U.S. Voter Turnout: A Sometime Thing

Looking for a vivid trademark of democracy? How about the right not to vote? Overturn the hard-won prerogative to stay at home, and a defining attribute of democracy gets overturned with it.

But Americans have long been accused of abusing the privilege. Election Day absenteeism is a veritable national folkway in the States, turnouts there comparing rather unfavorably with voter activity rates for other industrialized countries (though the matter isn’t quite that straightforward; see this cross-national survey for some comparative clarification). Per the above link, merely 53.6% of the American voter-age population made its way to the polls for the 2012 presidential election; and that means about 112 million citizens who could have failed to do the same.

The political implications of so massive a truancy are massive, apart from the civics-lesson remonstrances that could be aimed at the apathetic or disillusioned. If it could be demonstrated that the political gestalt of recalcitrant voters assumes a different shape from those who do make an appearance, some candidates are aren’t getting the most out of their constituency, e.g. this New York Times piece on an apparent shortfall of black voters in this year’s presidential contest.

For more detail on the problem we can turn to a raft of Census Bureau data on the turnout phenomenon, an assortment of spreadsheets that consider the demographics of voters in the 2008 presidential election (I can’t find equivalent numbers for 2012; note that the files are dated February of this year). This book plots turnout by state:

table-04a

But when politics come to spreadsheets the latter need be squared away before we can learn anything new about the former, and the latter is slightly messy. First, the Registered and Total Voted headers in row 5 occupy merged cells, and merged cells have no place in the pivot tabling enterprise. But moreover, a set of supplementary headers banner row 6, and two header rows have no more of an analytical place in the process than merged cells:

By selecting A5:M6 and subjecting the range to the Unmerge Cells command we’ve made a start; then delete the Registered and Total Voted entries (that excision is both necessary and harmless; the headers in row 6 continue to distinguish registration from vote data in any case). But the unmerge has also floated the headers in columns A:C to row 5; and as such they need to be pulled down to 6 if they’re to share header that row with all the other field identifiers. You’ve also likely concluded that the header for column A doesn’t really mean what it says: the data beneath it bears state names only (along with that of the nation’s capital, the District of Columbia), and as such the field should probably be renamed.

And if you’re planning to do anything more with the worksheet than read it, you’ll eventually need to delete the United States entry in row 7. That summative record behaves as a grand total, and as such will inflict a double-count of the values upon any pivot table. But before you send that record on its way you may want to think about the data it aggregates. Understand first that the sheet’s numbers are expressed in thousands, i.e. the Total Population of 225,499 in B7 shorthands an estimated 225,499,000; remember that the data report survey results, and as such are subject to the margins of error conveyed in the H and K columns that correlate negatively with state population; the larger the state, the slimmer the error margin. (Let the record also show that the state totals don’t precisely equate with those aggregate US figures in row 7, presumably a bit of fallout from the rounding activity imposed upon what are, after all, survey estimates.)

And do consider the denominators; that is, atop which demographic baseline is turnout data to be mounted? It seems to me that Total Citizen Population – apparently counting those Americans eligible to vote – serves as one, but only one such floor, along with an important alternative, Total Registered. Thus the Percent registered (Citizen +18) for the country in its entirety divides D7 by C7, or the number of estimated registrants by the entire voter-eligible population; and by extension the Percent voted (Citizen 18+) proportion of 63.6 derives from I7/C7. I will confess a laymen’s ignorance about the utility of the Total Population numbers, because they subsume residents who are presumably barred from voting in the first place.

Once those understandings are put in place another metric – which I’ll call Pct of registrants voting – offers itself, via a dividing of the Total Voted figures by Total Registered. To be sure, the measure is curiously subsidiary and self-selected, calculating as it does a subset of voters from among the subset of all potential voters who’ve actually registered. Nevertheless, I’d allow the parameter is worth plumbing, and I’d title column N the aforementioned Pct of registrants voting, and enter in N7, while formatting the field in percentage terms to two decimals:

=I7/D7

(Remember that these percentages possess a different order of magnitude than the native percent figures accompanying the worksheet. The latter are communicated in integer terms e.g. 60.8, not 60.8%.) After copying the formula down N, you’ll note that a very substantial segment of the registered population voted in 2008, a finding not quite as truistic as it sounds. On the one hand, of course, a citizen bothering to register could at the same time be expected to bother to vote, and no state has a Pct of registrants voting falling beneath 80%. Indeed – 22 states (including Washington DC) boast a percent of registrants topping 90%. On the other hand – and here I allude back to the Pew Research link referenced above – relative to other countries the US overall registration percentage vs. voter turnout disparity is high, suggesting a peculiar bifurcated enthusiasm among the electorate. Those taking the pains to register will overwhelmingly go on to vote (at least for presidential contests), but millions of their countrypersons simply don’t take those pains to begin with.

Now about pivot tabling…well, what is there to pivot table? We’ve encountered this mild puzzlement before; because the textual data – here state names – don’t recur, there’s nothing in the State field to aggregate. If we impose a set of coarse, recurring categories upon a new field, e.g. we assign each state a geographical region name, you will have contrived something to pivot, and I’m not sure that’s such a bad idea. An alternative could be to group the values of a selected numeric field, for example Total Population, and have it break out Pct of registrants voting, by way of additional example:

Rows: Total Population (grouped into bins of 1000, which again signify millions)

Values: Pct of registrants voting (formatted in percentages to two decimals)

But one doesn’t discover much variation therein. On the other hand, isn’t the absence of variation a finding?