The Determinants of Pricing Behaviour: A Study of the Canadian Cotton Textile Industry

The Determinants of Pricing Behaviour: A Study of the Canadian Cotton Textile IndustryAuthor(s): D. G. McFetridgeSource: The Journal of Industrial Economics, Vol. 22, No. 2 (Dec., 1973), pp. 141-152Published by: WileyStable URL: http://www.jstor.org/stable/2098125 .

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THE DETERMINANTS OF PRICING BEHAVIOUR: A STUDY OF THE CANADIAN COTTON

TEXTILE INDUSTRY

by D. G. McFETRIDGE*

I. INTRODUCTION

BEGINNING with the studies of Hall and Hitch (I939, PP. 12-45), the factors determining the behaviour of industrial prices have been the subject of extensive empirical investigation and debate among economists. Reacting to the assertion by Hall and Hitch that

(Prices) will be changed if there is a significant change in wage or raw materials costs but not in response to moderate or temporary shifts in demand'

economists have sought to discover whether prices respond to excess or deficient demand in the product market, ceteris paribus, and if so, in what direction.2

In the course of this debate other issues have been raised which also merit investigation. First, it has been argued that the relationship between demand and the rate of price change is asymmetric.3 It is asserted that while prices may rise relative to costs during periods of excess demand, there will not be a corresponding decrease during periods of deficient demand. Yordon (I96I, pp. 291-3) has observed a similar relationship between the cost of materials and the price of output. Eckstein (I964, P. 279) has called this the 'materials ratchet'. Eckstein (I964, PP. 276-7) has also suggested that the relationship between demand disequilibrium and the rate of price change may be subject to a threshold effect. Relatively small discrepancies between demand and output will not induce price changes. Increases in this discrepancy will ultimately result in more than proportional increase in the absolute value of the rate of price change. If this is the case, the relationship between demand disequilibrium and the rate of price change will be distinctly nonlinear.

Second, some investigators (Kaplan et al., 1958) have suggested that firms

* The helpful comments of Professors G. V. Jump and T. A. Wilson are gratefully ack- nowledged. The author retains full responsibility for the contents of the paper. I Hall and Hitch (I939, p. 33).

2 The prevalence of competitive forces would imply that prices fall relative to costs during the periods of deficient demand and rise during periods of excess demand while Eckstein and Fromm (I968, pp. i i59-83) have suggested that firms practising target return pricing may raise prices during the periods of deficient demand in order to maintain some target total profit.

3 Schultze (i959), see also Eckstein (i964, p. 279).

'4'



142 D. G. MCFETRIDGE

rely on 'normal' costs which are purged of cyclical influences, rather than actual costs, as a basis for the pricing decision. Others have argued that the use of normal costs is a characteristic of target return pricing which is itself confined to oligopolistic industries (Eckstein and Fromm, I 968, p. I i 66).

Third, since a change in labour cost exerts an immediate effect on the cost of output and may also serve as a signal to other firms to change prices, Rippe (1970, p. 40) has argued that labour cost will exert an effect on price which is out of proportion to its share in the value of output.

In recent years investigators have turned from questionnaires and inter- views to econometric price equations in their efforts to examine these issues. Price equations have been applied largely to aggregated data (Neild, 1963; Eckstein and Fromm, I968; Godley and Nordhaus, I972) although industry price equations have begun to appear (McCallum, I969; Moffatt, 1970; Rippe, 1970). Since pricing behaviour varies from industry to industry, resolution of the issues raised above requires investigation at the industry level.

This study employs an econometric price adjustment equation to examine the determinants of quarter to quarter price changes in the Canadian cotton textile industry during the period I958-69. Analysis of the determinants of price change in this industry is particularly rewarding for a number of reasons. First, the cotton textile industry is representative of a large proportion of the Canadian manufacturing sector. It is a tight oligopoly. The largest eight firms account for 95% of industry shipments. It produces a commodity, which is widely traded internationally, within the shelter of high effective tariff rates (38%) .4 Second, the data required for a satisfactory investigation of all the relevant issues are available and are reliable which is relatively uncommon at this level of disaggregation. Third, there is some variation in the industry selling price. A virtual absence of variation in reported prices is not uncommon at this level of disaggregation. In this case the econometric approach is unproductive. This is not true of the Canadian cotton textile industry.

Finally, the model is completely general and can be applied to other industries as reliable data become available.

The next section of this paper contains the derivation of models which facilitate the examination of the issues raised above and the testing of related hypotheses. Empirical results are reported and their implications discussed in the final section of the paper.

