THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE 17
Introduction utility function has the property that it can approximate an arbitrary linearly homogeneous function to the sec- 17.1 This chapter and the next cover the econo- ond order; i.e., in economics terminology, each of these mic approach to index number theory. This chapter three functional forms is flexible. Hence, using the ter- considers the case of a single household, while the fol- minology introduced by Diewert (1976), the Fisher, lowing chapter deals with the case of many households. Walsh and To¨ rnqvist price indices are examples of A brief outline of the contents of the present chapter superlative index number formulae. follows. 17.5 In paragraphs 17.50 to 17.54, it is shown that the 17.2 In paragraphs 17.9 to 17.17, the theory of the Fisher, Walsh and To¨ rnqvist price indices approximate cost of living index for a single consumer or household is each other very closely using ‘‘normal’’ time series presented. This theory was originally developed by the data. This is a very convenient result since these three Russian economist, A.A. Konu¨ s (1924). The relation- index number formulae repeatedly show up as being ship between the (unobservable) true cost of living index ‘‘best’’ in all the approaches to index number theory. and the observable Laspeyres and Paasche indices will Hence this approximation result implies that it normally be explained. It should be noted that, in the economic will not matter which of these three indices is chosen approach to index number theory, it is assumed that as the preferred target index for a consumer price households regard the observed price data as given, index (CPI). while the quantity data are regarded as solutions 17.6 The Paasche and Laspeyres price indices have a to various economic optimization problems. Many very convenient mathematical property: they are con- price statisticians find the assumptions made in the sistent in aggregation. For example, if the Laspeyres economic approach to be somewhat implausible. Per- formula is used to construct sub-indices for, say, food or haps the best way to regard the assumptions made clothing, then these sub-index values can be treated as in the economic approach is that these assumptions sub-aggregate price relatives and, using the expenditure simply formalize the fact that consumers tend to pur- shares on these sub-aggregates, the Laspeyres formula chase more of a commodity if its price falls relative to can be applied again to form a two-stage Laspeyres price other prices. index. Consistency in aggregation means that this two- 17.3 In paragraphs 17.18 to 17.26, the preferences of stage index is equal to the corresponding single-stage the consumer are restricted compared to the completely index. In paragraphs 17.55 to 17.60, it is shown that the general case treated in paragraphs 17.9 to 17.17. In superlative indices derived in the earlier sections are not paragraphs 17.18 to 17.26, it is assumed that the func- exactly consistent in aggregation but are approximately tion that represents the consumer’s preferences over consistent in aggregation. alternative combinations of commodities is homo- 17.7 In paragraphs 17.61 to 17.64, a very interesting geneous of degree one. This assumption means that each index number formula is derived: the Lloyd (1975) and indifference surface (the set of commodity bundles that Moulton (1996a) price index. This index number formula give the consumer the same satisfaction or utility) is a makes use of the same information that is required in radial blow-up of a single indifference surface. With this order to calculate a Laspeyres index (namely, base period extra assumption, the theory of the true cost of living expenditure shares, base period prices and current period simplifies, as will be seen. prices), plus one other parameter (the elasticity of sub- 17.4 In the sections starting with paragraphs 17.27, stitution between commodities). If information on this 17.33 and 17.44, it is shown that the Fisher, Walsh and extra parameter can be obtained, then the resulting index To¨ rnqvist price indices (which emerge as being ‘‘best’’ can largely eliminate substitution bias and it can be in the various non-economic approaches) are also calculated using basically the same information that is among the ‘‘best’’ in the economic approach to index required to obtain the Laspeyres index. number theory. In these sections, the preference func- 17.8 The section starting with paragraph 17.65 con- tion of the single household will be further restricted siders the problem of defining a true cost of living index compared to the assumptions on preferences made in the when the consumer has annual preferences over com- previous two sections. Specific functional forms for the modities but faces monthly (or quarterly) prices. This consumer’s utility function are assumed and it turns out section attempts to provide an economic foundation for that, with each of these specific assumptions, the con- the Lowe index studied in Chapter 15. It also provides sumer’s true cost of living index can be exactly calcu- an introduction to the problems associated with the lated using observable price and quantity data. Each of existence of seasonal commodities, which are considered the three specific functional forms for the consumer’s at more length in Chapter 22. The final section deals 313 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE with situations where there may be a zero price for a The period t price vector for the n commodities under commodity in one period, but where the price is non- consideration that the consumer faces is pt. Note that zero in the other period. the solution to the cost or expenditure minimization problem (17.1) for a general utility level u and general vector of commodity prices p defines the consumer’s cost The Konu¨ s cost of living index function, C(u, p). The cost function will be used below in order to define the consumer’s cost of living price and observable bounds index. 17.9 This section deals with the theory of the cost 17.11 The Konu¨ s (1924) family of true cost of living of living index for a single consumer (or household) indices pertaining to two periods where the consumer 0 0 0 that was first developed by the Russian economist, faces the strictly positive price vectors p ( p1, ..., pn) 1 1 1 Konu¨ s (1924). This theory relies on the assumption of and p ( p1, ..., pn) in periods 0 and 1, respectively, is optimizing behaviour on the part of economic agents defined as the ratio of the minimum costs of achieving (consumers or producers). Thus, given a vector of com- the same utility level u:f(q), where q:(q1, ..., qn)isa modity prices pt that the household faces in a given time positive reference quantity vector: period t, it is assumed that the corresponding observed 1 quantity vector qt is the solution to a cost minimization 0 1 C( f (q), p ) PK ( p , p , q) (17:2) problem that involves the consumer’s preference C( f (q), p0) or utility function f.1 Thus in contrast to the axiomatic approach to index number theory, the economic Note that definition (17.2) defines a family of price approach does not assume that the two quantity vec- indices, because there is one such index for each refer- tors q0 and q1 are independent of the two price vectors p0 ence quantity vector q chosen. and p1. In the economic approach, the period 0 quantity 17.12 It is natural to choose two specific reference 0 quantity vectors q in definition (17.2): the observed base vector q is determined by the consumer’s preference 0 0 period quantity vector q and the current period quan- function f and the period 0 vector of prices p that the 1 consumer faces, and the period 1 quantity vector q1 is tity vector q . The first of these two choices leads to the determined by the consumer’s preference function f and following Laspeyres–Konu¨s true cost of living index: 1 the period 1 vector of prices p . 0 1 0 1 0 C( f (q ), p ) 17.10 The economic approach to index number PK ( p , p , q ) 0 0 theory assumes that ‘‘the’’ consumer has well-defined C( f (q ), p ) preferences over different combinations of the n con- C( f (q0), p1) 2 = Pn using (17:1) for t=0 sumer commodities or items. Each combination of 0 0 items can be represented by a positive quantity vector pi qi q:[q , ..., q ]. The consumer’s preferences over alter- i=1 1 n Pn native possible consumption vectors, q, are assumed to 1 0 minq pi qi : f (q)=f (q ) be representable by a continuous, non-decreasing and i=1 3 1 0 = Pn (17:3) concave utility function f. Thus if f(q )>f(q ), then the 0 0 consumer prefers the consumption vector q1 to q0.Itis pi qi further assumed that the consumer minimizes the cost of i=1 achieving the period t utility level ut:f(qt) for periods using the definition of the cost minimization problem t=0, 1. Thus we assume that the observed period t that defines C( f(q0), p1) t consumption vector q solves the following period t cost Pn minimization problem: 1 0 pi qi i=1 Pn t t t t t Pn C(u , p ) minq pi qi : f (q)=u f (q ) p0q0 i=1 i i i=1 Pn = ptqt for t=0, 1 (17:1) 0 0 0 i i since q (q1, ..., qn) is feasible for the minimization i=1 problem 0 1 0 1 =PL( p , p , q , q ) 1 For a description of the economic theory of the input and output price indices, see Balk (1998a). In the economic theory of the output price index, qt is assumed to be the solution to a revenue maximization where PL is the Laspeyres price index. Thus the (unob- problem involving the output price vector pt. servable) Laspeyres–Konu¨ s true cost of living index is 2 In this chapter, these preferences are assumed to be invariant over bounded from above by the observable Laspeyres price time, while in the following chapter, this assumption is relaxed (one of index.4 the environmental variables could be a time variable that shifts tastes). 