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Eberhard Feess Summary of first session: Potential lessons for CREW. Two different issues Owen : Impact of a bundle of sector-relevant measures (deregulation, removal of barriers to entry,…) on sectors (and beyond) Natalie : Impact of enforcement of competition law My procedure
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Two different issues
Owen: Impact of a bundle of sector-relevant measures (deregulation, removal of barriers to entry,…) on sectors (and beyond)
Natalie: Impact of enforcement of competition law
Discuss insights from the two presentations separately;
Some points of the discussion referring to both presentations.
(not very controversial)
Identifying and quantifying direct impacts on sectors
- Core of CREW
- Plenty can be learned from Australia
Factors: Prices, productivity,…but also: quality (waiting loops), impact on single firms…
Key-points for data
Data for difference-in-difference
Timing issue (already implemented - then primary data collection is excluded - or not
- Computable GEM: Methodologically advanced, prohibitively high data requirements (?)….and should be complementary to World Bank Studies (?)
- Not the core of CREW, but still very important (see agriculture example). “Soft” analysis: Links between sectors, sectors most directly affected, interviews, qualitative assessment…
Generally important for CREW (?), but: Hardly possible with “hard” analysis: Panel data with sufficient variation and observations would be required.
Again: “Soft” analysis: Links between sectors, sectors most directly affected, interviews, qualitative assessment…for identifying which of the parts of the reform are crucial.
(far more controversial)
CS vs. CS+PS
Due to positive long-term (“dynamic”) effects, static CS may be a better proxy for long-term welfare than static CS+PS
Violates usual definitions of welfare
Neglecting negative (short-term) impacts on firms may jeopardize acceptance
Is it really CS (at least in ex-ante assessment) or just price reduction times quantity (if its about CS, how is E(p) calculated?)
Shall CS and PS really be estimated in CREW?
Or restrict attention to prices, productivity, quality…
Ex-ante: Which effects will the removal of the violation have?
Recommended thanks to its simplicity
Restricted to impact on consumers
Discussion: may be important if policymakers need to be convinced about action to be taken
- CREW is about the empirical assessment of measures- 10-15% for cartel, but for abuse?!
Seen as far more problematic for CREW due to data (before-after required, an 3 years may be too short)
Ex-post if far more ambitious both wrt scope (e.g. product selection) and methodology (e.g structural models; all in all closer to sector-analyses presented by Owen)
But: Is the simplicity really driven by ex-ante vs. ex-post or more owed to decisions on scope and methodology?
For instance, the impact of prices as estimated ex-ante can simple be observed ex-poast…
3) Going beyond single interventions: Deterrence effects of competition policy
done with surveys by the OFT
There are also a few econometric evidence on cartel prevention, in particular triggered by corporate leniency programs
Though interesting, this is not part of the CREW-project (?)
(I drop everything related to political economy-aspects and advocacy)
Data and methodology:
Take data where you get it from and work with even poor data
Apply different methodologies and adjust it to data availability (incl. qualitative assessments)
Difference-in-difference would be extremely valuable
Between countries-methodologies should be the same (?)
No oversimplified econometrics (Tansanie-study; GMM)
Factors agreed upon: Quality, distribution…
Factors emphasized by many but difficult: