Organizing by themes I: American politics

This site benefits/suffers/both from consisting of posts about a wide range of topics, all linked under the amorphous heading “data-driven storytelling.”

In an attempt to impose some coherent structure, I am organizing related posts both chronologically and thematically.

Given that I have multiple degrees in political science, with an emphasis on American politics, it is not surprising that I have written a few dozen posts in that field…and that is where I begin.

I Voted sticker

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I started by writing about the 2016 elections, many based on my own state-partisanship metric (which I validate here).

The absurdity of the Democratic “blue wall” in the Electoral College

Hillary Clinton’s performance in five key states (IA, MI, OH, PA, WI)

Why Democrats should look to the south (east and west)

How having (or not) a college degree impacted voting

An alternative argument about gerrymandering

An early foray into what I call “Clinton derangement”

The only statistic from 2016 that really matters

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Here are a few posts about presidential polling (before FiveThirtyEight jumped on the bandwagon)…

Be careful interpreting President Trump’s approval polls

…and the 2017 special election in Georgia’s 6th Congressional District (GA-6)

Ossoff and the future of the Democratic Party

Using GA-6 polls to discuss statistical significance testing (spoiler: I am not a fan)

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And then I started looking ahead to 2018…first to control of the United States House of Representatives (“House”). Note that posts are often cross-generic…

An alternative argument about gerrymandering

The impact of voting to repeal (and not replace) Obamacare (May 2017)

I debut my simple forecast model (June 2017)

Making more points about polls and probability

A March 2018 update

A followup March 2018 update (after which I stopped writing about the 2018 House elections)

…then the United States Senate

The view from May 2017

What it meant that the Senate voted NOT to repeal Obamacare in July 2017

The view from December 2017

…and, finally, races for governor in 2017 AND 2018.

The view from June 2017

A tangentially-related post may be found here.

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After Labor Day 2018, I developed models (based on “fundamentals” and polls) to “forecast” the Senate elections…

September 4

September 13

October 23

…and those for governor (the October 23 post addressed both sets of races)

September 16

These culminated in…

My Election Day cheat sheet

And my own assessment of how I did (spoiler: not half bad)

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Beginning in April 2019, I turned my attention to the 2020 elections.

First came a wicked early look at the relative standings of the dozens of women and men actually or potentially seeking the 2020 Democratic presidential nomination:

April 2019

Then came a wicked early look at the 2020 presidential election itself.

April 2019

And, of course, a wicked early look at races for Senate (2020) and governor (2019-20).

With the first of regular updates to both the 2020 Democratic presidential nomination and the 2020 presidential election in May 2019

This post both set up the first Democratic debates and had good news for Democrats looking ahead to 2020.

This post set up the second Democratic debates and drew some conclusions about who “won” and “lost” the first debates.

This post updated the data for August 2019 and drew some conclusions about who “won” and “lost” the second debates.

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Finally, there are other politics posts that defy easy categorization.

I indulged in some speculative alternative history about the presidential elections of 1948 and 2000.

I delineated issue differences between Democrats and Republicans.

I got a bit personal here and here, concluding with the fact that, despite overlapping in the same residential college at Yale for two years, I did NOT know Associate Justice Brett Kavanagh at all.

I argued for the abolition of the Electoral College.

Until next time…

Positively pondering pesky probabilities, perchance

One inspiration to start this “data-driven storytelling” blog was the pioneering work of Nate Silver and his fellow data journalists at FiveThirtyEight.com; their analyses are an essential “critical thinking” reality check to my own conclusions and perceptions. Indeed, when I finally get around to designing and teaching my course on critical thinking (along with my film noir course), the required reading would include Silver’s The Signal and the Noise and a deep dive into Robert Todd Carroll’s The Skeptic’s Dictionary. I will also include Ken Rothman’s Epidemiology: An Introduction; what drew me to epidemiology (besides my long career as a public health data analyst) was its epistemological aspect. By that I mean how the fundamental methods and principals of epidemiology allow us to critically assess any narrative or story.

To that end, I have been reading with great interest Silver’s 11-part series that “reviews news coverage of the 2016 general election, explores how Donald Trump won and why his chances were underrated by most of the American media.” And while I highly recommend the entire series of articles, the September 21 conclusion is the jumping off point for my own observations about assessing the likelihood of various events.

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Let me begin with a passage from that article:

In recent elections, the media has often overestimated the precision of polling, cherry-picked data and portrayed elections as sure things when that conclusion very much wasn’t supported by polls or other empirical evidence.

I personally think investigative journalists are heroic figures who will ultimately save American democracy from its current self-induced peril. But they are trained in a very specific way: deliver the fact of a story with certainty and immediacy. In so doing, they are responding to media consumers with little patience for complex narratives suffused with uncertainty.

To quote Silver again, “a story can be 1. fast, 2. interesting and/or 3. true — two out of the three — but it’s hard for it to be all three at the same time.”

One narrative that developed fairly early about the 2016 presidential election campaign was that Democratic nominee Hillary Clinton was the all-but-inevitable victor. I wrote about one version of this flawed narrative here.

Reinforcing this narrative were election forecasts issued during the last weeks of the campaign that practically said “stick a fork in Trump, he is finished.” But as Silver rightly observes, some of these models were flawed because they failed to account for the “correlation in outcomes between [demographically similar] states.” For example, were Republican nominee Donald Trump to outperform his polls in Wisconsin on Election Day, he would likely also do so in Michigan, Minnesota and Iowa. And that is essentially what happened.

Still, because aggregating polls yields a more precise picture of the state of an election at a given point in time, I aggregated these 2016 election forecasts. Going into Election Day, here were some estimated probabilities of a Clinton victory, ranked lowest to highest.

FiveThirtyEight 71.4%
Betting markets 82.9%[1]
The New York Times Upshot 84.0%
DailyKos 92.0%
HuffingtonPost Pollster 98.2%
Princeton Election Consortium (Sam Wang) 99.5%

The average and median forecast was 88.0%. Remove the most skeptical forecast (though Clinton still a 5:2 favorite), and the average and median jump to 91.3% and 92.0%, respectively. By contrast, if you remove the least forecast, the average and median drop to 84.1% and 83.5%, respectively.

It is an understandable human tendency to look at a probability over 80% and “round up” from “very likely, but not guaranteed” to “event will happen.” And, under the frequentist definition of probability, we would be correct more than 80% of the time in the long run.

But we would not be correct as much as 20% of the time.

Ignoring Wang’s insanely optimistic forecast for various reasons, the “aggregate” forecast I had in mind on Election Day was that Clinton had about an 84% chance of winning.

The flip side, of course, was that Trump had about a 16% chance of winning.

A good way to interpret this probability is to think about rolling a fair, six-sided die.

Pick a number from one to six. The chance that if you roll the die, the number you picked will come up, is 1 in 6, or 16.7%.

On Election Day, Trump metaphorically needed to roll his chosen number…and he did.

But even if take the Wang-inclusive average of 88%, that is still a 1 in 8 chance. Throw eight slips of paper with the numbers one through eight written on them in a hat (I like fedoras, myself), pick one and draw. If your number comes up (which will happen 12% of the time over many draws), you win.

Trump picked a number between one and eight then pulled it out of our hypothetical fedora, and he won the election.

One way people misunderstand probability (and one of many reasons I am resolutely opposed to classical statistical significance testing) is mentally converting event x has a very low probability (like, say, matching DNA in a murder trial—only a 1 in 2 million chance!) with that event cannot happen.

So, even the Wang forecast—which gave Trump only a 1 in 200 chance of winning—did NOT mean that Clinton would definitely win. It only meant that Trump had to pull a specific number between one and 200 out of our hypothetical fedora. He did, and he won.

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On the other end of the spectrum is an overabundance of caution in assessing the likelihood of an event. This usually occurs when interpreting election polls.

In this post, I discussed Democratic prospects in the 2017 and 2018 races for governor.

One of the two governor’s races in November 2017 is in Virginia, where Democratic governor Terry McAuliffe is term-limited. The Democratic nominee is Lieutenant Governor Ralph Northam, and the Republican nominee is former Republican National Committee chair Ed Gillespie.

Here are the 13 public polls of this race listed on RealClearPolitics.com[2] taken after the June 13, 2017 primary elections:

Poll Date Sample MoE Northam (D) Gillespie (R) Spread
Monmouth* 9/21 – 9/25 499 LV 4.4 49 44 Northam +5
Roanoke College* 9/16 – 9/23 596 LV 4 47 43 Northam +4
Christopher Newport Univ.* 9/12 – 9/22 776 LV 3.7 47 41 Northam +6
FOX News* 9/16 – 9/17 507 RV 4 42 38 Northam +4
Quinnipiac* 9/14 – 9/18 850 LV 4.2 51 41 Northam +10
Suffolk* 9/13 – 9/17 500 LV 4.4 42 42 Tie
Mason-Dixon* 9/10 – 9/15 625 LV 4 44 43 Northam +1
Univ. of Mary Washington* 9/5 – 9/12 562 LV 5.2 44 39 Northam +5
Roanoke College* 8/12 – 8/19 599 LV 4 43 36 Northam +7
Quinnipiac* 8/3 – 8/8 1082 RV 3.8 44 38 Northam +6
VCU* 7/17 – 7/25 538 LV 5 42 37 Northam +5
Monmouth* 7/20 – 7/23 502 LV 4.3 44 44 Tie
Quinnipiac 6/15 – 6/20 1145 RV 3.8 47 39 Northam +8

Eight of these polls have Northam up between four and seven percentage points, including four of the last six. Two polls show a tied race. No poll gives Gillespie the lead.

And yet, here was the headline on Taegan Goddard’s otherwise-reliable Political Wire on September 19, 2017, referring to the just-released University of Mary Washington (Northam +5) and Suffolk polls (Even): Race For Virginia Governor May Be Close.

Granted, the two polls gave Northam an average lead of only 2.5 percentage points, which, without context, suggest a close race on Election Day. Furthermore, all three Political Wire Virginia governor’s race poll headlines since then have been on the order of: Northam Maintains Lead In Virginia.

Here is the thing, however. Most people (as I did) will equate “close” with “toss-up.” But there is a huge difference between “we have no idea who is going to win because the polls average out to a point or two either way” and “one candidate consistently has the lead, but the margin is relatively narrow.”

The latter is clearly the case in the 2017 Virginia governor’s race, with Northam’s lead averaging 4.4 percentage points in eight September polls within a narrow range (standard deviation [SD]=3.3). We are still more than five weeks from 2017 Election Day (November 7), so this is unlikely to be “herding,” the tendency of some pollsters to adjust their demographic weights and turnout estimates to avoid an “outlier” result (undermining the rationale for aggregating polls in the first place).

The problem comes when members of the media try to interpret the results of individual polls. They have absorbed the lesson of the “margin of error” (MoE) almost too well.

For example, the Monmouth poll conducted September 21-25, 2017 gives Northam a five percentage point lead, with a 4.4 percentage point MoE. Applying that MoE to both candidates’ vote estimates, we have 95% confidence that the “actual” result (if we had accurately surveyed every likely voter, not a sample of 499) is somewhere between Gillespie 48.4, Northam 44.6 (Northam down 3.8) and Northam 53.4, Gillespie 39.6 (Northam up 13.8). It is this range of possible outcomes, from a somewhat narrow Gillespie victory to a comfortable Northam win that leads members of the media to imply through oversimplification that this race will be close, meaning “toss-up.”

And yet, even within this poll, the probability (using a normal distribution, mean= 5.0, SD=4.4) that Northam is as little as 0.0001 percentage points ahead is 87.2%, making him a 7:1 favorite, about what Hillary Clinton was on Election Day 2016.

OK, maybe that was not the best example…

But when you aggregate the eight September polls, the MoE drops to about 1.3[3], putting the probability Northam is ahead at well over 99%. Even if the MoE only dropped to 3.0, the probability of a Northam lead would still be about 93%.

My point is this. Every poll needs to be considered not just as an item in itself (polls as NEWS!) but within the larger context of other polls of the same race. And in the 2017 Virginia governor’s race, the available polling paints a picture of a narrow but durable lead for Northam.

I have no idea who will be the next governor of Virginia. But a careful reading of the data suggests that, as of September 29, 2017, Lt. Governor Ralph Northam is a heavy favorite to be the next governor of Virginia, despite being ahead “only” 4 or 5 percentage points.

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Finally, here is an update on this post about the Democrats’ chances of regaining control of the United States House of Representatives (House) in 2018.

