Daniel Levy
email: levyda@mail.biu.ac.il

Shantanu Dutta
email: sdutta@marshall.usc.edu

Mark Bergen
email: mbergen@csom.umn.edu

Peter Aranson

Laurence Ball

Robert Barsky

Susanto Basu

Stephen Cecchetti

Robert Chirinko

Hashem Dezhbakhsh

Paul Geroski

Steve Hoch

James Holmes

Abel Jeuland

Anil Kashyap

Evan Koenig

Greg Mankiw

Fred Mcchesney

Georg Müller

Allan Meltzer

Sam Peltzman

Carol Simon

Ruey Tsay

Harald Uhlig

Ken West

Tao Zha

Heterogeneity in Price Rigidity: Evidence from a Case Study Using Micro-Level Data

Keywords: Agricultural Prices, United States Business, Progressive Grocer, Refrigerated Transporter, Restaurant Business, Restaurant Hospitality, Restaurants and Institutions, Restaurant News, Supermarket Business, Supermarket

We combine two datasets to study price rigidity. The first consists of weekly time series of retail, wholesale, and spot prices for twelve products. These time series contain two exogenous cost shocks. We find that prices exhibit more rigidity in response to the second shock than the first. The second dataset consists of all publicly available information about the shocks. Content analysis of these information reveals that the first shock is larger and more persistent, and the market has more information on it than the second. We conclude, therefore, that prices are more flexible in response to cost shocks that are larger, that are more persistent, and on which market participants have more information

Introduction

Variation in price rigidity is an issue of considerable interest in macroeconomics because understanding its reasons may shed light on causes of price rigidity. 1 For example, according to Gordon (1981, p. 517), understanding it "... is crucial for the theory of price adjustment. " Caplin (1993, p. 21) describes it as unfortunate "... that so little attention has been given to characterizing the circumstances that give rise to high and low levels of nominal price inertia. Progress in this dimension calls for more detailed empirical work and for increased understanding of the manner in which corporations actually arrive at pricing decisions." Weiss (1993, p. 15) also suggests to include all "... relevant information at the level of the firm, including costs and demand data."

Similarly, Lach and Tsiddon (1992, p. 351) suggest to use actual transaction prices to study price rigidity because they "... most closely resemble the data envisioned by the cost of adjustment theory: price quotations at the level of the price setter." Unfortunately, only a handful of studies use actual transaction prices to study price rigidity [START_REF] Kashyap | Sticky Prices: New Evidence from Retail Catalogues[END_REF][START_REF] Genesove | The Nominal Rigidity of Apartment Rents[END_REF].

We combine two unique data sets to create a micro level case-study of time-varying price rigidity. The first data set consists of weekly retail, wholesale, and commodity prices for twelve orange juice products which are categorized as either refrigerated or frozen. A unique feature of this data set is that it contains two episodes of exogenous commodity cost shocks. The cost-price data suggest that manufacturers' and retailer's reactions to the shocks were different. Specifically, we find that prices exhibit significantly more rigidity in response to the second shock than the first.

To explain this variation in price rigidity we collected a second data set consisting of all public information on the cost shocks. Because it is difficult to know what information economic agents have and use, macroeconomists usually are forced to make assumptions of various kinds about the content of this information. For example, many empirical macroeconomic studies that make use of anticipated/unanticipated series rely on forecast generating equations to generate these series. We, in contrast, study a very specific product market where determination of the relevant information set is less ambiguous in comparison to studies that use aggregate data. Thus, we collected all publicly available information we could find about the causes and effects of the cost shocks, and by analyzing the content of these information, we are able to assess the extent of the actual information the orange juice market participants likely had. We shall also note the novelty of the method we use to identify shock persistence. In macroeconomics, identification of temporary and permanent components of shocks is usually accomplished by econometric means. The reason for this practice is that it is difficult to know how market participants assess economic variables' persistence. We are able to overcome this difficulty by focusing on specific cost shocks and by studying in detail their actual causes and effects and the events surrounding them, we are able to evaluate their likely permanence.

We find that (i) the first cost shock was larger than the second, (ii) the first shock was more persistent than the second, and (iii) the market had more information on the first shock than the second. These findings, therefore, suggest that prices are more flexible in response to cost shocks that are larger in size, more persistent, and on which the market participants have more information. This conclusion is particularly valuable because the nature of the price rigidity we are documenting, enable us to control for various market features that are frequently used to explain variation in price rigidity. For example, over the three-year sample period, the market structure and industry concentration, the nature of long term relationships, contractual arrangements, and the number of stages of processing, all have remained unchanged. Further, orange juice products have a constant quality. The variation in price rigidity we document in this paper, therefore, cannot be explained by variation in any one of these factors.

The paper is organized as follows. In section 2, we describe the data. In section 3, we analyse the retailer's and manufacturers' reactions to the two cost shocks. In section 4, we compare the cost shocks.

In section 5, we conclude by discussing the findings in the context of existing price rigidity theories. In the appendix we list the information collected and their sources.

Data

Cost-Price Data

The first data set consists of 168 weekly observations (September 7, 1989-November 19, 1992) of actual retail, wholesale, and commodity spot prices for twelve Florida orange juice products. We have data for three brands, Tropicana, Minute Maid, and the Store Brand (in-house supermarket brand). Each brand comes in two forms, frozen concentrated and reconstituted from frozen concentrate (refrigerated), and two sizes: the frozen concentrated orange juice comes in 12oz and 16oz cans while refrigerated juice comes in 64oz and 96oz (128oz for the Store Brand) containers. In the analysis that follows we focus on two representative products, one frozen concentrated orange juice (Store Brand, 12oz, displayed on Figure 1) and the other, refrigerated orange juice (Tropicana brand, 96oz, displayed on Figure 2). The remaining ten products exhibit similar behavior but are not discussed to save space. 2 Chart 1 displays a general description of the frozen concentrated orange juice market, which provides about 70 percent of the orange juice sold in the U.S. The chart indicates that this market consists of two channels: the retail channel, which represents the final goods market, and the wholesale channel, which represents the intermediate goods market. Thus, the market we study is characterized by a hierarchical structure, similar to the "stages of processing" structure studied by Blanchard (1983). 3 The data set has several unique features. First, it consists of actual retail and wholesale transaction prices and a measure of upstream commodity cost. The retail and wholesale prices come from the supermarket scanner. While scanner data are rarely used by economists, they have been extensively used in marketing to study such issues as consumer choice behavior [START_REF] Kamakura | A Probabilistic Choice Model for Market Segmentation and Elasticity Structure[END_REF]Russell, 1989, and[START_REF] Gonul | Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues[END_REF][START_REF] Gonul | Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues[END_REF], brand choice [START_REF] Allenby | Quality Perceptions and Asymmetric Switching Between Brands[END_REF][START_REF] Chintagunta | Investigating Heterogeneity in Brand Preferences In Logit Models for Panel Data[END_REF][START_REF] Villas-Boas | Endogeneity in Brand Choice Models[END_REF], pricing strategy [START_REF] Raju | The Introduction and Performance of Store Brands[END_REF], etc. This chain changes prices once a week on a chain-wide basis, and we have chosen a representative store from the Chicago area. 4 The wholesale prices are what the retailer pays the orange juice manufacturer, and is the cost measure the retailer uses in pricing decisions. Having access to the actual cost data is unique given that they are proprietary and rarely available. Further, having access to both actual price and actual cost data, enables us to consider a richer notion of price rigidity, following the works of [START_REF] Cecchetti | The Frequency of Price Adjustment: A Study of the Newsstand Prices of Magazines[END_REF], [START_REF] Hannan | The Rigidity of Prices: Evidence from the Banking Industry[END_REF], [START_REF] Neumark | Market Structure and the Nature of Price Rigidity[END_REF], [START_REF] Kashyap | Sticky Prices: New Evidence from Retail Catalogues[END_REF], and Slade (1996aSlade ( , 1996b)). According to this notion, prices are rigid if they do not respond to changes in cost or demand conditions. Due to the lack of cost data, many studies measure price rigidity indirectly, using price change frequency, time span between price changes, etc. Having both series for the same products enable us to study this broader notion of price rigidity.