17.13 The second of the two natural choices for 3 Note that f is concave if and only if f(lq1+(1 l)q2) lf(q1)+ a reference quantity vector q in definition (17.2) leads 2 1 2 (1 l) f(q ) for all 0 l 1 and all q 0n and q 0n. Note also that to the following Paasche–Konu¨s true cost of living q 0N means that each component of the N-dimensional vector q is non-negative, q 0n means that each component of q is positive and 4 q>0n means that q 0n but q=0n; i.e., q is non-negative but at least This inequality was first obtained by Konu¨ s (1924; 1939, p. 17). See one component is positive. also Pollak (1983). 314 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE index: Figure 17.1 The Laspeyres and Paasche bounds to the C( f (q1), p1) true cost of living index P ( p0, p1, q1) q K C( f (q1), p0) 2 Pn 1 1 pi qi i=1 1 1 1 = using (17:1) for t=1 q = (q 1 ,q 2 ) C( f (q1), p0) q 0* Pn 1 1 pi qi q 0 = (q 0,q 0) q 1* i=1 1 2 = Pn (17:4) 0 1 minq pi qi : f (q)=f (q ) i=1 q using the definition of the cost minimization problem O A B C D E F 1 that defines
Pn 1 1 pi qi line D. From equation (17.3), the Laspeyres–Konu¨ s true 0 0 i=1 1 1 1 index is C[u0, p1]=[ p0q0+p0q0], while the ordinary Las- Cð f ðq Þ; p Þ Pn since q (q1, ..., qn) 1 1 2 2 0 1 1 0 1 0 0 0 0 0 pi qi peyres index is [ p1q1+p2q2]=[ p1q1+p2q2]. Since the i=1 denominators for these two indices are the same, the is feasible for the minimization problem and thus difference between the indices is attributable to the dif- Pn ferences in their numerators. In Figure 17.1, this differ- 1 0 0 1 C( f (q ), p ) pi qi and hence ence in the numerators is expressed by the fact that the i=1 cost line through A lies below the parallel cost line 1 1 0 1 0 1 through B. Now if the consumer’s indifference curve =P ( p , p , q , q ) 0 C( f (q1), p0) Pn P through the observed period 0 consumption vector q 0 1 0 pi qi were L-shaped with vertex at q , then the consumer i=1 would not change his or her consumption pattern in where PP is the Paasche price index. Thus the (unobser- response to a change in the relative prices of the two vable) Paasche–Konu¨ s true cost of living index is boun- commodities while keeping a fixed standard of living. In 0* ded from below by the observable Paasche price index.5 this case, the hypothetical vector q would coincide with 0 17.14 It is possible to illustrate the two inequalities q , the dashed line through A would coincide with the (17.3) and (17.4) if there are only two commodities; dashed line through B and the true Laspeyres–Konu¨ s see Figure 17.1. The solution to the period 0 cost index would coincide with the ordinary Laspeyres index. minimization problem is the vector q0. The straight However, L-shaped indifference curves are not generally line C represents the consumer’s period 0 budget con- consistent with consumer behaviour; i.e., when the price straint, the set of quantity points q1, q2 such that of a commodity decreases, consumers generally demand 0 0 0 0 0 0 0 more of it. Thus, in the general case, there will be a gap p1q1+p2q2=p1q1+p2q2. The curved line through q is the consumer’s period 0 indifference curve, the set of between the points A and B. The magnitude of this gap 0 0 represents the amount of substitution bias between the points q1, q2 such that f (q1, q2)=f (q1, q2); i.e., it is the set of consumption vectors that give the same utility as the true index and the corresponding Laspeyres index; i.e., observed period 0 consumption vector q0. The solution the Laspeyres index will generally be greater than the 0 1 0 to the period 1 cost minimization problem is the corresponding true cost of living index, PK(p , p , q ). vector q1. The straight line D represents the consumer’s 17.15 Figure 17.1 can also be used to illustrate the period 1 budget constraint, the set of quantity points inequality (17.4). First note that the dashed lines E and F q , q such that p1q +p1q =p1q1+p1q1. The curved are parallel to the period 0 isocost line through 1 2 1 1 2 2 1 1 2 2 1* line through q1 is the consumer’s period 1 indifference C. The point q solves the hypothetical problem of curve, the set of points q1, q2 such that f (q1, q2)= minimizing the cost of achieving the current period utility 1 1 level u1:f(q1) when facing the period 0 price vector f (q1, q2); i.e., it is the set of consumption vectors that 0 0 0 1 0 0 1* 0 1* give the same utility as the observed period 1 con- p =( p1, p2). Thus we have C[u , p ]= p1q1 +p2q2 and sumption vector q1. The point q0* solves the hypothe- the dashed line E is the corresponding isocost line 1 1 0 1 tical problem of minimizing the cost of achieving the p1q1+p2q2=C[u , p ]. From equation (17.4), the 0 0 1 1 1 1 1 0 base period utility level u :f(q ) when facing the period Paasche–Konu¨ s true index is [ p1q1+ p2q2]=C[u , p ], 1 1 1 0 1 1 1 1 1 1 price vector p =(p1, p2). Thus we have C[u , p ]= while the ordinary Paasche index is [ p1q1+p2q2]= 1 0* 1 0* 0 1 0 1 p1q1 +p2q2 and the dashed line A is the corresponding [ p1q1+p2q2]. Since the numerators for these two indices 1 1 0 1 isocost line p1q1+p2q2=C[u , p ]. Note that the hypo- are the same, the difference between the indices is attri- thetical cost line A is parallel to the actual period 1 cost butable to the differences in their denominators. In Figure 17.1, this difference in the denominators is expressed by 5 This inequality is attributable to Konu¨ s (1924; 1939, p. 19); see also the fact that the cost line through E lies below the parallel Pollak (1983). cost line through F. The magnitude of this difference 315 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE represents the amount of substitution bias between the assumption. For the remainder of this section, it is true index and the corresponding Paasche index; i.e., the assumed that f is (positively) linearly homogeneous.7 In Paasche index will generally be less than the correspond- the economics literature, this is known as the assump- 0 1 1 8 ing true cost of living index, PK(p , p , q ). Note that this tion of homothetic preferences. This assumption is not inequality goes in the opposite direction to the previous strictly justified from the viewpoint of actual economic inequality between the two Laspeyres indices. The reason behaviour, but it leads to economic price indices that are for this change in direction is attributable to the fact that independent of the consumer’s standard of living.9 one set of differences between the two indices takes place Under this assumption, the consumer’s expenditure or in the numerators of the indices (the Laspeyres inequal- cost function, C(u, p) defined by equation (17.1), ities), while the other set takes place in the denominators decomposes as follows. For positive commodity prices of the indices (the Paasche inequalities). p 0N and a positive utility level u, then, using the 17.16 The bound (17.3) on the Laspeyres–Konu¨ s definition of C as the minimum cost of achieving the 0 1 0 true cost of living index PK(p , p , q ) using the base given utility level u, the following equalities can be period level of utility as the living standard is one-sided, derived: as is the bound (17.4) on the Paasche–Konu¨ s true cost of living index P (p0, p1, q1) using the current period level Pn K C(u, p) min p q : f (q , ..., q ) u of utility as the living standard. In a remarkable result, q i i 1 n i=1 Konu¨ s (1924; 1939, p. 20) showed that there exists an Pn 1 intermediate consumption vector q* that is on the = minq piqi : f (q1, ..., qn) 1 straight line joining the base period consumption vector i=1 u q0 and the current period consumption vector q1 such dividing by u > 0 that the corresponding (unobservable) true cost of living Pn 0 1 Ã q1 qn index PK ( p , p , q ) is between the observable Laspeyres = minq piqi : f , ..., 1 6 i=1 u u and Paasche indices, PL and PP. Thus we have the existence of a number l* between 0 and 1 such that using the linear homogeneity of f Pn 0 1 * 0 * 1 piqi q1 qn PL PK ( p , p , l q +(1 l )q ) PP or =u min : f , ..., 1 q u u u P P ( p0, p1, l*q0+(1 l*)q1) P (17:5) i=1 P K L Pn