[EL] Two great resources for campaign finance data

[Daniel Schuman]

Hi everyone,

I wanted to share with you a blogpost by my colleague Ethan Phelps-Goodman
on two tools that allow researchers/reports to make great use of publicly
available campaign finance data.

Daniel

Daniel Schuman
Director | Advisory Committee on Transparency<http://transparencycaucus.org/>
Policy Counsel | The Sunlight Foundation <http://sunlightfoundation.com/>
o: 202-742-1520 x 273 | c: 202-713-5795 | @danielschuman
<http://www.facebook.com/sunlightfoundation><http://twitter.com/sunfoundation><http://www.youtube.com/sunlightfoundation><http://sunlightfoundation.com/join/><http://blog.sunlightfoundation.com/feed/rss/>

 In Depth with Campaign Finance Data
Written byEthan Phelps-Goodman <http://sunlightlabs.com/blog/author/ethan/>
Date10/12/2011 11:03 a.m.
http://sunlightlabs.com/blog/2011/campaign-finance-in-depth/
 Introduction

Influence Explorer <http://influenceexplorer.com/> and
TransparencyData<http://transparencydata.com/> are
the Sunlight Foundation’s two main sources for data on money and influence
in politics. Both sites are warehouses for a variety of datasets, including
campaign finance, lobbying, earmarks, federal spending and various other
corporate accountability datasets. The underlying data is the same for both
sites, but the presentation is very different. Influence Explorer takes the
most important or prominent entities in the data--such as state and federal
politicians, well-known individuals, and large companies and
organizations--and gives each its own page with easy to understand charts
and graphs. TransparencyData, on the other hand, gives searchable access to
the raw records that make up each Influence Explorer page. Influence
Explorer can answer questions like, “who was the top donor to Obama’s
presidential campaign?” TransparencyData lets you dig down into the details
of every single donation to that campaign.

Every chart and figure in Influence Explorer is derived from the detailed
records in TransparencyData. But correctly computing totals from the raw
records isn’t always straightforward. As an example of the steps necessary
to derive the totals in Influence Explorer from the raw records in
TransparencyData, we’ll look at contributions from the accounting firm Ernst
& Young to Senator Chuck Schumer. We’ll use Ernst & Young and Schumer
because the data happens to include a lot of illustrative examples, not
because of any specially meaningful relationship between the two.

<http://influenceexplorer.com/organization/ernst-young/653ea5cad97c456c8d48d468910e47db>
 Ernst & Young's top contributions.
<http://influenceexplorer.com/organization/ernst-young/653ea5cad97c456c8d48d468910e47db>
<http://influenceexplorer.com/organization/ernst-young/653ea5cad97c456c8d48d468910e47db>

<http://influenceexplorer.com/politician/charles-e-schumer-d/e708669995e844af90f205003683f2fa>
 Sen. Schumer's top donors.
<http://influenceexplorer.com/politician/charles-e-schumer-d/e708669995e844af90f205003683f2fa>
<http://influenceexplorer.com/politician/charles-e-schumer-d/e708669995e844af90f205003683f2fa>

According to Influence Explorer, Ernst & Young has given $221,000 to
Schumer. The $221,000 figure can be seen on both Ernst & Young’s
page<http://influenceexplorer.com/organization/ernst-young/653ea5cad97c456c8d48d468910e47db>and
Schumer’s
page<http://influenceexplorer.com/politician/charles-e-schumer/e708669995e844af90f205003683f2fa>.
To see the raw records that make up this sum, you can search
TransparencyData for contributions with ‘Schumer’ as the recipient and
‘Ernst & Young’ as the organization. You should see a page like
this<http://transparencydata.com/contributions/#b3JnYW5pemF0aW9uX2Z0PUVybnN0JTIwJTI2JTIwWW91bmcmcmVjaXBpZW50X2Z0PVNjaHVtZXI=>.
If you download the data and open it in a spreadsheet program such as Excel,
you’ll be able to see details for every contribution. Summing up the
‘contribution_amount’ column for all 242 rows gives a total of $227,500.
This is $6,500 more than is listed in Influence Explorer. The rest of this
article will explain how the final figure of $221,000 is arrived at, and
along the way show some of the intricacies of campaign finance rules and
limitations of the data.


<http://transparencydata.com/contributions/#b3JnYW5pemF0aW9uX2Z0PUVybnN0JTIwJTI2JTIwWW91bmcmcmVjaXBpZW50X2Z0PVNjaHVtZXI=>
Transaction Types and Contributor Categories

Our campaign finance data comes from the Center for Responsive
Politics<http://www.opensecrets.org/>(CRP), which in turn gets its
data from the Federal
Election Commission <http://www.fec.gov/> (FEC). The FEC tracks a wide
variety of financing, categorizing every contribution into one of 68
transaction types <ftp://ftp.fec.gov/FEC/indiv_dictionary.txt>. In Influence
Explorer we’re only interested in straightforward contributions from
individuals or Political Action Committees (PACs) to candidates. We don’t
track money that goes from one PAC to another or from party committees to
candidates, and we don’t track various more esoteric accounting measures,
such as money that’s rolled over from one election cycle to the next. The
only FEC transaction types we include are the following: 10, 11, 15, 15e,
15j and 22y (for contributions from individuals) and 24k, 24r and 24z (for
contributions from PACs). This list of categories was adopted primarily to
maintain consistency with CRP’s methodology. If you're interested in some
less common forms of contributions you may want to compute the sums yourself
using a different set of transaction types.