As a measure of manufacturers' costs we construct spot market prices from the nearest futures contract price of frozen concentrated orange juice from the New York Cotton Exchange by adjusting it for storage and carrying cost using a cash-and-carry formula. 5 Deviations of the contract price from the spot price merely represent capital gains and losses to the buyer/seller. Thus, the spot price reflects the market and weather conditions fairly well and, therefore, is a reasonable proxy for manufacturers' costs.

The cost-price data have additional advantages. First, we control for various market features. For example, over the three year period, market structure and industry concentration, the nature of long term relationships, contractual arrangements, and the number of stages of processing, all have remained unchanged. Therefore, the price rigidity variation we find cannot be explained by any of them. Second, orange juice products have a constant quality, monitored by the Florida Department of Citrus and the United States Department of Agriculture, who set limits on the amount of sinking solids; the frozen concentrated orange juice needs also to pass a test which guarantees no gel pulp is left after reconstitution. Also, both frozen concentrated orange juice and refrigerated orange juice must have a minimum Brix content. Third, we examine the effect of exogenous cost changes on prices. Retail costs are exogenous with respect to retail price because: (i) the orange juice market has a hierarchical structure as the retailer follows the manufacturers in the channel of distribution; (ii) the manufacturers sell nationally, while the retailer is one of many local sellers; and (iii) as an orange juice seller, the retailer is significantly smaller than any one of the manufacturers. Similarly, the spot cost is exogenous with respect to the wholesale and retail prices [START_REF] Roll | Orange Juice and Weather[END_REF][START_REF] Baur | The Rationality and Price Effects of United States Department of Agriculture Forecasts of Oranges[END_REF]. Further, we explain variation in prices using costs, as it is done in pass-through literature [START_REF] Borenstein | Asymmetric Gasoline Price Responses to Crude Oil Price Changes[END_REF], following [START_REF] Roll | Orange Juice and Weather[END_REF] finding that most of the orange juice price volatility is due to supply shocks. Further, we found no evidence of demand changes in trade publications. 6 The studies conducted by Florida Citrus Commission and University of Florida Center for Citrus Research and Education, as well as a recent study by [START_REF] Dutta | Price Flexibility in Channels of Distribution: Evidence from Scanner Data[END_REF], reach similar conclusions. Finally, variation in orange juice demand is unlikely since orange juice is consumed on a weekly basis, similar to milk and bread.

Information Data

The data in our sample contain two exogenous cost increases. Figure 1, which plots the cost-price series for Store Brand, 12oz, frozen concentrated orange juice, shows the spot cost jumping significantly during the second half of December 1989 (weeks 15-17). Another big jump occurs during the second half of October 1991 (weeks 110-112). 7 It is the difference in the reaction of manufacturers and retailers to these two cost shocks that comprises the price rigidity variation we document. 8 To evaluate the extent of these shocks' persistence and the amount of information available about them, we undertook an exhaustive search of all public information sources including local and national newspapers, trade journals, United States Department of Agriculture, local and network TV, CNN, Florida Department of Citrus, Produce Manufacturing Association, University of Florida Center for Citrus Research and Education, and Florida Agricultural Statistics Service. For each shock we looked at all information starting two months before the shock until two months after the prices returned to their original level. The search was done through Lexus/Nexus using key words "FCOJ," "frozen concentrated orange juice," "FCOJ and freeze," "orange," "orange juice," "orange juice and freeze," "citrus," and "beverage." We also contacted the Produce Manufacturing Association which collects various trade information on produce including orange juice. The Produce Manufacturing Association personnel helped us compile all information pertaining to orange juice around the time of the two shocks.

In addition, we contacted all local TV stations in the Chicago area as well as the networks including CNN. We received information from WGN-Channel 9 and CNN. 9

After collecting these materials, we analyzed their content. Content Analysis, which is a systematic technique for analyzing a message content, is guided by rules to minimize the possibility that the findings reflect the analyst's subjective predispositions [START_REF] Holsti | Content Analysis for Social Sciences and Humanities[END_REF][START_REF] Kassarjian | Content Analysis in Consumer Research[END_REF]. We had two research assistants independently analyze the contents of all the material collected and summarize their main theme. 10 The findings reported below are based on consensus between the two researchers. This is a conservative approach since it requires that both researchers agree on the theme of all the reports. In published studies, an 80% or higher agreement is considered acceptable [START_REF] Kassarjian | Content Analysis in Consumer Research[END_REF]. 11 Although, there is always a possibility of some bias when it comes to interpretation of the content of some information, we should note that in most cases the interpretation of the news reports we collected were relatively straightforward and necessitated very little subjective judgement because of the factual nature of the information. This factual nature of the information collected also diminished our concern regarding any potential journalistic inaccuracy of the reports themselves. Based on the content analysis of all information collected we conclude that there were some fundamental differences between the two cost shocks in terms of their size, persistence, and information. These findings along with the information collected are described in Section 4. 12

Retailer's and Manufacturers' Reaction to the Cost Shocks

Reaction to the First Cost Shock Following the initial spot cost shock during the week of December 21, 1989 (week 15), wholesale price increases reach their peak during the week of April 12, 1990 (week 31). 13 Once the spot cost increases, it remains at that high level for about 24 weeks (weeks 20-44). The wholesale price exhibits a similar pattern, although it remains at the peak level for only 17 weeks, from March 29, 1990until July 19, 1990. On July 19, 1990, the wholesale price begins a downward adjustment to the commodity spot cost. The adjustment is gradual, and looks slower than the spot cost decrease. It takes the wholesale price over a year from the time it starts to decline (around week 47), until it reaches the pre-shock level (around week 100), while the spot price completes its decline to the pre-shock level by the 58th week. This suggests a possible asymmetry in the orange juice wholesale price adjustment, similar to gasoline prices [START_REF] Borenstein | Asymmetric Gasoline Price Responses to Crude Oil Price Changes[END_REF] and interest rates [START_REF] Hannan | The Rigidity of Prices: Evidence from the Banking Industry[END_REF]. 14 The retail price response to the wholesale price increase is faster than the response of the wholesale price to the spot cost increase. In fact, the retail price may be increasing faster than the wholesale price during the 20th-28th weeks, suggesting that the retailers may be responding, at least in part, to the spot cost increase. This is clearly possible from informational point of view: the retailers, like other market participants, already had information on the cause and severity of this cost shock several weeks earlier.

The retail price increases first to 13.3 cents/oz on week 21, to 14.1 cents/oz on week 29, and finally to 14.9 cents/oz on week 49, before starting to decline. The retail price remains at or above 14 cents/oz for almost 36 weeks, but it adjusts downwards, once the adjustment begins, rather quickly. The decrease in the retail price begins on the 64th week, and is fully complete by the 82nd week. Thus, the retail price adjusts to the wholesale price substantially faster in comparison to the adjustment of the wholesale price to the spot cost. The data, therefore, suggests that the cost shock leads to an increase in the wholesale price and consequently to an increase in the retail price. The upward adjustment of both series seems to be proportional to the size of the cost shock.

Reaction to the Second Cost Shock

The second shock occurs during the week of October 17, 1991 (110th week). Here the retail price shows no response to the spot cost increase. The wholesale price increases but the increase merely takes the wholesale price back to the level it was at during weeks 98-102, which is the same level as the prefirst-cost-shock level. The spot price begins declining almost as soon as it increases. The wholesale price, however, does not decline in response to this decrease. This pattern of behavior of the wholesale price suggests that its increase during the 110th week was merely a correction to the over-reaction it experienced during the weeks 98-102. Thus, the data suggest that both the wholesale and the retail price responded to the first cost shock, but they did not respond to the second cost shock. 15

Differences between the Two Cost Shocks

The finding that manufacturers' and retailer's responses to upstream cost shocks are more rigid in response to the second cost shock than the first cannot be explained by variation in the nature of long terms relationships, industry concentration, etc., as these factors have not changed during the sample period. This led us to focus on differences between the two shocks that may explain the findings. 16 Below we list these differences. In Table 3 we summarize the results. 17

The Cause of Shocks

First Cost Shock: The first shock was caused by a freeze. The Florida Department of Citrus (1994) lists it among the nine most "significant Florida Citrus Belt freezes" that occurred since 1957. 18 The freeze was particularly severe as the temperature dropped to below 25˚ F and stayed there for almost two days.

