Managerial and Decision Economics Volume 31 Issue 2-3 2010 [Doi 10.1002%2Fmde.1484] Mihai Copaciu;...

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MANAGERIAL AND DECISION ECONOMICS

Manage. Decis. Econ. 31: 235247 (2010)

Published online 24 November 2009 in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/mde.1484

Survey Evidence on Price-setting Patternsof Romanian Firms

Mihai Copaciua,, Florian Neagub and Horia Braun-Erdeic

aNational Bank of Romania, Monetary Policy and Modeling Department, Bucharest, RomaniabNational Bank of Romania, Financial Stability Department, Bucharest, Romania

cING Investment Management, Romania

This paper presents for Romanian firms the results of the first survey on price-setting patternsamong the New Member States of the EU. Diverging from Inflation Persistence Network(IPN) findings, generally small firms perceive higher competitive pressure and adopt themarket price, using a state-dependent rule, while lower perceived competition is consistentwith medium and large firms using mark-up pricing. Prices are reviewed and changed moreoften than for EMU firms and are more flexible than wages. Similar to IPN evidence,contracts are the main sources of price stickiness. The survey suggests full price transmissionof large unanticipated financial shocks. Copyrightr 2009 John Wiley & Sons, Ltd.

1. INTRODUCTION

The empirical evidence gathered to support New

Keynesian microfounded macroeconomic models

prominently those involving some type of price

stickinesshas been growing steadily in the recent

periods, looking both on aggregate and micro/firm-level data. Within this line of research, an increasing

set of studies uses a survey-based approach in

documenting various aspects of price stickiness.

The main advantage when compared with other

approaches1 lies in the fact that it allows for

additional insights and permits a clear inventory

and ranking of the causes and patterns of price

stickiness. Initiated by Blinder (1991) for the United

States, this class of research has spread considerably

on account of a number of survey-based studies

conducted within the Eurosystems Inflation

Persistence Network (IPN).2

However, when it comes to the New Member

States of the European Union (NMS), microlevel

evidence is rather scarce and, to our knowledge,

there are no studies that use a survey-based

approach.3 The present study fills this lacuna,

being the first survey among local companies

conducted for an NMS economy capturing various

price-setting patterns and comparing them with

results from developed economy surveys. Anothernovelty of this paper is using survey evidence to

capture the perceived impact of interest rate and/or

exchange rate shocks on prices and costs.

The main findings of the paper can be

summarized as follows: most Romanian firms

declare to set their prices internally; nevertheless,

they appear to be operating in a relatively high

competition environment, more prominently in the

case of small enterprises. In general, these are

predominantly market price followers, in contrast

to medium and large firms, which tend to prefer

mark-up pricing. Most of the firms surveyed use atime-dependent price-reviewing strategy with

state-dependent elements, the latter strategy

alone being adopted mostly by small firms. On

average, Romanian firms review and change prices

more often than firms surveyed by IPN studies,

with large firms being more active in adopting less

*Correspondence to: National Bank of Romania, MonetaryPolicy and Modeling Department, Bucharest, Romania.E-mail: [email protected]

Copyright r 2009 John Wiley & Sons, Ltd.


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rigid prices, probably due to nonbinding resource

constraints and higher mispricing costs. Similar to

IPN evidence, contracts in either their implicit or

explicit forms are the main sources of price

stickiness, with traditional theories (e.g. menu

costs) ranking at the bottom. Survey evidence

also suggests that wages are stickier than prices,

with around 72% of firms changing their wagesjust once per year or less. Finally, firms generally

admit to fully transmit into their prices the impact

of large unanticipated financial shocks.

Besides the general caveats of any survey-based

analysis, when interpreting our results one should

take into account the relatively low response rate

(19.83%) when compared to the average of the

IPN studies (45%4). Considering these latter

aspects and the central banks focus on CPI

inflation and its use of microfounded models in

policy research and forecasting, evidence from this

paper should be complemented by further

investigating the disaggregated data used for CPI

compilation.

The paper is organized as follows. Section 2

briefly introduces the macroeconomics background

and survey design, while Section 3 details the

results of the survey. Conclusions close the paper.

2. MACROECONOMIC BACKGROUND AND

SURVEY DESIGN

The survey was carried out with the help of the

National Bank of Romania (NBR) and the Public

Policy Center (CENPO) between September and

November, 2006. Firms were asked to refer in their

answers to their main product/service sold in the

course of the year 2005.

At that juncture, the Romanian economy has

been undergoing the transition process toward a

fully-fledged market economy, in the context of its

expected European Union (EU) accession.

Compared with the Central and Eastern Europe

(CEE) region, Romania has had a long history ofhigh and volatile inflation. However, the

20002005 period was characterized by an almost

continuous disinflation process, with inflation

declining from 40 to 50% per year to below 10%

at the end of the period mentioned. For the NBR,

which had conducted monetary policy mainly

through a strongly managed currency, the main

challenge was to reconcile its newly introduced

inflation targeting regime (since August 2005) with

the liberalization of the capital account and the

integration with EU financial markets. Another

challenge to consider has been the accommodation

of the catching-up economy, with fast expanding

domestic demand5 fuelling external imbalances

and inflation.

