Lecture 11 Applications of BLP. Bronwyn H. Hall Economics 220C, UC Berkeley Spring 2005

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1 Lecture 11 Applications of BLP Bronwyn H. Hall Economics 220C, UC Berkeley Spring 2005

2 Outline Autos Breakfast cereal Spring 2005 Economics 220C 2

3 Autos Petrin, A. (2002), Quantifying the Benefits of New Products: The Case of the Minivan, Journal of Political Economy 110 (4): Berry, S., J. Levinsohn and A. Pakes (2004), Differentiated Product Demand Systems From a Combination of Micro and Macro Data: The New Car Market, Journal of Political Economy 112(1, Part 1): BLP (1999), Effects of VERs, AER Spring 2005 Economics 220C 3

4 Effects of VERs Voluntary Export Restraints in Japan between 1981 and 1990 what was welfare effect in the US? BLP assume the VER acted as a unit-specfic tax and changed the profit function: πf = ( pj mcj λverj) sj( p, x, ξ; θ) j J f Allow λ to vary by country and by year US should not have significant λ variation by year tells us if they bind in practice Spring 2005 Economics 220C 4

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6 Predicted impact of VER Spring 2005 Economics 220C 6

7 Results VERs only bind for Japan Japanese prices go up by 10-20% US prices go up a small amount; European prices actually go down Loss in profits to Japan small; gain to US large US consumers lost more in welfare than US firms gained Spring 2005 Economics 220C 7

8 Demand for differentiated products Aviv Nevo (2001) on breakfast cereal Measuring market power in the RTE cereal industry, Econometrica 69(2): Ron Anand and Bharat Shachar (1998) on TV viewing The Effectiveness and Targeting of Television Advertising, Journal of Economics & Management Strategy 7(3): Peter Davis (2001) on movie theaters Spatial Competition in Retail Markets: Movie Theaters, LSE Working Paper No. Phillip Leslie (2003) on Broadway plays and price discrimination Price discrimination in Broadway Theatre, Rand Journal of Economics Spring 2005 Economics 220C 8

9 Nevo 2001 Measuring market power in the RTE (ready-to-eat) cereal industry estimates price-cost margins for a number of brands; asks how they are determined: markups due to differentiated product competition portfolio effect if a firm holds two similar brands (will price higher) price collusion among manufacturers Spring 2005 Economics 220C 9

10 Nevo 2001 Strategy: PCM determined from demand without using cost data (as in BLP) Then use estimated demand to predict markups under the 3 scenarios Findings: markups match Nash-Bertrand pricing game between firms (result 2) even though typical markup is 45-50% Spring 2005 Economics 220C 10

11 Nevo - details Data on sales ($9 billion in 1992) of RTE cereals: 25 brands of cereal (out of 200, covering 50-60% of total market), largest share is corn flakes, with 5% 6 major firms (C6>90%): Kellog, General Mills, Post, Quaker Oats, Ralston, Nabisco 65 US cities 20 quarters Data for estimation: market shares and prices in each city-quarter brand characteristics, advertising distribution of demographic characteristics Spring 2005 Economics 220C 11

12 Nevo - econometrics 1.correlation between price and brand-city-quarter specific demand shocks (error term) 1. use panel data, assume city-specific demand shocks uncorrelated conditional on brand and demographics 2. observed variation in city-specific marginal costs 2.large number of own and cross-price elasticities 1. use BLP-type methods, add brand fixed effect, but. 2. do not assume brand characteristics are exogenous 3. model heterogeneity across consumers using demographic data Spring 2005 Economics 220C 12

13 Cereal Market Shares Spring 2005 Economics 220C 13

14 Production cost and profit Spring 2005 Economics 220C 14

15 Sample information Spring 2005 Economics 220C 15

16 Instruments for price Disturbance = city-quarter specific deviation from brand fixed effect want instruments correlated with price but not with city-specific demand shocks previous work used characteristics of other products (not really exogenous) Nevo uses different instruments average price of the brand in other cities in the region (problem if advertising is regional) marginal costs vary across cities due to transportation costs, shelf space, and labor use region dummies, city density, aveage supermarket earnings Spring 2005 Economics 220C 16

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