible, need to introduce an associated quantity to represent it • Referred to as an index number • Examples of index numbers – Production Price Index – Consumer Price Index – JSE Mining, Industrial, Gold, All Share, Bond indices – Business Confidence Index 2
  • 3. What is an index number? • A measure that summarises the change in the level of activity, price or quantity, of a single item or a basket of related items from one time period to another • Expressing the value of an item in the period for which the index is calculated as a ratio of its value in the base period • Index is a percentage value Period of reference relative to which an index is calculated 3
  • 4. What is an index number? • Index number = Value in period of interest × 100 Value in base period • When the value exceeds 100, indicates an increase in the level of activity • When the value is less than 100, indicates a decrease in the level of activity Say: Index = 108.4 • Activity can indicate a change in price or quantity Say: Index = 98.6 There was a: – Price index There was a: 108.4 – 100 = 8.4% – Quantity index 100 – 98.6 = 1.4% increase decrease 4
  • 5. What is an index number? • Price indices - P – Price of the item in the period of interest – pn – Price of the item in the base period – p0 • Quantity indices - Q – Quantity of the item in the period of interest – qn – Quantity of the item in the base period – q0 5
  • 6. Simple index numbers • Simple price index indicates the change in price of a single item from the base period to the period under consideration pn P 100 p0 • Simple quantity index indicates the change in quantity of a single item from the base period to the period under consideration qn Q  100 q0 6
  • 7. Simple index numbers - example • The following table indicates the prices, in rand, and quantities (in 100) sold at a small supermarket for three years 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 7
  • 8. Simple index numbers - example • Simple price index for sugar in 2008 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 pn 5.29 P 100  100  106.01 6.01 % increase p0 4.99 8
  • 9. Simple index numbers - example • Simple quantity index for milk in 2009 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 qn 59.2 Q  100  100  121.06  21.06 % increase q0 48.9 9
  • 10. Simple index numbers - example • Simple quantity index for sugar in 2009 with 2008 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 qn 18.2 Q  100  100  97.3 2.7 % decrease q0 18.7 10
  • 11. Concept Questions • 1 – 6, p418, textbook 11
  • 12. Composite index numbers • Composite index reflect the average change in activity of a basket of items from the base period to the period under consideration – Unweighted composite indices – all items in the basket is considered to be of the same importance – Weighted composite indices – each item in the basket is weighted according to its relative importance 12
  • 13. Unweighted composite index numbers • Simple composite price index P p n 100 p 0 • Simple composite quantity index Q q n 100 q 0 13
  • 14. Unweighted composite index numbers - example • Simple composite quantity index for 2009 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 Q q n 100  14.2  18.2  59.2 100  115.5 15.5 % inc q 0 13.1  17.3  48.9 14
  • 15. Unweighted composite index numbers - example • Simple composite price index for 2008 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 P p n 100  15.99  5.29  8.99 100  132.4  32.4 % inc p 0 10.49  4.99  7.39 15
  • 16. Weighted composite index numbers • Weighted composite price index P  p w 100 n p w 0 • Weighted composite quantity index Q  q w 100 n q w 0 Where: w = weight assigned to each item in the basket 16
  • 17. Weighted composite index numbers - example • Weighted composite price index for 2008 with 2007 as base year using the profit for each item as weight 2007 2008 2009 Price Profit Price Profit Price Profit Coffee (500g) 10.49 70% 15.99 70% 17.99 70% Sugar (500g) 4.99 30% 5.29 30% 7.49 30% Milk (1 l) 7.39 20% 8.99 20% 9.39 20% P  p w 100 n p w 0 15.99(.7)  5.29(.3)  8.99(.2)  100  141.3 41.3 % inc 10.49(.7)  4.99(.3)  7.39(.2) 17
  • 18. Weighted composite index numbers - Laspeyres approach • The base period values will be assigned as weights to the items in the basket Price index: • Laspeyres price index weight is the quantity PL   pn q0 100 in the base period p q0 0 • Laspeyres quantity index Quantity index: weight is the price QL  q pn 0 100 in the base period q p0 0 18
  • 19. Weighted composite index numbers - Laspeyres approach • Advantage is that indices calculated for different period using the same basket of items may be compared directly as long as the base period remains unchanged • Disadvantage is that it over estimates increases in the prices as times goes by – it is necessary to adjust the base period from time to time 19
  • 20. Weighted composite index numbers - example • Laspeyres price index for 2009 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 PL  p qn 0 100  17.99(13.1)  7.49(17.3)  9.39(48.9) 100 p q0 0 10.49(13.1)  4.99(17.3)  7.39(48.9)  140.9  40.9 % inc 20
