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Methodologies to measure
market competition and Key
Issues
Professor Steve Davies,
UEA & CCP
OECD Workshop for Competition Authorities,
23 February 2021
1
Measuring competition: the way forward
A. Currently, many alternatives available, but all with
limitations. So safest approach is to use a plurality of
different measures
B. Looking to the future, we need to improve:
1. Our conceptualisation of what competition really is
2. Our level of aggregation: antitrust market not SIC industry
3. Our scoping of the market: imports, exports and multinational
firms, not just domestic producers
2
A A multitude of specific measures
• HHI (& other concentration indices, e.g. concentration ratio, CR)
• ΔHHI
• Market shares
• Entry rates
• Churn or Turbulence
• Lerner Price-Cost Margins
• Other Profitability measures
• Within-industry comparison of firms, e.g. Boone, Panzar & Rosse
• Surveys of Consumer or Business Sentiments
3
A typology and cocktail
I suggest a typology based on 4 dichotomous distinctions:
• Structural or “Performance”
• Static or Dynamic
• Firm or Industry level data
• Inter-industry or intra-industry comparisons
Ideally, use a cocktail of these different types of measure,
capturing both sides of each dichotomy
4
Room for Improvement
I have concerns about how measures have been used to date:
• Conceptualisation: they fail to capture the dynamic essence
of competition. Also ambiguous on identification and
causality
• Definitions: suffer from being too aggregate in definition and
measurement
• Scope: competition takes place between (not only) domestic
producers, but also importers and multinational firms
5
Conceptualisation: what is competition?
6
High concentration not necessarily indicative of
soft competition: brief history
• Structure-conduct-performance: high concentration leads to soft
competition (tacit or explicit collusion) and high profits
• Demsetz and Chicago – NO! Spurious correlation: concentration & profits
both the result of efficient firms for whom profits are reward, and
increased market shares inevitable, pushing up concentration.
• How to choose between explanations: examine differences in margins
between firms in the same industry. If it’s only the largest that earn high
profits, this confirms the efficiency hypothesis, but if all firms earn higher
profits, this reflects collusion.
• But even this test is inconclusive: the largest firms may earn higher profits
not because they are more efficient but because they are able to exploit
their dominance with anti-competitive practices.
7
Bringing it up to date: take account of the
dynamics of competition
• We need to move beyond aggregate measures of structure (HHI) and
profits at the industry level, or even static comparison of firms within
the industry at a point in time.
• Competition is a dynamic process which evolves over time. A never-
ending ebb and flow. Firms grow … and fall.. and maybe grow again
etc. Schumpeterian turbulence or churn.
• Philippon’s (2019) captures this neatly with his distinction between
“good” and “bad” concentration, but see also Davies & Geroski
(1997), Caves (1998).
8
The moral is…
• High concentration may indicate failing competition (BAD), but it may
alternatively be the outcome of a process of intense competition - survival
of fittest (GOOD) leading to a few very efficient firms, earning higher profits
• To distinguish between the two, we should delve deeper into the market:
GOOD is revealed by:
• Significant differences between firms at each point in time (Chicago), but also
• Significant volatility in firms’ market shares over time (Philippon)
• SMF (2017, 2018) studies of market competition in 10 consumer markets:
e.g. groceries (high concentration, considerable changes in market share) v
telecomm (high concentration and static market shares)
• NB Here I focus on concentration & market shares, but the same applies to
high profits/margins (market power or efficiency?)
9
Aggregation
10
Contrast between SIC industry & anti-trust market
• Nearly all studies employ data which is more aggregate than is ideal
• Official sources invariably define industries at the 4, or at best 5 or
6 digit NACE/SIC levels or, equivalently, 6 digit NAICS
• Company level databases report profits, value added, investment,
employment etc for the aggregate firm or its broad divisions. But
most big firms highly diversified and multinational
• While this is inevitable, given the data at our disposal, it runs the risk
that it is not fit for purpose – competition occurs between firms in
finely defined antitrust markets
11
Illustrative statistics
• Philippon’s (2019) disaggregates the manufacturing sector into 360
NAICS level 6 industries
• The Economist’s (2016) disaggregated the economy down to 893
NAICS level 6 industries
• CMA’s (2020) uses SIC data on 615 4-digit industries
• DGCOMP (cross Europe concentration) disaggregates down to just
156 ISIC categories
But there are far, far more anti-trust markets than this. A typical
NAICS/SIC/NACE industry will comprise many different antitrust
markets.
12
Antitrust markets typically much smaller than
SIC/NAICS/NACE industries
• Consider Werden’s Commerce Quotients (CQ): the size of the antitrust market as
a share of the aggregate SIC industry to which it belongs (turnover).
• In 1988, he found that:
• In 52 of 80 cartels, CQ < 1%
• In 17 of 47 merger cases, CQ<1%, and in only 14 was CQ >14%
• In 2018 (with Froeb), he finds
• 32 of 44 mergers cases had CQ< 1%.