The inequalities (17.5) are of some practical importance. =u minz pizi : f (z1, ..., zn) 1 letting If the observable (in principle) Paasche and Laspeyres i=1 qi indices are not too far apart, then taking a symmetric zi= =uC(1, p) using definition (17:1) average of these indices should provide a good approx- u imation to a true cost of living index where the reference =uc( p) (17:6) standard of living is somewhere between the base and current period living standards. To determine the precise symmetric average of the Paasche and Laspeyres indices, appeal can be made to the results in paragraphs 15.18 to 7 The linear homogeneity property means that f satisfies the following 15.32 in Chapter 15, and the geometric mean of the condition: f(lq)=lf(q) for all l>0 and all q 0n. This assumption is fairly restrictive in the consumer context. It implies that each indif- Paasche and Laspeyres indices can be justified as being ference curve is a radial projection of the unit utility indifference curve. the ‘‘best’’ average, which is the Fisher price index. Thus It also implies that all income elasticities of demand are unity, which is the Fisher ideal price index receives a fairly strong jus- contradicted by empirical evidence. tification as a good approximation to an unobservable 8 More precisely, Shephard (1953) defined a homothetic function to be theoretical cost of living index. a monotonic transformation of a linearly homogeneous function. However, if a consumer’s utility function is homothetic, it can always 17.17 The bounds (17.3)–(17.5) are the best that can be rescaled to be linearly homogeneous without changing consumer be obtained on true cost of living indices without mak- behaviour. Hence, the homothetic preferences assumption can simply ing further assumptions. Further assumptions are made be identified with the linear homogeneity assumption. below on the class of utility functions that describe the 9 This particular branch of the economic approach to index number consumer’s tastes for the n commodities under con- theory is attributable to Shephard (1953; 1970) and Samuelson and sideration. With these extra assumptions, the con- Swamy (1974). Shephard in particular realized the importance of the homotheticity assumption in conjunction with separability assump- sumer’s true cost of living can be determined exactly. tions in justifying the existence of sub-indices of the overall cost of living index. It should be noted that, if the consumer’s change in real income or utility between the two periods under consideration is not The true cost of living index when too large, then assuming that the consumer has homothetic pre- preferences are homothetic ferences will lead to a true cost of living index which is very close to Laspeyres–Konu¨ s and Paasche–Konu¨ s true cost of living indices 17.18 Up to now, the consumer’s preference func- defined by equations (17.3) and (17.4). Another way of justifying the tion f did not have to satisfy any particular homogeneity homothetic preferences assumption is to use equation (17.49), which justifies the use of the superlative To¨ rnqvist–Theil index PT in the context of non-homothetic preferences. Since PT is usually numeri- 6 For more recent applications of the Konu¨ s method of proof, see cally close to other superlative indices that are derived using the Diewert (1983a, p. 191) for an application to the consumer context and homothetic preferences assumption, it can be seen that the assumption Diewert (1983b, pp. 1059–1061) for an application to the producer of homotheticity will usually not be empirically misleading in the context. index number context. 316 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE where c(p):C(1, p) is the unit cost function that corre- equal to the value ratio) has the following form: sponds to f.10 It can be shown that the unit cost function Pn c(p) satisfies the same regularity conditions that f 1 1 pi qi satisfies; i.e., c(p) is positive, concave and (positively) i=1 11 0 1 0 1 linearly homogeneous for positive price vectors. Sub- Q( p , p , q , q ) Pn t t 0 1 stituting equation (17.6) into equation (17.1) and using pi qi PK ( p , p , q) ut=f(qt) leads to the following equation: i=1 c( p1)f (q1) Pn t t t t = 0 0 0 1 using ð17:7Þ pi qi =c( p )f (q ) for t=0, 1 (17:7) c( p )f (q )PK ( p , p , q) i=1 twice Thus, under the linear homogeneity assumption on the c( p1)f (q1) utility function f, observed period t expenditure on the n = 0 0 1 0 using (17:8) commodities is equal to the period t unit cost c(pt)of c( p )f (q )fgc( p )=c( p ) achieving one unit of utility times the period t utility f (q1) t t = (17:9) level, f(q ). Obviously, the period t unit cost, c(p ), can f (q0) be identified as the period t price level Pt and the period t level of utility, f(qt), as the period t quantity level Qt.12 Thus, under the homothetic preferences assumption, the 17.19 The linear homogeneity assumption on the implicit quantity index that corresponds to the true cost consumer’s preference function f leads to a simplifica- of living price index c(p1)/c(p0) is the utility ratio f(q1)/ tion for the family of Konu¨ s true cost of living indices, f(q0). Since the utility function is assumed to be homo- 0 1 PK(p , p , q), defined by equation (17.2). Using this geneous of degree one, this is the natural definition for a definition for an arbitrary reference quantity vector q: quantity index.
1 17.21 In subsequent material, two additional results 0 1 C( f (q), p ) from economic theory will be needed: Wold’s Identity PK ( p , p , q) C( f (q), p0) and Shephard’s Lemma. Wold’s (1944, pp. 69–71; 1953, c( p1)f (q) p. 145) Identity is the following result. Assuming that = using (17:6) twice the consumer satisfies the cost minimization assumptions c( p0)f (q) (17.1) for periods 0 and 1 and that the utility function f is c( p1) 0 1 = (17:8) differentiable at the observed quantity vectors q and q , c( p0) it can be shown13 that the following equation holds:
Thus under the homothetic preferences assumption, the @f (qt) entire family of Konu¨ s true cost of living indices collapses pt @q 1 0 i = i for t=0, 1 and k=1, ..., n (17:10) to a single index, c(p )/c(p ), the ratio of the minimum Pn Pn @f (qt) costs of achieving unit utility level when the consumer faces pt qt qt k k k @q period 1 and 0 prices respectively. Put another way, under k=1 k=1 k the homothetic preferences assumption, P (p0, p1, q)is t K where @f(q )/@qi denotes the partial derivative of the independent of the reference quantity vector q. utility function f with respect to the ith quantity qi, 17.20 If the Konu¨ s true cost of living index defined evaluated at the period t quantity vector qt. by the right-hand side of equation (17.8) is used as the 17.22 If the homothetic preferences assumption is price index concept, then the corresponding implicit made and it is assumed that the utility function is quantity index defined using the product test (i.e., the linearly homogeneous, then Wold’s Identity can be product of the price index times the quantity index is simplified into an equation that will prove to be very useful:14 10 Economists will recognize the producer theory counterpart to the result C(u, p)=uc(p): if a producer’s production function f is subject to t t pi @f (q )=@qi constant returns to scale, then the corresponding total cost function Pn = t for t=0, 1 and k=1, ..., n (17:11) C(u, p) is equal to the product of the output level u times the unit cost t t f (q ) pkqk c(p). k=1 11 Obviously, the utility function f determines the consumer’s cost function C(u, p) as the solution to the cost minimization problem in the first line of equation (17.6). Then the unit cost function c(p) is defined 13 To prove this, consider the first-order necessary conditions for the as C(1, p). Thus f determines c. But we can also use c to determine strictly positive vector qt to solve the period t cost minimization pro- f under appropriate regularity conditions. In the economics literature, blem. The conditions of Lagrange with respect to the vector of q this is known as duality theory. For additional material on duality variables are: pt=lt !f(qt), where lt is the optimal Lagrange multi- theory and the properties of f and c, see Samuelson (1953), Shephard plier and !f(qt) is the vector of first-order partial derivatives of f (1953) and Diewert (1974a; 1993b, pp.107–123). evaluated at qt. Note that this system of equations is the price equals a 12 There is also a producer theory interpretation of the above theory; constant times marginal utility equations that are familiar to econo- i.e., let f be the producer’s (constant returns to scale) production mists. Now take the inner product of both sides of this equation with respect to the period t quantity vector qt and solve the resulting function, let p be a vector of input prices that the producer faces, let t q be an input vector and let u=f(q) be the maximum outputP that can equation for l . Substitute this solution back into the vector equation n pt=lt !f(qt) and equation (17.10) is obtained. be produced using the input vector q. C(u; p) minq f i=1 piqi: f ðqÞ ug is the producer’s cost function in this case and c(pt) can be 14 Differentiate both sides of the equation f(lq)=lf(q) with respect to t identified as the period t input price level, while f(q ) is the period t lP, and then evaluate the resulting equation at l=1. The equation n aggregate input level. i=1fi(q)qi=f (q) is obtained where fi(q):@f(q)/@qi. 317 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE
