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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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eberhard feess summary of first session potential lessons for crew

Eberhard FeessSummary 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

Discuss insights from the two presentations separately;

Some points of the discussion referring to both presentations.

slide2

Owen

(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

Before-after required

Data for difference-in-difference

Timing issue (already implemented - then primary data collection is excluded - or not

slide3

2) Estimating economy-wide impacts

- 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…

slide4

Disentangling the impact of different measurements

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.

slide5

Natalie

(far more controversial)

CS vs. CS+PS

Pros:

Pragmatism

Due to positive long-term (“dynamic”) effects, static CS may be a better proxy for long-term welfare than static CS+PS

Cons:

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?)

Question:

Shall CS and PS really be estimated in CREW?

Or restrict attention to prices, productivity, quality…

slide6

2) Ex-ante vs. ex-post perspective

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

However:

- CREW is about the empirical assessment of measures- 10-15% for cartel, but for abuse?!

slide7

Ex-post: Which effects did the removal of the violation have?

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…

slide8

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 (?)

slide9

Mixed important aspects from discussion

(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)

BUT:

Before-after-comparison required

Difference-in-difference would be extremely valuable

Between countries-methodologies should be the same (?)

No oversimplified econometrics (Tansanie-study; GMM)

slide10

Factors to be taken into account:

Factors agreed upon: Quality, distribution…

Factors emphasized by many but difficult:

Employment

Poverty reduction