The Market for Diversity in Television News

Media Economics WorkshopNew Economic School, MoscowOctober 28-29, 2011

Lisa GeorgeHunter College and the Graduate CenterCity University of New York

Felix Oberholzer-GeeHarvard Business School

Question

• How does competition among local television stations influence diversity in local news programming?

• Do viewers value this diversity?• Implications

– Welfare?– Political engagement?– Policy?

What We Know

• Theory– Incentive to differentiate depends on relative importance of

price competition & market cannibalization effects• Empirical Evidence:

– Radio (Berry & Waldfogel, 2001; Sweeting 2010)– Newspapers (George 2007)– TV (Baker & George 2011)

Business stealing matters, consumption effects less clear

What We Don’t Know

• What dimensions of differentiation matter to consumers in news markets?– Politics?– Issues?– Race?– Localism?

Why Diversity Matters

• Some illustrations– Hispanic political participation– Newspaper readership– Political competition & turnout

Hispanic Political Participation

Source: Oberholzer-Gee & Waldfogel, AER 2009

Variety in Newspaper MarketsDistance(DMA)

Unique Beats

(DMA)

Topics Covered (DMA)

Topics Covered (DMA)

Per Capita Sales

(ABC)

Per Capita Sales

(ABC)(1) (3) (5) (6) (1) (2)

Owners -0.01 -1.02 -1.84 -1.50 -0.0021 -0.0007(1.86)+ (2.36)* (4.43)** (2.88)** (1.83)+ (0.46)

Papers 0.01 -0.23 -0.82 -0.0024(2.30)* (0.37) (1.08) (1.38)

Constant 0.20 16.80 35.33 38.87 0.0453 0.0483(6.70)** (5.34)** (18.28)** (10.22)** (17.61)*

*(14.27)*

*N 534 534 534 534 498 498DMA's 173 173 173 173 249 249

Source: Lisa M. George, Information Economics and Policy, 2007

Political Competition & Diversity0

510

1520

25

0 10 20 30 40Incument Years in Office

Number of Issues Covered Fitted values

Source: Lisa M. George, Content in Campaigns, 2011

Why Study TV News?

TV News remains the primary news source for US households.

9

Source: Pew Research Center for the People and the Press, Ideological News Sources: Who Watches and Why. September 10, 2010. Sample size about 1500.

Why TV is Hard to Study

• Typical empirical strategy – Identify changes in diversity measures from

(exogenous) changes in market structure• TV News

– Static markets with very limited entry & exit– Regulated ownership

• Need to measure content directly or infer variety from demand

10

Empirical Approach

• Demand-side diversity measures• Supply-side diversity measures

– Issues, Politics, Race, Geography• How do they relate –

– To each other?– To news viewing?– To ownership and other policy variables?

Data

• Newsbank Transcripts– 40 markets, 2006-2010

• FCC Market Structure Data– Number of stations and owners

• Nielsen Viewership– One month (all 210 markets) in 2006, 2008, 2010– Total viewing by timeslot & program type– Black & Hispanic viewing (not used here)

Demand-Side Diversity Measures

• Lead-in effects are important in TV– Cost of changing the channel

• Consumer tendency to switch channels from prime time programming to local news reveals programming differentiation.

• Two illustrations . . .

Local News Viewing . . . Lead-in Matters

ABC CBS NBC Fox Cable0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Tuesday

Entertainment Local News

ABC CBS NBC Fox Cable0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Thursday

Entertainment Local News

Local News and Entertainment Viewing -- Station Shares by Network

Local News & Lag News Viewing Population Share

Local News Viewing . . . Loyalty MattersLocal News and Entertainment Market Shares by Day (2010)

