Interrogating the campaign contribution data

The Campaign Spending Commission has finally posted the updated file of campaign contributions up to the day of the primary election.

I’ve been fiddling around trying to get some different ideas about ways of looking at it.

It’s one of the stages I go through in trying to make sense of the numbers. It doesn’t always pan out, as was the case here, unfortunately.

The usual approach in examine fundraising is to look at the total amounts raised during the election cycle.

I thought I would try something different, looking only at money raised during the last five weeks before the primary. I was wondering whether this might be a way to measure momentum. Is the flow of money to a candidate in the period immediately before the election an indication of the flow of public sentiment?

So I screened the data to include only contributions received from July 1 through the August 9 primary. Then I sorted by the office sought, although in this listing I didn’t go the next step and sort down to the district level. So you’ll have to do that in your head when looking at this list.

Well, click here to see the list of money raised by candidates in those last five weeks.

I have to admit that this approach didn’t seem to yield useful results.

It just doesn’t look like the amount raised in this period is useful in predicting who will end up being winners and losers.

Perhaps I’ll try again, looking at the percentage of the total campaign funds were raised in the last period.

Or maybe I should look at what was spent, rather than the amounts each campaign raised. That might be a more meaningful figure.

Any suggestions? What questions would you have about contribution patterns?


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2 thoughts on “Interrogating the campaign contribution data

  1. Doug

    Sheesh. I suggest you register for (or audit?) a social science methodology course. That would help you learn how to operationalize and define the concepts you are investigating, and would introduce to you a variety of ways to organize and analyze data.

    This presumes that the data available were useful in analyzing the concepts you are interested in. That is often a fatal presumption…

    Reply
  2. Natalie

    Contribution patterns: 1) How many donors (and how much $) are from outside the district? 2) How many donors are PACs and large corporations? 3) How many are individuals?

    I think comparisons made on these levels can provide useful information.

    Reply

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