• Duso et al (2021) construct a database of 2,000 EC mergers (1995-2014) and find
that these mergers covered 20,000 product/geographic antitrust markets
13
So what?
• The typical antitrust market is far more concentrated than the typical
SIC industry. Duso et al report a typical HHI = 3000 (st. dev. 2000).
This is 10 times greater than the typical HHI reported in most studies
of SIC industries
• In itself unsurprising. What is more important is whether HHI
observed at the SIC level is representative (albeit scaled up) of
concentration in its constituent anti-trust markets.
• On this we do not currently know. What matters is how homogenous
are anti-trust markets within SIC industries, and how diversified firms
are across those markets – Davies, ongoing research, (hopefully 2021)
14
Markets not industries
15
Imports, Exports & Multinational Firms
• UK Car Industry: top 6 manufacturers: JLR, Nissan, Mini, Toyota, Honda,
Vauxhall
• account for virtually all cars made in UK
• are all foreign owned multinationals. Most of their production is for export. They also
have considerable sales and production outside UK
• account for only 3 of the top 10 best selling models in the UK. The rest are imports
• Lessons for measuring competition in the UK market:
• Concentration measured by production statistics often totally meaningless
• Imports are not necessarily just a “competitive fringe”
• Intra-firm trade often important
• Major data task: combining trade and domestic industry structure
16
References cited in presentation
• Affeldt P, Duso T, Gugler K and J Piechucka, (2021) “Market concentration in Europe:
Evidence from Antitrust markets”, Competition Policy International, Feb 1, 2021
• Caves R E, (1998), “Industrial Organization and New Findings on the Turnover and
Mobility of Firms”, Journal of Economic Literature, Vol. 36, December: 1947-82
• CMA (2020), “The State of UK Competition”, CMA 133, 30 November 202
• Davies S W and Geroski P, (1997), “Changes in Concentration, Turbulence and the
Dynamics of Market Shares”, Review of Economics and Statistics, 79.3: 383-91
• The Economist (2016) “Too much of a good thing. Profits are too high. America needs a
giant dose of competition”, May 26th, 2016
• Philippon T (2019), How America Gave Up on Free Markets, Harvard University Press
• Social Market Foundation (SMF), Concentration not competition: the state of UK
consumer markets, (2017, 2018)
• Werden G J and L M Froeb (2018), “Don’t Panic: A guide to claims of increasing
concentration”, Antitrust Magazine, 5th April 2018
17

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Methodologies to measure market competition – Stephen Davies – Feb 2021 OECD Workshop

  • 1. Methodologies to measure market competition and Key Issues Professor Steve Davies, UEA & CCP OECD Workshop for Competition Authorities, 23 February 2021 1
  • 2. Measuring competition: the way forward A. Currently, many alternatives available, but all with limitations. So safest approach is to use a plurality of different measures B. Looking to the future, we need to improve: 1. Our conceptualisation of what competition really is 2. Our level of aggregation: antitrust market not SIC industry 3. Our scoping of the market: imports, exports and multinational firms, not just domestic producers 2
  • 3. A A multitude of specific measures • HHI (& other concentration indices, e.g. concentration ratio, CR) • ΔHHI • Market shares • Entry rates • Churn or Turbulence • Lerner Price-Cost Margins • Other Profitability measures • Within-industry comparison of firms, e.g. Boone, Panzar & Rosse • Surveys of Consumer or Business Sentiments 3
  • 4. A typology and cocktail I suggest a typology based on 4 dichotomous distinctions: • Structural or “Performance” • Static or Dynamic • Firm or Industry level data • Inter-industry or intra-industry comparisons Ideally, use a cocktail of these different types of measure, capturing both sides of each dichotomy 4
  • 5. Room for Improvement I have concerns about how measures have been used to date: • Conceptualisation: they fail to capture the dynamic essence of competition. Also ambiguous on identification and causality • Definitions: suffer from being too aggregate in definition and measurement • Scope: competition takes place between (not only) domestic producers, but also importers and multinational firms 5
  • 6. Conceptualisation: what is competition? 6
  • 7. High concentration not necessarily indicative of soft competition: brief history • Structure-conduct-performance: high concentration leads to soft competition (tacit or explicit collusion) and high profits • Demsetz and Chicago – NO! Spurious correlation: concentration & profits both the result of efficient firms for whom profits are reward, and increased market shares inevitable, pushing up concentration. • How to choose between explanations: examine differences in margins between firms in the same industry. If it’s only the largest that earn high profits, this confirms the efficiency hypothesis, but if all firms earn higher profits, this reflects collusion. • But even this test is inconclusive: the largest firms may earn higher profits not because they are more efficient but because they are able to exploit their dominance with anti-competitive practices. 7