Second Cost Shock:

The second shock occurred when the United States Department of Agriculture released a forecast of a lower than expected citrus crop in its October 1991 report. 19 As stated in the Wall Street Journal (October 14, 1991), "Behind the move was what traders and analysts called a shocking government forecast for a Florida crop of 136 million 90 pound boxes, or 10% below last year's crop. Industry analysts expected the government to predict the Florida crop would be as much as 10% bigger than last year." The United States Department of Agriculture report was released on October 12, 1991, after the closing of the New York Cotton Exchange. The spot price increased during the next three trading days followed by smaller increases during the following two weeks.

The Effect on Crops First Cost Shock:

The freeze destroyed about 20 percent of the trees and a portion of the fruit on trees thereby decreasing the orange crop from 146.6 million boxes to 110.2 million boxes, a decrease of 24.8 percent. The extent of damage can be seen in Table 1 where we report the Florida orange crop, price, and yield estimates. As the table indicates, the output of oranges during the 1989-90 growing season dropped by 24.8 percent in comparison to the 1988-89 season. The severity of the damage can also be seen by looking at the yield figures in terms of boxes/acre: during 1989-90, the yield was down by more than 26 percent and it was accompanied by a 35.5 percent increase in orange prices. Another indicator of the severity of the damage is the gallons/Brix yield reported in Table 2. This is a measure of the solid content of oranges and thus, of the quality of orange crop. According to the table, the United States Department of Agriculture's gallons per Brix yield estimate has dropped from 1.48 in December 1989 to 1.21 in April 1990, which is a 18 percent drop. 20

Second Cost Shock: Florida orange crop dropped from 151.5 million boxes in the 1990-91 season to 139.8 million boxes in the 1991-1992 season, a decrease of 7.78 percent. The reason for this decline was lower than normal temperatures during January-February and higher than normal temperatures during spring months of 1992 (Florida Agricultural Statistics Service, 1993). As a result, harvest began early because of the early bloom and ended earlier than normal. However, winter lows were above freezing and so no damage to trees or fruit was reported. Therefore, no decline in gallons per Brix yield is observed here. To the contrary, there was a slight increase, 2.7 percent, in this measure of yield.

Moreover, according to the November 27, 1992 Report of the CNN's John Zarrella, near perfect growing conditions had in the end produced the third largest crop ever of citrus fruits in Florida.

The Effect on Prices

First Cost Shock: Spot prices increased by 60% or $0.0353/oz. After the initial jump, the spot price remained high for over 7 months before it started to decline. A process of increased importation of Brazilian orange juice eventually lead to a gradual reduction in orange juice prices. Brazilian and Mexican orange juice products are often used as a substitute for Florida product in the production of frozen concentrated orange juice. (For example, many frozen concentrated orange juice products produced in the US, have labels which state: "Contains orange juice concentrate from Florida, Mexico, and Brazil.") At first, the market seemed uncertain about Brazil's ability to meet the demand (see the January 17, 1990 report by the New York Times, "Orange Juice Prices Up on Reports that Brazil May Not Meet Demand."), but according to the officials of the Florida Department of Citrus, these concerns never materialized. Indeed, in a series of articles published later in the year by the New York Times, the paper reported that "Orange juice prices are falling as US predicting big crops" (October 12, 1990), "Orange juice prices collapse to four-year low" (October 13, 1990), and "Orange juice prices down with speculation Brazil would dump frozen concentrate" (October 18, 1990).

Second Cost Shock:

Spot prices increased by 36% or $0.0211/oz. In contrast to the first shock, the spot price started declining immediately after the jump. This is an indicator of the temporary nature of the second shock, especially in comparison to the first shock.

Media Reports

First Cost Shock: The first shock, which began with a forecast of extremely cold weather in Florida, was widely documented in newspapers and other print media with 28 mentions between December 1989 and March 1990, and 23 of them talked about extensive damage to the citrus crop and higher orange juice prices. In fact, the Governor of Florida declared the entire state a disaster area and asked for Federal assistance to farmers. Further, we found six TV reports on a local TV channel (WGN-Channel 9, Chicago) and on CNN and all six mentioned significantly reduced orange crop prospects due to the freeze.

Second Cost Shock:

From October 1991 to January 1992 there were seventeen reports on this shock and eleven of them said prices were rising. However, over short period of time, the market seems to have revised its forecast of the Florida crop up from the United States Department of Agriculture's level. Further, these reports indicated that the price increase was due to speculative and psychological effects. For instance, the Wall Street Journal (November 7, 1991) reported that "... the cold in North Florida is not expected to affect the orange crop but the cold spell is having a psychological effect on the market." All six reports published between January 7, 1992 and January 25, 1992 indicated that commodity prices were actually coming down. The two CNN reports from this period even emphasized the positive prospects of the Florida orange crop. Thus, all printed and TV reports seemed to suggest that this cost shock was of a temporary nature.

Government Reports

Discussion of the Results and Conclusion

The findings suggest that (i) prices are more rigid in response to small cost shocks in comparison to large shocks, (ii) prices are more rigid in response to temporary cost shocks in comparison to permanent shocks, 21 and (iii) prices are more rigid in response to shocks on which there is limited information in comparison to shocks on which there is more information. 22 The idea that size of a shock may affect price rigidity has been exploited to test the empirical validity of menu cost theories. Under menu costs, firms will adjust to large shocks but not to small shocks. Therefore, large shocks will have a disproportionate effect on prices, which explains a large fraction of movements in postwar U.S. inflation [START_REF] Ball | Relative Price Changes as Aggregate Supply Shocks[END_REF]. A distinguishing characteristic of our result is that we find it at the level of an individual product using actual transaction prices.

While some studies suggest the importance of shock persistence for price rigidity (see, for example, [START_REF] Mccallum | New Classical Macroeconomics: A Sympathetic Account[END_REF][START_REF] Caplin | State Dependent Pricing and the Dynamics of Money and Output[END_REF][START_REF] Sheshinski | Optimal Pricing, Inflation, and the Cost of Price Adjustment[END_REF][START_REF] Taylor | Low Inflation, Pass-Through, and the Pricing Power of Firms[END_REF], the existing empirical evidence is mostly indirect and rely on aggregate data (see, [START_REF] Meltzer | Information, Sticky Prices, and Macroeconomic Foundations[END_REF] for a recent survey).

We use a novel method to identify shock persistence. The usual practice is to econometrically identify temporary and permanent components of shocks. The reason for this practice, as [START_REF] Meltzer | Information, Sticky Prices, and Macroeconomic Foundations[END_REF] indicates, is that it is difficult to know how people assess economic variables' persistence. We are able to overcome this difficulty by focusing on specific cost shocks and by studying in detail their actual causes and effects we evaluate their likely permanence. Our findings at the spot-to-wholesale level are also consistent with [START_REF] Carlton | The Theory and the Facts of How Markets Clear: Is Industrial Organization Valuable for Understanding Macroeconomics?[END_REF] suggestion that a firm may not raise price in response to temporary cost increases for fear of loosing customers who may interpret the price increase as permanent. Therefore, the firm will absorb the temporary cost increase.

Macroeconomic importance of imperfect information has long been recognized [START_REF] Lucas | Expectations and Netrality of Money[END_REF]. 23 It is difficult, however, to know what information economic agents really have. Macroeconomists, therefore, are forced to make ad hoc assumptions of various kinds about the content of this information.