The population from which the sample was

drawn included all firms reporting valid balancesheets and profit reports to the fiscal authority in

June 2005, i.e. theoretically the whole population

of the Romanian firms. In order to avoid over-

representing very small firms, we followed the

approach of A lvarez and Hernando (2005) and

Martins (2005) and chose to filter out firms with

fewer than 10 employees. For this population,

stratified random sampling based on relative

number of employees was used. Firms were split

into 114 mutually exclusive strata based on firm

size and NACE sector. Small, medium and large

firms were identified using cutoffs of 10, 50 and

250 employees, respectively. Considering the fast

and overreaching changes across the Romanian

economy, the sector coverage is in our case

broader than in most of the studies carried out

within IPN, including 38 NACE sectors grouped

into six main categories: agriculture and related

activities (NACE 1, 2 and 5), manufacturing

(NACE 1537), energy (NACE 40 and 41),

constructions (NACE 45), trade, hotels and

restaurants (NACE 5052, 55), and transport

and communications (NACE 6064).

The sample of 1901 firms accounted for 10% of

the initial population in terms of employment. Out

of these, a number of 377 firms eventually

answered the questionnaire, thus producing

an answer rate of 19.83%. A post-weighting

procedure, using the number of employees as the

benchmark measure, was applied to these firms

answers, considering that the ex-post sample

displayed an overrepresentation bias in favor of

large firms.6 Throughout the paper, the reported

results pertain to the post-weighted answers.

The survey draws closely to those developed inthe context of the IPN, thus seeking to ensure a

comparable basis with their results. However,

unlike the other surveys, we test the reaction of

firms prices and costs to potential macroeconomic

shocks in the form of ranking-type questions

attached to various interest rate and exchange

rate scenarios. Otherwise indicated, firms were

asked to consider the year 2005 as the reference

period.

M. COPACIU ET AL.236

Copyright r 2009 John Wiley & Sons, Ltd. Manage. Decis. Econ. 31: 235247 (2010)

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3. SURVEY RESULTS

3.1. Product, Market and Client Type

When completing the questionnaire, firms were

asked to relate all the answers to their main

product/service, identifiable as the one that

contributed the most to the companys turnoverin 2005. The responses indicated that the main

product generated an average of 81% of firms

turnover,7 with a lower contribution for the

wholesale and retail trade sectors/large firms,

which is consistent with the larger number of

products these companies usually sell.

The main market was identified by the firms as

being the domestic one. Namely, 84% of their

turnover was generated on average from sales in

Romania, while approximately 14% indicated EU

as the main market (the general case for large

firms8 and for manufacturing and transportationfirms).

Similar to those surveyed within the IPN9

(Fabiani et al ., 2005), most Romanian firms

(around 71%) have other firms as their main

clients, while only a relatively small fraction (27%)

count on the population as representing the main

customer base, the latter aspect suggesting the

relevance of the results for the price-setting

behavior in the whole economy and not

specifically in the more CPI inflation-relevant,

consumer goods sector.

3.2. Perceived Competition

The degree of competition firms perceived is an

important variable in the price-setting process. In

a perfectly competitive environment there will be

no price rigidities as firms will set their prices equal

with marginal costs. For price rigidities to exist,

some departures from the case of perfect

competition should be in place, generally in the

form of companies exercising a certain degree of

market power. Several questions were included inthe survey in order to assess Romanian companies

perceived degree of competition either directly or

indirectly.

Our conclusions are based mainly on the

evidence obtained from the indirect questions

because answers obtained to the direct questions

were often contradictory. For instance, a number

of small firms indicated that they have a high

number of competitors and at the same time they

enjoy a market share of close to 100%, while other

firms that chose a very narrow identification of

their competitor base, e.g. only local competitors,

also indicated a low market share. A lvarez and

Hernando (2005) point out at least three reasons

why the answers to such questions might not

properly proxy the degree of competition: the

subjectivity in identifying the competitors and/orthe local market, the possibility of having fierce

competition on some oligopolistic markets and the

coexistence of a high number of competitors and

high market share over some predetermined small

area.

Indirect questions for which answers were more

reliable included those regarding the perceived

elasticity of demand to a 10% price increase and

the importance that firms attach to competitors

prices when setting their own.

When asked about the perceived elasticity of

demand to a 10% price increase, 40% of firms

estimated that the quantity sold would go down by

more than 10%, 12% indicated a unit elasticity

and 19% a below unit elasticity.10 The highest

percentage of firms reporting an above unit price

elasticity was recorded in the agricultural sector,

while the similar measure varied inversely with the

size of the firm.

