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CREW PAC Meeting. CREW Discussion Paper. Pooja Pokhrel Nathan India (Pvt.) Ltd. 14 March 2013, Jaipur. Purpose of Paper. Literature review to survey methodologies used to assess impact of competition reform Recommend a methodology for CREW
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CREW PAC Meeting CREW Discussion Paper Pooja Pokhrel Nathan India (Pvt.) Ltd. 14 March 2013, Jaipur
Purpose of Paper • Literature review to survey methodologies used to assess impact of competition reform • Recommend a methodology for CREW • Develop a rationale for selecting 4 countries and 2 common sectors for CREW • Recommend 4 countries and 2 sectors
Presentation Overview • Part I: Literature Review • Commonly Used Methodologies • Pros/Cons of each • Suggested methodology for CREW • Part II: Country/Sector Selection • Country Selection Approach • Recommendations for CREW countries • Sector Selection Approach • Recommendations for CREW sectors
Commonly Used Methodologies • Time Series Variation • Comparing outcomes before and after reform • Spatial Variation • Comparing outcomes between regulated and unregulated markets • Structural estimation/Simulation model • Shocking an economic model with reform variables to investigate the effect on other structural variables • Cost Benefit Analysis • Comparing monetized costs and benefits of reform • Surveys • Targeting agents and beneficiaries specific to the particular case, industry or market under investigation
Time Series Variation (Contd.) • Pros: • Simple to use and expedient. • Works with aggregate or micro-level data. • Richer dataset can allow us to control for external shocks • Cons: • No counterfactual • If used too simplistically and without econometric rigor, can introduce estimation errors. • Choosing data time periods is crucial. If post-reform data is too close, transitional issues. If too far away, difficult to establish changes in outcomes to reform and not other external sources. • If nature of reform is drawn out, then defining a reform period becomes problematic.
Spatial Variation • Pros: • Allows researches to simulate a counterfactual • Hence, more precise estimates than time-series • Cons: • Data intensive • Often difficult to find two sample sets that are characteristically similar • Does not give a broader view of what may have happened over time
Structural estimation/Simulation model • Pros: • Builds on a strong background in modern economic theory • Effects of reform can be explained by interactions of several economic variables • Accuracy of the underlying model can be tested through calibration with real market data
Structural estimation/Simulation model (Contd.) • Cons: • Often referred to as “black boxes” because of intricacies of inherent economic equations • High cost of entry for new modelers • Data demands not insignificant
Cost Benefit Analysis • Pros: • Provides a quick view of whether proposed reform options are worth it • Does not require much econometric or modeling experience • Cons: • Monetizing indirect and intangible benefits or costs often difficult to do • Aggregating individual wellbeing to estimate social wellbeing is often critiqued • Overstating either benefits or costs can severely misrepresent the outcome.
Surveys • Pros: • Useful if no data exists • Can be used to assess perceived impact • Provides a broader supplement to methods described above • Cons: • Expensive to conduct, esp. if using field surveys • Not a rigorous method on its own to measure impact
What does this mean for CREW? • “Methodologies have methodological flaws” • Data will always be a problem • A fixed rigid approach will not work, esp. when dealing with multiple countries & multiple sectors • Methodologies will need to be tailored, yet be consistent across the board
CREW Country Selection Conditions • 2 countries from Africa and 2 from Asia • At least one SADC country • At least one ASEAN member state • At least two DFID priority countries • History of CUTS engagement in each country • Only Anglophone countries in Africa
Empirical Evidence • Very few studies deal with what contributes to the highest impact of reform • Kronthaler (2010) studies what contributes to effectiveness of competition reform • Level of economic development, Control of Corruption, and the time a competition law exists matter
Country Selection Approach • Start with 99 countries in Asia and Africa • Employ a 3-step screen: • Step 1: Income considerations • Step 2: Considerations of effectiveness in existing policies • Step 3: CREW implementation considerations
Step 1: Income Considerations • Focus on developing countries (only LI & LMI) • Immediately eliminates 32 countries, including Brunei and Singapore in ASEAN • Screen out countries with per capita income of less than $600 • Proxy for level of economic development • 44 countries remaining
Step 2: Effectiveness of Policies • Avg. WEF index “Effectiveness of anti-monopoly policies” for past 2 years<= 3.5 • Variable of interest • 33 countries remaining • Avg. WGI “Regulatory Quality Index” for past 5 years<= -1.0 • Competition policy embedded with regulatory environment • 19 countries remaining • Avg. WGI “Control of Corruption Index” for past 5 years <= -1.0 • Consistent with Kronthaler & data correlation • 16 countries remaining
Step 3: Implementation Considerations • Countries with CUTS experience • Only Anglophonic countries • Arrive at a list shortlist of 8 countries, of which 2 (Nigeria & Ghana) do not have a competition law in place • Final shortlist of 7 countries • Africa: Ghana, Zambia • Asia: India, Indonesia, Philippines, Sri Lanka, Vietnam
Sector Selection Approach • Based on sector characteristics • Existence of sector policies and other signs of sectoral reform • Nature of market • Impact on the poor • Data Availability • Assign scores to make objective cross-country comparisons
Sector policies & reform • Score ranging from 0 to 4. • 0: No sector regulation or policy • 1: Sector policy but no sector regulation • 2: Sector policy and/or sector regulatory law • 3: Also a sector regulator • 4: Additional signs of reform.
Nature of Market • Review number of market players, market shares, influence of SOEs • Score ranges from 1 to 3 • 1: Primarily a monopoly or if there are no organized market players • 2: Has one or a few large players with some other smaller participants • 3: Seems to have multiple market players and competition.
Data Availability • Reviewed based on proposed CREW methodology • Assign score ranging from 1 to 3 • 1: Aggregate-level data available • 2: Micro-level household and/or firm data available • 3: Relevant data, particularly at the micro-level available, both before and after reform.
Impact on the poor • Review focused on current reach of the sector to the poor, proportion of the poor’s expenditure on sector • Assign score between 1 and 2 • 1: Relatively less impact • 2: Relatively high impact
Sector Selection • Reviewed 6 sectors • Domestic Fuel • Electricity • Passenger Transport • Pharmaceuticals • Staple Food • Telecommunications • For 7 shortlisted countries • Only sectors, not product markets
Proposed Countries & Sectors • Sectors • Pharmaceuticals, Telecommunications, Passenger Transport (in that order) • Countries • Ghana, India, Indonesia, and Zambia