To match Influence Explorer's totals in the Ernst & Young example there's
only one row that needs to be excluded: row 200, transaction type 18j. (18j
indicates that the contribution was already reported elsewhere as part of
another contribution.)

In addition to excluding transactions based on their type, transactions are
also excluded based on the category of the contributor. Contributor
categories are codes assigned by CRP that usually encode the industry of the
company, but also encode special cases like party committees, candidate
self-financing and unitemized contributions. A full list of category codes
is available here <ftp://ftp.fec.gov/FEC/indiv_dictionary.txt>. For
Influence Explorer we exclude all records with contributor_category starting
with Z, except for Z90s (candidate self-financing), which are included. In
this example there are no Z contributions.
Identifying Corporations and Their Subsidiaries

Another set of concerns relates to how an organization or its parent
organization is labeled in the data. TransparencyData search results will
include all records that contain the words you search on–in this case the
words ‘Ernst’ and ‘Young’. The Influence Explorer totals, on the other hand,
are based only on records where organization_name or
parent_organization_name exactly matches "Ernst & Young". The stricter
matching in Influence Explorer makes sense, since we don’t want to
erroneously include a record. In TransparencyData the more permissive
matching is useful, since the user has a chance to look at each record and
decide what is relevant.

A contributor’s employer information, as submitted to the FEC by the
contributors themselves, is listed in the field labeled contributor_employer.
This information is not standardized in any way. Some of the variations in
this column for these search results include “ERNST & YOUNG”, “ERNST & YOUNG
LLP” AND “ERNST & YOUNG, LLP”. To make the data more useable, CRP has
undertaken the significant task of standardizing the many variations of
organization names. The standardized name assigned by CRP is listed in the
organization_name column. CRP also adds information on corporate
relationships by listing any parent company in parent_organization_name. Our
example data shows several rows where Ernst & Young is listed as the parent
company. These records will be included in the Influence Explorer totals for
Ernst & Young, even when the original contributor_employer didn’t directly
mention Ernst & Young.

This standardization process is unfortunately not perfect or complete. For
example, in row 7 you’ll see that the original contributor_employer is
listed as “WASHINGTON COUNCIL ERNST & YOUNG”, but CRP has erroneously
standardized the name to “Akin, Gump et al”. Because of this error, the
$1000 contribution will not be included in Influence Explorer’s totals for
Ernst & Young.Update: CRP informs us that this is not an error. Although the
individual had listed Ernst & Young as his employer, CRP researchers
determined through lobbying records that the individual also worked for
Akin, Gump et al, and that this was a more appropriate assignment. Errors
can also run the other direction, causing contribution to be included where
they should not be. Examples of this are found in rows 124 and 179, which
have ‘CAP GEMINI ERNST & YOUNG’ in the original contributor_employer field.
Cap Gemini Ernst & Young is actually a separate firm, sold off from Ernst &
Young in 2001. But the field has been standardized to ‘Ernst & Young’, so
the two contributions will show up in Influence Explorer’s Ernst & Young
totals. Update: CRP has since corrected this error. If you notice errors in
the data yourself, CRP happily accepts corrections <info at crp.org>.

Both CRP and Sunlight Foundation work hard to find an eliminate errors, but
with over 40 million campaign finance records, this will always remain
somewhat of a work in progress. Despite the occasional flaws, this data is
still an enormous improvement over what's available directly from the FEC or
any other source.
Other Considerations

Within the field of campaign finance reporting, it is standard practice to
determine the total amount a company gave by grouping contributions from
employees together with contributions from the company’s PAC. This is a
necessary simplification, but it ignores the reality that not all employees
are giving because of their corporate affiliation, and not all candidates
will view every contribution from an individual as being representative of
individual’s employer. If you are only interested in direct contributions
from the corporation's PAC then you can limit the records you consider to
those with contributor_type of C (for committee).

It is also worth noting that CRP, and therefore Influence Explorer, counts
the contributions of immediate family members towards the organization. An
example of this can be seen in row 205, where Patricia Laskaway (occupation
homemaker) is listed as affiliated with Ernst & Young by virtue of Phillip
Laskaway (occupation Ernst & Young LLP).

Finally, the FEC only requires itemized disclosure of contributions from
donors that gave more than $200 in an election cycle. So the $221,000 from
Ernst & Young to Schumer doesn’t include any money that came from smaller
donors.
More Resources

This is only a brief introduction to a complex field. More information on
the data itself is available from our data providers. For federal campaign
finance and lobbying data this is CRP <http://www.opensecrets.org/>, which
in turns gets its data from the FEC <http://www.fec.gov/>. More details on
our handling of the data are available on the Influence Explorer methodology
pages for campaign
finance<http://influenceexplorer.com/about/methodology/campaign_finance>and
lobbying <http://influenceexplorer.com/about/methodology/lobbying>. For
information on sources and methodology for our other data sets see the
Influence Explorer About page <http://influenceexplorer.com/about>.

If you have any questions or comments we'd love to hear from
you<http://influenceexplorer.com/contact/>
.
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