Out of curiosity, I built two simple linear regression models. One estimates the number of House seats Democrats will gain in 2018 only as a function of the change from 2016 in the Democratic share of the total vote cast in House elections. The Democrats lost the total 2016 House vote by 1.1 percentage points, so if they were to win the 2018 House vote by 7.0 percentage points, that would be an 8.1 percentage point shift.

Right now, FiveThirtyEight estimates Democrats have an 8.0 percentage point advantage on the “generic ballot” question (whether a respondent would vote for the Democratic or the Republican House candidate in their district if the election were held today).

My simple model estimates a pro-Democratic House vote shift of 9.1 percentage points would result in a net pickup of 26.7 House seats, a few more than the 24 they need to regain control. The 95% confidence interval (CI) is a gain of 17.0 to 36.4 seats.

But the probability that Democrats net AT LEAST 24 House seats is 71.1%, making the Democrats 5:2 favorites to regain control of the House in 2018.

My more complex model adds a variable that is simply 1 for a midterm election and 0 otherwise, as well as the product of this “dummy” variable and the change in Democratic House vote share. I hypothesized (correctly) that this relationship would be stronger in midterm elections.

This model estimates that a 9.1 percentage point increase from 2016 in the Democratic share of the House vote would result in a net gain of 31.8 seats. However, with two additional independent variables (and only 24 data points), the 95% CI is much wider, from a loss of 7.0 seats to a history-making gain of 68.3 seats.

Still, this translates to a 66.1% probability (2:1 favorites) the Democrats regain the House in 2018.

Figure 1 shows the estimated probability the Democrats regain the House in 2018 using both models and a range of percentage point changes in House vote share from 2016.

Figure 1: Probability Democrats Control U.S. House of Representatives After 2018 Elections Based Upon the Change in Democratic Share of the House Vote, 2016-18

Democratic Probability 2018 House capture

The simple model (blue curve) gives the Democrats no chance to recapture the House in 2018 until the pro-Democratic change in vote share reaches 6.5 percentage points, after which the probability rises sharply and dramatically to a near-certainty at the 10.0 percentage point change mark. The more complex model (red curve), meanwhile, assigns steadily increasing chances for the Democrats, flipping to “more likely than not” at the 7.0 percentage point change mark; even at a truly historic 15 percentage point change, the complex model only gives the Democrats an 85.3% chance to recapture the House in 2018.

For the record, I lean toward the more complex model.

It is worth noting that in the current FiveThirtyEight estimate, 15.8% of the electorate is undecided or chose a third party candidate (when an option). If the undecided vote breaks heavily toward the party not controlling the White House in a midterm election (one way electoral “waves” form), a 66-71% would likely be an underestimate of the Democrats’ chances of regaining control of the House in 2018.

And…apropos of nothing…Happy 51st Birthday to me (September 30, 2017)!!

Until next time…

[1]  To be honest, I do not recall where I got this number from…possibly from fivethirtyeight.com or maybe from https://betting.betfair.com/politics/us-politics/…

[2] Accessed September 28, 2017

[3] The total number of voters sampled across these eight polls is 4,915, which is 9.85 times higher than the 499 sampled in the Monmouth poll. The square root of 9.85 is 3.14. Dividing 4.1 by 3.14 gives you 1.31.

Using Jon Ossoff polling data to make a point about statistical significance testing

I do not like the phrase “statistical dead heat,” nor do I like the phrase “statistical tie.” These phrases oversimplify the level of uncertainty accruing to any value (e.g., polling percentage or margin) estimated from a sample of a larger population of interest, such as the universe of election-day voters; when you sample, you are only estimating the value you wish to discern. These phrases also reduce quantifiable uncertainty (containing interesting and useful information) to a metaphorical shoulder shrug: we really have no idea which candidate is leading in the poll, or whether two estimated values differ or not.

For example, a poll released June 16, 2017 showed Democrat Jon Ossoff leading Republican Karen Handel 49.7% to 49.4% among 537 likely voters in the special election runoff in Georgia’s 6th Congressional District. The margin of error (MOE) for the poll was +/-4.2%, meaning that we are 95% confident that Ossoff’s “true” percentage is between 45.5 and 53.9%, while Handel’s is between 45.2% and 53.6%.