As further indirect evidence, competitors prices

ranked high among factors explaining firms

decisions to change their prices, namely third in

the case of price increases and first in that of price

decreases (see Table 3, Section 3.4.2). Answers to

this question were deemed as decisive in assessing

the degree of competition in a number of similar

studies (e.g. A lvarez and Hernando, 2005, for

Spain). Besides the differentiated answers for price

decreases and increases, we also found an

asymmetry in that competitors prices were

ranked as more important by small and medium

firms when compared with the large ones.

Corroborated with answers from the previous

question, this suggests that the degree of

perceived competition is higher for small firmswhen compared to large ones, which is a

distinctively different result from that reported

by Fabiani et al. (2005) for EMU countries, where

the degree of perceived competition varies directly

with the size of the firm.

One possible explanation could be that EMU

integration has spurred higher competition for

large firms, as cross-border expansions of business

has become less costlyin other words national

SURVEY EVIDENCE ON PRICE 237


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monopolies and oligopolies have become less

relevant in the context of a Single Market.

A second point is that the challenges of European

integration and the single currency may have

stimulated smaller firms in the EMU to adopt

more client-oriented strategies, such as product

customization and niche specialization, thus being

better positioned to shrug off direct competition.Finally, the difference between Romania and IPN

countries may be artificially induced by the fact

that in some of the IPN surveys the starting cutoff

for firm selection is higher than ours.

In general, a higher autonomy in price setting is

associated with the presence of price rigidities. In

the Romanian case, despite the high perceived

competition, 63% of firms declared to have full

autonomy in setting the price of their main

product, while main customers setting directly the

prices of their suppliers ranked second with a

percentage of 29% of all firms. The latter

proportion is significantly higher than that

obtained in similar studies for Portugal and

Spain (A lvarez and Hernando, 2005, for Spain;

Martins, 2005, for Portugal) and it is mainly due

to sectors such as agriculture and transport and

communications. It is also more relevant for larger

rather than smaller firms, which is consistent with

the former having a higher relative proportion of

corporate customersforeign firms and other

large Romanian companieswith which they

nurture a stable relationship.

3.3. Price-Setting Behavior

3.3.1 The how in the pricing decision

The first four questions on pricing behavior

aimed to capture the main techniques used in the

pricing decision. As mentioned before, firms which

have authority over this decision represent 63%

of the sample. Among these, most firms prefer

either setting a markup over costs (for 43% of

these firms) or adopting the market price (for

roughly 50% of this subsample). It is worth

mentioning that compared to estimates for

the EMU or the United States, Romanian firmsdisplay a lower preference toward markup pricing

and a higher one toward market pricing. Markup

pricing is more prominent among firms in the

manufacturing sector (for 46% of these it is the

most preferred strategy)11 and especially in the

case of large firms (74% of the total), while small

firms are generally more likely to prefer market

pricing. This makes sense, as larger firms have

higher autonomy over their price-setting process

and are more likely to operate in a monopolistic

market, thus their choice of markup pricing is

more probable. This pattern is also consistent with

earlier results on perceived competition and the

higher occurrence of long-term customer relations

in the case of larger versus smaller firms. The

difference in perceived competition partly explains

the contrast between our results and those

reported for most EMU countries by Fabiani

et al. (2005), where smaller firms were more likely

to adopt markup pricing while perceiving a lower

competition when compared with large firms

(Figure 1).

Price discrimination can represent an additional

feature of the price-setting process, as some firms

may attempt to use this as a means of extracting

part of the consumer surplus. We seek to find out

whether such a strategy is used by sampled firms

by asking them if their unit price is the same for all

units sold or else depends on quantity sold or other

Figure 1. Price setting features inside the company.



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factors.12 Firms (44%) declared that they charge

the same price for all customers. This figure might

seem low at first glance, but it is in fact relatively

high when compared with EMU evidence (around

20%, according to Fabiani et al., 2005).

The New Keynesian literature stresses the

importance of forward-looking factors in

modeling macroeconomic variables such asinflation. While purely forward-looking Phillips

curves are rarely used in forecasting models, the

most widespread specification has become that of

a hybrid Phillips curve, such as the ones proposed

by Fuhrer (1997) or Smets (2003). Although we are

aware of the possible limitations of survey

evidence in this debate, we asked firms to weigh

their use of backward against forward-looking

information. Unsurprisingly, the great majority of

firms (78%) said they use a combination of past

information and price projections, which would

support a hybrid Phillips curve rather than pure

forward or backward-looking-based pricing rule.

3.3.2 The when and the how much in the pricing

decision

Both time- and state-dependent models assume

that firms operate in an environment of imperfect

competition, that is, they are price setters.

However, while time-dependent pricing models

like the ones of Taylor (1999), Calvo (1983) or

Fischer (1980), assume a constant duration of

price quotation, synchronized within store pricechanges13 with firms not being able to respond to

shocks that occur in the intervals between two

predetermined adjustments, in state-dependent

pricing models, such as those pioneered by

Sheshinski and Weiss (1977), price changes do

not depend on fixed periods of adjustment, but

rather they are triggered by comparison between

the distance to the optimal price and some

predetermined costs of adjustment. In these latter

models, prices are thus allowed to respond to

shocks and frequency of price adjustments is

random.

