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Eberhard Feess Summary of first session: Potential lessons for CREW

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

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  1. 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.

  2. 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

  3. 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…

  4. 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.

  5. 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…

  6. 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?!

  7. 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…

  8. 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 (?)

  9. 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)

  10. Factors to be taken into account: Factors agreed upon: Quality, distribution… Factors emphasized by many but difficult: Employment Poverty reduction

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