17.23 Shephard’s (1953, p. 11) Lemma is the fol- Superlative indices: The Fisher lowing result. Consider the period t cost minimization problem defined by equation (17.1). If the cost function ideal index C(u, p) is differentiable with respect to the components 17.27 Suppose the consumer has the following uti- of the price vector p, then the period t quantity vector lity function: t q is equal to the vector of first-order partial derivatives sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi of the cost function with respect to the components Pn Pn of p: f (q1, ..., qn) aikqiqk, i=1k=1 t t t @C(u , p ) qi= for i=1, ..., n and t=0, 1 (17:12) where aik=aki for all i and k (17:17) @pi Differentiating f(q) defined by equation (17.17) with 17.24 To explain why equation (17.12) holds, con- respect to q yields the following equation: sider the following argument. Because it is assumed i t that the observed period t quantity vector q solves the n t t t P cost minimization problem defined by C(u , p ), then q 2 aikqk must be feasible for this problem so it must be the case 1 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffik=1 t t t fi(q)= for i=1, ..., n that f(q )=u . Thus, q is a feasible solution for the 2 Pn Pn following cost minimization problem where the general ajkqjqk price vector p has replaced the specific period t price j=1 k=1 vector pt: Pn aikqk Pn Pn k=1 t t t = (17:18) C(u , p) minq piqi : f (q1, ..., qn) u piqi f (q) i=1 i=1 (17:13) t where fi(q):@f(q )/@qi. In order to obtain the first equation in (17.18), it is necessary to use the symmetry t where the inequality follows from the fact that q conditions, aik=aki. Now evaluate the second equation t t (q1, ..., qn) is a feasible (but usually not optimal) solu- in (17.18) at the observed period t quantity vector tion for the cost minimization problem in equation t t t q (q1, ..., qn) and divide both sides of the resulting (17.13). Now define for each strictly positive price vector equation by f(qt). The following equations are obtained: p the function g(p) as follows: Pn Pn t t t t aikqk g( p) piqi C(u , p) (17:14) fi(q ) k=1 i=1 = for t=0, 1 and i=1, ..., n (17:19) f (qt) fgf (qt) 2 where, as usual, p:(p1, ..., pn). Using equations (17.13) and (17.1), it can be seen that g(p) is minimized (over all Assume cost minimizing behaviour for the consumer in strictly positive price vectors p)atp=pt. Thus the first- periods 0 and 1. Since the utility function f defined by order necessary conditions for minimizing a differenti- equation (17.17) is linearly homogeneous and differ- able function of n variables hold, which simplify to entiable, equation (17.11) will hold. Now recall the equation (17.12). definition of the Fisher ideal quantity index, QF, defined 17.25 If the homothetic preferences assumption is earlier in Chapter 15: made and it is assumed that the utility function is linearly vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffivffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u u homogeneous, then using equation (17.6), Shephard’s u Pn u Pn Lemma (17.12) becomes: u p0q1 u p1q1 u i i u i i Q ( p0, p1, q0, q1)=u i=1 u i=1 @c( pt) F t Pn t Pn qt=ut for i=1, ..., n and t=0, 1 (17:15) p0q0 p1q0 i @p k k k k i k=1 k=1vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiu Pn Combining equations (17.15) and (17.7), the following u p1q1 Pn q1 u i i equation is obtained: = f (q0) i u i=1 i f (q0)t Pn i=1 p1q0 qt @c( pt) k k i = c( pt) for i=1, ..., n and t=0, 1 k=1 Pn @p pt qt i using equation (17:11) for t=0 k k vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi k=1 u sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,u Pn (17:16) u p1q0 Pn q1 u k k 0 i uk=1 17.26 Note the symmetry of equation (17.16) with = fi(q ) 0 t Pn i=1 f (q ) 1 1 equation (17.11). It is these two equations that will be pi qi used in subsequent material in this chapter. i=1 318 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi , 18 Pn 1 Pn 0 form) a superlative index number formula. Equation 0 qi 1 qi = fi(q ) 0 fi(q ) 1 (17.20) and the fact that the homogeneous quadratic i=1 f (q ) i=1 f (q ) function f defined by equation (17.17) is a flexible functional form show that the Fisher ideal quantity using equation (17:11) for t=1 index QF defined by equation (15.14) is a superlative sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi index number formula. Since the Fisher ideal price index Pn Pn 1 Pn Pn 0 P satisfies equation (17.21), where c(p) is the unit cost 0 qi 1 qi F = aikqk 2 aikqk 2 function that is generated by the homogeneous quad- i=1k=1 fgf (q0) i=1k=1 fgf (q1) ratic utility function, PF is also called a superlative index using equation (17:19) number formula. sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 17.30 It is possible to show that the Fisher ideal price 1 1 index is a superlative index number formula by a dif- = fgf (q0) 2 fgf (q1) 2 ferent route. Instead of starting with the assumption that the consumer’s utility function is the homogeneous using equation (17:17) and cancelling terms quadratic function defined by equation (17.17), it is f (q1) possible to start with the assumption that the consumer’s unit cost function is a homogeneous quadratic.19 Thus, = 0 (17:20) f (q ) suppose that the consumer has the following unit cost Thus under the assumption that the consumer engages function: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi in cost-minimizing behaviour during periods 0 and 1 Pn Pn and has preferences over the n commodities that corre- c( p1, ..., pn) bik pi pk spond to the utility function defined by equation (17.17), i=1 k=1 the Fisher ideal quantity index QF is exactly equal to the 15 where b =b for all i and k: (17:22) true quantity index, f (q1Þ=f ðq0). ik ki 17.28 As was noted in paragraphs 15.18 to 15.23 of Differentiating c(p) defined by equation (17.22) with Chapter 15, the price index that corresponds to the respect to pi yields the following equations: Fisher quantity index QF using the product test (15.3) is Pn the Fisher price index PF, defined by equation (15.12). Let c(p) be the unit cost function that corresponds to 2 bik pk 1 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffik=1 the homogeneous quadratic utility function f defined by ci( p)= for i=1, ..., n 2 Pn Pn equation (17.17). Then using equations (17.16) and bjk pj pk (17.20), it can be seen that j=1 k=1 Pn c( p1) 0 1 0 1 bik pk PF ( p , p , q , q )= 0 (17:21) c( p ) = k=1 (17:23) c(q) Thus, under the assumption that the consumer engages t in cost-minimizing behaviour during periods 0 and 1 where ci(p):@c(p )/@pi. In order to obtain the first and has preferences over the n commodities that corre- equation in (17.23), it is necessary to use the symmetry spond to the utility function defined by equation (17.17), conditions. Now evaluate the second equation in (17.23) t t t the Fisher ideal price index PF is exactly equal to the at the observed period t price vector p ( p , ..., p ) 1 0 1 n true price index, c(p )/c(p ). and divide both sides of the resulting equation by c(pt). 17.29 A twice continuously differentiable function The following equation is obtained: f(q)ofn variables q:(q1, ..., qn) can provide a second- Pn order approximation to another such function f *(q) t t bikpk around the point q*, if the level and all the first-order ci( p ) k=1 and second-order partial derivatives of the two func- = 2 for t=0, 1 and i=1, ..., n (17:24) c( pt) fgc( pt) tions coincide at q*. It can be shown16 that the homo- geneous quadratic function f defined by equation (17.17) As cost-minimizing behaviour for the consumer in per- can provide a second-order approximation to an arbi- iods 0 and 1 is being assumed and, since the unit cost trary f* around any (strictly positive) point q* in the function c defined by equation (17.22) is differentiable, class of linearly homogeneous functions. Thus the equations (17.16) will hold. Now recall the definition of homogeneous quadratic functional form defined by equation (17.17) is a flexible functional form.17 Diewert 18 Fisher (1922, p. 247) used the term superlative to describe the Fisher (1976, p. 117) termed an index number formula ideal price index. Thus, Diewert adopted Fisher’s terminology but 0 1 0 1 Q(p , p , q , q ) that was exactly equal to the true attempted to give some precision to Fisher’s definition of super- quantity index f(q1)/f(q0) (where f is a flexible functional lativeness. Fisher defined an index number formula to be superlative if it approximated the corresponding Fisher ideal results using his