II. THE MODEL

Beginning with a simple mark-up equation5 4 For industry concentration ratios see Department of Consumer and Corporate Affairs

(1970, pp. 56-7I). For rates of effective tariff protection see Wilkinson and Melvin (I968, p. 22).

s If unit costs are constant and M = ele + I where e is equal to the price elasticity of demand for the industry's output, expression (i) is also the profit maximizing identity.



PRICING BEHAVIOUR 143

(1) P = M(ULC+ UMC) M>1

where P = the industry selling price M = the mark-up factor

ULC = unit labour cost UMC = unit materials cost,

take the total differential, divide by P and collect the terms to obtain

dP ULC dULC UMC dUMC dM (2) = M. +M. p U + M P ULC P UMC M

Expressing (2) in discrete terms but omitting time subscripts yields

AP AULC AUMC AM (3) p aULC +a2 UMC +a3

Full adjustment of prices to cost changes implies that

a, +a2= 1 a1 = ULC/(ULC + UMC) a2 = UMC/(ULC + UMC).

If the mark-up factor is increased during periods of excess demand and de- creased during periods of deficient demand, then

(4) AM = kXD+ Y k1 >0

where XD = excess demand in the product market

V = a random error term.

Substituting (4) into (3) yields

A AULC A Mc (5) p = a1 ULC + a2 UMC +a3k,XD+ '

where V' is the error term obtained on the assumption that both (3) and (4) are stochastic equations.

Equation (5) can be used to test the basic Hall and Hitch hypothesis. If the estimated value of a3k1 is not significantly different from zero one must infer that the industry mark-up is not altered in response to product market demand conditions. Before this test can be conducted, however, excess demand must be expressed in terms of observable variables.

Excess demand is the discrepancy between the quantity demanded and the output of the industry. In an industry which produces purely to order, excess demand at any point in time is the sum of past deviations between new orders and shipments. This is the same as the backlog of unfilled orders. The firms



I44 D. G. MCFETRIDGE

involved may consider some positive order backlog to be desirable.6 In this case excess demand is equal to the deviation between the actual and desired order backlogs. Thus, in an industry producing purely to order

(6) XDt= Ut

or

(6a) XDt = (Ut- t)

where U =the unfilled order backlog at the end of quarter t, and U* = the unfilled order backlog desired by firms at the end of quarter

t. If U* is constant, (6) and (6a) can be used interchangeably in the model.

In an industry which produces purely to stock, excess demand can be expressed as the deviation between desired and actual finished goods inventory. That is, the discrepancy between actual inventory holdings and the inventory level which firms consider necessary reflects the extent to which, in past periods, demand has exceeded production and been satisfied partially from inventory.7 Thus, in an industry producing purely to stock

(7) XDt = (I* - It)

where I* = the finished goods inventory which firms desire to hold at the end of quarter t,

It = the finished goods inventory actually held by firms at the end of quarter t.

Since the cotton textile industry produces both to stock and to order, demand disequilibrium will manifest itself through disequilibria in both unfilled order backlogs and finished goods inventories.

Both U* and I* are unobservable. Values of both U* and I* can, however be generated under a number of alternative assumptions. To obtain U* assume that the firms in this industry wish to maintain a constant ratio of unfilled orders to shipments. Assume in addition that the ratio desired is equal to the average unfilled orders: shipments ratio prevailing over the sample period. Then (Ut - U*) is equal to [Ut/St - (U7)].

The alternative methods of generating I* has been discussed by Courchene (1969, pp. 315-36) and by McFetridge (I972, pp. 42-7). In this study it is simply assumed that the firms involved desire to maintain finished goods inventories equal to a constant fraction of their current shipments. If one assumes that this desired fraction is equal to the average inventory: shipments ratio prevailing over the sample period (I* -I) can be written as - [ItSt- (7S)].

Demand disequilibrium variables [Ut/St - (T1)] and - [It/St - (1/)] can 6 The implications of this are discussed in Hay (1970, pp. 531-45). ' A more formal discussion of the relationship between demand and inventory disequilibria

is given in McFetridge (1972, pp. 42-7).




either be substituted directly into expression (4) or, provided one allows for the existence of a constant term, be replaced in expression (4) by UIS, and It/st.

Adopting the latter alternative (and omitting time subscripts) one obtains

(4a) AM = dl(U/S)+d2(I/S)+d3+V d1>O, d2<O.

