1.
Methodologies to measure market
competition:
Recalling old lessons and some practical issues
Hearing on Methodologies to Measure Market Competition, OECD
PROF. CAMILA C. PIRES-ALVES
A S S I S T A N T P R O F E S S O R O F E C O N O M I C S
R E S E A R C H G R O U P O N L A W , E C O N O M I C S , A N D C O M P E T I T I O N ( G D E C )
U N I V E R S I D A D E F E D E R A L D O R I O D E J A N E I R O ( U F R J ) / B R A Z I L
JUNE 2021 – [0 5 / 2 2 / 2 0 2 1 V E R S I O N ]

2.
Introduction
Main focus: Issues on methodologies to measure competition for inter-industry comparisons with
Competition Advocacy purposes
◦ Not looking at competition measures to be used in mergers and abuse of dominance cases.
Considering the benefits and challenges of these sort of analyses by:
1) Discussing some past theoretical and empirical contributions that remain or are illustrative of
today’s concerns
◦ Endogeneity and Dynamics
◦ Patterns of competition and differences between sectors/industries
2) Presenting practical issues and bringing some Brazilian perspective

3.
Recalling old lessons…
Non- univocal direction of causality
Static x Dynamic
How competition works matters
In essence, in enforcement of cases by competition authorities – these are well established
challenges
◦ Assessing real competitive dynamic and these two directions of causality are essential to modern competition policy
◦ Standardized assessment and tools are insufficient as they do not fit the reality of each case (“case-by-case” analyses)
◦ Despite time restrictions and information asymmetries between economic agents and authority, data access and quality of
information are essential and are not usually a constraint
◦ The policy needs to deal with relevant markets’ specificities and the adequacy of the choice of analytical tools
◦ Innovative markets, platforms, for example
Structure Performance
Conduct

4.
When measuring competition comparing
industries with advocacy purposes...
Mix of structural and performance variables is desirable
In the past, the problems with measuring structure-performance variables and with estimating
their relationship (endogeneity) were relevant issues to cross-section studies interpretation
(Schmalensee, 1989).
◦ Still valuable lessons to our today’s debate
In these applications, understanding the meaning of these different measures requires a
comprehension of firms’ behavior and how they differ between sector/industries

5.
Considering for differences between
industries in sample
If ranking industries – how to interpret differences? One might consider looking into groups:
◦ Homogeneous x differentiated
◦ Less or more innovative
Some useful typologies may help (along with being country-specific):
For the Brazilian economy, for example, some studies on competitiveness of manufacturing and
extractive sectors group industries by patterns of competition (considering both their demand and
supply-side conditions) (Torracca, 2017):
◦ Industrial commodities: homogeneous, more efficient players, vertical integrated, relevance of exports.
◦ Agricultural commodities: similar to industrial commodities, but different due to the nature of raw materials
(longer maturation cycle).
◦ Technological intensive: differentiated products, more sophisticated, R&D, intense intra-industry trade.
◦ Traditional: low minimum scale, low technological content, coexistence of firms with different sizes, product
lines, capabilities and performance.
These differences may affect choices of variables, how to measure, importance of data concerns, how
to interpret results, etc.

6.
The “innovation” example
The importance of innovation as a performance measure depends on each industry and its role to the
competitive dynamic.
Innovation success depends on key issues that vary inter-industry
Sectorial/industrial patterns
◦ Schumpeter Mark I
◦ Schumpeter Mark II
◦ Innovation competition for the Market, and not within the Market
◦ Incremental x Disruptive
◦ …
Correct analysis and interpretation should consider for
◦ Low innovation, but correct measure?
◦ Endogeneity of measures
◦ Continuous process and diversity
◦ Cumulativeness and tacit knowledge
◦ Product cycle and industries’ dynamics

7.
Practical issues for authorities and some
Brazilian perspective
As a consequence: it is relevant to ensure continuity over time of the calculated measures
◦ Authorities will need access to comparable data overtime (it may depend on relationship with statistics institutions)
Access to data (Industry level, firm level, degree of aggregation– market x industry)
◦ Brazilian statistics and availability
◦ Dealing with possible sources: agreements with institutions, internal sources, and data confidentiality
Diversification or vertical integration issues and quality of data issues
◦ Firms’ primary classification method may vary over time
+ Multinational, imports, intra-firm trade, heterogeneity of firms issues
Issues are country and industry-specific in relevance

8.
Implication to Competition Policy
authorities' choices
Unavoidable costs x benefits discussion
Using this sort of industry-level analyses or competition measures may be
important
◦ To connect Competition Policy with other economic policies and giving a wider view of
economy and industries
◦ With all the necessary cautious or controls, to select industries for closer monitoring or for
market studies
◦ As a way to stimulate or produce complementary analyses (from nation level to industry
level, using more than regular concentration or markups measures, etc.)
◦ To provoke and support with data more empirical and sophisticated analyses (from inside or
outside researchers) to answer the authorities and society concerns