15 data set. For the early history of this result, see Diewert (1976, p. 184). 19 16 Given the consumer’s unit cost function c(p), Diewert (1974a, p. 112) See Diewert (1976, p. 130) and let the parameter r equal 2. showed that the corresponding utility function f(q) can be defined as 17 Diewert (1974a, p. 133) introduced this term into the economics follows:P for a strictly positive quantity vector q, f (q) 1= maxp n literature. f i=1piqi:c( p)=1g. 319 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE the Fisher ideal price index, PF, given by equation function simplifies as follows: (15.12) in Chapter 15: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn Pn vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffivffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u u c( p1, ..., pn) bibkpipk u Pn u Pn u p1q0 u p1q1 i=1 k=1 u i i u i i sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 0 1 0 1 u i=1 u i=1 Pn Pn Pn PF ( p , p , q , q )=t Pn t Pn 0 0 0 1 = bipi bkpk= bipi (17:27) pkqk pkqk i=1 k=1 i=1 k=1 kv=1ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiu Pn Substituting equation (17.27) into Shephard’s Lemma u p1q1 Pn 0 i i (17.15) yields the following expressions for the period t ci( p )u = p1 u i=1 quantity vectors, qt: i c( p0)t Pn i=1 p0q1 k k t k=1 t t @c( p ) t q =u =biu i=1, ..., n; t=0, 1 (17:28) using equation (17:16) for t=0 i @p vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi i u sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,u Pn u p0q1 Thus if the consumer has the preferences that corre- Pn c ( p0) u k k spond to the unit cost function defined by equation = p1 i uk=1 i 0 t Pn (17.22) where the bik satisfy the restrictions (17.26), i=1 c( p ) 1 1 pi qi then the period 0 and 1 quantity vectors are equal i=1 0 0 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi to a multiple of the vector b:(b1, ..., bn); i.e., q = bu 1 1 Pn 0 Pn 1 and q =bu. Under these assumptions, the Fisher, ci( p ) ci( p ) = p1 p0 Paasche and Laspeyres indices, P , P and P ,all i c( p0) i c( p1) F P L i=1 i=1 coincide. Thepreferenceswhichcorrespondtothe using equation (17:16) for t=1 unit cost function defined by equation (17.27) are, sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi,sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi however, not consistent with normal consumer beha- 1 1 = viour since they imply that the consumer will not sub- fgc( p0) 2 fgc( p1) 2 stitute away from more expensive commodities to cheaper commodities if relative prices change going using equation (17:22) and cancelling terms from period 0 to 1. c( p1) = : (17:25) c( p0)
Thus, under the assumption that the consumer engages Quadratic mean of order r in cost-minimizing behaviour during periods 0 and 1 superlative indices and has preferences over the n commodities that corre- spond to the unit cost function defined by equation 17.33 It turns out that there are many other super- (17.22), the Fisher ideal price index PF is exactly equal to lative index number formulae; i.e., there exist many the true price index, c(p1)/c(p0).20 quantity indices Q(p0, p1, q0, q1) that are exactly equal 17.31 Since the homogeneous quadratic unit cost to f(q1)/f(q0) and many price indices P( p0, p1, q0, q1) that function c(p) defined by equation (17.22) is also a are exactly equal to c(p1)/c(p0), where the aggregator flexible functional form, the fact that the Fisher ideal function f or the unit cost function c is a flexible func- price index PF exactly equals the true price index tional form. Two families of superlative indices are 1 0 c(p )/c(p ) means that PF is a superlative index number defined below. formula.21 17.34 Suppose the consumer has the following 22 17.32 Suppose that the bik coefficients in equation quadratic mean of order r utility function. (17.22) satisfy the following restrictions: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn Pn r r r=2 r=2 f (q1, ..., qn) aikqi qk (17:29) bik=bibk for i, k=1, ..., n (17:26) i=1 k=1 where the n numbers bi are non-negative. In this special where the parameters aik satisfy the symmetry condi- case of equation (17.22), it can be seen that the unit cost tions aik=aki for all i and k and the parameter r satisfies the restriction r=0. Diewert (1976, p. 130) showed that the utility function f r defined by equation (17.29) is a flexible functional form; i.e., it can approximate an 20 This result was obtained by Diewert (1976, pp. 133–134). arbitrary twice continuously differentiable linearly 21 Note that it has been shown that the Fisher index PF is exact for the homogeneous functional form to the second order. Note preferences defined by equation (17.17), as well as the preferences that that when r=2, f r equals the homogeneous quadratic are dual to the unit cost function defined by equation (17.22). These function defined by equation (17.17). two classes of preferences do not coincide in general. However, if the n by n symmetric matrix A of the aik has an inverse, then it can be shown 1 22 that the n by n matrix B of the bik will equal A . The terminology is attributable to Diewert (1976, p. 129). 320 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE
Pn Pn pffiffiffiffiffiffiffiffiffi 17.35 Define the quadratic mean of order r quantity 1 1 0 0 1 r pi qi pi qi qi index Q by: i=1 i=1 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi = Pn Pn pffiffiffiffiffiffiffiffiffi Pn p0q0 p1 q0q1 r 0 1 0 r=2 i i i i i si (qi =qi ) i=1 i=1 i=1 r 0 1 0 1 Pn Pn pffiffiffiffiffiffiffiffiffi Q ( p , p , q , q ) sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi (17:30) 1 1, 1 0 1 Pn pi qi pi qi qi r s1(q1=q0)r=2 i=1 i=1 i i i =Pn Pn pffiffiffiffiffiffiffiffiffi i=1 0 0 0 0 1 pi qi pi qi qi P i=1 i=1 t t t n t t where si pi qi = k=1pkqk is the period t expenditure Pn share for commodity i as usual. 1 1 pi qi 17.36 Using exactly the same techniques as were i=1 0 1 0 1 = Pn =PW ( p , p , q , q ) (17:33) used in paragraphs 17.27 to 17.32, it can be shown that 0 0 Qr is exact for the aggregator function f r defined by pi qi i=1 equation (17.29); i.e., the following exact relationship r r between the quantity index Q and the utility function f where PW is the Walsh price index defined previously by 1* holds: equation (15.19) in Chapter 15. Thus P is equal to PW, the Walsh price index, and hence it is also a superlative f r(q1) price index. Qr( p0, p1, q0, q1)= (17:31) f r(q0) 17.39 Suppose the consumer has the following quadratic mean of order r unit cost function:24 Thus under the assumption that the consumer engages sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn Pn in cost-minimizing behaviour during periods 0 and 1 r r r=2 r=2 c ( p1, ..., pn) bikpi pk (17:34) and has preferences over the n commodities that corre- i=1k=1 spond to the utility function defined by equation (17.29), the quadratic mean of order r quantity index QF is where the parameters bik satisfy the symmetry condi- r 1 r 0 23 exactly equal to the true quantity index, f (q )/f (q ). tions bik=bki for all i and k, and the parameter r satisfies Since Qr is exact for f r and f r is a flexible functional the restriction r=0. Diewert (1976, p. 130) showed that form, it can be seen that the quadratic mean of order r the unit cost function cr defined by equation (17.34) is quantity index Qr is a superlative index for each r=0. a flexible functional form; i.e., it can approximate an Thus there is an infinite number of superlative quantity arbitrary twice continuously differentiable linearly indices. homogeneous functional form to the second order. Note 17.37 For each quantity index Qr, the product test that when r=2, cr equals the homogeneous quadratic (15.3) in Chapter 15 can be used in order to define the function defined by equation (17.22). corresponding implicit quadratic mean of order r price 17.40 Define the quadratic mean of order r price index Pr*: index Pr by: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi n P Pn 1 r=2 1 1 r pi pi qi r* 1 s0 r* 0 1 0 1 i=1 c ( p ) i 0 P ( p , p , q , q ) = r 0 1 0 1 i=1 pi Pn r* 0 P ( p , p , q , q ) sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi (17:35) 0 0 r 0 1 0 1 c ( p ) r=2 pi qi Q ( p , p , q , q ) r Pn p1 i=1 1 i si 0 i=1 pi (17:32) P where st ptqt= n pt qt is the period t expenditure where cr* is the unit cost function that corresponds to i i i k=1 k k share for commodity i as usual. the aggregator function f r defined by equation (17.29). 17.41 Using exactly the same techniques as were For each r=0, the implicit quadratic mean of order r used in paragraphs 17.27 to 17.32, it can be shown that price index Pr* is also a superlative index. Pr is exact for the aggregator function defined by 17.38 When r=2, Qr defined by equation (17.30) equation (17.34); i.e., the following exact relationship simplifies to Q , the Fisher ideal quantity index, and Pr* F between the index number formula Pr and the unit cost defined by equation (17.32) simplifies to P , the Fisher F function cr holds: ideal price index. When r=1, Qr defined by equation (17.30) simplifies to: cr( p1) Pr( p0, p1, q0, q1)= (17:36) sffiffiffiffiffi sffiffiffiffiffi cr( p0) Pn 1 n Pn 1 qi P qi s0 p1q1 p0q0 Thus, under the assumption that the consumer engages i q0 i i i i q0 1 0 1 0 1 i=1 sffiffiffiffiffii i=1 i=1 sffiffiffiffiffii in cost-minimizing behaviour during periods 0 and 1, Q ( p , p , q , q ) =Pn Pn q0 0 0 Pn q0 and has preferences over the n commodities that cor- 1 i pi qi 1 1 i si 1 i=1 pi qi 1 respond to the unit cost function defined by equation i=1 qi i=1 qi 24 This terminology is attributable to Diewert (1976, p. 130), this unit 23 See Diewert (1976, p. 130). cost function being first defined by Denny (1974). 321 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE
(17.34), the quadratic mean of order r price index PF is Superlative indices: exactly equal to the true price index, cr(p1)/cr(p0).25 Since Pr is exact for cr and cr is a flexible functional The To¨ rnqvist index form, it can be seen that the quadratic mean of order r 17.44 In this section, the same assumptions that price index Pr is a superlative index for each r=0. were made on the consumer in paragraphs 17.9 to 17.17 Thus there are an infinite number of superlative price are made here. In particular, it is not assumed that the indices. consumer’s utility function f is necessarily linearly 17.42 For each price index Pr, the product test (15.3) homogeneous as in paragraphs 17.18 to 17.43. in Chapter 15 can be used in order to define the corre- 17.45 Before the main result is derived, a pre- sponding implicit quadratic mean of order r quantity liminary result is required. Suppose the function of n r index Q *: variables, f(z1, ..., zn):f(z), is quadratic; i.e., Pn 1 Pn Pn Pn 1 1 f (z1, ..., zn) a0+ aizi+ aikzizk pi qi r* 1 i=1 2 i=1k=1 r* 0 1 0 1 i=1 f ( p ) Q ( p , p , q , q ) Pn = r* 0 and aik=aki for all i and k (17:39) 0 0 r 0 1 0 1 f ( p ) pi qi P ( p , p , q , q ) i=1 where the ai and the aik are constants. Let fi(z) denote (17:37) the first-order partial derivative of f evaluated at z with respect to the ith component of z, zi. Let fik(z) denote the second-order partial derivative of f with where f r* is the aggregator function that corresponds r respect to zi and zk. Then it is well known that the sec- to the unit cost function c defined by equation ond-order Taylor series approximation to a quadratic (17.34).26 For each r=0, the implicit quadratic mean r function is exact; i.e., if f is defined by equation (17.39), of order r quantity index Q * is also a superlative then for any two points, z0 and z1, the following equa- index. tion holds: 17.43 When r=2, Pr defined by equation (17.35) r Pn ÈÉ simplifies to PF, the Fisher ideal price index, and Q * 1 0 0 1 0 f (z ) f (z )= fi(z ) z z defined by equation (17.37) simplifies to QF, the Fisher i i r i=1 ideal quantity index. When r=1, P defined by equation Pn Pn ÈÉÈÉ 1 0 1 0 1 0 (17.35) simplifies to: + fik(z ) zi zi zk zk (17:40) 2 i=1k=1 sffiffiffiffiffi sffiffiffiffiffi It is less well known that an average of two first-order Pn p1 Pn Pn p1 s0 i 1 1 p0q0 i Taylor series approximations to a quadratic function is i 0 pi qi i i 0 i=1 pi i=1 i=1 pi also exact; i.e., if f is defined by equation (17.39) above, P1( p0, p1, q0, q1) sffiffiffiffiffi = sffiffiffiffiffi Pn then for any two points, z0 and z1, the following equa- Pn p0 0 0 Pn p0 1 i pi qi 1 1 i tion holds:27 si 1 i=1 pi qi 1 i=1 pi i=1 pi 1 Pn ÈÉÈÉ Pn Pn pffiffiffiffiffiffiffiffiffi 1 0 0 1 1 0 1 1 0 0 1 f (z ) f (z )= fi(z )+fi(z ) zi zi (17:41) pi qi qi pi pi 2 i=1 = i=1 i=1 Pn Pn pffiffiffiffiffiffiffiffiffi Diewert (1976, p. 118) and Lau (1979) showed that 0 0 1 0 1 pi qi qi pi pi equation (17.41) characterized a quadratic function and i=1 i=1 called the equation the quadratic approximation lemma. Pn Pn pffiffiffiffiffiffiffiffiffi 1 1, 1 0 1 In this chapter, equation (17.41) will be called the pi qi qi pi pi i=1 i=1 quadratic identity. =Pn Pn pffiffiffiffiffiffiffiffiffi 17.46 Suppose that the consumer’s cost func- 0 0 0 0 1 28 pi qi qi pi pi tion C(u, p), has the following translog functional i=1 i=1 form:29 Pn 1 1 pi qi Pn 1 Pn Pn i=1 C u p a a p a p p b u = =Q ( p0, p1, q0, q1) (17:38) ln ( , ) 0+ i ln i+ ik ln i ln k+ 0 ln Pn W i=1 2 i=1k=1 0 0 p q Pn i i 1 2 i=1 + bi ln pi ln u+ b00(lnu) (17:42) i=1 2 where QW is the Walsh quantity index defined pre- where ln is the natural logarithm function and the 1* viously in footnote 30 of Chapter 15. Thus Q is equal parameters ai, aik, and bi satisfy the following to QW, the Walsh quantity index, and hence it is also a superlative quantity index. 27 The proof of this and the foregoing relation is by straightforward verification. 25 See Diewert (1976, pp. 133–134). 28 The consumer’s cost function was defined by equation (17.6) above. 26 r* r 29 The functionP f can be defined by using c as follows: f r*(q) Christensen, Jorgenson and Lau (1971) introduced this function into n r 1= maxp f i=1 piqi:c ( p)=1g. the economics literature. 322 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE restrictions: the following equation is obtained: Pn Pn Pn ln C(u*, p1) ln C(u*, p0) aik=aki, ai=1, bi=0 and aik=0 i=1 i=1 k=1 Pn * 0 * 1 ÈÉ 1 @ ln C(u , p ) @ ln C(u , p ) 1 0 for i, k=1, ..., n (17:43) = + ln pi ln pi 2 @ ln pi @ ln pi i=1 These parameter restrictions ensure that C(u, p) defined 1 Pn Pn by equation (17.42) is linearly homogeneous in p,a = a + a ln p0+b ln u*+a 2 i ik k i i property that a cost function must have. It can be shown i=1 k=1 Pn ÀÁ that the translog cost function defined by equation 1 * 1 0 (17.42) can provide a second-order Taylor series approx- + aik ln pk+bi ln u ln pi ln pi imation to an arbitrary cost function.30 k=1 Pn Pn pffiffiffiffiffiffiffiffiffi 17.47 Assume that the consumer has preferences 1 0 0 1 = ai+ aik ln pk+bi ln u u +ai that correspond to the translog cost function and that 2 i=1 k=1 the consumer engages in cost-minimizing behaviour 0 1 Pn pffiffiffiffiffiffiffiffiffi ÀÁ during periods 0 and 1. Let p and p be the period 0 and 1 0 1 1 0 + aik ln p +bi ln u u ln p ln p 0 1 k i i 1 observed price vectors, and let q and q be the period k=1 0 and 1 observed quantity vectors. These assumptions Pn Pn 1 0 0 imply: = ai+ aik ln pk+bi ln u +ai 2 i=1 k=1 Pn Pn 0 0 0 0 1 1 1 1 Pn ÀÁ C(u , p )= pi qi and C(u , p )= pi qi (17:44) 1 1 1 0 i=1 i=1 + aik ln pk+bi ln u ln pi ln pi k=1 where C is the translog cost function defined above. Pn C u0 p0 C u1 p1 ÀÁ Now apply Shephard’s Lemma, equation (17.12), and 1 @ ln ( , ) @ ln ( , ) 1 0 = + ln pi ln pi the following equation results: 2 i=1 @ ln pi @ ln pi Pn ÀÁÀÁ @C(ut, pt) 1 0 1 1 0 qt= for i=1, ..., n and t=0, 1 = si +si ln pi ln pi using equation (17:47): i 2 i=1 @pi C(ut, pt) @ ln C(ut, pt) (17:49) = (17:45) pt @ ln p i i The last equation in (17.49) can be recognized as the Now use equation (17.44) to replace C(ut, pt) in equation logarithm of the To¨ rnqvist–Theil index number formula (17.45). After some cross multiplication, this becomes PT, defined earlier by equation (15.81) in Chapter 15. the following: Hence, exponentiating both sides of equation (17.49) yields the following equality between the true cost t t t t pi qi t @ ln C(u , p ) of living between periods 0 and 1, evaluated at the Pn si = t t @ ln pi intermediate utility level u* and the observable pkqk 31 k=1 To¨ rnqvist–Theil index PT: for i=1, ..., n and t=0, 1 (17:46) * 1 C(u , p ) 0 1 0 1 =PT ( p , p , q , q ) (17:50) or Cðu*, p0) Pn Since the translog cost function which appears on the t t t si =ai+ aik ln pk+bi ln u for i=1, ..., n and t=0, 1 left-hand side of equation (17.49) is a flexible functional k=1 form, the To¨ rnqvist–Theil price index PT is also a (17:47) superlative index. t 17.49 It is somewhat mysterious how a ratio of where si is the period t expenditure share on commodity i. 17.48 Define the geometric average of the period 0 unobservable cost functions of the form appearing on and 1 utility levels as u*; i.e., define the left-hand side of the above equation can be exactly pffiffiffiffiffiffiffiffiffi estimated by an observable index number formula. The u* u0u1 (17:48) key to this mystery is the assumption of cost-minimizing behaviour and the quadratic identity (17.41), along Now observe that the right-hand side of the equation with the fact that derivatives of cost functions are that defines the natural logarithm of the translog cost equal to quantities, as specified by Shephard’s Lemma. function, equation (17.42), is a quadratic function of the In fact, all the exact index number results derived in variables zi:lnpi if utility is held constant at the level u*. paragraphs 17.27 to 17.43 can be derived using trans- Hence the quadratic identity (17.41) can be applied, and formations of the quadratic identity along with Shep- hard’s Lemma (or Wold’s Identity).32 Fortunately, 30 It can also be shown that, if all the bi=0 and b00=0, then for most empirical applications, assuming that the C(u, p)=uC(1, p):uc(p); i.e., with these additional restrictions on the parameters of the general translog cost function, homothetic pref- 31 erences are the result of these restrictions. Note that it is also assumed This result is attributable to Diewert (1976, p. 122). that utility u is scaled so that u is always positive. 32 See Diewert (2002a). 323 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE
0 1 0 1 r 0 1 0 1 consumer has (transformed) quadratic preferences will @PT ( p , p , q , q ) @P ( p , p , q , q ) be an adequate assumption, so the results presented in t = t @qi @qi paragraphs 17.27 to 17.49 are quite useful to index s* 0 1 0 1 number practitioners who are willing to adopt the eco- @P ( p , p , q , q ) 33 = t nomic approach to index number theory. Essentially, @qi the economic approach to index number theory provides for i=1, ..., n and t=0, 1 (17:53) a strong justification for the use of the Fisher price index PF defined by equation (15.12), the To¨ rnqvist–Theil price index PT defined by equation (15.81), the implicit 2 0 1 0 1 2 r 0 1 0 1 quadratic mean of order r price indices Pr* defined by @ PT ( p , p , q , q ) @ P ( p , p , q , q ) t t = t t equation (17.32) (when r=1, this index is the Walsh price @pi @pk @pi @pk index defined by equation (15.19) in Chapter 15) and the 2 s* 0 1 0 1 r @ P ( p , p , q , q ) quadratic mean of order r price indices P defined by = t t equation (17.35). In the next section, we ask if it matters @pi @pk which one of these formulae is chosen as ‘‘best’’. for i, k=1, ..., n and t=0, 1 (17:54)
@2P ( p0, p1, q0, q1) @2Pr( p0, p1, q0, q1) The approximation properties of T = @pt@qt @pt@qt superlative indices i k i k @2Ps* ( p0, p1, q0, q1) 17.50 The results of paragraphs 17.27 to 17.49 pro- = t t vide price statisticians with a large number of index @pi @qk number formulae which appear to be equally good from for i, k=1, ..., n and t=0, 1 (17:55) the viewpoint of the economic approach to index num- ber theory. Two questions arise as a consequence of these results: 2 0 1 0 1 2 r 0 1 0 1 @ PT ( p , p , q , q ) @ P ( p , p , q , q ) Does it matter which of these formulae is chosen? = @qt@qt @qt@qt If it does matter, which formula should be chosen? i k i k 2 s* 0 1 0 1 17.51 With respect to the first question, Diewert @ P ( p , p , q , q ) = t t (1978, p. 888) showed that all of the superlative index @qi @qk number formulae listed in paragraphs 17.27 to 17.49 for i, k=1, ..., n for t=0, 1 (17:56) approximate each other to the second order around any point where the two price vectors, p0 and p1, are equal 0 1 where the To¨ rnqvist–Theil price index PT is defined and where the two quantity vectors, q and q , are equal. by equation (15.81), the implicit quadratic mean of In particular, this means that the following equalities are s* 0 1 order r price indices P is defined by equation (17.32) valid for all r and s not equal to 0, provided that p =p r 0 1 34 and the quadratic mean of order r price indices P is and q =q . defined by equation (17.35). Using the results in the P ( p0, p1, q0, q1)=Pr( p0, p1, q0, q1)=Ps*( p0, p1, q0, q1) previous paragraph, Diewert (1978, p. 884) concluded T that ‘‘all superlative indices closely approximate each (17:51) 0 1 0 1 r 0 1 0 1 other’’. @PT ( p , p , q , q ) @P ( p , p , q , q ) 17.52 The above conclusion is, however, not true t = t @pi @pi even though the equations (17.51) to (17.56) are true. @Ps*( p0, p1, q0, q1) The problem is that the quadratic mean of order r price = indices P r and the implicit quadratic mean of order s @pt i price indices P s* are (continuous) functions of the para- for i=1, ..., n and t=0, 1 (17:52) meters r and s respectively. Hence, as r and s become very large in magnitude, the indices P r and P s* can differ substantially from, say, P2=P , the Fisher ideal 33 F If, however, consumer preferences are non-homothetic and the index. In fact, using definition (17.35) and the limiting change in utility is substantial between the two situations being com- properties of means of order r,35 Robert Hill (2002, p. 7) pared, then it may be desirable to compute separately the Laspeyres– r Konu¨ s and Paasche–Konu¨ s true cost of living indices defined by showed that P has the following limit as r approaches equations (17.3) and (17.4), C(u0, p1)/C(u0, p0) and C(u1, p1)/C(u1, p0), plus or minus infinity: respectively. In order to do this, it would be necessary to use econo- metrics and estimate empirically the consumer’s cost or expenditure lim Pr( p0, p1, q0, q1)= lim Pr( p0, p1, q0, q1) function. r!+1 r! 1 34 To prove the equalities in equations (17.51) to (17.56), simply dif- sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ferentiate the various index number formulae and evaluate the deri- p1 p1 0 1 0 1 i i vatives at p =p and q =q . Actually, equations (17.51) to (17.56) are = mini 0 maxi 0 (17:57) still true provided that p1=lp0 and q1=mq0 for any numbers l>0 and pi pi m>0; i.e., provided that the period 1 price vector is proportional to the period 0 price vector and that the period 1 quantity vector is pro- portional to the period 0 quantity vector. 35 See Hardy, Littlewood and Po´ lya (1934). 324 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE
Using Hill’s method of analysis, it can be shown that the spective, as well as from the stochastic viewpoint, and implicit quadratic mean of order r price index has the the Walsh index PW defined by equation (15.19) (which following limit as r approaches plus or minus infinity: is equal to the implicit quadratic mean of order r price indices Pr* defined by equation (17.32) when r=1) lim Pr*( p0, p1, q0, q1)= lim Pr*( p0, p1, q0, q1,) seems to be best from the viewpoint of the ‘‘pure’’ price r!+1 r! 1 index. The results presented in this section indicate that Pn p1q1 for ‘‘normal’’ time series data, these three indices will i i give virtually the same answer. To determine precisely sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffii=1 = which one of these three indices to use as a theoretical Pn 1 1 0 0 pi pi target or actual index, the statistical agency will have to pi qi mini 0 maxi 0 i=1 pi pi decide which approach to bilateral index number theory is most consistent with its goals. For most practical (17:58) purposes, however, it will not matter which of these three indices is chosen as a theoretical target index for Thus for r large in magnitude, P r and P r* can differ 1 1* making price comparisons between two periods. substantially from PT, P , P =PW (the Walsh price 2 2* 36 index) and P =P =PF (the Fisher ideal index). 17.53 Although Hill’s theoretical and empirical results demonstrate conclusively that not all superlative Superlative indices and indices will necessarily closely approximate each other, two-stage aggregation there is still the question of how well the more commonly 17.55 Most statistical agencies use the Laspeyres used superlative indices will approximate each other. All formula to aggregate prices in two stages. At the first the commonly used superlative indices, P r and P r*, fall 37 stage of aggregation, the Laspeyres formula is used to into the interval 0 r 2. Hill (2002, p. 16) summar- aggregate components of the overall index (e.g., food, ized how far apart the To¨ rnqvist and Fisher indices were, clothing, services); then at the second stage of aggrega- making all possible bilateral comparisons between any tion, these component sub-indices are further combined two data points for his time series data set as follows: into the overall index. The following question then The superlative spread S(0, 2) is also of interest since, naturally arises: does the index computed in two stages in practice, To¨ rnqvist (r=0) and Fisher (r=2) are by far coincide with the index computed in a single stage? the two most widely used superlative indexes. In all 153 Initially, this question is addressed in the context of the bilateral comparisons, S(0, 2) is less than the Paasche– Laspeyres formula.39 Laspeyres spread and on average, the superlative spread 17.56 Suppose that the price and quantity data for is only 0.1 per cent. It is because attention, until now, has t t focussed almost exclusively on superlative indexes in the period t, p and q , can be written in terms of M sub- range 0 r 2 that a general misperception has persisted vectors as follows:
