Moura, Marcelo

Rossi, José

English

Research Papers in Economics

Price-Setting Policy 
Determinants: Micro-Evidence 
from Brazil
Marcelo Moura
José Rossi
Insper Working Paper
WPE: 127/2008Copyright Insper. Todos os direitos reservados.
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Price-Setting Policy Determinants:  
Micro-Evidence from Brazil 
 
 
Marcelo Moura 
1 
Ibmec São Paulo – Business School 
 
 
 
José Rossi 
Ibmec São Paulo – Business School 
 
 
 
 
Abstract 
 
The paper studies the determinants of the frequency of price changes from survey data 
on Brazilian companies. Strong evidence of price-nominal rigidities is found in the data 
with average and median price durations very close to results reported for the euro area 
and the United States. We find that empirical determinants of price-change duration are 
mostly competition, size, product specialisation and sector dummies.  
 
Keywords: price-setting; frequency of price changes; nominal rigidities; sticky prices; 
survey data. 
 
JEL classification: E31, D40. 
 
 
 
 
 
 
 
                                                 
1 Corresponding Author: Rua Quatá 300 sala 405, Vila Olímpia, São Paulo, SP, CEP: 04546-042, Brazil. Tel.: + 55 
11 45042435; fax: + 55 11 45042350. E-mail address: marcelom@isp.edu.br.       2
1.  Introduction  
 
Price-stickiness and nominal rigidities play a central role in modern 
macroeconomic models. For instance, as emphasised by Angeloni et al. (2006), the 
baseline model for monetary policy evaluation relies on an assumption that firms set 
prices individually on a staggered basis. Usually, a Calvo (1983) formulation is used, 
where at each period there is a fixed probability that a given firm will change its price 
independently of its history.  
 
The validity of those theoretical results has recently been studied empirically. 
For instance, Álvarez et al. (2006) summarise micro-evidence of price-setting policies 
and point to some stylised facts: (i) firms change price infrequently, on average once a 
year; (ii) price-setting behaviour is heterogeneous across firms; (iii) implicit or explicit 
contracts and coordination failure theories are important and (iv) downward price-
rigidity is slightly higher than upward rigidity. As Angeloni et al. (2006) have said, 
these new findings seriously challenge the most commonly-used assumptions in micro-
founded macro models. 
 
Our main goal is to look for micro-evidence of sticky-pricing policies in 
Brazilian companies, if there is any and what determines it. A secondary goal is to add 
to the literature a study of micro-evidence of price-nominal rigidities for emerging 
economies like Brazil with a recent past history of high inflation. The paper is 
structured as follows. Section 2 presents the data used in the analysis and investigates 
the evidence for price-stickiness. Section 3 studies the empirical determinants of price-
change durations. Section 4 concludes.        3
 
2. Data 
  
We looked at a survey of 281 Brazilian firms organised by the research 
department of Ibmec São Paulo and conducted by Sensus, a market and opinion 
research institute. The sample was selected randomly from the financial survey 
conducted by Gazeta Mercantil, one of the major business newspapers in Brazil. This 
way we were able to merge data from the two independent surveys. 
 
  Table 1 presents the defined variables which we employed in our analysis. 
Motivated by the existent literature, we selected: the wage-change duration as a proxy 
for cost structure; market share or number of competitors, for competition level; log of 
net revenues, for size effects; participation of the main product in total sales, for 
diversification level and demand elasticity for market conditions. Those variables were 
drawn from a larger questionnaire involving a total of ninety questions. Questions were 
answered at the company site by the company’s owner, the director, or the financial 
manager, in the majority of the cases.     
 
Table 2 presents summary statistics for our variables of interest. A striking fact 
is that price average and median durations in Brazil are surprisingly high: the mean is 
10.06 months and the median is twelve months. Although Brazil has a very high 
inflation tradition, with yearly rates above 100% from 1980 to 1994, we detect no such 
thing as an inflationary culture that could induce more frequent price changes. In fact, 
Brazilian numbers are quite similar to those of the euro area and even higher than in the 
United States.  Álvarez and colleagues (2006) report that for the euro area and the      4
United States, the respective mean-price durations are 10.8 and 8.3 months. This is in 
accordance with the fact that the CPI in the Brazilian economy was only 3.1% in 2006 
and 4.5% in 2007, inflation rates just slightly above the euro area and US standards. 
This result is similar to that of Gagnon (2007), who studies the Mexican economy price-
setting and finds that for annual inflation rates below 10%, price average durations in 
Mexico are very close to US values.  
 
Wage-change duration is closely matched by the mean and median values for 
price changes; it has, however, a much lower variability. Market share and number of 
competitors indicate the presence of strong power in Brazilian companies. Mean and 
median values for main product percentage on total sales indicate that Brazilian 
companies are, in general, not very diversified across products. The average demand 
elasticity demonstrates that the majority of Brazilian companies are in the elastic region 
of their demand curves. The number of observations across variables varies, owing to 
the lack of available responses to some questionnaires.  
 