Substitution of (4a) into (3) yields

AP AULC AUMC (8) p = a1 ULC +a2 UMC +a3d,(U/S)+a3d2(I/S)+a3d3+V'

which will henceforth be referred to as model (8). The hypothesis that prices rise relative to costs during periods of excess

demand but do not fall correspondingly during periods of deficient demand may be tested by dichotomizing demand disequilibrium into excess and deficient demand. Thus, the unfilled order backlog becomes [UI/S- (UIS) P which equals the positive deviation of the unfilled orders: shipments ratio from its period mean when such deviations occur and zero otherwise and [UtSt - (JS)]N which is equal either to the negative deviation from the mean or zero. Inventory disequilibrium is similarly dichotomized. Model (8) with dichotomized demand variables is then written as

AP AULC AUMC (8a) p = a, ULC +a2 UMC +a3dAUIS-(U/S)] +

+a3d5EU/S- (UIS)]N + a3d6[I/S-(I/5)]P+

+a3d7[I/S-(I/S)]N+ V'

and referred to as model (8a). If neither (a3d4-a3d5) nor (a3d6-a3d7) differ significantly from zero, one must reject the hypothesis that the relationship between the rate of price change and demand disequilibrium is asymmetric.

Since demand disequilibrium is expressed in terms of the deviation between actual and desired levels of both unfilled orders and finished goods inventory, model (8a) does not include a constant. However, the omission of relevant exogenous variables or the use of an incorrect functional form may result in the appearance of a non-zero constant term. In this case it would be in- appropriate to force the regression line through the origin. For this reason the constant term is allowed to assume values other than zero in initial estimates of (8a).

The other issues raised in section I involved hypotheses about the role of costs in the price equation. Further development of these hypotheses requires a short discussion of the cost concepts employed in this study. Actual or measured unit labour costs is defined as

E J.I.E.




ULC = W(H - N)/Q

where W = average hourly earnings of hourly rated workers H = average weekly hours of hourly rated employees N = number of hourly rated employees Q = index of industrial production.

AULC/ULC is therefore the quarter to quarter rate of change in actual unit labour cost. As suggested in section I, prices may be changed only in response to cost changes which are considered permanent. Changes in unit labour cost due to cyclical productivity variation do not enter the pricing decision. Normal unit labour cost will be determined by the wage rate and the long-run trend of productivity. In this case

ULCN = W(H - N)/Q)T

where ((H- N)/Q)T is the antilog of the semi logarithmic trend value of (H. N)/Q. Since it proved impossible to purge average hourly earnings of the effects of overtime premiums, ULCN may still have some cyclical content.

If the firms in the cotton textile industry do, in fact, use normal labour cost rather than actual unit labour cost in their pricing decision, one expects that the partial correlation between AP/P and AULCNIULCN which is obtained when the latter is used in model (8) will exceed the partial correlation between AP/P and AULC/ULC.

Unit materials cost is defined as

UMC = MC(J/Q)

where MC = price index of materials used by the cotton textile industry (J/Q) = units of materials used per unit of output.

Since there is no information on the quarterly behaviour of (J/Q) it is assumed constant. In this case AUMC/UMC is equal to AMC/MC, the rate of change in the raw materials price index.8

The materials price index is a weighted sum of the price indices of each of the material inputs used by the cotton textile industry. Each of these component indices is assigned a weight equal to the proportion of the total materials bill for which it accounts. The proportions are calculated from the I96I input-output table (DBS I5-502, I969).

An indication of the relative influence of current labour and materials cost changes on price changes may be obtained by comparing the regression coefficients with their long-run, or full adjustment values. It was argued that when all adjustment is completed a I % increase in labour cost should result in a price increase of (ULC/(ULC+ UMC) per cent. The importance of current labour cost changes can be gauged by comparing the regression

8 An alternative assumption is that the behaviour of (J/Q) can be approximated by a semi log trend which would appear in the constant term of the regression.




coefficient of AULC/ULC in model (8) with its full adjustment value. A similar calculation will indicate the relative importance of current materials cost changes.

