Who Benefits Whom in Product Markets?

1. Who Benefits Whom in Product Markets? Joel Waldfogel The Wharton School University of Pennsylvania

2. Introduction • What happens when fixed costs are large and preferences differ across groups of consumers? • “Preference Externalities” • product variety and welfare grow in market size • But who benefits whom? • You make me better off only to the extent that we share similar preferences.

3. Do markets avoid tyranny of the majority? • Q: Does Friedman dichotomy hold? • Capitalism and Freedom: Markets avoid strain on social cohesion required by collective choice • A: not with FC and heterogeneous preferences

4. Theoretical Mechanisms • entry and positioning • Depends on size of FC • Perhaps endogenously large • Think of Hotelling line • Density of most preferred products • One-dimensional • Positive “transport costs” • Suppose FC large enough to support only one product

5. Positioning: where does the product locate? • Here, “lefts” have large transport costs • Here, “rights” have high transport costs Density of consumers People are happier, as consumers, when more people share their preferences

6. Entry vs positioning • Suppose fixed costs are lower but still “substantial” • Then get multiple products but get more products nearer denser masses of potential consumers

7. Entry illustration • When a lot of people share my preferences, there are more products near our ideal Close to products Far to products

8. Preference Externalities • As more people share my preferences • More products targeted to us • Greater satisfaction • As more people disagree with my preferences • Entry – no effect on me (“zero across-group effects”) • Positioning – the product moves away from me (“negative across group effects”)

9. Operation and Detection • Operation requires • large fixed costs relative to market size • heterogeneous preferences • Detection requires • Data on multiple markets • Goods not easily traded • Variation in group sizes, shares • Data on products, groups’ tendencies to consume

10. Evidence • Local media market research • Radio (Rand 2003) • Daily newspapers (JPE 2003) • Television (BWPUA 2004) • Today, preliminary results on restaurants as well

11. Preferences • Preferences differ sharply • Blacks and whites • Hispanics and non-Hispanics • In radio, tv, and newspapers

12. radio Hispanics and non-Hispanics listen to different radio Blacks and whites listen to different radio

13. TV Preferences • The top 10 shows among black viewers (few weeks ago) • (1) Girlfriends (UPN) • (2) NFL Monday Night Football (ABC) • (3) Half and Half (UPN) • (4) Second Time Around (UPN) • (5) One on One (UPN) • (6) Eve (UPN) • (7) NFL Monday Showcase (ABC) • (8) Kevin Hill (UPN) • (9) America’s Next Top Model (UPN) • (10) CSI: NY (CBS). In top 10 for all viewers The average overall ranking of the remainder is 96 (among 141 ranked shows).

14. Newspaper Preferences • Tabloid/broadsheet shares differ sharply across zip codes • Whiter zip codes prefer more “hard” news

15. Product Entry and Positioning • Race and radio Markets with larger black population shares have proportionately more black- targeted radio stations

16. Race and local TV Markets with more blacks have more black-targeted local half hours

17. Newspaper positioning • Market demographic composition affects positioning of product

18. Consumer Satisfaction: Who Benefits Whom? • Positive within-group effects for blacks and whites • In radio, television, newspapers • Cross-effects • Generally zero • Negative cross effect of whites on black newspaper reading

19. Restaurants • Smaller fixed costs • MSA of 1 million has 600 restaurants • ( 20 radio stations, 1 daily, 5 broadcast TV) • But market size may be much smaller • MSA? x mile radius? • Questions • How large is the market? • Do preferences differ across groups? • Does agglomeration of like persons promote availability of preferred products?

20. How Large are Restaurant Markets? • Strong relationship between population and restaurants at the MSA level • Local supply serving local demand • Very similar relationships at narrower geography • Mean radius • 3-digit zip: 15 • 4-digit zip: 6 • 5-digit zip: 3

21. 3 vs 4 digit zip code

22. 4 vs 5 digit zip code

23. Implied Restaurant Market Size • Local demand bears same relationship with local supply at broad and narrow levels of geography • (different for fancy restaurants) • Implies • Small markets (5-digit zip) • “exports” balance “imports”

24. Some Fast Food Preferences Percent of group patronizing selected chains in past 30 days

25. Local Chain Availability • If restaurant markets are geographically small, then it matters whether I have an appealing restaurant nearby • Look at data on all locations of 140 chains, by zip code • Are heavily (black/educated/?) zip codes more likely to have restaurants targeting group?

26. Agglomeration of likes promotes availability of preferred cuisine While 25 percent of metro zips have a major coffee/bagel chain, 50 percent of heavily educated zips do While 30 percent of metro zips have a major chicken chain, 60 percent of heavily black zips do

27. Forces limiting preference externalities in food markets • Trade and market expansion • Prepared food does not travel well • Consumers do not travel far for most meals • Grocery superstores may liberate consumers from their neighbors’ tastes • If consumers travel to them

28. Trade complications • NYT and “local” papers • Tradeoff between high quality national coverage and local coverage • Wal-Mart and “local” grocers • Tradeoff between low prices and local tailoring • Winners and losers among consumers • “globalization”

29. Conclusion • How do differentiated products markets work with large fixed costs and heterogenous consumers? • “who benefits whom?” • Evidence - local media and restaurants • Agglomeration of likes promotes satisfaction • Trade can allow consumers to benefit from distant persons • But introduces complications • These perspectives may be useful for food