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FIJIAN COMPETITION AND CONSUMER COMMISSION
(FCCC)
THE ROLE OF ECONOMISTS IN MERGER TEAMS AND QUALITATIVE EVIDENCE REVIEW
1
ECONOMISTS AT THE FCCC
 We have a separate corps of economists in the Research department – Chief Economist,
Senior Resea...
RECENT MAJOR MERGER CASES IN FIJI
 Pacific Neptune Lines / Pacific Direct Line (2019)
 Grand Pacific Hotel Group / Fiji ...
NATURE OF COMPETITION
 Customers can book space directly with a shipping company, or can arrange this through a
shipping ...
THEORIES OF HARM
 Largely by looking at the parties shares of supply (in capacity terms) we could narrow it down to the
f...
COMPLICATING FACTORS
 Buying space with a shipping firm doesn’t necessarily mean that your goods will be
transported on o...
COMPLICATING FACTORS
 Hard to quantify market share reliably because shipping firms change their routes and
services rela...
QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL
 We were eventually faced with a judgement call: should we try to use quant...
QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL
 Why did we decide to focus on qualitative evidence and not diversion ratio...
QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL
 Why did we decide to focus on qualitative evidence and not diversion ratio...
QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL
 Why did we decide to focus on qualitative evidence and not diversion ratio...
HOW DID WE APPROACH OUR ANALYSIS
 Given that we had decided that a detailed quantitative study of profit margins and dive...
WHAT DID OUR ANALYSIS SHOW US
 The key part of our analysis came down to considering the likelihood of entry into the mar...
WHAT DID OUR ANALYSIS SHOW US
 While Neptune and PDL were big players on the NZ-Fiji route, there were lots of other majo...
USES OF QUALITATIVE DATA
 Our analysis was based around combining qualitative evidence with high-level qualitative data (...
ROLE OF ECONOMISTS
 Key points in this case:
 Deciding whether the information necessary for diversion ratio/GUPPI/VGUPP...
ROLE OF ECONOMISTS
 This is an example of an aspect of analysis which tends to get left out when we discuss how we analys...
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Economic Analysis in Merger Investigations – Break-out Session 3 – The role of economists in merger teams and qualitative evidence review – Fiji

This presentation by the Fiji was prepared for the break-out Session 3, “The role of economists in merger teams and qualitative evidence review”, in the discussion “Economic Analysis in Merger Investigations” at the 19th OECD Global Forum on Competition on 9 December 2020.

More papers and presentations on the topic can be found at http://oe.cd/eami.

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Economic Analysis in Merger Investigations – Break-out Session 3 – The role of economists in merger teams and qualitative evidence review – Fiji