  • 8. Bringing it up to date: take account of the dynamics of competition • We need to move beyond aggregate measures of structure (HHI) and profits at the industry level, or even static comparison of firms within the industry at a point in time. • Competition is a dynamic process which evolves over time. A never- ending ebb and flow. Firms grow … and fall.. and maybe grow again etc. Schumpeterian turbulence or churn. • Philippon’s (2019) captures this neatly with his distinction between “good” and “bad” concentration, but see also Davies & Geroski (1997), Caves (1998). 8
  • 9. The moral is… • High concentration may indicate failing competition (BAD), but it may alternatively be the outcome of a process of intense competition - survival of fittest (GOOD) leading to a few very efficient firms, earning higher profits • To distinguish between the two, we should delve deeper into the market: GOOD is revealed by: • Significant differences between firms at each point in time (Chicago), but also • Significant volatility in firms’ market shares over time (Philippon) • SMF (2017, 2018) studies of market competition in 10 consumer markets: e.g. groceries (high concentration, considerable changes in market share) v telecomm (high concentration and static market shares) • NB Here I focus on concentration & market shares, but the same applies to high profits/margins (market power or efficiency?) 9
  • 11. Contrast between SIC industry & anti-trust market • Nearly all studies employ data which is more aggregate than is ideal • Official sources invariably define industries at the 4, or at best 5 or 6 digit NACE/SIC levels or, equivalently, 6 digit NAICS • Company level databases report profits, value added, investment, employment etc for the aggregate firm or its broad divisions. But most big firms highly diversified and multinational • While this is inevitable, given the data at our disposal, it runs the risk that it is not fit for purpose – competition occurs between firms in finely defined antitrust markets 11
  • 12. Illustrative statistics • Philippon’s (2019) disaggregates the manufacturing sector into 360 NAICS level 6 industries • The Economist’s (2016) disaggregated the economy down to 893 NAICS level 6 industries • CMA’s (2020) uses SIC data on 615 4-digit industries • DGCOMP (cross Europe concentration) disaggregates down to just 156 ISIC categories But there are far, far more anti-trust markets than this. A typical NAICS/SIC/NACE industry will comprise many different antitrust markets. 12
  • 13. Antitrust markets typically much smaller than SIC/NAICS/NACE industries • Consider Werden’s Commerce Quotients (CQ): the size of the antitrust market as a share of the aggregate SIC industry to which it belongs (turnover). • In 1988, he found that: • In 52 of 80 cartels, CQ < 1% • In 17 of 47 merger cases, CQ<1%, and in only 14 was CQ >14% • In 2018 (with Froeb), he finds • 32 of 44 mergers cases had CQ< 1%. • Duso et al (2021) construct a database of 2,000 EC mergers (1995-2014) and find that these mergers covered 20,000 product/geographic antitrust markets 13
  • 14. So what? • The typical antitrust market is far more concentrated than the typical SIC industry. Duso et al report a typical HHI = 3000 (st. dev. 2000). This is 10 times greater than the typical HHI reported in most studies of SIC industries • In itself unsurprising. What is more important is whether HHI observed at the SIC level is representative (albeit scaled up) of concentration in its constituent anti-trust markets. • On this we do not currently know. What matters is how homogenous are anti-trust markets within SIC industries, and how diversified firms are across those markets – Davies, ongoing research, (hopefully 2021) 14
  • 16. Imports, Exports & Multinational Firms • UK Car Industry: top 6 manufacturers: JLR, Nissan, Mini, Toyota, Honda, Vauxhall • account for virtually all cars made in UK • are all foreign owned multinationals. Most of their production is for export. They also have considerable sales and production outside UK • account for only 3 of the top 10 best selling models in the UK. The rest are imports • Lessons for measuring competition in the UK market: • Concentration measured by production statistics often totally meaningless • Imports are not necessarily just a “competitive fringe” • Intra-firm trade often important • Major data task: combining trade and domestic industry structure 16
  • 17. References cited in presentation • Affeldt P, Duso T, Gugler K and J Piechucka, (2021) “Market concentration in Europe: Evidence from Antitrust markets”, Competition Policy International, Feb 1, 2021 • Caves R E, (1998), “Industrial Organization and New Findings on the Turnover and Mobility of Firms”, Journal of Economic Literature, Vol. 36, December: 1947-82 • CMA (2020), “The State of UK Competition”, CMA 133, 30 November 202 • Davies S W and Geroski P, (1997), “Changes in Concentration, Turbulence and the Dynamics of Market Shares”, Review of Economics and Statistics, 79.3: 383-91 • The Economist (2016) “Too much of a good thing. Profits are too high. America needs a giant dose of competition”, May 26th, 2016 • Philippon T (2019), How America Gave Up on Free Markets, Harvard University Press • Social Market Foundation (SMF), Concentration not competition: the state of UK consumer markets, (2017, 2018) • Werden G J and L M Froeb (2018), “Don’t Panic: A guide to claims of increasing concentration”, Antitrust Magazine, 5th April 2018 17