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Media Ownership Study 8a-Peer Review

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Released: July 27, 2011
Report on a New Local News Media Diversity
Measure
Ethan Kaplan
University of Maryland at College Park
May 4, 2011
Abstract
Review of "Local Media Ownership and Viewpoint Diversity in Local
Television News" by Adam D. Rennho¤ and Kenneth C. Wilbur.
1
Paper Description
"Local Media Ownership and Viewpoint Diversity in Local Television News"
has two components to it: (1.) a new measure of local news media diversity and
(2.) a method for estimating the impact of various measures of media owner-
ship on local media news diversity. Their main contribution is their measure of
diversity. One approach to measuring diversity has been to look at viewership.
A location, then, is said to have diverse media if there is substantive variation
in viewership across di¤erent news sources. However, viewership numbers are
impacted by both supply and demand side factors. The authors try to separate
out the demand side factors so that they can construct a supply side measure
of media diversity. The do this with a structural model based essentially on
comparing relative viewership on local versus national news. Since supply-side
parameters for news are …xed across locations, the authors use cross-sectional
variation to recover demand parameters (essentially a variance in preferences
parameter) and then, assuming invariance of parameters between local and na-
tional news, use the demand-side parameters to recover supply-side parameters
for local news. The measure of diversity, then, is an absolute measure of media
diversity (i.e. based solely on di¤erences in perspective across locations inde-
pendent of di¤erences in preferences across locations). The idea is quite nice
in theory and I think that more can be done with it. Partially, it is nice be-
cause it introduces an easy to compute one-dimensional measure of diversity.
Unfortunately, as the paper currently stands, the identi…cation also relies upon
some very strong assumptions about functional form of the distribution of pref-
erences and invariance of the functional form (up to one location and one scale
parameter) across locations in addition to assumptions that viewership is solely
decided upon using political perspective as opposed to quality.
1

The authors then use the measure to estimate the impact of ownership
changes on diversity. They try a few speci…cations. Their main speci…cations
use …rst di¤erence estimation and pooled OLS estimation. They …nd very little
impact of changes in local news ownership upon changes in local news diversity.
This result has a very similar ‡avor to the well known paper by Gentzkow and
Shapiro (2010) who show that, conditional on state …xed e¤ects, measures of
newspaper ideology are much more strongly correlated with demand-side fac-
tors than supply-side factors. However, the current paper bases their measure
of diversity on viewership whereas a measure of diversity based upon Gentzkow
and Shapiro’s work would be based upon content (language usage by local news
media).
2
Measure of Diversity
2.1
Distributional Functional Form Assumption
The authors assume that the distribution of preferences is the same across lo-
cations up to the distribution mean and the distribution variance. Assume that
di¤erences in metric of ideology should be measured as di¤erences in inverse
of readership from an associated normal distribution. The shape of the nor-
mal distribution then impacts the measures of diversity that get constructed.
Di¤erences in viewership shares lead to larger di¤erences in measured ideology
when the viewership shares are very unequal (i.e. 10% and 60% as opposed to
35% and 35%); however, this is not true, for example, if a uniform distribu-
tion is used. Moreover, it is not clear that the preferences over the ideological
component of demand for news follows a normal distribution.
The formula for diversity is:
D
1
m =
m
(1
sm
3 )
1 (sm
1 )
(1)
where sm can be are viewership shares for local news stations. Substituting in
i
for
m (a parameter measuring the dispersion of preferences which is obtained
from viewership of national t.v. news), we get:
1 (1
sm
= ^
xN
3 )
1 (sm
1 )
BC
^
xN
AB
(2)
1 (1
sm)
1 (sm)
C
A
where sm are viewership shares for national news stations. From the above
k
formula, we see that essentially the relative measure of diversity across locations
is determined solely by (1.) the size of the second national news station (diversity
is decreasing in the size of the second news station’s viewership) and (2.) the size
of the second local news station’s viewership (diversity is increasing in the size of
the second news station’s viewership). To …t the normal model, it must be that
the smaller the size of local viewership of the second news station, the higher the
variance of preferences in the local distribution and, thus, for a given percentage
of the population di¤erentially viewing the third and …rst local news media
2

