Wk 11 Supplement

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STICKY PRICES IN THE EURO AREA:A SUMMARY OF NEW MICRO-EVIDENCE

Luis J. lvarezBanco de Espaa

Emmanuel DhyneBanque Nationale de Belgique

Marco HoeberichtsDe Nederlandsche Bank

Claudia KwapilOesterreichische Nationalbank

Herv Le BihanBanque de France

Patrick LnnemannBanque Centrale du Luxembourg

Fernando MartinsBanco de Portugal

Roberto SabbatiniBanca dItalia

Harald StahlDeutsche Bundesbank

Philip VermeulenEuropean Central Bank

Jouko VilmunenBank of Finland

AbstractThis paper summarises the vast evidence on micro price-setting recently obtained for euro areacountries. We consider studies with micro data on consumer and producer prices, as well assurvey information. The main findings are: (1) prices in the euro area are sticky and stickierthan in the US; (2) downward price rigidity is only slightly more marked than upward pricerigidity; (3) heterogeneity and asymmetries are observed in price-setting; and (4) the relevanceof theories that explain price stickiness, such as implicit or explicit contracts, marginal costs,and coordination failure, is confirmed, whereas menu costs, pricing thresholds, and costlyinformation explanations are judged much less relevant by firms. (JEL: C25, D40, E31)

Acknowledgments: We are grateful to national statistical institutes for providing the individualprice records, all co-authors of national papers, all members of the Eurosystem Inflation PersistenceNetwork (IPN), especially Silvia Fabiani, Jordi Gal, Vitor Gaspar, Ignacio Hernando, JohannesHoffmann, Thomas Math, Frank Smets, and Giovanni Veronese, as well as participants at the 2005meeting of the European Economic Association, a CEMFI seminar, and the Universit de ToulouseT2M 2006 conference for helpful comments and suggestions. The views expressed in this paper arethose of the authors and do not necessarily reflect the views of the central banks with which they areaffiliated.E-mail addresses: L. J. lvarez: [email protected]; Emmanuel Dhyne: [email protected];Marco Hoeberichts: [email protected]; Claudia Kwapil: [email protected]; HervLe Bihan: [email protected]; Patrick Lnnemann: [email protected];Fernando Martins: [email protected]; Roberto Sabbatini: [email protected]; Harald Stahl: [email protected]; Philip Vermeulen: [email protected]; Jouko Vilmunen: [email protected]

Journal of the European Economic Association April-May 2006 4(23):575584


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576 Journal of the European Economic Association

1. Introduction

A better empirical understanding of individual price-setting is crucial for buildingmacroeconomic models of inflation with adequate microeconomic foundationsthat may help in the design of monetary policy.1 However, micro-founded macro

models of inflation are typically based on highly stylised assumptions on firmspricing behaviour and implications for inflation dynamics depend on assumedmicro price-setting. In addition, the speed of adjustment of inflation to shocksto the economy is directly linked to the speed of price adjustment of individualagents.

This paper brings together original evidence on price-setting in the euro areabased on recently available individual price data underlying official consumer(CPI) and producer (PPI) price indices, as well as survey information.2 These

empirical analyses have been produced in the context of the Inflation PersistenceNetwork (IPN), a large research effort conducted by economists of the Eurosys-tem. Available databases for consumer prices and producer prices contain severalmillion monthly price quotes for 10 countries (Austria, Belgium, Finland, France,Germany, Italy, Luxembourg, the Netherlands, Portugal, and Spain) in the caseof the CPI and 5 countries (Belgium, Germany, Italy, Portugal, and Spain) inthe case of the PPI. The typical CPI and PPI quantitative information used isthe price trajectory associated to one particular product sold in one particular

outlet (in the case of CPI) or by one specific manufacturing firm (in the case ofPPI). Examples of price trajectories taken from the Belgian CPI and Italian PPIdatasets are given in Figure 1. Such large data sets are particularly well-suitedfor the analysis of price-setting behaviour, because they have a comprehensivecoverage of retail and manufacturing prices and extend over several years. Thiscontrasts with most previous micro-studies (e.g., Cecchetti 1986 or Carlton 1986),which mostly focused on very specific products or markets. The third source ofinformation stems from surveys to firms, following Blinder et al. (1998). More

than 11,000 firms from 9 countries (Austria, Belgium, France, Germany, Italy,Luxembourg, the Netherlands, Portugal, and Spain) were questioned about theirprice-setting practices.

The remainder of the paper is organised as follows. Section 2 presentsa set of stylised facts describing firms price-setting practices with CPI andPPI data. Section 3 presents interesting survey information and Section 4concludes.