In other words, these data suggest a wide range of possible values, anywhere from Ossoff being ahead 53.9 to 45.2% to Handel being ahead 53.6 to 45.5%. In fact, there is a 5% chance that either candidate is further ahead than that. Finally, because random samples such as these are drawn from a normal (or “bell curve”) distribution, percentages closer to those reported (Ossoff ahead 49.7 to 49.4%) are more likely than percentages further from those reported.

But this is a lot to report, and to digest, so we use phrases like “statistical dead heat” or “statistical tie” as cognitive shorthand for “there is a wide range of possible values consistent with the data we collected, including each candidate having the exact same percentage of the vote.”

Each phrase has its roots in classical statistical significance testing. The goal of this testing is to assure ourselves that any value we estimate from data we have collected (a percentage in a poll, a relative risk, a difference between two means) is not 0.

To do so, we use the following, somewhat convoluted, logic.

Let’s assume that the value (or some test statistic derived from that value) we have estimated actually is 0; we will call this the null hypothesis. What is the probability (we will call this the “p-value”) that we would have obtained this value/test statistic or one even higher purely by chance?

Got that?

We are measuring the probability—assuming that the null hypothesis is true—that a value (or one higher) was obtained purely by chance.

And if the probability is very low, it would therefore be very unlikely that we have gotten our value purely by chance, so it must be the case that we did NOT get it by chance. And so we can “reject” the null hypothesis (even though we assumed it to be true to arrive at this rejection), given that value that we got was so high.

The higher the probability, the more difficult it becomes to reject the null hypothesis.

By a historical accident,  any p-value less than 0.05 is considered “statistically significant,” meaning that we can reject the null hypothesis.

Of course, we REALLY want to know how probable the null hypothesis itself is, but that is a vastly trickier proposition.

Or, even better…we REALLY want to know how likely the actual value we observed is.

Think about it. All we are really learning from classical statistical significance testing is either “our value is probably not 0” or “we can’t be certain that our value is not 0…it just might be.” This tells us nothing about the quality of the actual estimate we obtained is, how near the “true” value it actually is.

Now, to be fair to the 0.05 cut-point for determining “statistical significance,” it does have an analogue in the 95% confidence interval.

The 95% confidence interval (CI) is very similar to the polling MOE discussed earlier. It is a range of values (often calculated as value +/-1.96*standard error[1]) which we are 95% confident includes the “true” value.

Let’s say you estimate the impact of living in a less walkable neighborhood relative to living in a more walkable neighborhood on incident diabetes over 16 years of follow-up. Your estimate is 1.06 (i.e., you have 6% higher risk of contracting diabetes), with a 95% CI of 0.90 to 1.24. In other words, you are 95% confident that the “true” effect is somewhere between a 10% decrease in incident diabetes risk and a 24% increase in incident diabetes risk.

Ahh, but this is where that pesky cognitive shorthand comes back. See, that 95% CI you reported includes the value 1.00 (i.e., no effect at all). Therefore, there is likely no effect of neighborhood walkability on incident diabetes.

No, no, a thousand times no.

It simply means that there is a specified range of possible measures of effect, only one of which is “no effect.” In fact, the bulk of the possible effects are on the risk side (1.01-1.24), rather than on the “protective side” (0.90-0.99).

Just bear with me while I come to the point of this statistical rigmarole.

Early this morning, I posted this on Facebook:

The election-eve consensus is that the Jon Ossoff-Karen Handel race (special election runoff in Georgia’s 6th Congressional District) is a dead heat, with Handel barely ahead. This consensus is based in large part on the RealClearPolitics polling average (Handel +0.25). However, the RCP only looks at the most recent poll by any given pollster, and only within a very narrow time frame

Hogwash (for the most part).

All polls are samples from a population of interest, meaning that you WANT to pool recent polls from the same pollster (each is a separate dive into the same pool using the same methods). Also, I found no evidence that the polling average has changed much since the first election April 19

My analysis (90% hard science, 10% voodoo) is that Ossoff is ahead by 1.4 percentage points. Assume a very wide “real” margin of error of 9 percentage points, and Ossoff is about a 62% favorite to win today. 

Meaning, of course, that there is a 38% chance Handel wins

That is still a very close race, but I would give Ossoff a small edge

And, bloviating punditry aside, for Ossoff even to lose by a percentage point would be a remarkable pro-Democratic shift for a Congressional seat Republicans have dominated for 40 years.