For example, most of the empirical studies that make use of anticipated or unanticipated series have to rely on forecast generating equations with some autoregressive, autoregressive moving average, or autoregressive-distributed lag structures [START_REF] Levy | Specification and Estimation of Forecast Generating Equations in Models with Rational Expectations[END_REF]. In contrast, here we study a very micro-level and well-specified product market where determination of the relevant information set is less ambiguous, in comparison to studies that use aggregate level data. Specifically, we collected all the relevant publicly available information we could find about the causes and effects of the shocks, and by analysing the content of these information, we were able to assess the extent of the actual information the orange juice market participants likely had.

The product categories we study are widely used and representative of typical retail items. Also, the pricing practices of the supermarket chain we study are representative of many large U.S. grocery chains. Thus, the market we study is representative of the U.S. grocery industry. However, this is only one case-study. Further, the data only contain two large cost shocks. Therefore, future research should examine price response to cost shocks across other products, retailers, and markets, in order to see whether the results we report generalize to other industries and markets. 24 Footnotes 1. See, for example, [START_REF] Encaoua | Price Dynamics and Competition in Five Countries[END_REF][START_REF] Blinder | Asking About Prices: A New Approach to Understanding Price Stickiness[END_REF][START_REF] Geroski | Price Dynamics in UK Manufacturing: A Microeconomic View[END_REF], and Levy and Young (2001).

2. The results for these ten products are available from the authors upon request.

3. This is different from the input-output structure of [START_REF] Gordon | What is New-Keynesian Economics?[END_REF] and [START_REF] Basu | Intermediate Goods and Business Cycles: Implications for Productivity and Welfare[END_REF]. As [START_REF] Gordon | What is New-Keynesian Economics?[END_REF] suggests, the input-output view of the market is better suited for more aggregated and complex products produced using many inputs. In contrast, here we study individual products, and also the products themselves are simple, produced with few inputs.

4. The retail prices reflect retailer's coupons and discounts, but not manufacturer coupons, which are rarely used in this market. The wholesale prices do not include lumpy payments like slotting allowances which, according to the price manager of the chain, were not common in the orange juice category during the period covered in our study.

5. The use of nearest futures price as a proxy of the spot price means that once a month there may be a change from month n contract to month n + 1 contract. We adjust the series for storage and carrying cost to resolve this problem. We use the interest rate on 6-month treasury bill to compute the storage cost. Monthly carrying cost data are described in Florida Department of Citrus' (1994) Citrus Reference

Book. The spot cost is divided by 1,600 to get a $/oz price. The price quoted at New York Cotton Exchange is for orange concentrate level of 57˚ Brix. A Brix is a temperature-adjusted measure of pound solids and sugar content in one gallon orange juice. The Brix level of frozen concentrated orange juice and refrigerated juice is 41.8˚ and 11.7˚, respectively. Therefore, we adjusted downwards the New York Cotton Exchange spot price to ensure identical quality of the orange juice at all levels of the channel.

6. Two aggregate demand shocks could affect the orange juice market: (i) the Kuwait War of January 17, 1991-February 27, 1991, and(ii) the July 1990-March 1991 recession. We, however, found no evidence of such effects on the orange juice market. 7. Figure 2 displays the cost-price data for the Tropicana brand refrigerated orange juice, 96oz. Because of the difference in the Brix content of the frozen concentrated orange juice and refrigerated orange juice, we had to adjust the spot cost data downwards to ensure the equality in the Brix-adjusted quality of the orange juice prices plotted on Figure 2.

8. The frequent promotional activity visible in the retail and wholesale prices are standard practice for retailers of these and similar products [START_REF] Levy | Price Adjustment at Multiproduct Retailers[END_REF]. Its main reason is the competitive nature of the retail food industry. 9. Other stations do not keep records going so far back or do not have information readily available.

Local radio stations do not have well-organized archives and so we could not get any information from them. 10.A "theme" is the most common unit of focus in content analysis [START_REF] Holsti | Content Analysis for Social Sciences and Humanities[END_REF][START_REF] Kassarjian | Content Analysis in Consumer Research[END_REF]. 11.See [START_REF] Tse | Becoming a Consumer Society: A Longitudinal and Cross-Cultural Content Analysis of Print Ads from Hong Kong, the People's Republic of China, and Taiwan[END_REF] for recent examples of studies that use content analysis.

12.In Tables A1-A3 and A4-A6 of the appendix, we report the specific informational items we were able to find that relate to the first and second cost shocks, respectively. A list of all information sources consulted is provided at the end of the appendix.

13.The wholesale price decrease on the 8th week of the sample and its increase back to the original level by the 14th week seems to be of a promotional nature and is unrelated to the cost shock that occurred on the 15th week, because, as mentioned in the text, that shock was unanticipated.

14.We should mention, however, that [START_REF] Müller | Asymmetric Price Responses to Cost Changes: Evidence from the Retail Grocery Industry[END_REF] examines in more detail the issue of asymmetric price adjustment to cost changes using a dataset from the same retailer, and finds mixed results for the orange juice category.

15.We should note a possible link between price rigidity and promotional activities. For example, in response to higher costs, a retailer may decrease the frequency of "sales" instead of increasing the price.

A visual examination of Figure 1, however, reveals that the decrease in the frequency of sales in response to the second cost shock is no different from a similar decrease in the sales frequency in response to the first cost shock, if one considers the first six month from the time the shocks occur. The idea, nevertheless, seems interesting and could be fruitfully explored with a larger data set, perhaps as part of a study of non-price adjustment mechanisms.

16.We have also explored the effect of cost changes on wholesale and retail prices econometrically by estimating a VAR model incorporating the exogeneity assumptions discussed in section 2 as the identifying restrictions. We estimated the model for the September 7, 1989-May 16, 1991and May 23, 1991-November 19, 1992 periods. The split point was selected based on a recursive estimation of the model along with Chow test statistics. In order to quantify the idea of dynamic price adjustment to cost changes, we computed the cumulative impulse response of price in dollars to one dollar shock in cost.

The findings, which are not reported here to save space but are available upon request, are consistent with our interpretation of the cost-price data. Specifically, we find that the first sample period is characterized by higher price flexibility than the second. It should be noted, however, that these impulse responses represent the dynamic response of prices to average cost shocks, not to the two specific shocks we have focused on. But since the first cost shock is larger than the second, the average shock in the first sample is larger than the second and therefore, the econometric findings are consistent with our data interpretation. 17.The only commonality of the two shocks is that neither shock was anticipated, according to Ed Moore of the Florida Department of Citrus and John Attaway of the Florida Agricultural Statistics Service (personal communication).

18.These freezes are unpredictable until 2-3 days before the freeze, and even then its severity is unknown [START_REF] Roll | Orange Juice and Weather[END_REF][START_REF] Baur | The Rationality and Price Effects of United States Department of Agriculture Forecasts of Oranges[END_REF]. According to John Attaway of the University of Florida Center for Citrus Research and Education (personal communication), Florida Department of Citrus defines as a "significant freeze" any freeze that results in a 25 percent of more decrease in crop. Indeed, as Table 1 indicates, the orange crop during the 1989-90 season was down by 24.8 percent and the yield was down by more than 26 percent.

19.United States Department of Agriculture is required to issue a monthly report of its Florida crop projections. The first report is released on the 2nd week of October followed by monthly updates till July. Their goal is to help growers, processors, and other market participants to plan their future activities. The release of the United States Department of Agriculture orange crop reports is widely anticipated, especially the October report [START_REF] Baur | The Rationality and Price Effects of United States Department of Agriculture Forecasts of Oranges[END_REF] but its content is unknown. Since the effect of these projections on the frozen concentrated orange juice market can be dramatic, United States Department of Agriculture keeps them extremely secret until their release. 20.See also the July 1990 Florida Orange Crop Reports of the Florida Agricultural Statistics Service and the Florida Citrus Processors Association.

