broadcasting competition and programming costs david genesove hebrew university of jerusalem and...
TRANSCRIPT
Broadcasting Competition and
Programming Costs
David Genesove Hebrew University of Jerusalem and CEPR
Comments by Lisa GeorgeDepartment of EconomicsHunter College and the Graduate School, CUNY
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Overview Competing Effects of Competition on Program Quality
More Firms → More Competition for Listeners → Incentives to Attract Listeners → Higher Quality Programs (Direct Effect)
Fewer Firms → Higher Ad Revenue per Listener → Incentives to Attract Listeners → Higher Quality Programs (Indirect Effect)
Dominant Effect Depends on Disutility of Distance / Disutility of Ads Theoretical Contribution
Extension of Salop’s Circular City Extend Choi (2006), Armstrong & Weeds (2006) to Non-Linear
Transport Cost Result: When Transport Cost a Super-Unitary Power of Distance
(targeting extra-important), Quality Increases with N and Dominates Ad Effect
Empirical Framework Goal: Estimate Effect of Concentration on Quality (Overall &
Conditional on Ad Revenue) Setting: Expansion of AM Radio in 1940’s Data
• Quality = Programming Cost• Station Advertising Revenue • Concentration = Number of Stations
Estimation Strategy• Instruments: Concurrent & Lagged Economic Growth• FCC Freeze – Concentration Differenced Out• Wartime Entry – Exogenous
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Results
Effect of Concentration on Quality (Overall and Conditional) OLS – Both Zero IV – Overall effect large but statistically insignificant IV-- Conditional effect is zero.
Effect of Concentration on Ad Revenue OLS – Zero IV Positive but weakly significant
Results suggest convex distance function (decreasing marginal disutility of distance)
Programming expenditures sensitive to market size
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Comments
Useful, Practical Model Paper Structure
Market for Talent -- Theoretical and Empirical Aside Free Entry Equilibrium – Theoretical Aside Empirical Road Map
• Graphs of stations, revenue, programming?• Describe what is estimated & why (estimation variables vs.
structural variables)• Separate OLS & IV?
• Need to consider estimation challenges & biases along with data (Section 3 & 4)
• Interpret coefficients alone and in terms of structural equation Other Estimation Issues
Relationship between program expenditure & quality over time?
Restricted 1944 sample? Network Shows – All Stations? Multi-station firms? Multiplication Factor – 2.5