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1 Efficiency and Productivity Measurement: Index Numbers D.S. Prasada Rao School of Economics The University of Queensland, Australia.

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Presentation on theme: "1 Efficiency and Productivity Measurement: Index Numbers D.S. Prasada Rao School of Economics The University of Queensland, Australia."— Presentation transcript:

1 1 Efficiency and Productivity Measurement: Index Numbers D.S. Prasada Rao School of Economics The University of Queensland, Australia

2 2 Index number methods Index numbers are used in measuring changes in a set of related variables: –consumer prices; –stock market prices; –quantities produced; etc. Index numbers can also be used in comparing levels of a set of related variables across space or firms: –Agricultural output in two different countries; –Input indexes across two farms or firms; –Price levels in different countries; etc. In general we compute –Price Index Numbers –Quantity Index Numbers –Decompose Value ratios into Price and Quantity index numbers

3 3 Outline A simple TFP index example Price index numbers Quantity index numbers Tornqvist TFP index A small empirical example Properties of index numbers Additional issues –Indirect index numbers –Chaining index numbers –Transitive index numbers

4 4 TFP growth Productivity growth means getting more output from a particular level of inputs When we have just one input and output the TFP change between period 1 and 2 is: When we have more inputs and outputs we must aggregate using index numbers A basic property of any TFP index is that when q 2 =aq 1 and x 2 =bx 1, then TFP 12 =a/b

5 5 Index number formulae When we have more than one input or output we need to find an aggregation method Four most popular index number formulae are: –Laspeyres –Paasche –Fisher –Tornqvist We will look at price indices first - they are more familiar

6 6 Price Index Numbers Measure changes (or levels) in prices of a set of commodities. Let p mj and q mj represent prices and quantiies (m-th commodity; m = 1,2,...,M and j-th period or firm j = s, t). The index number poblem is to decompose value change into price and quantity change components.

7 7 Laspeyres price index numbers Price change index for N goods from period s to period t p it = price of i-th good in t-th period, q it = quantity Uses base-period (period s) quantity weights Share-weighted sum of individual price indices Often used in CPI calculations

8 8 Paasche price index numbers Uses current-period (period t) quantity weights Share-weighted harmonic mean of individual price indices Paasche Laspeyres - when people respond to relative price changes by adjusting mix of goods purchased (in periods of inflation)

9 9 Fisher price index numbers Fisher index is the geometric mean of the Laspeyres and Paasche index numbers Paasche Fisher Laspeyres - when consumers respond to relative price changes by adjusting mix of goods purchased (in periods of inflation) Paasche and Fisher more data intensive and costly because we need to obtain expenditure weights in each period

10 10 Tornqvist price index numbers Share-weighted geometric mean of individual price indices Uses average of value share from period t and period s Log form is commonly used in calculations - has an approximate percentage change interpretation

11 11 Quantity Index Numbers There are three approaches to the compilation of quantity index numbers. 1. Simply use the same formulae as in the case of price index numbers – simply interchange prices and quantities. 2. Use the index number identity:

12 12 Quantity Index Numbers 3. Compute quantity index directly Malmquist approach Using distance functions defined before Economic theoretic approach Comments All the three approaches have some common elements Fisher index can be derived using all the three approaches Tornqvist index can be derived using the first and the last approaches Fisher index is known as the ideal index.

13 13 Four quantity index numbers To obtain the corresponding quantity index numbers we interchange prices and quantities:

14 14 Which index is best for use in TFP studies? Two methods are used to assess the suitability of index number formulae: –economic theory or functional approach Exact and superlative index numbers –axiomatic or test approach Index numbers that satisfy a number of desirable properties Both approaches suggest that the Fisher and Tornqvist are best (Diewert) We outline these arguments later in this session

15 15 Tornqvist TFP index The Tornqvist has been the most popular TFP index This approach is also know as the Hicks-Moorsteen Approach – defines productivity index simply as the ratio of output and input index numbers.

16 16 Example Recall our example in session 2 Two firms producing t-shirts using labour and capital (machines) Let us now assume that they face different input prices

17 17 In this example we compare productivity across 2 firms (instead of 2 periods) First we calculate the input cost shares Labour share for firm A = (2 80)/(2 80+2 100) = 0.44 Labour share for firm B = (4 90)/(4 90+1 120) = 0.75 Thus the capital shares are (1-0.44)=0.56 and (1-0.75)=0.25, respectively

18 18 Ln Output index = ln(200)-ln(200) = 0.0 Ln Input index = [0.5(0.44+0.75)(ln(2)-ln(4)) +0.5(0.56+0.25)(ln(2)-ln(1))] = -0.13 ln TFP Index = 0.0-(-0.13) = 0.13 TFP Index = exp(0.13)=1.139 ie. firm A is 14% more productive than firm B

19 19 Properties of index numbers Used to evaluate index numbers –Economic theory –Axioms Both suggest Tornqvist and Fisher best for TFP calculations

20 20 Economic theory arguments Laspeyres and Paasche imply simplistic linear production structures Fisher is exact for quadratic - Tornqvist is exact for translog - both are 2nd-order flexible forms - thus superlative indices If we assume technical efficiency, allocative efficiency and CRS, then Tornqvist and Fisher indices can be interpreted as production function shift (technical change) Read more in text…

21 21 The Test or Axiomatic Approach Basically we postulate a number of desirable properties of index numbers in the form of axioms and tests and see which index number satisfy these properties Fisher (1922) provided a list of these tests.