21.Despite a wide variation in shock persistence across industries and markets [START_REF] Brunner | Money and Economic Activity, Inventories and Business Cycles[END_REF][START_REF] Andersen | Price Rigidity: Causes and Macroeconomic Implications[END_REF][START_REF] Chirinko | Economic Fluctuations, Market Power, and Returns to Scale: Evidence from Firm-Level Data[END_REF], it has not received as much attention in the empirical price rigidity literature as other factors like industry concentration, which according to [START_REF] Carlton | The Theory and the Facts of How Markets Clear: Is Industrial Organization Valuable for Understanding Macroeconomics?[END_REF] is the most commonly cited reason for price rigidity. As Carlton (1989, p. 911) suggests, "... differences in market characteristics such as shock persistence may well be of more importance to macroeconomists than the effects of differences in concentration."

22.We cannot prove that market participants actually "collected and used" more information about the first cost shock than the second. We are only able to demonstrate that the market provided more information about the fist shock than the second. It should be noted also that it is impossible to know precisely what information is used by particular market participants. It is likely that all market participants are exposed to the information circulated by mass media such as radio, TV, and newspapers, regardless of their incentives. However, for some market participants the stakes are obviously higher, and therefore, they are likely to invest more resources in the relevant information gathering activity. Thus, we predict that spot and wholesale market participants who deal with large volumes and fluctuating market conditions in the frozen concentrated orange juice markets are more likely to gather the relevant information from specialized sources such as the United States Department of Agriculture reports, the Florida Department of Citrus reports, trade publications, etc. The retailers and their customers, on the other end of the channel, are least likely to invest in information gathering from any particular source because their stakes are smaller in this matter.

23.See also [START_REF] Caplin | The Economics of Adjustment[END_REF]. 24.For example, the analysis conducted here could be fruitfully applied to larger scanner data sets such as the data sets used by [START_REF] Barsky | What Can the Price Gap Between Branded and Generic Tell Us about Markups?[END_REF], [START_REF] Chen | Consumer Menu Costs and Asymmetry in Small Price Adjustments: Theory and Evidence[END_REF]Levy (2001) and[START_REF] Judith | Why Don't Prices Rise During Periods of Peak Demand? Evidence From Scanner Data[END_REF]. Note: Chart 1 provides a simplified description of the organizational structure of the Florida orange juice market. Orange juice growers sell the fruit to orange juice manufacturers/processors who convert the oranges into frozen concentrate. There are two types of processors: one group of processors are privately owned and produce orange juice for private label. The other group of processors are owned by national orange juice manufacturers like Tropicana and Minute Maid, and they produce nationally branded products. The manufacturers/processors package and sell the concentrated juice to retailers, either in its frozen form or reconstituted from concentrate and packaged as refrigerated juice. Oranges are also sold for other uses such as for preparing freshly-squeezed juice, for table use, for producing food additives, and so forth through other channels of distribution. These additional uses and their associated channels are not shown on the chart since in this paper we only study the market for frozen concentrated and refrigerated (reconstituted from frozen concentrated) orange juice. See [START_REF] Ward | The Citrus Industry: A Domestic and International Perspective[END_REF] 1988-89 1989-90 1990-91 1991-92 1992-93 Orange

Prices:

Stay high for about 28 weeks after the increase.

Start to decline immediately after the increase.

Print media: 28 mentions (23 reports mention extensive 17 mentions (11 reports mention price increase). But some suggest damage to the citrus crop and the resulting price speculative and psychological reasons for it. Six reports in January increase).

1992 mention orange juice prices actually coming down because the fear of freeze seem unwarranted.

TV Reports: 6 reports (WGN-Chicago and CNN): all six No TV report on price increase. The only report (on CNN, December discuss the severity of the damage. 24, 1991) actually mentioned increased orange crop expectations.

FDC & USDA: 5 reports: all predict low output and high price.

One report: lower-than-expected 1991-92 crop was an aberration and The freeze has been classified by Florida Department of did not change their forecast of record crops in the future. Citrus as one of the 9 major freezes over the last 40 years.

Emergency:

Governor of Florida declares the entire state a None. disaster area and asks for Federal assistance.

(a) About 90% of the fruit was still on trees when the freeze occurred.

Newspapers/Popular Magazines

  First Cost Shock: This shock was mentioned in five Florida Department of Citrus and United States Department of Agriculture reports. According to the July 12, 1990 United States Department of Agriculture report, the freeze reduced the output as well as the yield. These reports also suggested that commodity prices would go up due to reduced supply. Second Cost Shock: Florida Department of Citrus and United States Department of Agriculture reports suggested that the lower-than-expected 1991-92 crop (i.e., the forecasted decline in the citrus output) was an aberration and did not change their long-term (i.e., the Florida Department of Citrus' assessment of the Florida citrus output trend over the next 3-5 year horizon) forecast of record crops in the future. In fact, in December 1991, United States Department of Agriculture (Report No. 91/92-3) revised upward its citrus crop estimate for the 1991-92 growing season from 191,195,000 boxes to 198,180,000 boxes. The actual production for that season turned out to be 208,170,000 boxes (United States Department of Agriculture Citrus Estimate Report No. 92/93-1).

TABLE 1

 1 CROP, PRICE, AND YIELD OFFLORIDA ORANGES, 1988-93

	Growing Season

  : (a) 90 pound box; Source: Florida Department of Citrus (1994, p. 10). (b)1 3/5 bushel box; Source: Florida Agricultural Statistics Service (1994, p. 14). (c) 90 pound box; Source: Florida Agricultural Statistics Service (1994, p. 8).

	Crop (million box) a	146.60	110.20	151.50	139.80	186.60
	Florida Oranges Price (per box) b	7.61	10.31	8.46	8.52	3.80
	Yield Per Acre (box) c	377.00	276.00	360.00	315.00	381.00

Notes

TABLE 2

 2

	USDA ESTIMATES OF FLORIDA FROZEN CONCENTRATED ORANGE JUICE GALLONS-
	PER-BRIX YIELD
				Growing Season
	Month	1988-89 1989-90 1990-91 1991-92 1992-93
	October	1.52	1.48	1.52	1.50	1.48
	November	1.52	1.48	1.52	1.50	1.48
	December	1.52	1.48	1.50	1.50	1.48
	January	1.50	1.30	1.48	1.50	1.52
	February	1.52	1.29	1.48	1.51	1.55
	March	1.52	1.24	1.48	1.52	1.57
	April	1.53	1.21	1.47	1.52	1.57
	May	1.53	1.22	1.45	1.54	1.58
	June	1.53	1.23	1.45	1.55	1.58
	July	1.53	1.23	1.45	1.55	1.58

Notes: Measurement units are 42˚ Brix gallons.

Source: Florida Department of

Citrus (1994, p. 15

).

TABLE 3 SUMMARY

 3 OF THE INFORMATION ON THE TWO COST SHOCKS October 12 "shocking" forecast of 10% lower than last year's crop. The market expected 10% higher than last year's crop.Temperature:Below 25˚F for two days. January 1992 temperature was below normal. Spring temperatures and rainfall were above normal. As a result, harvest began early and it was concluded earlier than normally.Damage to fruit:A portion of the fruit on trees is lost. a No damage to fruit. 8% decrease in boxes/acre and 13.2% 12.5% decrease in boxes/acre and 2.7% increase in gallons/brix. decrease in gallons/brix.

	First Shock

INFORMATION ON THE TWO COST SHOCKS


Mark Bergen

Shantanu Dutta

Daniel Levy

Mark Ritson

Mark Zbaracki

Shattering the Myth of Costless Price Changes

Keywords: M31, M10, M20, L11, L16, E31, D40, Pricing, price setting, price adjustment, cost of price adjustment, price change management, investment in pricing processes, supply chains, customer costs of price adjustment

In this paper we argue that pricing is all about price changes, and that the costs of price changes are often simultaneously subtle and substantial. We discuss a framework to deal with the dynamics of changing prices. This framework incorporates customer interpretations of price changes, an awareness of the organizational costs of price changes, investments in future pricing processes, and an understanding of the role that supply chains play in price change strategy. The framework can be used at the tactical level to improve the specific price changes chosen and made, at the managerial level to decide whether or not to make a particular price change at all, and at the strategic level to determine what price adjustment processes should be invested in to improve pricing effectiveness in the future.