1. See Angeloni et al. (2006) for a discussion of the implications of our findings for macroeconomicmodeling and the design of monetary policy.2. See the summaries by Dhyne et al. (2006), Vermeulen et al. (2005), and Fabiani et al. (2005)and references to national papers on which they are based therein.


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lvarez et al. Sticky Prices in the Euro Area 577

Figure 1. Examples of individual price trajectories.Note: Price trajectories from the Belgian CPI and Italian PPI databases (See Aucremanne and Dhyne 2004 and Sabbatiniet al. 2005). Prices are in Belgian Francs and euro, respectively.

2. Firms Price-setting Practices: Stylised Facts

The following stylised facts emerge consistently in the different countriesconsidered.

Firms Change their Prices Rather Infrequently. On average, 15% of consumerprices are changed in a given month in the euro area compared to 25% in the US(Table 1). Producer prices in the euro area are adjusted slightly more frequently:around 20% are changed each month. These frequencies imply average pricedurations close to one year in the euro area and slightly above half a year inthe US. According to surveys, price durations are also longer in the euro areathan in the US. These results are also in line with implied durations derived fromNew Keynesian Phillips curves for the euro area and the US by Gal, Gertler, andLpez-Salido (2001, 2003). In contrast, Lnnemann and Wintr (2005) find thatin the euro area prices set on the Internet of products with high technologicalcontent change much more frequently than those sold by traditional channels.Moreover, frequencies of price adjustment do not differ substantially between theUS and the 3 largest euro area countries.

Several factors can be put forward to explain the discrepancy in the frequencyof price changes between the euro area and the US: (i) the level and variabilityof inflation, (ii) the structure and degree of competition of the distribution sector,(iii) price collecting methods by statistical institutes, (iv) the frequency and mag-nitude of cost and demand shocks, and (v) the composition of the consumptionbasket. Next we consider each of these arguments.

First, both the level and the volatility of inflation in the sample period weresomewhat higher in the US than in the euro area. Second, small corner shops,which change their prices less frequently than supermarkets (e.g., Baudry et al.,2004), have a higher market share in euro area countries than in the US (Pilat1997). Third, there are methodological differences in price-collecting procedures
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Table 1. Measures of price stickiness in the euro area and the US (% per month unlessotherwise stated).

Statistics Euro area US

CPI Frequency 15.1 24.8Average duration (months) 13.0 6.7Median duration (months) 10.6 4.6

PPI Frequency 20.0 n.aSurveys Frequency 15.9 20.8

Average duration ( months) 10.8 8.3NKPC Average durations ( months) 13.519.2 7.28.4Internet prices Frequency 79.2 64.3

Notes: Dhyne et al. (2006) for the euro area, Bils and Klenow (2004) for the US. Euro area refers to the aggregate ofAustria, Belgium, Finland, France, Germany, Italy, Luxembourg, the Netherlands, Portugal, and Spain.

Vermeulen et al. (2005). Euro area corresponds to the aggregate of Belgium, Germany, Italy, Portugal, and Spain.Fabiani et al. (2005) for the euro area and Blinder et al. (1998) for the US. Euro area refers to the aggregate of Austria,

Belgium, France, Germany, Italy, Luxembourg, the Netherlands, Portugal, and Spain. Converted from original intervalgrouped figures.

Gali,Gertler, and Lpez-Salido (2001, 2003). Estimates correspondto the GDP deflator and are convertedfrom originalquarterly figures.

Lnnemann and Wintr (2005). Euro area corresponds to the aggregate of Germany, France, and Italy and are convertedfrom original daily figures.

by the different statistical institutes; in particular, price changes due to sales andpromotions were not considered in most euro area countries, in contrast with theUS.Fourth,ahighervariabilityofwagesandotherinputpricesintheUSmayhelp

explain more frequent price changes than in the euro area. Finally, differences inconsumption patterns do not explain the price flexibility gap, as the expenditureshare of the more flexible components of the CPI is larger in the euro area thanin the US.

Price Adjustment is Heterogeneous Across Sectors. Firms that change theirprices very frequently coexist with those keeping them constant for relativelylong periods (Table 2). Specifically, CPI price changes are relatively frequent forenergy and unprocessed food products, but infrequent for services and, to a lesserextent, for non-energy industrial goods. In turn, processed food products occupyan intermediate situation. The same ranking of product categories is also foundin the US. As regards producer prices, energy and food products are also char-acterised by more frequent price changes, whereas capital goods and durablesare the stickier components. This suggests that the frequency of price changesdecreases with the degree of sophistication of the product. Finally, survey evi-dence points out that prices of services other than trade are stickier than thosefor manufacturing goods and trade. Within trade, prices of food and energy arechanged more frequently than for other goods or services (lvarez and Hernando2005), in line with CPI evidence.