In order to test which of these theories seems tobetter explain Romanian firms timing of price

changes, the subjects of our survey were asked if

their prices are reviewedwithout necessarily

being changed(i) at regular time intervals, (ii)

just as a reaction to shocks, or (iii) usually at fixed

periods but also in reaction to certain events

(Figure 2).

The answers revealed that approximately 15%

of the firms appear to follow a purely time-

dependent rule, 43% follow a purely state-

dependent rule, while the rest employs a mixed

strategy. Time-dependent pricing is above average

in the case of firms from agriculture (34%) and

energy, gas and water supply (47%), which can be

explained by the seasonality of prices and by

regulatory guidelines, respectively.14 Small firms

follow mostly state-dependent strategies, while for

medium and large firms, the mixed strategy is

mostly preferred. For the latter, the proportion

preferring a time-dependent policy is slightly

above the sample average, which is consistent

with the IPN data, where the preference for time-

dependent pricing is directly proportional to firm-

size (Fabiani et al., 2005).15

Firms were also asked about the number of

price revisions and the number of price changes for

the year 2005. Although all firms were asked to

answer, the focus was on firms choosing a strategy

Figure 2. Price reviewing process: time versus state dependent elements.



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with time-dependent elements and the results

presented here refer to these. Survey answers

indicate a much lower degree of price stickiness

for Romanian firms compared to Eurosystem

countries covered by Fabiani et al. (2005). While

for the former, the average frequency of price

reviews is circa 4.4 times per year (that is

approximately once every 2.7 months), themedian frequency of price changes/reviews in the

Euro area is around once per year.16 This

difference comes as no surprise considering the

history of high inflation in Romania. Price changes

for firms following pure or mixed time-dependent

rules amounted to around 2.5 times per year (on

average every 5 months). Price reviews were thus

taking place more often than price changes,

roughly in a 2:1 ratio for most firms, with the

exception of the energy, water and gas sector

where the frequencies of reviews and changes are

equal, due to regulatory requirements. Large firms

review and change their prices much more often

than medium or small ones. Although inconsistent

with the finding on perceived competition, this

latter aspect might be the result of a stronger

concern regarding costs of mispricing, a higher

diversity of their products leading to

complementarities in price setting in case of large

firms (Table 1).

In a question related to the one on frequency of

price reviews/changes, we also asked firms about

the frequency of wage adjustments. More than half

(58%) of respondents indicated only one wage

adjustment a year (with a further 14% indicating

even less than one change a year), which suggests

that in the Romanian case, wages are much

stickier than prices. Wage stickiness is often

brought up in the context of a New Keynesian

model as an explanation of the empiricallyfounded inertia in both inflation and real output

(Blanchard and Gali, 2007).

Besides inquiring on the frequency of price

changes, we were also interested in the magnitude

of a typical price increase/decrease in 2005 and

particularly to potential asymmetries between

price increases and decreases. The choices were

grouped in four intervals centered on 8%, which is

close to the level of CPI inflation for 2005. The

results of the query suggest the existence of a

certain degree of asymmetry, as price increases are

more evenly distributed between the 04% and the

48% brackets, while price decreases are obviously

skewed toward the 04% interval (Figure 3).

This type of asymmetry is also manifest with

respect to the direction of price changes (there

were only 286 answers for the magnitude of a

typical price increase and 129 answers for the

magnitude of a typical price decrease). While

the prevalence of upward price changes in the

Romanian case is to be expected due to moderate-

to-high inflation environment, one may also

Table 1. Number of Price Reviews and Price Changes in 2005

Number of Total NACE1 NACE2 NACE3 NACE4 NACE5 NACE6 Small Medium Large

Price reviews 4.42 5.55 4.71 2.49 3.2 4.58 3.43 3.91 4.67 8.93

Price changes 2.47 1.97 2.48 2.21 2.32 2.8 1.59 2.3 2.17 5.5

Figure 3. Average size of price change.



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emphasize the role of the higher frequency and

magnitude of inflationary shocks in 2005:

administered price and excise tax hikes in April,

bad agricultural crops due to two rounds of floods,

large upswings of the international oil price and

the positive demand shock due to the introduction

of a flat income tax rate of 16%. Looking across

economic sectors, the highest proportion of largeprice increases (i.e. larger than 12%) was obtained

for firms in the public utilities sector (electricity,

gas and water supply). Together with the data on

price change frequencies for this sector, this comes

to confirm the intuition that regulated prices are

modified less often than market prices, but when

they are, they tend to come in relatively large

shocks. As for the largest price decreases, these are

mostly characteristic of firms in the agricultural

sector. This again is an intuitive result, since food

prices (especially fruit and vegetables) are known

to have a strong seasonal pattern, with large price

discounts recorded in the third-quarter of every

year.