Pricing In Today's Marketplace Is All About Change

Pricing, in today's fast-paced, ever-changing marketplace, is all about change: from how to deal with new pricing formats on the Internet to how to change prices internationally in response to hyperinflation and the Euro. Firms are constantly forced to consider whether, when, and how to change their pricing. Consider the changes in Ford's pricing in the last two years, which includes how to do auctions on-line with suppliers, to adopting "smart pricing" with customers. Proctor & Gamble chose to change its pricing structure to Every Day Low Pricing. Retailers such as Barnes & Noble and Best Buy have had to decide how to change prices in the on-line world. Meanwhile companies such as Amazon.com have experimented with "dynamic pricing" in the same ononline environment. Companies such as Abbott Laboratories, DuPont and 3M are constantly deciding when to complicate their pricing to allow more bundles and systems offerings into their pricing mix. Internationally, Daimler-Chrysler, which has had to deal with changing prices in Europe as they adopt the new currency, the Euro, and Unilever has had to adjust prices in response to hyperinflationary pressures in Brazil, Eastern Europe and Asia. From how to change prices to be more effective in e-commerce, to international issues such as the Euro and hyperinflation, to new technologies that allow yield management and smart pricing -the biggest issue most firms face in pricing today is when, and how, to change their pricing.

The Myth of Costless Price Changes

Strangely, there is little in the pricing literature to help a manager deal with the process of changing prices. We talk as if changing prices happens magically, and that there are no costs to changing prices in our firms. Studies have stated that price wars are becoming more common because managers tend to view a price change as an easy, quick, and reversible action i .

Essentially we live with a myth that "prices are easy and costless to change". Yet price changes are not easy, and they are certainly not costless. Just ask Proctor and Gamble about the substantial costs of changing to an Every Day Low Price strategy for their products.

There were huge internal costs associated with communicating, educating and convincing managers about this price change within the organization. The sales force had to be retrained to sell without promotions and the organization had to be restructured to take full advantage of this new form of pricing. P&G had to re-engineer their purchasing, engineering, manufacturing and distribution functions for value pricing to succeed. Further, it required changes in product development and the roles of both brand managers and the sales force had to be restructured. The company had to change its incentives and compensation scheme to be in line with this new form of pricing. The costs of communicating with, educating, and convincing customers were even larger. Many customers were very angry. The CEO of Stop and Shop went so far as to say that "P&G is acting like a dictator. Like all dictators they will fall. We will do everything in our power to undermine their plan". Wholesalers were also upset. SuperValu added a special surcharge to P&G products above its regular fees, and many wholesalers discontinued or stopped merchandising P&G brands. One senior P&G manager said, "I had never in my 30 years in this business seen our customer base as angry, both in what we were doing, and in how we were doing it." ii Or just ask executives at Amazon.com. The customer outrage at the price changes being made by Amazon.com with their experiments in dynamic pricing was immense. The outcry was so large that they had to rescind their pricing policy immediately, and issue both public apologies and offer money back to those customers who were affected.

Internationally, just ask executives for companies selling in Europe dealing with the Euro. Jacques-Etienne de T'Serclaes, partner at PriceWaterhouseCoopers in Paris, and formerly the managing director of Euromarche, states that firms will incur "major up-front costs in implementing the changeover to the new currency". They will have to "train their workers … modify their computer systems and checkout machines. They will have to re-price everything in their stores, and in most cases, maintain two prices for each product -the new Euro price and the old national price." Manfred Gentz, a member of the Board of Management of Daimler-Chrysler, in Stutgart Germany was appointed to lead Daimler-Chrysler's Euro initiative. Gentz stated that the costs of price changeover to the new currency has been substantial and that "Approximately 1,500 of our employees are involved in euro-related projects, and we expect to spend DM 200 million on the changeover." iii Even academics agree. According to the literature on the economics of price adjustment, prices are often very costly to change. Recent field studies have documented that the process of changing prices can be very expensive whether in retail markets or industrial markets. Further, the most important costs of changing prices are the time and attention required of managers to gather the relevant information and to make and implement decisions and preparing customers about the price changes. iv

Emerging Perspectives on Managing Price Changes

Fortunately for managers, there is an emerging literature in marketing and economics that can help them know when a price change is appropriate, and how to change prices most effectively.

In this paper we'll draw on that literature, and on experiences from firms who have faced the challenge of pricing, to show you how to deal more effectively with changing prices at your firm.

From e-commerce to international markets, this perspective on the dynamics of pricing offers managers new tools and perspectives to tackle the kinds of pricing challenges they'll be facing in the years ahead. We develop a framework for understanding the variety of customer, supply chain, and company aspects of changing prices. This framework is valuable at the tactical level for people making specific pricing decisions, at the managerial level where firms set up pricing processes, and at the strategic level where an understanding of pricing dynamics is critical to the long-term viability of a firm.

Be Aware of the Costs of Changing Price Within Your Organization

Changing prices can impose hidden costs throughout your firm. This may seem surprising at first, as it was to a Coca-Cola manager, who's initial reaction to this suggestion was: "they're not that high here", but on further reflection realized that: "the more I think about it, our costs are high" and after measuring them, found that in fact they were much larger than he had supposed.

The first inherent cost that many managers experience in changing prices is simple physical costs. These costs can be defined as the costs incurred in the actual physical act of changing prices. Originally these costs were called "menu costs" in the economics literature because they represented the literal costs of altering an existing menu of posted prices v . Large retailers such as Best Buy, Target, and Tesco experience these physical costs on a weekly basis through the labor costs associated with changing thousands of shelf prices within their stores. Another way in which these costs are often experienced by firms such as 3M, Ericsson, and Xerox is through the costs of producing, printing, and distributing their price books. These costs can be substantial. In the retail grocery industry the costs of changing prices is over $100,000 annually per store, generating millions of dollars in costs for a major chain, and taking up as much as 40% of the reported profits for some of these chains vi .

Another source of costs are managerial costs. Managerial costs are defined as "the time and attention required of managers to gather the relevant information and to make and implement decisions." vii Typically these costs are incurred within an organization as a result of three distinct activities: information gathering, decision-making, and communication. viii Initially, it is important for companies to gather information on their production and selling costs, competitive actions, and their customers' likely reactions to price changes. Usually this information resides in many places throughout an organization. Accounting and finance have the cost information, the sales force has customer and competitive information, and marketing has the other sources of customer and market information. MIS must help set up systems and software to allow managers to gather, store, evaluate and communicate this information in the company.

Second, managers need to analyze this data and evaluate the benefits of various pricing actions and reactions. Actuaries at companies like Prudential spend a great deal of time analyzing the prices of their product offerings looking at costs, actuarial tables, competitive prices, customer information and company goals. The process of evaluating their price changes can take months.

At one company the pricing manager lamented that "the pricing season lasts longer than the NFL". Aside from the enormous amount of time, many people throughout the organization can be involved in analyzing pricing data. At Proctor and Gamble, for example, there are pricing specialists who support brand managers who make pricing decisions. Particularly large price changes must be approved by the board. Upper management also sets goals and objectives for pricing, handles internal disputes about pricing strategies, and deals with customers wanting to complain about or renegotiate prices. Upper management often has to resolve conflicting views of pricing between the corporate managers and the sales force. Another factor in the managerial analysis costs is the frequency of price change decisions. In large industrial firms, like 3M or Abbott Laboratories, this frequency is often annual, whereas in the retail business like Safeway, the frequency of price changes runs on a weekly basis. Price change decisions can even be made on a daily level, as is the case at American Airlines with their yield management systems. The combination of the time committed to a price change, the number of employees that are involved, and the frequency with which these decisions are made can add up to enormous managerial costs during the analysis stage.

Third, price changes have to be sold or communicated within the firm. Price changes must be communicated internally to upper management, to the sales force, and to other employees. In each case, not only must the prices themselves be communicated, but also the logic behind the change. This is partly so that members of the organization can make sense of the price change, and also because many of these employees will eventually be responsible for communicating this logic externally to customers. This communication requires preparation, and often results in long hours of discussion and education across the organization. For example, when DHL was attempting to revise its pricing, the Worldwide Sales and Marketing Director had to communicate his decisions to country managers and their staff in over 50 countries. Each country's managers had different reactions to these changes. This created an immense communication task for DHL, and its managers.