  • 21. Weighted composite index numbers - Paasche approach • The consumed current period values will be assigned as weights to the items in the basket • Paasche price index Price index: weight is the quantity PP  p q n n 100 in the current period p q 0 n • Paasche quantity index Quantity index: weight is the price QP  q p n n 100 in the current period q p 0 n 21
  • 22. Weighted composite index numbers - Paasche approach • Advantage is that indices calculated for different period using the same basket of items may be compared directly as long as the base period remains unchanged • Disadvantage is that it over estimates increases in the prices as times goes by – it is necessary to adjust the base period from time to time 22
  • 23. Weighted composite index numbers - example • Paasche quantity index for 2009 with 2007 as base year 2007 2008 2009 Price Quantity Price Quantity Price Quantity Coffee (500g) 10.49 13.1 15.99 12.8 17.99 14.2 Sugar (500g) 4.99 17.3 5.29 18.7 7.49 18.2 Milk (1 l) 7.39 48.9 8.99 53.6 9.39 59.2 QP  q pn n 100  14.2(17.99)  18.2(7.49)  59.2(9.39) 100 q p 0 n 13.1(17.99)  17.3(7.49)  48.9(9.39)  114.9 14.9 % inc 23
  • 24. Weighted composite index numbers - Fischer approach • Fischer price index PF  PL  PP • Fischer quantity index QF  QL  QP • May only be used if the indices for Laspeyres and Paasche have the same base period 24
  • 25. Example The price of bread (rands/bread), meat (rands/kg), Cabbage (rands/cabbage) and wine (rands/bottle), as well as the quantities (in millions) consumed during 2006, 2007 & 2008 are given in the following table:- Price Quantity 2006 2007 2008 2006 2007 2008 Bread 7.0 6.6 8.4 900 1000 900 Meat 44.0 46.0 59.0 600 600 700 Cabbage 7.0 7.3 9.6 5 6 5.5 Wine 30.4 30.4 32.1 90 90 100 Calculate the:- 1. Simple quantity index for meat in 2008 with 2006 as base year 2. Simple composite price index for 2007, with 2006 as base year 3. Lapeyres price index for 2008 with 2007 as base year 4. Paasche price index for 2008 with 2007 as base year 5. Fischer price index for 2008 with 2007 as base year 6. Simple composite quantity index for 2008 with 2007 as base year 7. Fischer quantity index for 2007 with 2006 as base year 25
  • 26. EXAMPLE ANSWER 1. 1) Q =  q  100 = 700  100 = 116.67 n q 0 600 2) P=  p  100 = 90.3  100 = 102.15 n p 0 88.4 3) PL =  p q  100 = 46146.6  100 = 124.79 n 0 p q 0 036979.8 4) PP =  p q  100 = 52122.8  100 = 126.45 n n p q 0 41220.15 n 5) PF = PL  PP = (124.79)(126.45) = 125.62 6) Q =  q  100 = 1705.5  100 = 100.56 n q 0 1696 7) QL =  q p  100 = 36178  100 = 101.99 n 0 q p 0 35471 0 QP =  q p  100 = 36979.8  100 = 101.84 n n q p 036312.5 n 26 QF = QL  QP = (101.99)(101.84) = 101.92
  • 27. The index series • Collection of indices for the same item or basket of items constructed for a number of consecutive periods using the same base period • The base period will be the period = 100 27
  • 28. The index series - example • Construct an index series for the monthly electricity usage for a household – use June as base month Month April May June July August Useage (kw) 680 754 820 835 798 82.9 92.0 100 101.8 97.3 qnn q 100  680 100  82.9  17.1% dec 754 Q Q  100  100  92.0  8 % dec q00 q 820 820 28
  • 29. Important indices – Consumer price index • Composite price index of a representative basket of consumer goods and services • Serves as a measure of relative change in the prices of services and goods consumed in SA • Stats SA publish the CPI monthly • Price information in the index refers to the first 7 days of that month • Published in the second half of the next month • Info used to determine the CPI is obtained from a survey in each of 12 urban areas for each of 3 income groups and contains almost 600 items in 17 categories 29
  • 30. Important indices – Consumer price index • A weight is assigned to each item in the basket according to their relative importance p0 q0 w  p0 q0   w pn p0 CPI  w 30
  • 31. Important indices – Consumer price index • CPI is used to determine the inflation rate • Deflate other value series • Adjust prices, wages, salaries and other variables for changes in the inflation rate • It is available quickly • A disadvantage is that it is based on a household with on average 1.6 children, takes only certain good and services into account, includes indirect taxes but excluded direct taxes • Can use consecutive CPI’s as a time series to make forecasts on future values and trends 31
  • 32. EXAMPLES OF IMPORTANT INDICES • JSE all share index • JSE gold index • CPI- consumer price index – used to calculate inflation rate and cost of living • Inflation rate • PPI – Production price index • Business confidence index • New car sales index 32
  • 33. Statistics SA • Look at www.stassa.gov.za 33
  • 34. Example • Activity 1, p197 Module Manual 34
  • 35. Example • Activity 2, p199 Module Manual 35
  • 36. Classwork/Homework • Revision exercises 1,2,3 p 200 module manual 36