It was stated at the outset that this particular industry is a tariff protected producer of a widely traded commodity. The landed price of foreign cotton textiles sets an upper limit on the price which Canadian producers can obtain. If Canadian producers set prices with the object of excluding foreign textiles, an increase in the landed price of imports will result in an increase in the Canadian price. The landed price of imports will increase if the Canadian dollar depreciates relative to the currency of other producers or if the import price of other producers rises. It was impossible to obtain an appropriately weighted world price for cotton textiles. However, the Canadian exchange rate floated during part of the sample period and it is posited that the mark-up of Canadian producers responded to both domestic demand conditions and to the landed price of imports. Thus

(9) AM/M= b 1 (U/S) + b2(I/S) + b3AR/R + b4+V b1>O, b2<O, b3>.O

where AR/IR the quarterly rate of change in the price of the United States dollar in terms of Canadian dollars.

Substituting (9) into (8) yields model (io) which is

(10) AP/P = a, AULC/ULC+a2AUMC/UMC+a3b(UIS) + a3b2(I/S) + a3b3 AR/R+ a3b4+ V'

where a3b1>0, a3b2<0, a3b3>0.

III. EMPIRICAL RESULTS

The ordinary least squares estimate of an unlagged version of model (8) appears as equation (i) on Table I. The sample period is I958-69. All basic series are seasonally adjusted. Three coefficients are significant at the 990O confidence level and one at the 9500 level (one tail t-test). The strong partial correlation between the rate of price change and both demand variables implies an unequivocal rejection of the Hall and Hitch hypothesis as it applies to this particular industry.9 Prices change relative to costs under the pressure demand disequilibrium in the product market.

The rate of change in normal unit labour cost is significant in all equations estimated while the rate of change in actual unit labour cost is not. One must infer that, in this industry, it is normal rather than actual labour cost which is relevant to the pricing decision.

The proportion of the variance in quarter to quarter price change which is explained is highly significant and, considering the randomness inherent

9 An alternative measure of demand disequilibrium, U,/P,, where U, is the backlog of unfilled orders at the end of period t and P, is the industry selling price prevailing during period t, shows an equally high partial correlation with AP/P.




in quarter to quarter price changes at this level of disaggregation, very encouraging.10

TABLE I

ESTIMATES OF MODELS (8) (8a) AND (IO)

(i) APIP = - .567+ .115 AULCNIULCv+ .I4o AMC/MC+ 3.46 U/S-!2.8I I/S (1I47) (I.89) (3.56) (5.00) (3.80)

R2=.44 Ni=47 D.W. = 2.Io F= Io.2

(2) AP/P = - .706 + .237 (AULCNIULCN)*+ .228 (AMC/MC)*+ 3.67 U/S- 2.09 I/S (1.90) (2.55) (3.94) (5.63) (4.09

R2=.49 N=47 D.W.=2.3I F= I3.3

(3) AP/P = - .707+ .232 (AULCN/ULCN)*+ I I5 AMC/MC+ .048 (AMC/MC)- (I.87) (2.35) (3.07) (i.,56)

+ .033 (AMC/MC)-2+ .030 (AMC/MC)-3+ 3.68 U/S- 2.90 I/S ( I.44) (.97) (5.53) (4.02) R2= ,47 N= 47 D. W. = 2.29 F = 7.3

(4) AP/P - .252 (AULCN/ULCN)*+ .226 (AMCIMC)*+ 3.90 [U/S- (VTS)1" (2.90) (3-77) (4-43)

+ 2.99 [U!S_(f7S)]N- 3-II [I/S-(7f&)]P_2.20 [I/S -((73)]N (I.80) (3.33) (1.28)

R2= .48 N= 47 D. W. = 2.30 F = 9.6

(5) AP/P = - .75I + .272 (AULCNIULCN)*+ .I98 (AMCIMC)*+ 3.38 U/S-2.56 I/S (2.0I) (2.75) (3.07) (4-77) (3.30)

.I63 AR/R + (I .03)

R2 = ,49 N= 47 D. W. = 2.39 F = 9.8

In the derivation of model (8) it was argued that a complete adjustment of price to cost changes implied a coefficient on the rate of change in unit labour cost equal to the share of labour cost in total cost (ULC/(ULC+ UMC)) and a coefficient on the rate of change in materials cost equal to the share of materials cost in total cost (UMC/(ULC+ UMC)). The estimated coefficients of both the current rate of change in normal unit labour cost and the current rate of change in the materials price index are significantly less than their full adjustment values." Changes in labour and materials cost are not fully reflected in the price of output during the quarter in which they occur. Lags in the adjustment of price to changes in raw materials cost have also been observed by Neild (I963, pp. io-I I) and by Yordon (i96i, p. 292)

10 Quarter to quarter precentage changes, while avoiding a great many serious econometric problems, display a relatively low signal to noise ratio. For further discussion see Eckstein and Wyss (1970, pp. 4-5).