  The stylised fact of price adjustments being heterogeneous across sectors is 
replicated in our survey. Table 3 displays data on price frequencies across sectors and 
compares them with euro area and US data. From it, we can see a strong heterogeneity 
across sectors which is closely matched by euro area and US data. In general, the 
trading sector has longer price durations, followed by agricultural and food products. 
Industry and services have the longest durations and lower frequencies.  
 
In summary, we can associate two stylised facts with our data. First, prices are 
indeed sticky and have high average durations. Second, price-changing decision-rules      5
are very heterogeneous across firms. Now we turn to the question of price-change 
determinants.  
 
3. Determinants of price durations  
 
Since our dependent variable, price-change duration, is a discrete ordered 
variable, we employ an ordered qualitative response model for the price-change 
frequency. In particular, we apply an ordered probit model:  
 
* Pr( ) Pr( ) Pr( )
tt J i i J yJ y X u γ βγ = =< = + <                                 (1.1), 
 
where yt is the price-change duration and Xi is the matrix of explanatory variables, 
including all the remaining variables in Table 1 and dummies for economic sectors. In 
addition,  β  and  
J γ  are the estimated parameters. The expression Pr( )
t yJ =  is the 
probability of yt assuming the values J = 0,1,2,….,60.  
 
Table 4 reports our empirical results. The degree of competition, represented 
either by the market share or the number of competitors, is significant in all of the 
specifications. We find that a higher degree of competition results in lower price 
durations. Larger firms will also change price less regularly. As expected from the 
analysis of section 2, the industrial and service sectors have significantly higher price-
duration than the other sectors, trade and agribusiness. Our results corroborate the 
empirical results of Hoeberichts and Stockman (2004) for Dutch companies, and 
Álvarez and Hernando (2005) for Spanish companies, with regard to the signs and 
significance of competition, firm size and sector dummies variables.      6
 
The level of specialisation in production also seems to play an important role, as 
firms more devoted to one product will change price less frequently. The coefficient for 
wage-duration changes has the expected sign, although it is not statistically significant 
in some specifications. Demand elasticity has an interesting effect, in that price-change 
duration decreases with demand elasticity. The result makes economic sense, since 
higher demand elasticity (in absolute value) will induce more volatile changes in sales 
when price changes, a risk that firms’ managers would prefer to avoid. 
 
4. Conclusion 
  
The paper studied price-setting policies, using as micro-evidence survey data for 
281 Brazilian companies. The analyses demonstrate interesting stylised facts, some 
already observed in other micro-evidence studies for the euro area and the US. The 
empirical results help an understanding of commonly-used macroeconomic modelling 
for monetary policy evaluation, particularly those models that imply nominal rigidities. 
New research on the topic has two equally productive veins: investment in theoretical 
pricing-rule models that replicate empirical stylised facts, and further exploration of 
empirical determinants of different price-setting policies across firms. 
 
Acknowledgements 
 
 
The authors would like to thank Tânia de Toledo Lima for excellent research 
assistance.  
 
      7
References  
 
Álvarez, L.; Dhyne, E.; Hoeberichts, M.; Kwapil, C.; Le Bihan, H.; Lünnemann, P.; 
Martins, F.; Sabbatini, R.; Stahl, H.; Vermeulen, P.; Vilmunen, J. (2006) Sticky Prices 
in the Euro Area: A Summary of New Micro-evidence, Journal of the European 
Economic Association, 4, 575 - - 584.  
Álvarez, L. J.; Hernando, I. (2005) Price Setting Behavior in Spain: Stylized Facts 
Using Consumer Price Micro Data, European Central Bank Working Paper Series, 538. 
Angeloni, I.; Aucremanne, L.; Ehrmann, M.; Galí, J.; Levin, A.; Smets, F. (2006) New 
Evidence on Inflation Persistence and Price Stickiness in the Euro Area: Implications 
for Macro Modeling, Journal of the European Economic Association, 4 (2-3), 562 - - 
574. 
Calvo, G. A. (1983) Staggered Prices in a Utility-Maximizing Framework, Journal of 
Monetary Economics, 12, 383 - - 398. 
Gagnon, E. (2007) Price Setting During Low and High Inflation: Evidence form 
Mexico,  Board of Governors of the Federal Reserve System - International Finance 
Discussion Papers, 896.   
Hoeberichts, M.; Stockman, A. (2004) Pricing behavior of Dutch companies: main 
results from a survey, De Nederlandsche Bank, mimeo.      8
Tables 
Table 1: Variable definitions. 
 