22 22 Positivity: The index (price or quantity) should be everywhere positive. Continuity: The index is a continuous function of the prices and quantities. Proportionality: If all prices (quantities) increase by the same proportion then P st (Q st ) should increase by that proportion. Units invariance: The price (quantity) index must be independent of the units of measurement of quantities (prices).

23 23 Time-reversal test: For two periods s and t: I st =1/I ts. Mean-value test: The price (or quantity) index must lie between the respective minimum and maximum changes at the commodity level. Factor-reversal test: A formula is said to satisfy this test if the same formula is used for direct price and quantity indices and the product of the resulting indices is equal to the value ratio (P Q=V).

24 24 Factor Test: The product of the price and quantity index numbers should be equal to the value index. Circularity test (transitivity): For any three periods, s, t and r, this test requires that: I st =I sr I rt. That is, a direct comparison between s and t yields the same index as an indirect comparison through r (we provide an example later).

25 25 How many tests are satisfied? Diewert (1992) looks at 22 tests for TFP indices - Tornqvist fails factor reversal and transitivity - Fisher fails transitivity. Factor reversal is not greatly important - transitivity is important when making spatial comparisons - Tornqvist and Fisher indices often produce identical numbers (to 2 or 3 significant digits).

26 26 Chaining indices Example: 4 time periods Calculate indices between adjacent years (I 12, I 23, I 34 )=(1.03, 1.04, 0.98) Then form the chained index: C 1 =1.00 C 2 =C 1 ×I 12 =1.00×1.03=1.03 C 3 =C 2 ×I 23 =1.03×1.05=1.08 C 4 =C 3 ×I 34 =1.08×0.98=1.06 Advantage is that weights change regularly

27 27 Transitivity Example: 3 firms Calculate all direct comparisons: (I 12, I 23, I 13 )=(1.10, 1.10, 1.15) These are not consistent (ie. transitive) because 1.10×1.10=1.21 1.15 The EKS method is used to convert non- transitive indices into transitive indices:

28 28 EKS is minimum sum of squares deviation from original index number series Original indices: (I 12, I 23, I 13 )=(1.10, 1.10, 1.15) Transitive indices: TI 12 =(I 11 ×I 12 ) 1/3 ×(I 12 ×I 22 ) 1/3 ×(I 13 ×I 32 ) 1/3 =1.0815 TI 23 =(I 21 ×I 13 ) 1/3 ×(I 22 ×I 23 ) 1/3 ×(I 23 ×I 33 ) 1/3 =1.0815 TI 13 =(I 11 ×I 13 ) 1/3 ×(I 12 ×I 23 ) 1/3 ×(I 13 ×I 33 ) 1/3 =1.1697 Note that TI 12 ×TI 23 = 1.0815×1.0851 = 1.1697 = TI 13

29 29 Transitive Tornqvist TFP index Recall that the binary TFP Index using Tornqvist formula is given by: We note that this index is not transitive

30 30 Transitive Tornqvist TFP Index If we apply the EKS method and generate transitive index numbers, we can show that

31 31 Transitive Tornqvist TFP Index This can be interpreted as an indirect comparison through the sample mean The transitive Tornqvist can be calculated directly using this formula The Fisher index has no equivalent formula - one must calculate the Fisher indices first and then apply EKS Need to recalculate all when one new observation added

32 32 Productivity comparisons using index numbers We note the following important properties: 1.Productivity measures can be computed using data on just two firms (i.e., very limited data); 2.If the data refers to the same firm over two periods and if the firm is technically and allocatively efficient in both periods, then under the assumption of constant returns to scale the productivity measures provided correspond to theoretical measures of productivity growth (Malmquist productivity index – to be discussed next week). 3.Since the TFP index is based only on two observations for s and t, the index is not transitive. If we have several firms, then we need to make the measures transitive. Normally the EKS (Elteto-Koves-Szulc) method is used for this purpose.

33 33 Output Data for the Australian National Railways Example

34 34 Capital inputs Other inputs

35 35 Output, Input and TFP index numbers All the index numbers reported here are calculated using the Tornqvist index number formula. All the indices here are reported for the base year 79/80. While there is a steady increase in output over the years, the input index shows a secular decline resulting in TFP growth over time.

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