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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]
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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.
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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
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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.
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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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