Variable  Survey question  Answer  
Price change 
duration 
‘In which frequency does 
your company change 
prices?’ 
Open answer, number of months.  
Wage change 
duration 
‘In which frequency does 
your company change 
wages?’ 
Open answer, number of months.  
Market share  ‘What was the market 
share of your main product 
in 2006?’ 
Open answer, %0-100.  
Log Net 
revenue (R$)  
‘What were the total net 
revenue sales of your 
company in 2006?’ 
Open answer, thousands of 
Brazilian reais (R$). 
Participation of 
the main 
product 
‘What is the percentage of 
your main product in total 
revenues?’ 
Open answer, %0-100. 
Number of 
Competitors 
‘How many competitors 
are in the market for your 
main product?’ 
Open answer, discrete number. 
Demand 
Elasticity 
‘All else being equal, in 
2006, if you increase your 
price by 10%, what 
happens to your sales?’ 
Multiple choice
a  
(a) Nothing;         
(b) Decrease by 10% to 30%; 
(c)Decrease by 30% to 60%; 
(d) Decrease by 60% to 100%;       
(e) Decrease by more than 100%. 
Source: Ibmec São Paulo / Sensus Brazilian Companies Survey. 
Note: Values were converted to numbers: option (a) is 0; option (b) is 2; option (c) is 4; options (d) and 
(e) are 8. 
  
      9
Table 2: Summary statistics. 
 
Variable Median  Mean  Std.  Dev.  Obs. 
Price-change  duration  12.0 10.06 8.14  202 
Wage-change  duration 12.0 11.58 2.41  258 
Market share  30.0  35.70  32.29  154 
Log Net revenue 
(R$1,000*)  
10.1 10.02 2.29  281 
% main product  70.0  67.00  31.60  214 
Numb. of Competitors  70.0  16.44  27.64  211 
Demand Elasticity  2.0  2.17  1.69  237 
Source: Ibmec São Paulo / Sensus Brazilian Companies Survey. 
Note: * R$1,000 is approximately US$600, according to average quotes as at April 2007.  
 
      10 
Table 3: Price frequency changes by sector. 
 
Sector  Median 
duration 
Mean 
duration 
Duration 
Std. Dev. 
Obs. Freq.
a 
Brazil  
Freq.
a 
US 
Freq.
a 
Euro A. 
All sectors  3  10.1  8.1  202  21.9  20.8  15.9 
Agricultural and 
Food Products 
6  8.3  9.9  23  29.4  27-48
b  14-28
b 
Trade  4  6.2  6.2  49  43.8  n.a.  18 
Industry  12  11.5  8.4  64  14.3  22
c  9
c 
Services  12  12.2  7.5  66  10.3  n.a.  11 
Source: Ibmec São Paulo / Sensus Brazilian Companies Survey., Álvarez and colleagues (2005) for US and euro area values.  
Notes:   a - Mean frequency prices in percentage points per month (2005).  
  b - Unprocessed and processed food CPI data.  
  c - Non-energy industrial goods CPI data.    
 
      11 
Table 4: Ordered Probit-Dependent Variables – Price-change Duration. 
 
Independent 
variable 
Specifications 
Wage  duration  .1509***  .1509***  .0952 .0555 .0520  .1033* 
  (.0477) (.0477) (.0602) (.0443) (.0450) (.0618) 
Market  share  .0084** .0084** .0084**      .0077* 
  (.0034) (.0035) (.0038)      (.0040) 
Number of         -.0102***  -.0108***   
competitors      (.0039)  (.0040)   
Log revenue     -.0003  -.0919  -.0826*  -.1277**  -.1626** 
    (.0471) .0603 (.0484)  (.0510)  (.0669) 
% main product      .0086**  .0120***  .0097***  .0037 
      (.0041) (.0033) (.0035) (.0044) 
Dem.  Elasticity      -.1681** -.0158  -.0438 -.1933** 
      (.0725) (.0621) (.0641) (.0770) 
Trade       -.4317  -.4833 
       (.3561)  (.4446) 
Industry       .6919**  .7303* 
       (.3386)  (.4149) 
Services         .9809***  1,2753*** 
       (.3555)  (.4696) 
Pseudo R
2  .0443 .0443 .0676 .0565  .118  .1438 
        
Number  of  obs.  119  119 97 126  126 97 
        
Note: The asterisks ***, ** and * denote statistical significance at 1%, 5% and 10% respectively. 
 
 
 
 

New Evidence on Inflation Persistence and Price Stickiness in the Euro Area: Implications for Macro Modeling,

Price Setting Behavior in Spain: Stylized Facts Using Consumer Price Micro Data, European Central Bank Working Paper Series,

Price Setting During Low and High Inflation: Evidence form Mexico,

Pricing behavior of Dutch companies: main results from a survey, De Nederlandsche Bank,

Staggered Prices in a Utility-Maximizing Framework,

Sticky Prices in the Euro Area: A Summary of New Micro-evidence,

Price-Setting Policy Determinants: Micro-Evidence from Brazil

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Price-Setting Policy Determinants: Micro-Evidence from Brazil

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