  1. 1. FIJIAN COMPETITION AND CONSUMER COMMISSION (FCCC) THE ROLE OF ECONOMISTS IN MERGER TEAMS AND QUALITATIVE EVIDENCE REVIEW 1
  2. 2. ECONOMISTS AT THE FCCC  We have a separate corps of economists in the Research department – Chief Economist, Senior Research and Policy Officer, Research and Policy Officer  Other departments are arranged by the focus of their work – Economic Regulation, Competition and Compliance, Price Control and Monitoring. Each of these departments have staff with an economics background.  Economists are deployed to work with other departments as and when need arises.  In each of our recent merger cases, analysis and evidence gathering has been carried out 100% by economists. Other staff become involved in implementation and enforcement 2
  3. 3. RECENT MAJOR MERGER CASES IN FIJI  Pacific Neptune Lines / Pacific Direct Line (2019)  Grand Pacific Hotel Group / Fiji National Provident Fund (2019)  Telecom Fiji Limited / Fiji International Telecommunication Limited (2018)  Vonu Brands / Paradise Beverages (2014)  Fijian Holdings Limited / Pernix (Fiji) Limited (2014) 3
  4. 4. NATURE OF COMPETITION  Customers can book space directly with a shipping company, or can arrange this through a shipping agent.  Once the goods have been unloaded in port, they can either be collected by the customer or transported onwards by one of the logistics firms like W&G  So the transaction entails:  Vertical integration (Shipping firms with agencies, shipping firms with logistics firms, logistics firms with agencies)  Horizontal integration (shipping firms, agencies, logistics/freight-forwarding firms) 4
  5. 5. THEORIES OF HARM  Largely by looking at the parties shares of supply (in capacity terms) we could narrow it down to the following markets of interest based on publicly available schedules:  Shipping Services: Horizontal (Fiji-NZ)  Agency Services: Horizontal & Vertical  Shipping Services: Vertical (Freight Forwarder Foreclosure)  This was largely driven by a relatively simple quantitative analysis of capacity share by service-provider and vessel-owner 5
  6. 6. COMPLICATING FACTORS  Buying space with a shipping firm doesn’t necessarily mean that your goods will be transported on one of the their ships.  Different customers have different requirements from their shipping firm  E.g. perishables vs non-perishables  Market dynamics are partly determined overseas – some vessels will travel between many different ports on each journey 6
  7. 7. COMPLICATING FACTORS  Hard to quantify market share reliably because shipping firms change their routes and services relatively frequently (although this wasn’t the case on the Fiji-NZ route)  However, their ability to do this is temporarily limited by Fiji’s port infrastructure  Matter of national importance – absolutely essential to get the decision right 7
  8. 8. QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL  We were eventually faced with a judgement call: should we try to use quantitative approaches, or is a purely qualitative approach better?  We considered trying to construct a dataset from which we could apply the GUPPI/VGUPPI or look at diversion ratios between PDL and NPL 8
  9. 9. QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL  Why did we decide to focus on qualitative evidence and not diversion ratios? Widely diffused information  The information required to establish diversion ratios is widely diffused between many players in the market. Shipping firms don’t necessarily know who is transporting goods on their vessels, or what was paid for the space on those vessels.  For example, a customer might use shipping agency A to transport goods in a slot leased by shipping firm B on a vessel owned by shipping firm C.  Moreover, shipping firm C may know that 20 TEU slots on its vessels have been leased to shipping firm D, but it won’t know how full those units are or who is transporting goods in them.  No single firm necessarily has all the information on prices, quantities and customer identities necessary. The data required for this is spread across many firms and sometimes many jurisdictions. 9
  10. 10. QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL  Why did we decide to focus on qualitative evidence and not diversion ratios? Widely diffused information  Similarly, for many of the other shipping firms, their scheduling decisions may be driven by business decisions relating to other jurisdictions  We have no legal information gathering powers in these jurisdictions  The essential point: the nature of the information is so diffuse that gathering it would have been time-consuming, so the opportunity cost in terms of other kinds of analysis was potentially very high. 10
  11. 11. QUALITATIVE VS QUANTITATIVE: A JUDGEMENT CALL  Why did we decide to focus on qualitative evidence and not diversion ratios? Questions about how meaningful the quantitative analysis would be  Many shipping companies’ choices of routes and schedules are relatively changeable - conditions of competition can change fairly rapidly.  Many customers decisions were based on qualitative factors (esp. weekly delivery and perceived commitment to the market),  We thought that this could make current diversion ratios an unreliable guide to behaviour if these market conditions changed which, as noted above, we thought they were liable to. 11
  12. 12. HOW DID WE APPROACH OUR ANALYSIS  Given that we had decided that a detailed quantitative study of profit margins and diversion ratios would be extremely time-consuming and that the insights provided might not offer a reliable guide to the future in a changing market, we decided to focus on other sources of evidence  In particular, we focused on gathering the views of stakeholders and then applying that to the quantitative data we did have to see what kind of picture it painted in the market. We talked to:  Top 10 customers for both parties’ shipping businesses  Top 10 shipping firms in region  Other freight-forwarding and agency firms  In most cases we had several meetings or conversations with each of these stakeholders as we went back and forth trying to build up a concrete picture of the market.  We also received several extensive written submissions from the Pacific Neptune Lines. 12
  13. 13. WHAT DID OUR ANALYSIS SHOW US  The key part of our analysis came down to considering the likelihood of entry into the market.  We concluded that Neptune and PDL were the biggest players on the NZ-Fiji-NZ route which is a major bottleneck for our imports.  We were concerned that the merged entity could have market power under current conditions, but this concern would be materially offset if we believed that it was easy for other firms to enter the market. 13
  14. 14. WHAT DID OUR ANALYSIS SHOW US  While Neptune and PDL were big players on the NZ-Fiji route, there were lots of other major players in global shipping operating in the region who could theoretically enter the market.  We concluded that the threat of entry by major shipping firms would probably constrain the merged entity’s pricing.  However, this left us with a problem. If there was indeed a credible prospect of entry, why had there been no real sign of possible entry in the recent past?  Answer: it came down to Fiji’s port infrastructure – changes to this mean quantitative analysis now isn’t necessarily informative for the future, because its undergoing major improvement works 14
  15. 15. USES OF QUALITATIVE DATA  Our analysis was based around combining qualitative evidence with high-level qualitative data (e.g. capacity share data by route) without getting too focused on some of the more complex quantitative work we could have done.  We were analysing quite a data-rich environment, but had to use our judgement to decide when quantitative analysis made sense and when a less data-driven approach focused around stakeholder submissions was more appropriate.  Some aspects of the market were changing (e.g. Fiji’s port infrastructure) and this made it unclear how useful diversion ratios etc. would be for forecasting behaviour, given that they would be calculated for one set of market conditions and may no longer make sense after the port infrastructure had been upgraded 15
  16. 16. ROLE OF ECONOMISTS  Key points in this case:  Deciding whether the information necessary for diversion ratio/GUPPI/VGUPPI-style analysis would be worth gathering.  Deciding whether these analyses would be informative in the circumstances  In both cases, we decided the answer was “no” – this was based on some preliminary economic analysis which determined how we analysed the transaction.  We considered that the market dynamics before and after the improvements to port infrastructure would be sufficiently different that things like diversion ratios from before the improvements wouldn’t be that informative.  In the circumstances, we decided that a qualitative understanding of the market would serve us better than the nitty-gritty of quantitative assessment 16
  17. 17. ROLE OF ECONOMISTS  This is an example of an aspect of analysis which tends to get left out when we discuss how we analyse cases – the analysis that’s carried out early on in cases to understand what kind of analysis would be helpful.  While this case (just) predates the Covid-19 Pandemic, in many ways it mirrors some of the decisions we are going to have to make in merger assessments in future:  When we use quantitative analysis, how informative is this likely to be?  Data from 2020 may be completely non-comparable with other years because of the pandemic  Data from before 2020 may reflect different, vanished market conditions – what happens, for example, if competitors have gone under or consumer behaviour has radically changed?  Key role in future for economists in the near future – using broad understanding of market dynamics to work out when quantitative analysis is helpful and when it is not. 17

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