Both physical costs and managerial costs make up the total costs of price changes within a firm.

In general, despite their relative subtlety, the managerial costs dwarf the physical costs of price change and are by far the more important costs of adjustment ix . One recent study estimates managerial costs to be over six times the magnitude of the physical costs incurred in firms that were observed changing prices x . It is important for managers to be aware that more visible physical costs may mask much larger managerial costs. For example, if bricks and mortar retailers such as Best Buy or Barnes and Noble were to only look at the physical costs of pricing they could easily change prices much more frequently on their web pages than in their stores. The internet, however, does not necessarily reduce the managerial costs inherent in a price change. In fact, quite the opposite was true for both Barnes and Noble and Best Buy. Their attempts to set "click" prices lower than the "brick" prices were initially plagued by internal resistance from their offline businesses fearing cannibalization. The internet can actually increase the internal organizational costs of price adjustment, due to the added complexity of dealing with e-prices and in-store pricing, the added data from people buying through web sites, and the additional knowledge and systems that are required to understand e-buying. It is a trait of many new technologies (such as electronic shelf labels, Coke's automatic vending machine, and the internet) to claim that they can lower the costs of changing price. However, these technologies actually only reduce the physical costs of changing price. It is not clear whether these technologies will lower the managerial and previously mentioned customer costs. Yet it is these costs that form the vast majority of the costs incurred in changing price.

Managers must be fully aware of the full range of managerial costs that may exist within their organizations when they change their prices. By being aware of these costs you are less likely to jump to the newest fad in pricing, and you are less likely to rely on price cuts as an initial response to competitive actions. Further, these costs may limit your company's ability to react to price changes effectively. Managers considering new pricing formats, from yield management to bundling/systems selling should be aware that the costs of changing pricing formats especially the internal organizational and customer preparation costs can be substantially higher than the costs to change prices within an existing pricing format. For example, salespeople at companies like Signode, John Deere and Abbott Laboratories complain that price change processes requires many levels of authorization and therefore cause large delays in the price change decisions. This is crucial because in many cases an inability to react to price changes effectively can cost lost sales. An understanding of managerial costs is critical in understanding whether a price change should be undertaken and also how it can be most effectively implemented.

Be Ready to Invest in Changing the Way You Change Prices

It would be a mistake to portray the costs of changing prices as static limitations that every manager must accommodate into their pricing strategy. Aside from identifying the current costs of changing prices, firms can also strategically modify their pricing processes in order to reduce the costs that will be incurred in future price changes. Firms can reduce the number of people involved in the pricing process, invest in systems that improve the flow of information among participants in the pricing process, and invest in training managers so that they are more effective with the time and analysis they spend on pricing. Creating more efficient pricing systems can save a firm money and simultaneously give it a competitive advantage in pricing. For example, American Airlines estimated that the cost savings it could gain by reducing its number of fares from 700,000 to 500,000 could reach $25,000,000 annually and reinforce their position as a price leader in the market xi .

One of the most natural places to think about re-engineering these costs is in firms in economies facing inflation and hyperinflation. Firms in countries such as Brazil, Turkey, Eastern Europe and Asian countries such as Korea and Japan, adopt a variety of activities to reduce their costs of changing prices. In Israel in the 1980's stores would go from putting prices on each product to putting prices on a chalk board at the front of the store, by the checkout stands, so that prices could be changed more easily. Another method that Israeli bookstores invented to reduce the menu cost caused by the need to frequently adjust prices because of the hyperinflation was to group books by price groups and assign two digit code numbers to the books in each group.

Afterwards, to change the prices of the books they simply altered the price that corresponded to each price group thus saving time and, more importantly, the physical costs of changing price.

Another process to reduce the cost of adjusting prices is known as "dollarization" xii , which refers to the tendency in inflationary economies to post prices in foreign currency units, in this case dollars, that remain stable. As the domestic currency depreciates and thus looses value, there is a need to adjust prices upward to keep the real prices stable. If the value of the US dollar remains stable, then by quoting prices in the US dollars, the seller eliminates the need to adjust the price.

The adjustment takes places automatically as the price of the US dollar in terms of the domestic currency increases. This practice of dollarization was undertaken by firms in Israel during periods of hyperinflation. Prices of durable goods, electronics, and houses were always listed in dollars, from hundreds to thousand of dollars per item. This was especially interesting given that, by law, no-one in Israel was allowed to hold more than $100 U.S. dollars demonstrating that although the prices were listed and calculated in dollars, they were being paid for in Shekels.

It is important to note that a firm may need to invest money today in order to create more efficient pricing processes xiii and thus reduce costs tomorrow. A recent study xiv identified three types of investments that firms can make to improve their pricing processes: human capital, systems capital, and social capital. Human capital refers to investments made in the knowledge and skills of employees engaged in pricing activities. For example, Abbott Laboratories developed a specific pricing training course for all the members of one of their divisions.

Systems capital refers to investments made in the hardware and software used to facilitate pricing processes. For example, one major automotive supplier invested millions of dollars in new software systems to analyze the financial implications of price changes. In future years this reduced the managerial time and labor spent on price adjustment substantially. Social capital refers to investments made in the communication and organization structure and culture that unites the different participants in a particular firm involved in pricing activity. For example, a pricing manager at a major automotive manufacturer created pricing teams drawn from key participants from all over the company in order to specifically create better interactions and communication around pricing decisions. Regardless of the actual investments made, these examples highlight the rich array of potential solutions that are available to managers who attempt to improve their pricing processes and thus reduce the costs of changing price in the future.

Understand How Your Supply Chain Experiences Price Changes

When prices are changed they can have an enormous impact on your supply chain partners. At SuperValu, the largest wholesaler in the United States, the senior pricing manager stated: "Whenever a supplier like Kraft changes their prices we have to evaluate what new price we charge our retailers, and then our retailers have to make similar calculations." Thus, a price change by Kraft created costs for their customers, like Supervalu, and their customers' customers, like Kowalskis. Essentially a price change "ripples" down through the supply chain.

At one large supplier of industrial parts the management lowered its list prices, thinking that this would be well received by its customers. But many of these customers were actually upset by this price cut because their computer systems were only set up to deal with price increases. In this instance the price decrease would have proved costly because each decrease would have had to have been entered by hand into the system. Interestingly, many managers are only conscious of the costs that they incur when their supplier changes prices to them. They are not cognizant of the costs that they create for their customers when they change their prices. Many times channel efficiencies can be obtained and customer relationships can be extended when managers take a broader view of the costs of changing price throughout their supply chain.

On a more mercenary level, it is also possible for a manager to use their cognizance of the pricing change costs of their supply chain partner to their pecuniary advantage. Consider an example of the supply chain in the grocery industry. One manager at IRI used his understanding of these costs to make additional profits for his clients. He realized from his data that retailers incurred costs from small price changes and therefore wouldn't always change their retail prices in response to small price changes from the manufacturer. These sizes ranged from a nickel to a quarter depending on the product category. He counseled his clients against small price decreases because they wouldn't be passed on to the end consumers. He also supported small price increases because they wouldn't lead to higher prices for end customers. As a general rule, if you're going to lower prices be certain that there is no place in your supply chain where the costs of price change can become barriers to getting those price reductions to move to the end customers. xv

Be Sensitive to Customer Interpretations of Price Changes

Changing prices can be a source of customer frustration if they view the changes as unfair. For example, Coke recently considered using new technologies to allow their vending machines to change prices based on the temperature. Chairman Doug Ivester was quoted as telling a Brazilian magazine that people watching, say, a sports event in summer heat would naturally develop a powerful craving for a drink. "So it's fair that it should be more expensive … The machine will simply make this process automatic." The customer reaction to this idea was swift and intensely negative. In fact, when Ivester was forced out in December, many media sources partly attributed it to the public relations fiasco. Coke immediately dropped all interest in trying these kinds of price changes. xvi Similarly Amazon.com began experimenting with changing prices by customer on their web site.