3.4. Theories of Price Stickiness and Determinants

of Price and Wage Changes

3.4.1 The why not in pricing decisions

Different explanations have been advanced by

economists to motivate price stickiness. Our

survey listed seven such explanations for firms to

assess their importance. The choice was made byinvestigating similar studies and eliminating some

explanations, which were inappropriate for the

Romanian context.17 The tested theories, together

with the results are presented in Table 2.

The answers received to this question indicate

that only two of the above factorsthe implicit

contracts and the explicit contractswere regarded

as important (i.e. scored above 3). The implicit

contract theory assumes the existence of an invisible

mutual agreement between firms and customers that

prevents firms from changing prices. Rotemberg

(2005) argues that a reason for nominal price

rigidities is that some price changes are perceived

by consumers as unfair. Thus, firms avoid suchchanges, giving extra signals on their loyalty to

customers through periods of stable prices. Explicit

contracts theory refers to the idea that, until

eventual re-negotiation, firmclient relationships

are governed by the constraints imposed by

written contracts.

All other options scored as less important, i.e.

below the neutral threshold of 2.5. These included

quality adjustmentsreferring here mainly to

price decreases, namely to the case that a price

decrease may signal to customers a reduction in

product qualityand price readjustments. The

latter refers to firms being reluctant to change

prices in a given direction for fear of having to

change it in the opposite direction in a short period

of time.

Coordination failure theory ranked fifth

overall. According to this theory, firms hesitate

to change prices for fear of being the only ones

doing so, preferring instead to wait for others to

make the first move, which implies a high degree of

synchronization in the timing of price changes

across vendors.

Information and menu costs rank last in the

present survey, although they are often cited as

the main reasons for justifying price stickiness. The

information costs concept is part of a broader

understanding of menu costs, referring mostly to

the time and attention required of managers to

gather the relevant information and make and

implement decisions(Ball and Mankiw, 1994). The

low importance managers confer to this theory

points toward the prevalence of the rigidities in the

second stage of the price-setting process. Menu

costs theory which refer here to the narrow sense ofthe concept, namely that firms tend to keep their

prices unchanged because price changes imply

physical costs (e.g. printing new catalogues,

changing the price tags, changing the information

posted on their websites) has the lowest importance

in explaining price stickiness.

Overall, the results are consistent with those

showing the dominance of long-term customer

relationships (for 85% of firms) and other firms

Table 2. Most Important Factors for PriceStickiness

Factor Mean p-value

Implicit contracts 3.12 0.97Explicit contracts 3.10 0Quality adjustments 2.19 0.43Price readjustments 2.15 0.02Coordination failure 1.97 0Information costs 1.74 0.01Menu costs 1.62

Note: Firms were asked to indicate the importance of eachoption in a scale ranging from 4 (very important) to 1 (notimportant). The p-values were computed for testing thehypothesis that the mean of a given theory is the same as thatfor the theory ranked just below.



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being the main clients (for around 71% of our

survey respondents). The gap between the scores

obtained by the implicit and explicit contract

theories and the other five factors is uniform

across sectors and firm size.

Although equally important from a statistical

point of view at aggregate level, explicit and

implicit contracts have different relativeimportance across firm size and across economic

sectors. Thus, explicit contracts are considered

more important by firms from the public utilities

(energy, gas and water supply) and constructions

sectors, reflecting the contractual nature of these

activities, while implicit contracts are dominant for

the wholesale and retail trade group. Furthermore,

explicit contracts importance is increasing with

firm size, while the implicit contracts relative

ranking is inversely related to it. This is perhaps a

reflection of small firms client base having a larger

inclusion of population as main clients compared

to the overall sample.

All national surveys conducted in the context of

the Eurosystems IPN project included some form

of testing of the main theories of price stickiness in

their query. Fabiani et al. (2005), who summarize

the results obtained up to the publication date,

report that implicit and explicit contracts are

ranked first and second across the euro area, a

result similar with the one obtained in the current

study. However, due to the heterogeneity of scores

across countries, the average scores for these two

theories are lower than the ones reported here (see

Kwapil et al., 2005, for similar magnitude of the

results). These two factors also score well in the

studies performed outside the IPN framework. For

example, implicit contracts are ranked first in the

study of Apel et al. (2005) for Sweden, while

explicit contracts lead the way for UK firms as

reported by Hall et al. (1997). The exception is the

study by Blinder et al . (1998), where implicit

contracts are ranked fourth, while the explicit

contract theory is ranked fifth. A possible

explanation for the different ranking obtained by

Blinder et al. (1998) may consist of the different

way the questionnaire was administered, namelythrough direct meetings with the managers of the

sampled firms, while in the other studies, the

current included, the (e)mail was the preferred

option.

3.4.2 The why in the pricing decisions

As for the main determinants of price changes,

respondents were asked to assess on a scale from

4(very important) to 1(not important) the

importance of each of a list of underlying

factors, separately for price increases and for

price decreases. The factors considered were

similar to those used in similar studies (Table 3),

except that we included as additional determinants

exchange rate fluctuations and the inflation rate.