' With full adjustment al = ULC/(ULC+UMC) = .231

and a2 = UMC/ULC+ UMC) = .769. At the 95%o confidence level, confidence intervals around the values of d, and d2 do not include a, and a2 respectively.



PRICING BEHAVIOUR I49

while Eckstein and Fromm (I968, p. I I73) found a lag in the adjustment of price to changes in normal unit labour cost.

There are a number of alternative methods by which these adjustment lags may be taken into account. Lagged values of AMC/MC or AULCN/ULCN can be inserted in model (8) and their weights inferred from the regression coefficients. The sum of the estimated coefficients of current and lagged values of AMC/MC and AULCNIULCN should not differ significantly from UMC/ (ULC+ UMC) and ULC/(ULC+ UMC) respectively. A second alternative is to specify a priori the weights to be attached to current and lagged values of AMC/MC and AULCN/ULCN. This approach calls for the creation and in- sertion in model (8) of two new variables,

n n

(AMCIMC)* =Z bi (AMC/MC)-i bi= 1 s=o ~~~i=O

and n n

(AULCNIULCN)* = E bi (AULCNIULCN)_i, E bi = 1,

which are n+ I period moving averages of AMC/MC and AULCNIULCN respectively. The estimated coefficients of (AMCIMC)* and (AULCN/ULCN)* should not differ significantly from UMC/(ULC+ UMC) and ULC/(ULC+ UMC) respectively. A final alternative is to constrain the weights on current and past values of both AMC/MC and AULCNIULCN to lie along a polynomial of a specified degree. This is the familiar Almon lag technique.12

Experiments were conducted with each of these three approaches. A four quarter moving average of the current and past values of AULCNIULCN with arithmetically declining weights provided the most accurate description of the pattern of adjustment of price to changes in labour cost. This approach also provided the most accurate depiction of the lag structure of AMC/MC. A four quarter distributed lag with weights constrained to lie along a third degree polynomial was also effective in revealing the lag structure of AMC/ MC.13

A lagged version of model (8) employing four quarter weighted moving averages of both AULCNIULCN and AMC/MC appears as equation (2) on Table I. An alternative lagged version of model (8) employing a weighted moving average of AULCNIULCN and polynomially distributed weights on the current and lagged values of AMC/MC appears as equation (3) on Table II.

In neither equation (2) nor equation (3) does the coefficient of (AULCNI ULCN)* differ significantly from its full adjustment value. Indeed, both point estimates are virtually identical to their full adjustment value.14

Both the coefficient of (AMC/MC)* in equation (2) and the sum of the 12 See Almon (I965, pp. 178-96). 13 Lag structures were evaluated on the basis of their contribution to R2. 14 With full adjustment a, = .23i. In equation (2) al = .237 while in equation (3) di =

.232. Needless to say a confidence interval around either value of d1 includes a,.




coefficients of the current and lagged values of AMC/MC in equation (3) remain significantly less than their full adjustment value.'5 While this is by no means crucial, it is puzzling. Since the problem does not lie in the length of the lag (lags of up to six quarters were used) or with the form of the lag distribution, it must be in the nature of the materials price index itself. It is possible that measurement error has biased the estimated regression coefficient downwards.'6 The omission of the price of some vital input from the materials price index would bring about a similar result.

The estimate of model (8a) appears as equation (4) on Table I. It contains the dichotomized demand variables required to test the hypothesis that the relationship between demand disequilibrium and the rate of price change is asymmetric. Initial estimates showed that the constant term had a t-ratio less than one and it was dropped from the equation.17 As was explained in section II, if there is no significant difference between the coefficients of the positive and negative deviations from either the desired order backlog or the desired finished goods inventory, one must reject the asymmetry hypothesis. Application of the appropriate test results in the rejection of the asymmetry hypothesis.'8 In this industry the rate of price change responds equally to excess or deficient demand.

A similar test also results in the rejection of the hypothesis that the relationship between the rates of change of price and materials cost is asymmetric.'9 The 'materials ratchet' observed by Yordon does not exist in this industry.

15 With full adjustment a2 = .76i. In equation (2) d2 is the coefficient of (AMCIMC)*. Hence d2 = .228. A confidence interval around d2[.228+ 2.o2i (.058)] excludes d2.

In equation (3) 62 is the sum of the coefficients on current and lagged values of AMC/MC. Hence d2 = .227. A confidence interval around a2 [.227+ 2.02 I (.o88)] excludes d2.