sources, the media sources must be more polarized. This can be very misleading
if the true distribution of preferences is skewed (and thus not normal). In that
case, its possible, for example, that having a small percentage of the population
watching the middle news source is evidence of low not high variance in the local
distribution of political preferences and thus, for a given di¤erential percentage
of media consumers watching local news, the gap in ideology across local news
stations is larger. The assumption of normally distributed political preferences
with a common metric is probably incorrect (and veri…ably so - i.e. if one media
market has high viewership for national news 1 and 3 and another media market
for 2 and 3, they would be incompatible). Most likely this assumption leads to
strong biases in measurement of local media diversity.
2.2
National Media Relationship to Local Media
I do think that using national media to infer ideological preferences over media
is a nice idea. Instead, I would argue for a more "non-parametric" approach
which partials out national media by controlling for national media viewership
rates.
2.3
Other Comments
1. It wasn’t clear to me how the decision of what is considered media outlets
numbers 1, 2, and 3 are. The order matters a lot since the measure of
diversity is completely determined by the relative size of the 2nd news
outlet.
2. There isn’t much variation in the political viewpoints of the main non-
cable networks; most of the variation across locations could be noise. What
about benchmarking diversity measures with Fox, CNN, and MSNBC
viewing? These should be available in all but a few localities.
3. The measure of diversity of media is increasing in the percentage of the
population watching local media station #2:
1 (1
sm
3 )
1 (sm
1 ) :
It is not clear to me that media diversity is increasing in the percentage
of people watching media station #2. For example, suppose that all 3
media stations were identical and 1/3 of the population watched media
#2. Now increase the media diversity. Suppose that pulls people away
from source #2, media diversity has increased but the measure of media
diversity will have decreased. Again, this is due to the assumption of a
common distribution of preferences - up to mean and variance - across
localities which is normally distributed.
4. There are two notions of media diversity that could be computed. One is
an absolute measure which just looks at di¤erences in perspectives across
locations. The other is a relative measure which incapsulates the possibility
for media to in‡uence public debate. For example, if a locality is very right
wing and there are two news stations: one is far right and the other far-left,
3

then local media will be very diverse but will not encourage public debate.
A less diverse media, then, will increase diversity of thought in public
debate. I de…nitely think that absolute measure like the one presented by
the authors should be constructed but I do think that conditional measures
would also be both useful for the FCC and interesting.
5. Many things besides political preferences could impact viewership such as
production quality. In other words, there might be concentrated viewer-
ship in a locality due to quality di¤erentials across stations rather than
diversity of views (diversity in quality may be strongly positively corre-
lated with the authors’measure of diversity).
3
Estimation of Impact of Ownership on Diver-
sity
1. There are endogeneity concerns. For example, ownership changes could be
related to quality issues. An ownership change may change product qual-
ity. For example, if an acquisition increases quality, that could increase
viewership for a less-viewed station which lower measured diversity. Of
course, the opposite is also possible.
2. Another concern is obviously that there could be lags in adjustment in
media markets. This could be due either to (1.) lags in change in pro-
gramming after a change or (2.) lags in viewership response.
3. The authors say that they can not estimate the …xed e¤ects model due
to an incidental parameters problem. Actually, they do have the degrees
of freedom to estimate …xed e¤ects. However, It is true that they can
not get consistent estimates of the …xed e¤ects. Nonetheless, they can
subtract the group mean from each observation. This "within estimator"
is identical in linear models and is easily implemented in stata using areg.
4. First di¤erencing the data induces autocorrelation. After …rst di¤erencing
the data:
mt
=
t
t 1
mt 1
=
t 1
t 2
Thus,
cov
mt;
mt 1
=
2
Therefore, the data should be clustered at the group level when …rst dif-
ferencing. The authors can test for autocorrelation both with and without
…rst di¤erencing using tests like the Dickey-Fuller test or just be regressing
residuals on lagged residuals by media market.
4

5. There are very high R-squared in levels estimation ( 65%) but very low
ones ( 2.5%) in …rst di¤erence speci…cation. The R-squareds are so high
in the …rst di¤erence estimation because of the high degree of serial cor-
relation in viewership of local media within localities. The persistence is
most likely especially high because the time period is short and during a
period without a lot of change in local tv programming. There are two
possible reasons for the low …xed e¤ects R-squareds : (1.) changes in media
diversity are hard to predict, (2.) the measure of media diversity is not
terribly informative. The latter is potentially worth investigating empiri-
cally. The authors could do this by drop their …rst di¤erencing e¤ects and
see what R-squareds look like cross-sectionally with just the demographic
variables. Moreover, the authors could compare the explanatory power of
covariates on their measure to other measures of local news media diver-
sity. It would also be nice for the authors to discuss the relation between
their measure and other measures of media diversity.
6. Fixed e¤ects can exacerbate measurement error. For similar reasons, so
can …rst di¤erencing the data. This can cause coe¢ cient attenuation. This
may not be an issue if the ownership variable is well measured. On the
other hand, the measurement of the ownership variable should be at the
time of the Nielsen data collection. This could exacerbate measurement
error.
7. The tables could be more self-explanatory.
4
Bibliography
Gentzkow, Matthew and Jesse Shapiro (2010), "What Drives Media Slant? Ev-
idence from U.S. Daily Newspapers.", Econometrica 78(1), pp. 35-71.
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