The reason is linked to the historical pattern of

some Romanian firms automatically indexing

their prices to the exchange rate or to past or

anticipated inflation rates, which in itself

represents a characteristic of price-setting

behavior in countries with a high inflation and

volatile exchange rate environment.

The gap between raw material costs (scoring

3.4) and labor costs (scoring almost 3) at the top of

price-increasing factors is large, probably

reflecting a relatively lower correlation between

price and wage dynamics. This should be

corroborated with evidence on determinants of

wage changes presented below, suggesting that the

Table 3. Most Important Factors for a Price Increase/Decrease Decision

Price increases Price decreases

Factor Mean p-value Factor Mean p-value

Raw materials 3.40 0 Competitors price 3.15 0.85Labor costs 2.97 0.38 Raw materials 3.15 0.75Demand changes 2.91 0.76 Demand changes 3.11 0Competitors price 2.91 0.17 Exchange rate 2.78 0.68Exchange rate 2.83 0.2 Labor costs 2.75 0Inflation rate 2.72 0 Inflation rate 2.40 0.03Financial costs 2.35 0.03 Seasonal factors 2.26 0.55Seasonal factors 2.16 Financial costs 2.20Other 2.64 Other 2.29

Note: Firms were asked to indicate the importance of each option in a scale ranging from 4 (very important) to 1 (notimportant). The p-values were computed for testing the hypothesis that the mean of a given theory is the same as that of thetheory ranked just below with the exception of the other option.



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wages are better correlated with productivity

growth than with inflation. Notwithstanding the

faster disinflation and the significant currency

appreciation of the recent years, exchange rate

movements and the inflation rate still play a

relatively important role in Romanian firms

price setting, especially compared with financial

costs which received a low score. This presumablyreflects Romanian firms relying more heavily on

internal resources and trade credit to finance their

activities and much less on resources borrowed

from financial institutions (NBR, 2007).

Although the actual average scores have

different magnitudes, our factor rankings look

rather similar to those reported by Fabiani et al.

(2005) for the euro area average. Thus, in both

cases, the changes in the cost of raw materials and

those in labor costs are at the top of the drivers of

price increases and the changes in competitors

prices, those in raw material costs and the

fluctuations in demand lead the hierarchy of

price decrease determinants. Furthermore, the

asymmetry between the causal factors of positive

and negative price changes shows similar patterns

to the IPN results, with supply side factors being

more relevant for price increases and less so for

price decreases, while the reverse is true about

demand side factors. Inflation and exchange rate

fluctuations (to a lower extent though), the items

specific to our survey, act in a similar manner with

the cost factors, exerting a stronger influence on

price increases than on price cuts. This is again a

reflection of the specificity of the Romanian

macroenvironment in terms of high inflation and

volatile exchange rate (especially after the

liberalization). Figure 4 presents the asymmetry,

computed as the difference between the average

score received by a specific factor for price

increases and decreases.

In a related question, firms were also asked

about the main factors affecting wage changes.

Respondents had to choose from variation in four

factors, namely: productivity, inflation, taxes and

demand. Only changes in productivity were

considered more than important (scored above

3), while the other three factors had average scores

around the neutral level of 2.5 (Table 4). The

ranking of the factors were generally similar across

large sectors and firm size.The below shown ranking, together with the low

importance of inflation being supported also by the

finding that approximately 63% of the firms do not

index their wages to inflation,18 should be taken

with a grain of salt for several reasons. First, a few

explaining factors of wage dynamics may have been

left out, such as labor market shortages or exchange

rate developments (given that some companies

negotiate salaries in euro terms), which may have

biased to some extent the answers we received.

Second, some respondents may have had difficulties

in distinguishing between productivity growth

(measured in real or output terms) and total or

per employee revenue growth (which is measured in

nominal terms), thus implicitly including inflation in

the answer, which should have referred solely to

productivity dynamics. Third, some respondents

may have viewed the choice of productivity growth

as the right answer to give, thus perhaps

misrepresenting actual firm practices. This might

Figure 4. Determinants of price changes: difference in the mean scores for price increases versus price cuts.

Table 4. Most Important Factors for WageChanges

Factor Mean p-value

Productivity 3.19 0Taxes 2.61 0.55Demand 2.59 0.19Inflation 2.44

Note: Firms were asked to indicate the importance of eachoption in a scale ranging from 4 (very important) to 1 (notimportant). The p-values were computed for testing thehypothesis that the mean of a given theory is the same as thatfor the theory ranked just below.



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be the case for instance for the public utilities sector

whose answers distribution is strongly skewed

toward the productivity option, although index-

ation practices persist.19

3.5. Reaction to Potential Financial Shocks20

Investigating the reaction of firms to potentialfinancial shocks in a survey form is a new approach

introduced by this paper. Table 5 presents the six

scenarios and the received average scores. These

scenarios were tailored to count for a shock of

approximately 10 or 30% domestic currency

depreciation (and 20% appreciation, respectively)

and an almost twofold hike in interest rates (RON

or EUR). At the time the companies received the

questionnaire (SeptemberNovember 2006), the

exchange rate was quoted at around 3.5 RON/

EUR and the average domestic interest rates for

outstanding loans granted to companies were

around 13.5% for domestic currency loans and

7.2% for loans in EUR.