Heterogeneity is found to be related to differences in costs and market com-petition. For instance, the degree of consumer price flexibility is related to thevolatility of input prices (Hoffmann and Kurz-Kim 2006) and differences in the


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Table 2. Frequency of price changes by type of good (% per month).

Non-energyUnprocessed Processed industrial

CPI food food goods Energy Services

Euro area 28 14 9 78 6US 48 27 22 74 15

ConsumerDurable non durable Intermediate Capital

PPI Food goods non food Energy goods goods

Euro area 26 10 12 70 22 9

Surveys Goods Trade Other services

Euro area 16 18 11

Notes: Dhyne et al. (2006) for the euro area, Bils and Klenow (2004) for the US.Vermeulen et al. (2005).Fabiani et al. (2005). See additional information in Table 1.

cost structure across sectors help explain differences in the degree of producerprice flexibility (lvarez, Burriel, and Hernando 2005 and Sabbatini et al. 2005),a result also found with survey data (lvarez and Hernando 2005). Specifically,labour intensity negatively affects the frequency of price adjustmentsgiven thatwages are typically changed once a yearwhereas the share of costs of interme-diate goods in variable costs affects it positively. Regarding market competition,

survey evidence shows that sectors in which the perceived degree of competitionis high feature less sticky prices (lvarez and Hernando 2005, 2006). Similarly,the frequency of producer price changes is positively related to import penetration(lvarez, Burriel, and Hernando 2005). Moreover, consumer price flexibility ispositively related to the number of competitors and the frequency of price reduc-tions is negatively affected by the market share (Lnnemann and Math 2005).

Price Decreases are Common. Around 40% of CPI and 45% of PPI monthly

price changes are price decreases (Table 3). This somewhat surprising fact is inline with the evidence obtained by Klenow and Kryvstov (2005) for the US andcharacterises all euro area countries. Nevertheless, large sectoral discrepanciesare again observed. Particularly, price decreases are relatively uncommon in theservice sector, where only 1 price change out of 5 is a price reduction (Dhyneet al. 2006). This may reflect that wages do not go down frequently.

Price Changes are Sizeable. The average size of price increases (8.2%) anddecreases (10.0%) are high relative to the inflation rate. In the US, the size of CPIprice decreases is also slightly larger than that of price increases. Mean sizes ofPPI price increases and decreases are smaller than for the CPI.

There is also sectoral heterogeneity in the size of price changes. Prices ofunprocessed food products change by a large amount, whereas energy prices


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Table 3. Frequency and size of price increases and price decreases (% per month).

CPI Euro area US

Price increases Frequency 8.3 16.1Average size 8.2 12.7

Price decreases Frequency 5.9 13.2Average size 10.0 14.1

PPI

Price increases Frequency 11.0Price decreases Frequency 9.0

Notes: Dhyne et al. (2006) for the euro area, Klenow and Kryvstov (2005) for the US.Vermeulen et al. (2005). See additional information in Table 1.

change very often but by a limited amount. This is consistent with the pronounced

variability of marginal costs and the large incidence of indirect taxation on theseproducts.

3. The Mechanics of Price-setting

This section highlights some features of price-setting practices drawing on thesurvey evidence summarised in Fabiani et al. (2005).

Competition and Price-setting Rules. Surveysshowthat,eventhoughmostfirmsoperate in competitive environments, they still possess some degree of price-setting autonomy. Indeed, mark-up pricing is the dominant pricing rule in the euroarea (Table 4). Furthermore, as expected, the use of mark-up pricing increasesas the perceived level of competition goes down. In addition, firms facing strongcompetitive pressures tend to adjust their prices more frequently.

Asymmetries in Price Reaction to Shocks. Surveys show that cost shocks aremore relevant in driving prices upwards than downwards (Peltzman 2000),whereas changes in market conditions (in demand and competitors prices) mat-ter more for price decreases. The most important factors driving prices upwardare labour and raw materials costs, although these factors are less relevant inexplaining price decreases. As regards market conditions, the competitors priceis the most important factor explaining price decreases, ranking third among theexplanations for price increases. In addition, firms in highly competitive marketsare more likely to respond to shocks, in particular to demand ones.

The time lag of a price reaction after a shock by the median firm lies between1 and 3 months. Furthermore, there is no evidence that prices adjust faster upwardthan downward, or respond more quickly to cost shocks than to demand shocks.Both aspects are in line with the evidence for the US (Blinder et al. 1998).


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Table 4. Survey evidence on price setting (mean scores, unless otherwise stated).