16 See Johnston (I972, pp. 28I-3)d 17 This result is consistent with the expectation that a model employing the demand

disequilibrium variables in deviation form would not require a constant. Dropping an explanatory variable with a t-ratio less than one will also reduce the standard error of estimate.

18 Using model (8a) the appropriate test statistic is defined as (a3d4-a3d5)/a(a3d4-a3d5) for unfilled orders and (a3d6 - a3d7)/a(a3d6 - a3d7) for inventories. The value of the former is .44 and the value of the latter is .43. Neither is significantly different from zero. The power of this test is vitiated somewhat by the relatively low t-ratio attached to the estimate of a3d7 in equation (4). While a3d6 and a3d7 do not differ significantly, a3d6 is significantly greater than zero while a3d7 is not.

19 The test statistic is defined in footnote i8. In this case it has a value of .7I. Again the conclusion reached must be qualified. While the coefficient of positive changes in MC does not differ significantly from the coefficient of negative changes the former is significantly greater than zero at the ninety-five percent confidence level while the latter is not.

Variable Definitions and Sources P = Industrial Selling Price Index, DBS 62-528 W = Average Hourly Earnings, DBS 72-202 H = Average Weekly Hours, DBS 72-202 N = Index of Employment, DBS 72-201 Q = Index of Industrial Production, 6 I-508

MC = Materials Price Index (McFetridge, 1972) I = Finished Goods Inventory, DBS 31-001 U = Unfilled Orders, DBS 3I-001 S = Shipments, DBS 31-001 R = Price of the United States dollar in terms of Canadian dollars (Bank of Canada,

Monthly Statistical Review, various issues).



PRICING BEHAVIOUR 15 I

Extensive experimentation was undertaken with nonlinear demand disequilibrium variables in search of the threshold effect described by Eckstein. While significant partial correlations were observed, none exceeded the partial correlations between AP/P and the linear demand disequilibrium variables. One must conclude that in this industry the relationship between the rate of price change and demand disequilibrium is linear.

The estimate of model (IO) is reported as equation (5) on Table I. An eight quarter moving average of the rate of change in the exchange rate has the correct sign but is significant only at the 86%4 confidence level (one tail t-test). One is thus unable to accept the hypothesis that the mark-up factors ofdomestic producers are altered in response to changes in the exchange rate. Inspection of equation (Io) reveals that AMC/MC and AR/R are highly correlated. The reason for this is that changes in the exchange rate change the Canadian price of imported raw cotton a principal component of the materials price index. Changes in the exchange rate exert an effect on the output price through their effect on the raw materials price index rather than through any effect on the margin.

In summary, it has proven possible to explain half the variance in the quarterly rate of change in the selling price index of the Canadian cotton textile industry. The industry mark-up factor increases during periods of excess demand and decreases during periods of deficient demand. Excess and deficient demand manifest themselves through deviations between desired and actual values of both the backlog of unfilled orders and finished goods inventory. The relationship between these measures of demand disequilibrium and the rate of price change is linear and symmetric. On the cost side, changes in normal unit labour cost are fully reflected in the price of output within four quarters. None of the equations estimated indicates full adjustment of the price of output to changes in the raw materials price index. The adjustment which does occur is fully completed within four quarters. Finally, there is only weak evidence to indicate that the mark-up factor responds to changes in the landed price of foreign textiles resulting from changes in the external value of the Canadian dollar. The influence of the exchange rate is transmitted instead through the cost of material inputs, namely imported raw cotton.

The approach used in this paper has made possible a relatively large number of unambiguous inferences about the determinants of price behaviour in a particular industry. It would be illegitimate, however, to attempt any generalization. The correct procedure is to estimate similarly detailed models of other industries at this level of disaggregation and to undertake an inter-industry comparison of these models. This comparison would yield the type of generalizations about pricing behaviour which can never be obtained from price equations estimated at higher levels of aggregation.

UNIVERSITY OF WESTERN ONTARIO



I52 D. G. MCFETRIDGE

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DEPARTMENT OF CONSUMER AND CORPORATE AFFAIRS, Concentration in the Manufacturing Industries of Canada (Ottawa, 197 I).

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ECKSTEIN, OTTO, ' A Theory of the Wage-Price Process in Modern Industry', Review of Economic Studies (Oct. I964) PP. 267-86.

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The Determinants of Pricing Behaviour: A Study of the Canadian Cotton Textile Industry