in the index number literature that all superlative indexes t t1 t2 tM t t1 t2 tM approximate each other closely. p =( p , p , ..., p ) and q =(q , q , ..., q ) Thus, for Hill’s time series data set covering 64 com- for t=0, 1 (17:59) ponents of United States gross domestic product from where the dimensionality of the subvectors ptm and qtm is 1977 to 1994 and making all possible bilateral compar- N for m=1, 2, ..., M with the sum of the dimensions isons between any two years, the Fisher and To¨ rnqvist m N equal to n. These subvectors correspond to the price price indices differed by only 0.1 per cent on average. m and quantity data for subcomponents of the consumer This close correspondence is consistent with the results price index for period t. Now construct sub-indices for of other empirical studies using annual time series each of these components going from period 0 to 1. For data.38 Additional evidence on this topic may be found the base period, set the price for each of these sub- in Chapter 19. components, say P 0 for m=1, 2, ...M, equal to 1 and set 17.54 In the earlier chapters of this manual, it is m the corresponding base period subcomponent quantities, found that several index number formulae seem ‘‘best’’ say Q0 for m=1, 2, ..., M, equal to the base period value when viewed from various perspectives. Thus the Fisher m of consumption for that subcomponent for m= ideal index P =P2=P2* defined by equation (15.12) F 1, 2, ..., M: seemed to be best from one axiomatic viewpoint, the To¨ rnqvist–Theil price index P defined by equation PNm T 0 0 0m 0m (15.81) seems to be best from another axiomatic per- Pm 1 and Qm pi qi for m=1, 2, ..., M i=1
36 Hill (2002) documents this for two data sets. His time series data (17:60) consist of annual expenditure and quantity data for 64 components of Now use the Laspeyres formula in order to construct United States gross domestic product from 1977 to 1994. For this data 1 set, Hill (2002, p. 16) found that ‘‘superlative indexes can differ by a period 1 price for each subcomponent, say Pm for more than a factor of two (i.e., by more than 100 per cent), even m=1, 2, ..., M, of the CPI. Since the dimensionality of though Fisher and To¨ rnqvist never differ by more than 0.6 per cent’’. 37 Diewert (1980, p. 451) showed that the To¨ rnqvist index PT is a 39 r Much of the material in this section is adapted from Diewert (1978) limiting case of P ,asr tends to 0. and Alterman, Diewert and Feenstra (1999). See also Balk (1996b) for 38 See, for example, Diewert (1978, p. 894) or Fisher (1922), which is a discussion of alternative definitions for the two-stage aggregation reproduced in Diewert (1976, p. 135). concept and references to the literature on this topic. 325 CONSUMER PRICE INDEX MANUAL: THEORY AND PRACTICE the subcomponent vectors, ptm and qtm , differs from the index calculated in two stages equals the Laspeyres dimensionality of the complete period t vectors of prices index calculated in one stage. and quantities, pt and qt, it is necessary to use different 17.57 Now suppose that the Fisher or To¨ rnqvist symbols for these subcomponent Laspeyres indices, say formula is used at each stage of the aggregation. That is, m PL for m=1, 2, ..., M. Thus the period 1 subcomponent in equation (17.61), suppose that the Laspeyres formula m 0m 1m 0m 1m prices are defined as follows: PL ( p , p , q , q ) is replaced by the Fisher formula m 0m 1m 0m 1m m PF ( p , p , q , q ) or by the To¨ rnqvist formula PT PNm 0m 1m 0m 1m 1m 0m ( p , p , q , q ); and in equation (17.65), suppose pi qi * 0 1 0 1 * * 1 m 0m 1m 0m 1m i=1 that PL(P , P , Q , Q ) is replaced by PF (or by PT )and Pm PL ( p , p , q , q ) 0 1 0 1 PNm PL (p , p , q , q ) is replaced by PF (or by PT). Then is it 0m 0m pi qi the case that counterparts are obtained to the two- i=1 stage aggregation result for the Laspeyres formula, for m=1, 2, ..., M (17:61) equation (17.65)? The answer is no; it can be shown that, in general, Once the period 1 prices for the M sub-indices have been defined by equation (17.61), then corresponding sub- P* (P0, P1, Q0, Q1) 6¼ P ( p0, p1, q0, q1)and component period 1 quantities Q1 for m=1, 2, ..., M F F m * 0 1 0 1 0 1 0 1 can beP defined by deflating the period 1 subcomponent PT (P , P , Q , Q ) 6¼ PT ( p , p , q , q ) (17:66) values Nm p1m q1m by the prices P1 i=1 i i m Similarly, it can be shown that the quadratic mean of PNm r 1m 1m order r index number formula P defined by equation pi qi (17.35) and the implicit quadratic mean of order r index i=1 Q1 for m=1, 2, ..., M (17:62) number formula Pr* defined by equation (17.32) are also m P1 m not consistent in aggregation. Now define subcomponent price and quantity vectors 17.58 Nevertheless, even though the Fisher and for each period t=0,1 using equations (17.60) to (17.62). To¨ rnqvist formulae are not exactly consistent in Thus define the period 0 and 1 subcomponent price aggregation, it can be shown that these formulae are vectors P0 and P1 as follows: approximately consistent in aggregation. More specifi- cally, it can be shown that the two-stage Fisher formula P0=(P0, P0, ..., P0 ) 1 and P1=(P1, P1, ..., P1 ) * 1 2 M M 1 2 M PF and the single-stage Fisher formula PF in the in- (17:63) equality (17.66), both regarded as functions of the 4n variables in the vectors p0, p1, q0, q1, approximate each where 1M denotes a vector of ones of dimension M and 1 other to the second order around a point where the two the components of P are defined by equation (17.61). price vectors are equal (so that p0=p1) and where the The period 0 and 1 subcomponent quantity vectors Q0 0 1 1 two quantity vectors are equal (so that q =q ), and a and Q are defined as follows: similar result holds for the two-stage and single-stage To¨ rnqvist indices in equation (17.66).40 As was seen in Q0=(Q0, Q0, ..., Q0 )andQ1=(Q1, Q1, ..., Q1 ) 1 2 M 1 2 M the previous section, the single-stage Fisher and (17:64) To¨ rnqvist indices have a similar approximation prop- where the components of Q0 are defined in equation erty, so all four indices in the inequality (17.66) approx- (17.60) and the components of Q1 are defined by equa- imate each other to the second order around an equal tion (17.62). The price and quantity vectors in equations (or proportional) price and quantity point. Thus for (17.63) and (17.64) represent the results of the first-stage normal time series data, single-stage and two-stage aggregation. Now use these vectors as inputs into Fisher and To¨ rnqvist indices will usually be numerically very close. This result is illustrated in Chapter 19 for an the second-stage aggregation problem; i.e., apply the 41 Laspeyres price index formula, using the information in artificial data set. equations (17.63) and (17.64) as inputs into the index 17.59 Similar approximate consistency in aggrega- number formula. Since the price and quantity vectors tion results (to the results for the Fisher and To¨ rnqvist formulae explained in the previous paragraph) can be that are inputs into this second-stage aggregation pro- r blem have dimension M instead of the single-stage for- derived for the quadratic mean of order r indices, P , and for the implicit quadratic mean of order r indices, mula which utilized vectors of dimension n, a different r symbol is required for the new Laspeyres index: this is P *; see Diewert (1978, p. 889). Nevertheless, the results * of Hill (2002) again imply that the second-order chosen to be PL. Thus the Laspeyres price index com- * 0 1 0 1 puted in two stages can be denoted as PL(P , P , Q , Q ). Now ask whether this two-stage Laspeyres index equals 40 See Diewert (1978, p. 889). In other words, a string of equalities the corresponding single-stage index P that was studied similar to equations (17.51) to (17.56) holds between the two-stage L indices and their single-stage counterparts. In fact, these equalities are in the previous sections of this chapter; i.e., ask whether still true provided that p1=l p0 and q1=mq0 for any numbers l>0 and m>0. * 0 1 0 1 0 1 0 1 PL(P , P , Q , Q )=PL( p , p , q , q ): (17:65) 41 For an empirical comparison of the four indices, see Diewert (1978, pp. 894–895). For the Canadian consumer data considered there, the If the Laspeyres formula is used at each stage of each chained two-stage Fisher in 1971 was 2.3228 and the corresponding aggregation, the answer to the above question is yes: chained two-stage To¨ rnqvist was 2.3230, the same values as for the straightforward calculations show that the Laspeyres corresponding single-stage indices. 326 THE ECONOMIC APPROACH TO INDEX NUMBER THEORY: THE SINGLE-HOUSEHOLD CASE approximation property of the single-stage quadratic 17.62 In this section, the same assumptions about mean of order r index Pr to its two-stage counterpart the consumer are made that were made in paragraphs will break down as r approaches either plus or minus 17.18 to 17.26 above. In particular, it is assumed that the infinity. To see this, consider a simple example where consumer’s utility function f(q) is linearly homo- there are only four commodities in total. Let the first geneous43 and the corresponding unit cost function is 1 0 price ratio p1=p1 be equal to the positive number a, let c(p). It is supposed that the unit cost function has the 1 0 the second two price ratios pi =pi equal b and let the last following functional form: price ratio p1=p0 equal c, where we assume a