Monday Tuesday Wednesday Thursday Friday0

0.1

0.2

0.3

0.4

0.5

CBS Local NewsCBS Prime TimeABC Local NewsABC Prime Time

Monday Tuesday Wednesday Thursday Friday0

0.1

0.2

0.3

0.4

0.5

NBC Local NewsNBC Prime TimeFOX Local NewsFOX Prime Time

Measuring Differentiation

ABC News

NBCNews

Other

NBCPrime

ABCPrime

Other

Estimating Differentiation

• Lagged Viewing (LV) coefficients measure diversity. • Pairwise estimates are summed across competitors for a

station-market-year measure.• Alternatives & adjustments

I= Local News Indicator for S = {1,0}LV = Lagged Viewing for SS={ABC, CBS, NBC, FOX, Other}

m=market = 210 DMA’s, y=Year={2006, 2008, 2010} D= Day ={M, T, W, Th, F}, T= ½ Hour Timeslot {9pm-12am}

Station Cross-Effects

Prime TimeABC CBS NBC FOX Other

Local News

ABC 0.054 -0.030 -0.038 0.058 0.021

CBS -0.006 0.076 -0.008 -0.054 -0.005

NBC -0.048 -0.080 0.151 -0.110 0.019

FOX 0.013 -0.020 -0.020 0.033 -0.015

Other NA NA NA NA NA

Average effect of an additional prime-time viewer on local news viewing.

Pairwise effects summed over competing (off-diagonal) stations.

Supply-Side Diversity Measures

• Basic Measure – Word Counts– Word share (keyword frequency/total words)– Market Deviations in word shares

• Issues: “Policy Agenda Projects” categories– Keywords matched to categories– Inductive keywords (next round)

• Politics & Race– Members of Congress by party & race (Shares & Totals)

• Geography & Localism– Local place names & local titles

 Mean Word Share (%)

(N=1523)Market St. Deviation

(N=398)Crime 0.976 0.205Weather 0.615 0.187Government 0.391 0.091Business & Economics 0.226 0.045Foreign Affairs & Trade 0.161 0.040Education 0.152 0.031Defense 0.138 0.035TV & Media 0.112 0.031Social Welfare 0.108 0.021Health 0.097 0.029Traffic 0.096 0.044Infrastructure & Environment 0.087 0.022Sports 0.069 0.018Ideological Issues 0.062 0.017Labor & Employment 0.054 0.016Taxes 0.041 0.016Agriculture 0.008 0.004Death Notices 0.0003 0.0003

Issue Diversity Metrics

Political Diversity MetricsMean Word Share

(%)N=1523

Market Standard Deviation

N=398Ethnicity & Race

All Minority 0.0019 0.0020Non-Hispanic White 0.0320 0.0102

Party & OfficeDemocrats House 0.0062 0.0037Republicans House 0.0039 0.0022Democrats Senate 0.0111 0.0042Republicans Senate 0.0100 0.0036

Politician Counts Mean St. Dev.Total Covered Politicians 56 26Average Share of Stations Covering 44% 5.9%

Local Diversity MetricsMean Word Share (%)N=1523

Market St. Deviation

N=398 

Place Coverage 0.592 0.114  Local Government Titles 0.086 0.025  

 Place Counts Mean St. Dev.  Total Place References 1152 304  Average Share of Stations Covering 61% 5%

 

Some Results

• Diversity and market structure• Diversity and content

– Issue Diversity– Political Diversity

• Diversity and viewership

Larger markets, more

differentiation.

More stations (owners), less

differentiation.

No relationship between racial diversity and

differentiation.

Market-level measures do not get us far.

Differentiation & Market Structure

Differentiation & Coverage (Word Shares)

*

*

*

*

*

*

*

*

*

*

*

All issues included in each specification, split table.

Differentiation & Coverage (Word Deviations)

*

*

*

*

*

*

*

All issues included in each specification, split table.

Differentiation & Politics

Specifications with network interactions indicate this is not a FOX effect, but rather a CBS effect.

Differentiation & Race

Covering minority politicians does not contribute to loyalty.

Differentiation & Viewing (All Stations)

Differentiation & Viewing(Most Differentiated Station)

Some Conclusions & Extensions• First attempt to measure diversity in local television news• Initial evidence on points of differentiation

+ Ideology- Government+ Politicians

• Differentiation increases viewing, largest effect for stations• Still to do –

– Inductive differentiation measures– Adjusted loyalty measures

• Extensions – Station loyalty & the market for advertising– Minority coverage & viewership