They set higher prices to loyal customers, under the assumption that they valued Amazon's services and had a stronger relationship with Amazon. Yet once they were discovered to be changing prices this way, there was a huge public outcry with a number of loyal Amazon customers stating that they would never buy from Amazon again. Firms such as Eddie Bauer and Fingerhut have faced similar problems when they have set different prices on their catalog versus their prices on the web. They are concerned that customers will be frustrated to see different prices between the two formats. So if it doesn't make sense to change prices on the catalogue it won't be done on the web.

Price changes can also be perceived as unfair by customers during periods of currency changes.

For instance, Jacques-Etienne de T'Serclaes, partner at Price Waterhouse Coopers in Paris, and formerly the managing director of Euromarche, talking about the European conversion to the Euro, states that "The way shoppers behave when confronted with the new currency will have immediate and lasting repercussions for retailers, managers and the entire European economy." He suggests that the new currency will "disorient people", have a "strong psychological impact", and that customers "will be suspicious that retailers are using rounding to cheat them". xvii It is clear from these examples that a manager must be able to predict how different markets will react to your price changes. This means more than simple estimates. It means using lead users, market research, previous price changes, to accurately anticipate your customers' likely responses. Managers must accept that there may be irrational or emotional responses to a price change that have been made very rationally and for good economic reasons. If price changes are associated with changes in costs or with maintaining the business in response to competitive pressures then customers are more likely to perceive price changes as fair. In contrast, however, if these price changes are associated with taking advantage of customers' value, or their lack of price sensitivity, or the lack of competitive alternatives in the market, then they are perceived to be unfair. xviii The key for managers is to attempt to understand the way in which a price change will be interpreted by the market and to accept the fact that different customers, in different market segments, may well perceive exactly the same price change in an entirely different way. In our field work, for example, we visited the top ten customers for one particular client. The client had recently lowered all their list prices for a particular product line in an attempt to signal to customers that their products were competitive in this marketplace. Yet each customer, when confronted with this price change, developed a completely different interpretation of the price decrease. One customer suggested that the manufacturer must be going out of business, another customer thought the manufacturer anticipated a new competitor in the market, a third customer was convinced that the price change was designed to aid a different distributor at their expense.

These very different interpretations could often be attributed to what was happening in each customer's particular market. For example, the first customer was going out of business, the second was facing a new market entrant, and the third was struggling to negotiate with the manufacturer. Looking into your customers' environments and understanding their issues from their perspective is often critical in understanding how to communicate a price change.

Another way that customer interpretations of prices are encountered is as "norms". Sometimes the real cost of a price change is that it creates a precedent or a market expectation for future price changes. Pricing actions in one period therefore have repercussions in future periods since they create a norm that is hard to change. Some managers describe cutting prices as "feeding the animal." A classic example of this is the pressure most managers experience in using sales promotions to increase sales. Eventually the overuse of these promotions can create customer norms in which a sales promotion is expected, indeed demanded, before purchase will occur xix .

These customer norms are also a cause of falling prices in the computer and other high technology industries today. Conversely, customers can also develop norms that expect increasing rather than decreasing price changes. One company we studied had been raising prices for years, but now wanted to lower prices. When confronted with the managerial suggestion to lower prices, the sales force asked management to raise prices instead. In effect, price increases had become the norm for their industry and the sales managers were afraid of the effect that changing this norm would have on future price changes and negotiations with their customers.

Managers can often form their own interpretation of whether a price change is good or bad in isolation from the market. In reality, all price changes are interpreted by customers through a lens of their existing pricing norms.

Too often firms concentrate on the level of the price change at the expense of the explanation behind it. At a minimum this suggests that firms should invest in continually monitoring the pricing norms that are manifest in the market. It also suggests that firms should allocate resources to communicating with customers in order to deliver a coherent message when changing prices.

As the examples above illustrate, it is critical for firms to communicate the logic behind their price changes so that customers can make sense of these changes in the way that the firm intended. Finally, in some situations an understanding of customer interpretations of price changes may also constrain a firm to not change price. Coke and Amazon.com have both publicly stated that, based on their past experiences, they would not change prices in this manner again.

Shatter the Myth of Costless Pricing Within Your Organization

In response to the effectiveness of Walmart's every day low pricing strategy Sears launched their version called "Everyday Fair Pricing". Yet adjusting to this new pricing format imposed substantial costs on Sears. Externally, they needed to communicate this change to customers who had prevailing price norms related to Sears existing pricing policies. The communication task turned out to be more difficult and expensive than they had expected. There were serious customer concerns with the apparent fairness of the new pricing scheme and these concerns were exacerbated by competitors like J.C. Pennys who ran ads asking consumers: "If Sears are pricing fairly now, how were they pricing to you over the last one hundred years?". Internally Sears had to change their systems, knowledge, and culture to be able to undertake EDFP effectively. In the end Sears had to drop Everyday Fair Pricing, despite having paid for many of the costs that this change in pricing strategy imposed upon them. Had Sears realized that in order to successfully change their pricing format they would have to first incur these customer and managerial costs, perhaps they would have been able to avoid this pricing fiasco.

If we have succeeded in our quest, you leave this paper with a different view of pricing than when you began. First, you understand that pricing is all about price changes, and that these changes are often simultaneously subtle and substantial. This awareness alone will help you avoid the kinds of mistakes that Amazon.com, Coca-Cola, and Sears have experienced. Second, you leave with a framework to deal with the dynamics of changing prices. This framework incorporates customer interpretations of price changes, an awareness of the organizational costs of price changes, investments in future pricing processes, and an understanding of the role that supply chains play in price change strategy. The framework can be used at the tactical level to improve the specific price changes you make, at the managerial level to decide whether or not to make a particular price change at all, and at the strategic level to determine what price adjustment processes should be invested in to improve pricing effectiveness in the future.

We challenge you to shatter the myth of costless pricing in your organization.

vii Ibid (Ball and Mankiw 1994, p. 142).

viii These suggestions are based on the field research undertaken by [START_REF] Zbaracki | Managerial and Customer Costs of Price Adjustment: Direct Evidence from Industrial Markets[END_REF], "Managerial and Customer Costs of Price Adjustment: Direct Evidence from Industrial Markets", Review of Economics and Statistics, forthcoming.

ix Ibid (Ball and Mankiw 1994, p. 142).

x Ibid (Zbaracki et. al., forthcoming). xiv Mark Zbaracki, Mark Ritson, Daniel Levy, Shantanu Dutta and Mark Bergen (2002), "Pricing as a Strategic Capability", Sloan Management Review.

xv We find exactly this pattern of small wholesale price adjustments in "Asymmetric Wholesale

  xi Alvin J. Silk and Steven C. Michael, "American Airlines' Value Pricing (A)". HBS Case Study: 0-594-001. xii Alan Chen et al, "A Behavioral Explanation for the Use of Payments During Hyperinflation", University of Minnesota Working Paper 326-B. xiii Dutta, Shantanu, Mark Bergen and Mark Zbaracki (2003), ""Pricing Process as a Capability: A Resource Based Perspective", 2003, Strategic Management Journal.

  Price Adjustment: Downstream Menu Costs and Upstream Channel Pricing" (Sourav Ray, Haipeng Chen, Mark Bergen and Daniel Levy), currently under revise and resubmit at Marketing Science. xvi Coca-Cola's New Vending Machine (A): Pricing to Capture Value or Not? HBS 9-500-068; Los Angeles Times 2 Oct 2000.

  17

xvii

  Ibid Nicholas G. Carr xviii Richard Thaler, Daniel Kahneman and Jack Knetsch, "Fairness as a Constraint on Profit-Seeking: Entitlements in the Market", American Economic Review, 1986. xix The Double Jeopardy of Sales Promotions, John Phillip Jones, Harvard Business Review, 1990 (Sept / Oct), p. 2-9.