Use of price setting rules (percentages)

Markup 54Competitors price 27Other 18

Importance of factors driving price increases Importance of factors driving price decreasesCosts of raw materials 3.0 Costs of raw materials 2.5Labour costs 3.0 Labour costs 2.1Competitors price 2.4 Competitors price 2.8Demand 2.2 Demand 2.5Financial costs 2.2 Financial costs 1.9

Source: Fabiani et al. (2005).Note: Mean scores correspond to a scale from 1 (not important) to 4 (very important).

Time-dependent versus State-dependent Price Reviewing. Firms apply bothtime-dependent rules (i.e., they review prices with a given periodicity) and state-dependent rules (i.e., in response to market conditions). Around one third followpure time-dependent strategies, whereas the rest use some sort of state-dependentrules (Table 5). Among these, firms that mainly follow time-dependent rules, butchange prices in the case of specific events predominate. These findings are in linewith those obtained for the US, where the share of firms following time-dependentrules is 40%.

Indirect evidence of time and state dependence is also found with CPI andPPI data. For instance, the frequency of price adjustment or the probability ofprice change is generally found to be related to sectoral or aggregate price orwage developments, changes in indirect taxation, and the euro-cash changeover(Dhyne et al. 2006). Moreover, prices exhibit a seasonal pattern: Prices are morelikely to be changed in January or in September. This may be interpreted as a signof time dependence, especially given that a fraction of retailers keep their pricesunchanged for one year, although seasonality in demand or costs could also lead

to a seasonal pattern in price changes.

Information Set and Market Behaviour. Firms were also asked to report theinformation set used in reviewing their prices, with a view to determiningthe appropriateness of considering inflation a backward-looking variable, as in

Table 5. Survey evidence on price reviewing (percentages).

Price reviewing rules Information set used in price reviewsTime-dependent 34 Rule of thumb n.a.State-dependent 20 Past and present 34Both 46 Present and future 48

Past, present and future n.a.

Source: Fabiani et al. (2005).


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Table 6. Theories of price stickiness.

Euro area US(mean score) (ranking)

Implicit contracts 2.7 4Explicit contracts 2.6 5Cost-based pricing 2.6 2

Coordination failure 2.4 1Judging quality by price 2.1 12Temporary shocks 2.0Change non-price factors 1.7 3Menu costs 1.6 6Costly information 1.6Pricing thresholds 1.6 8

Sources: Euro area: Fabiani et al. (2005). US: Blinder et al. (1998).

the traditional expectations-augmented Philips curve, or as a forward-lookingvariable, as in the New Keynesian Philips curve. Around one half of firms con-sider a large information set, which includes expectations about future economicdevelopments. However, one third of firms make price decisions without usingeconomic forecasts. Further evidence that firms do not optimise when reviewingprices is available for Belgium, Luxembourg, Portugal, and Spain: Around 30%of firms use a rule of thumb (e.g., CPI or wage growth indexation) in price-setting.

Main Theories of Price Stickiness. Amongexplanationsabout thereasonswhichprevent a prompt adjustment of prices, the theory ofimplicit contracts ranks first(Table 6). This result is consistent with the fact that 70% of firms have long-termrelationships with their customers and may also explain why firms are more likelyto increase their prices in response to cost shocks than to demand shocks, as theytry not to jeopardise customer relationships.

Other explanations considered as important by firms were explicit contracts,which are costly to renegotiate, marginal costs that vary too little when costsare an important determinant in firms pricing decisions, and coordination fail-ure problems arising from the preference of firms not to change prices unlesstheir competitors do so. In contrast, alternative explanations such as menu costs,pricing thresholds, and costly information were not considered very relevant byrespondents. These results are in line with US (Blinder et al. 1998) and UK evi-dence (Hall, Walsh, and Yates 2000), although the existence of implicit or explicitcontracts is considered less important in the US than in the euro area. This couldalso partly explain the higher frequency of price changes observed in the US.

The four most relevant theories underlying price stickiness do not concern theprice review decision, suggesting that the main impediment to price adjustmentslies at the stage in which firms consider the possibility of changing the price,without necessarily taking any action. Indeed, the theory of costly informationreceived the lowest score in the euro area surveys.


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4. Conclusions

The research summarised in this paper has produced numerous new empiricalresults on the characteristics and determinants of price-setting in the euro area.The four most noticeable are the following. First, prices in the euro area are sticky

and stickier than in the US. Second, there is no apparent general downward pricerigidity: Around 40% of price changes are decreases. Third, there is evidenceof heterogeneity and of asymmetries in price-setting that suggest the need toconsider models with several sectors. Fourth, the relevance of some theoreticalexplanations is confirmed by survey analyses (explicit contracts, marginal costs,and coordination failure); others, instead, are judged much less relevant by firms(menu costs, pricing thresholds, and costly information).

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