Strong potential exchange rate movements

generally received a higher overall average score

than the scenarios looking at interest rate

movements. The results were in line with

expectations, mainly because in 2005: (i) most of

the Romanian companies (and 45% from the

adjusted sample) did not take loans and disposed

of sizeable bank liquidities; these firms were net

creditors to the banking sector, and a hike in

the interest rates might even positively affect

them; overall, the Romanian firms rely to a

greater extent on internal resources and on trade

credit to finance their activities than on resources

borrowed from financial institutions; this is also

reflected by the relatively low level of financial

intermediation;21 and (ii) the share of foreign

currency loans (domestic and external) in total

loans granted to firms has been quite important in

the case of Romania standing at 64% in December

2006 (NBR, 2007).

Furthermore, the preliminary information from

the earlier questions in the survey showed that while

both exchange rate movements and financial cost

factors ranked below most factors listed for the

explanation of price changes, the average scoreswere statistically higher in the case of exchange rate

movements as compared with financial costs, for

both price decreases and increases.

However, only the leading scenario (exchange

rate depreciation to 4.6 RON/EUR) and the one

having the lowest average score (an increase of

interest rate to EUR/USD credits to 15%) are

statistically different from the one below (above),

both when the impact on prices and that on costs

are considered. The overall average scores are

high, reflecting the shock potential these scenarios

have.

The price and cost impacts are similar (from a

statistical point of view) for all scenarios but that

assuming an exchange rate appreciation to 2.7

RON/EUR. Thus, one might argue that, except

for this scenario, firms fully transmit into their

prices the impact of shocks. In a model where

firms keep their prices stable because they are

concerned about losing customers or market share

(an important factor for the sampled firms

considering the high ranking implicit contracts

received among price stickiness factors),

Kleshchelski and Vincent (2008) show that

shocks affecting the marginal cost of a single

firm have a lower pass-through to prices than in

the case when an entire sector is hit (24% in the

former case and 62% in the latter). If one

considers that the shocks that we listed in our

questions usually affect entire sectors, the high

average scores are thus being explained.

Table 5. Impact of Potential Shocks on Prices and Costs

Scenario Prices Costs

Mean p-value Mean p-value

Exchange rate depreciates to 4.6 RON/EUR 3.6 0 3.59 0Exchange rate appreciates to 2.7 RON/EUR 3.19 0.21 3.05 0.73Interest rate to RON credits increases to 30% 3.09 0.12 3.05 0.35Exchange rate depreciates to 3.9 RON/EUR 2.97 0.12 2.97 0.23Interest rate to RON credits increases to 20% 2.83 0 2.85 0.04Interest rate to EUR/USD credits increases to 15% 2.6 2.62

Note: Firms were asked to indicate the importance of each option in a scale ranging from 4 (very important) to 1 (notimportant). The p-values were computed for testing the hypothesis that the mean of a given theory is the same as that for thetheory ranked just below.



DOI: 10.1002/mde


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Large companies register higher scores in case

of a sudden move in EUR/RON exchange rate. An

explanation might be that according to their

balance sheet data, these companies bear almost

60% of the total unhedged foreign exchange risk

belonging to the Romanian corporate sector.

Related to this, as mentioned before, the main

clients are represented by foreign entities in a wellabove average proportion. Small firms in their

turn rank higher the importance of the scenario of

the interest rate to RON loans soaring at 30%.

This might be due to the large and increasing

position of SMEs as net debtors to the banking

sector (amounting to 15% of their total balance

sheet, as compared with the SMEs from the euro

area, which currently retain a net debtor position

of only 23%, NBR, 2007).

4. CONCLUSIONS

Using a survey-based approach, similar to those

employed by the Eurosystem in its IPN project,

the current paper investigates the price-setting

behavior of Romanian firms in 2005. In

interpreting the results, one should take into

account the relatively low answer rate, which is

about half that of the average registered for the

IPN studies.

Although operating in a competitive

environment, most of the firms claim to have full

autonomy in setting the price of their main

product. Among these, around half use the

market price as the main pricing rule, with a

slightly lower share of firms setting the price as a

mark-up over costs. Differing from the IPN

findings, small firms perceive a higher degree of

competition and predominantly adopt the market

price, while lower perceived competition is

consistent with medium and large firms using

mostly mark-up pricing.

The large majority of firms use a combination ofbackward and forward-looking information when

reviewing prices. Around 60% of firms use either a

time-dependent pricing rule or one that incorporates

both time- and state-dependent elements. Pure

state-dependent pricing is dominant only in the

case of small firms.

Romanian firms revised and changed their

prices in 2005 much more frequently than what

the evidence summarized in Fabiani et al. (2005)

suggests was the case for euro zone firms.

