When the candidate with the big data advantage didn’t win the presidency

Much was made of the effective use of big data by Barack Obama’s campaigns. That analytic advantage didn’t help the Clinton campaign:

Clinton can be paranoid and self-destructively self-protective, but she’s also capable of assessing her own deficiencies as a politician in a bracingly clear-eyed way. And the conclusion that she drew from her 2008 defeat was essentially an indictment of her own management style: Eight years earlier, she had personally presided over a talented, sloppy, squabbling, sprawling menagerie of pals, longtime advisers and hangers-on who somehow managed to bungle the building of a basic political infrastructure to oppose Obama’s efficient, data-driven operation.

To do so, Mook hired a buddy who had helped Terry McAuliffe squeak out a win in the 2014 Virginia governor’s race: Elan Kriegel, a little-known data specialist who would, in many ways, exert more influence over the candidate than any of all-star team of veteran consultants. Kriegel’s campaign-within-a-campaign conducted dozens of targeted surveys—to test messaging and track voter sentiment day-by-day, especially in battleground states—and fed them into a computer algorithm, which ran hundreds of thousands of simulations that were used to steer ad spending, the candidate’s travel schedule, even the celebrities Clinton would invite to rallies.

The data operation, five staffers told me, was the source of Mook’s power within the campaign, and a source of perpetual tension: Many of Clinton’s top consultants groused that Mook and Kriegel withheld data from them, balking at the long lead time—a three-day delay—between tracking reports. A few of them even thought Mook was cherry-picking rosy polling to make the infamously edgy Clinton feel more confident…

In numerous interviews conducted throughout the campaign, Clinton staffers attested to Mook’s upbeat attitude and mastery of detail. But, in the end, Brooklyn simply failed to predict the tidal wave that swamped Clinton—a pro-Trump uprising in rural and exurban white America that wasn’t reflected in the polls—and his candidate failed to generate enough enthusiasm to compensate with big turnouts in Detroit, Milwaukee and the Philadelphia suburbs.

It would be fascinating to hear more. The pollsters didn’t get it right – but neither did the Clinton campaign internally?

The real question is what this will do to future campaigns. Was Donald Trump’s lack of campaign infrastructure and reliance on celebrity and media coverage (also highlighted nicely in the article above) something that others can or will replicate? Or, would the close margins in this recent presidential election highlight even more the need for finely-tuned data and microtargeting? I’m guessing the influence of big data in campaigns will only continue but data will only get you so far if it (1) isn’t great data in the first place and (2) people know how to use it well.

Connecting sundown towns and votes for Trump in Wisconsin

Sundown towns were once common in the North and one academic looks at the connections between such communities and voting for Donald Trump:

Did sundown towns elect Trump in Wisconsin? My research assistant, Kathryn Robinson, and I tried to find out. Since it is much easier to get county-level election returns than municipal ones, we concentrated on “sundown counties,” those having a county seat that could be established as a sundown town or likely sundown town in Loewen’s mapping. An incredible 58 of the state’s 72 counties fit into such a category. Of the 58 sundown counties 31 are 1% or less African American (and only eight more than 2%), suggesting that the proxy of the county seat works in identifying sundown areas at the county level.

The simple answer on Trump and sundown towns in Wisconsin is: “Clearly they elected him.” Sundown counties gave Trump almost 935,000 votes to Clinton’s just over 678,000. His margin in the sundown areas exceeded 256,000 votes. That Clinton won the fifteen non-sundown counties by almost 230,000 votes could not make up for Trump’s 58% to 42% margin in the sundown ones. Just short of two/thirds of all Trump voters in Wisconsin came from sundown counties. Only nine sundown counties chose Clinton with 49 for Trump…

Our appreciation of the critically important historical dimension to sundown voting—both Robinson and I are trained in that discipline—ironically came through a sociologist. That is, when I contacted Loewen to outline the project to him, he mentioned having recently been to Calhoun County, a tiny sundown county in Illinois near where I grew up. That county, he told me, had voted for Obama in the same proportions as the rest of the country in 2008. I then looked up its 2016 vote, a landslide for Trump. Robinson and I had reason to wonder if a similar swing from Obama to Trump characterized the 2008 to 2016 trajectory of sundown county voters in Wisconsin.

The pattern could hardly been more striking. In 2008, Barack Obama defeated John McCain in all but eight of Wisconsin’s sundown counties. These virtually all-white counties delivered to the African American candidate a majority of nearly 143,000 votes. The fifteen very small sundown counties discussed above supported Obama in 2008 by 57.4% to 42.6%. The countervailing continuity lay in the metro Milwaukee suburbancounties, where the vote went to the conservative candidate in both 2008 and 2016, by overwhelming margins in both cases. The intervening 2012 election proved a halfway house, with the Milwaukee suburban counties solidly for Romney but Obama splitting the other sundown counties with the Republican ticket. By 2016, just under 400,000 votes had switched from the Democratic to the Republican candidate in sundown Wisconsin. Outside of the sundown counties the pro-Republican swing from 2008 to 2016 was just 17,000 votes.

