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Effects of Local News on Political Representation
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newspapers vary in the extent to which their circulation area overlaps congressional districts. There are actually two aspects of this problem: 1) A newspaper may contain only a single congressional district within its primary circulation area, or it may contain a great many; whatever coverage a candidate gets in a given paper is likely to be made more salient to readers in the former than the latter case 2) Independently, a congressional district may be wholly within one paper’s circulation area, or it may be straddle two or three newspaper areas; again, whatever coverage a candidate gets in a given paper is likely to be more salient in the former than the latter case.
3
Using data from the International Yearbook of Editor and Publisher, we have combined these two factors into a single variable, which we call Paper Convergence. The variable takes a maximum value of 1 for the case of a newspaper the covers only a single CD which is itself wholly within that news paper’s circulation area; the variable takes values near 0 for districts that straddle several newspaper areas that in turn each contain several districts. The variable is formed by dividing number of markets covering any part of the district by the total number of newspapers covered by those papers. This media coverage variable ranges between a minimum of .025 and 1, with a mean of .17 and a standard deviation of .12. In the analysis that follows, we use this variable as a stand-alone measure and as a weight for a headline count variable created by Arnold. We call the weighted variable – which is calculated as “Headline Count/ Paper Convergence” -- Weighted Newspaper. The Weighted Newspaper variable has been logged to reduce skew and then scaled to a 0-1 range. The distribution of the weighted measure is shown in Figure 4.
0
.1
.2
.3
F
rac
tion
0
.2
.4
.6
.8
1
Weighted newspaper coverage, n=187
Arnold's measure of coverage, weighted by market structure
Figure 4. Distribution of newspaper coverage scores
3
If a congressional district is covered by N
i
newspapers, and if newspaper N
i
covers T
i
districts, then our
measure is
∑
∑
i
i
T
N
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| | Authors: Cohen, Marty., Noel, Hans. and Zaller, John. |
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9
newspapers vary in the extent to which their circulation area overlaps congressional
districts. There are actually two aspects of this problem:
1) A newspaper may contain only a single congressional district within its primary
circulation area, or it may contain a great many; whatever coverage a candidate gets in a
given paper is likely to be made more salient to readers in the former than the latter case
2) Independently, a congressional district may be wholly within one paper’s circulation
area, or it may be straddle two or three newspaper areas; again, whatever coverage a
candidate gets in a given paper is likely to be more salient in the former than the latter
case.
3
Using data from the International Yearbook of Editor and Publisher, we have combined
these two factors into a single variable, which we call Paper Convergence. The variable
takes a maximum value of 1 for the case of a newspaper the covers only a single CD
which is itself wholly within that news paper’s circulation area; the variable takes values
near 0 for districts that straddle several newspaper areas that in turn each contain several
districts. The variable is formed by dividing number of markets covering any part of the
district by the total number of newspapers covered by those papers. This media coverage
variable ranges between a minimum of .025 and 1, with a mean of .17 and a standard
deviation of .12.
In the analysis that follows, we use this variable as a stand-alone measure and as a weight
for a headline count variable created by Arnold. We call the weighted variable – which is
calculated as “Headline Count/ Paper Convergence” -- Weighted Newspaper. The
Weighted Newspaper variable has been logged to reduce skew and then scaled to a 0-1
range. The distribution of the weighted measure is shown in Figure 4.
0
.1
.2
.3
F
r
ac
t
i
on
0
.2
.4
.6
.8
1
Weighted newspaper coverage, n=187
Arnold's measure of coverage, weighted by market structure
Figure 4. Distribution of newspaper coverage scores
3
If a congressional district is covered by N
i
newspapers, and if newspaper N
i
covers T
i
districts, then our
measure is
∑
∑
i
i
T
N
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