Conditional on following a time and mixed-

dependent pricing rule, Romanian prices were

revised quarterly and changed on average every

5 months. Large firms revised and changed their

price much more often than medium and small

ones, probably due to more significant costs of

mispricing their products and lower costs of priceoptimization. Wages are found to be stickier than

prices, with around 72% of firms changing their

wages once per year or less often.

Costs of raw materials in the case of price

increases and competitor prices, raw materials

costs and demand changes in case of price

decreases are the main factors determining price

changes. Implicit and explicit contracts rank first

when it comes to the main causes of price

stickiness, similar to the rankings obtained for

selected EMU countries.

Firms fully transmit into their prices the impact

of large unanticipated financial shocks. Large

variations of the exchange rate are typically

perceived more strongly than interest rate shocks.

At this stage, further analysis should be carried out

in complementing the present evidence with

research based on microdata used for CPI

compilation.

NOTES

1. One such approach is to analyze data on a cross-section of products within a particular sector/firm(e.g. Kashyap, 1995; Levy et al., 1997). Anotherapproach is based on analyzing disaggregated dataused for the construction of the CPI/PPI indices(e.g. Bills and Klenow, 2002).

2. Fabiani et al. (2005) offer an overview of the survey-based results for selected euro area countries.

3. The only related research analyses either firm-leveldata (Copaciu, 2004, and Ratfai, 2007, forHungary) or micro-CPI data (Coricelli andHorvath, 2006, for Slovakia and Gabriel andReiff, 2007, for Hungary).

4. Weighted average results based on data presented inFabiani et al. (2005).

5. Real GDP growth has averaged 5.7% p.a. between2001 and 2005, while average real wage and creditgrowth rates for the same period were 27.4 and49.3%, respectively (NBR, 2007).

6. This is reflected by the fact that the 19.83% of thesampled firms that returned the questionnaireactually accounted for 67% of the total number ofemployees in the sample. The procedure followsclosely that used by Kwapil et al. (2005) forAustrian firms.



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7. Otherwise mentioned, all the numbers reported arerounded to the nearest integer.

8. More precisely 47% in the case of Romania, a figuresimilar with that obtained in the case of Portugal(Martins, 2005).

9. Although in their case there is a predominance ofthe industrial sector in the national samples, whichis not our case.

10. Almost 29% of the respondents did not answer thisquestion. However, this is a low figure since for asimilar question less than half of the firms answeredin Italy (Fabiani et al ., 2004) and Belgium(Aucremanne and Druant, 2005).

11. Except for firms in the electricity, water supplyand gas sector for which prices are generallyregulated.

12. Price discrimination according to the quantity soldis higher for large firms (54%), while small firmsdiscriminate less than the medium and larger ones(47% charge the same price), facts consistent againwith the degree of perceived competition.

13. While Taylor assumes that the price-setter knows in

advance, through contracts, the path of the price-adjustment process, in Calvos model the price isaltered only when the firm receives a random signalthat follows an exogenously specified distribution.Fischer (1980) instead assumes that prices arepredetermined but not fixed; different prices foreach period are possible when multi-periodcontracts are established.

14. A similar pattern is obtained in the case of Spain(A lvarez and Hernando, 2005).

15. Overall, the share of firms choosing a time-dependent strategy alone is smaller whencompared with the average for the United States(40%, Blinder et al., 1998), the United Kingdom(79%, Hall et al ., 1997) and the EMU (34%,Fabiani et al ., 2005), but there are somesimilarities to the results obtained in the case ofindividual countries such as Belgium (26%,Aucremanne and Druant, 2005) and Sweden(23%, Apel et al., 2005).

16. Although there are countries where price reviews aretaking place quarterly like Austria or France(Fabiani et al.).

17. For example, the pricing points theory could not beapplied due to the denomination of the Romaniancurrency, which took place throughout the periodfirms should relate their answers to.

18. Only approximately 24%/13% of firms declared toindex wages to past/expected inflation. This may be

a reflection of improving inflation expectations,following an almost uninterrupted trend ofdisinflation in the 20012007 period, with theaverage inflation falling to a single-digit level aslate as 2005.

19. More than 50% of the firms from this sectorindicated the indexation of wages either to past orexpected inflation.

20. It should be mentioned that the higher complexityof this section resulted in a slightly lower number ofanswers being received.

21. The nongovernment credit to GDP ratio was 21.1%in 2005 and 27.2% in 2006, while similar ratios forthe euro area countries have been consistently largerthan 100% (NBR, 2007).

Acknowledgements

This research was supported by a grant from the CERGE-EI

Foundation under a program of the Global DevelopmentNetwork. Additional support was received from the NationalBank of Romania. All opinions expressed are those of theauthors and have not been endorsed by CERGE-EI or theNBR. We thank Cezar Botel, Edward Christie, Randall Filer,Ion Dragulin, Roman Horvath, Felix Hammermann, IgnacioHernando, Fernando Martins and Romulus Mircea for theiruseful comments and suggestions. All errors are our own.

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