It would be worthwhile to see such research carried out elsewhere as there were more sundown towns than people imagine (even if actual laws or records about them are difficult to find).

While Loewen alerts us to this important history, it is also interesting to consider how sundown counties or towns can experience rapid racial and ethnic change. This article cites a rural community that suddenly had an influx of Latino workers for several manufacturing plants. Or, imagine some suburban areas after World War Two that had rapid development and demographic change. I’m thinking of Naperville, Illinois, a sundown town that due to high quality residential and job growth is a suburb today that is increasingly non-white and where city leaders praise the growing diversity. Is there a point where the effects of being a sundown town disappear or could such effects pop up again depending on the situation (economic factors, racial and ethnic change, certain leaders, etc.)?

Should Trump promote a third wave of American suburbanization?

Walter Russell Mead suggests Donald Trump could help usher in a new wave of suburbanization:

What President-elect Trump has the opportunity to do now is to launch a third great wave of suburbanization, one that can revive the American Dream for the Millennial generation, produce jobs and wealth that can power the American economy, and take advantage of changing technology to create a new wave of optimism and dynamism in American life.

There’s a confluence of trends that make this possible. In the first place, the Millennials, like the Boomers, are a large generation that needs both jobs and affordable homes. Second, the shale revolution means that energy in the United States will likely be relatively abundant and cheap for the foreseeable future. Third, both financial markets and the real economy have recovered from the shock of the financial crisis, and, whatever hiccups and upsets may come their way, are now ready for sustained expansion. Fourth, revolutions in technology (self-driving cars and the internet) make it possible for people to build a third ring of suburbs even farther out from the central cities, where land prices are still low and houses can be affordably built.

For national politicians, this is a huge opportunity. Creating the infrastructure for the third suburban wave—new highways, ring roads and the rest of it for another suburban expansion—will create enormous numbers of jobs. The opportunity for cheap housing in leafy places will allow millions of young people to get a piece of the American Dream. Funding the construction of this infrastructure and these homes gives Wall Street an opportunity to make a lot of money in ways that don’t drive the rest of the country crazy.

This approach meshes very well both with the President-elect’s economic instincts and with the economic interests of the people who voted for him. It also works for the Republican dominated states around the country. It capitalizes on one of America’s distinctive advantages: less densely-populated than other advanced countries, the United States has the elbow room for a new suburban wave.

There are all sorts of fascinating things going on with this argument. Let’s just pick out a few.

To start, this argument suggests Eisenhower and Reagan were great because they helped make the suburbs happen. How much did they do in this regard? By the early 1950s, suburbanization was well underway with a postwar housing shortage and lots of developers and local officials interested in building out. The Federal Highway Act of 1956 certainly helped the process and is often credited for helping urban residents flee cities (even though highways were already under construction in many places). This is a good example of presidents getting credit for things that don’t have much direct control over.

Second, this equates Republicans with suburbs. There are certainly patterns here: suburbanites have tended to vote Republican for a long time (particularly the further out one gets) and both Republicans and Democrats have argued more sprawl leads to more Republicans. At the same time, not every conservative loves suburbs nor does every Democrat love cities. If you had to summarize Republicanism since World War II, would suburbs come to mind or other things?

Third, it sounds like this argument is in favor of government spending to promote a certain way of life. In other words, the federal government should subsidize more suburban growth because it helps generate jobs and housing. While this may fit older images of moderate Republicans (Eisenhower was one, Reagan not so much), it doesn’t fit well with more libertarian/small government Republicans. Why should the government promote certain ways of life?

To conclude, it is clear that all of this requires an optimistic view of suburban life. It is the fulfillment of the American Dream. This is a common American image. Does it match all of reality? Are the suburbs open to all? Would the new spending even further from cities open new opportunities for non-whites, immigrants, and the lower class (who are increasingly in the suburbs) or would it allow whiter, wealthier residents to flee even further from urban problems? What are the environmental costs of another ring of suburbia? What does it do to civic life to continue to promote automobile driven culture (even if those self-driving cars are safer and more environmentally friendly)? These are not easy questions to answer even if many Americans would enjoy a third wave of suburbanization.

Just how many McMansions have actually collapsed like Trump’s polling figures?

One common critique of the McMansion is that they are poorly built. The story continues that because they are mass-produced, the materials are bottom of the line so builders don’t have to do anything more than necessary  in the search for big profits. This idea was found in a recent story about the decline of Donald Trump’s polling figures:

Public Policy Polling finds Donald Trump’s numbers collapsing like a poorly-built McMansion.

Might some people find this phrase redundant and ask whether McMansions are poorly-built by definition?

Perhaps I am being too literal here but this gets me thinking about how many McMansions have actually collapsed. I would guess that not too many have collapsed on their own so perhaps the more appropriate figures to search for would measure how many McMansions needed major renovations or fixes and then how this data compares to other kinds of homes. Would HGTV, the network always on the search for homes that need help, be a good source for figures? This is probably not the kind of data builders would want to keep and it would be difficult to collate the information from millions of individual homeowners.

And what would be a better metaphor for the collapse of Donald Trump’s polling numbers?