Polls close at 7 pm EST. 

Here is the full extent of my reasoning.

I collected all 12 polls of this race taken after the first round of voting on April 20, 2017. Four were conducted by WSVB-TV/Landmark and showed Ossoff ahead by 1 percentage point (polling midpoint 5/31/2017), 3 (6/7), 2 (6/15) and 0 (6/19) percentage points. Two each were conducted by the Republican firm Trafalgar Group (Ossoff +3 [6/12], Ossoff -2 [6/18]) and by WXIA-TV/SurveyUSA (Ossoff +7 [5/18], even [6/9]). Other polls were conducted by Landmark Communications (Ossoff -2 [5/7]), Gravis Marketing (Ossoff +2 [5/9]), the Atlanta Journal-Constitution (Ossoff +7 [6/7]) and Fox 5 Atlanta/Opinion Savvy (Ossoff +1 [6/15]).

On average, these polls show Ossoff ahead by an average of 1.85 percentage points.

Using a procedure I suggest here, I subtracted the average of all other polls from those from a single pollster. For example, the average of the four WSVB-TV/Landmark was Ossoff +1.5, while the average of the other eight polls was Ossoff +2.0. This difference—or “bias”—of -0.5 percentage points shows the WSVB-TV/Landmark polls may have slightly underestimated the Ossoff margin.

I then “adjusted” each poll by subtracting its “bias” from the original polling value (e.g., I added 0.5 to each WSVB-TV/Landmark Ossoff margin). For convenience, I lumped the pollsters releasing only one poll into a single “other” category; its “bias” was only 0.2.

The “adjusted” Ossoff margin was now +1.865.

To see whether the Ossoff margin had been increasing or decreasing monotonically over time, I ran an ordinary least squares (OLS) regression of Ossoff margin against polling date midpoint (using the average, if polls had the same midpoint date). There was no evidence of change over time; the r-squared (a measure of the variance in Ossoff margin accounted for by time) was 0.01.

Still, out of a surfeit of caution, I decided to assign a weight of “2” to the most recent poll by WSVB-TV/Landmark, Trafalgar Group and WXIA-TV/SurveyUSA and a weight of 1 to the other nine polls.

Using the bias-adjusted polls and this simple weighting scheme, I calculated an Ossoff margin of 1.38, suggesting recent tightening in the race not captured by my OLS regression[2].

So, let’s say that our best estimate is that Ossoff is ahead by 1.38 percentage points heading into today’s voting. There is a great deal of uncertainty around this estimate, resulting both from sampling error (an overall MOE of 2.5 to 3 percentage points around an average Ossoff percentage and an average Handel percentage, which you would double to get the MOE for the Ossoff margin—say, 5 to 6 percentage points) and the quality of the polls themselves.

Now, let’s say that our Ossoff margin MOE is nine percentage points. I admit up front that this is a somewhat arbitrary MOE-larger-than-6-percentage-points I am using to make a point.

In a normal distribution, 95% of all values are within two (OK, 1.96) standard deviations (SD) of the midpoint, or mean. If you think of the Ossoff margin of +1.38 as the midpoint of a range of possible margins distributed normally around the midpoint, then the MOE is analogous to the 95% CI, and the standard deviation of this normal distribution is thus 9/1.96 = 4.59.

To win this two-candidate race, Ossoff needs a margin of one vote more than 0%. We can use the normal distribution (mean=1.38, SD=4.59) to determine the probability (based purely upon these 12 polls taken over two months with varying quality) that Ossoff’s margin will be AT LEAST 0.01%.

And the answer is…61.7%!

Using a higher SD will yield a win probability somewhat closer (but still larger than) 50%, while a lower SD will yield an even higher win probability.

Here is the larger point.

It may sound like Ossoff +1.38 +/-9.0 is a “statistical dead heat” or “statistical tie” because it includes 0.00 and covers a wide range of possible margins (Ossoff -7.62 to Ossoff +10.38, with 95% confidence), but the reality is that this range of values includes more Ossoff wins than Ossoff losses, by ratio of 62 to 38.

You can reanalyze these polls and/or question my assumptions, but you cannot change the mathematical fact that a positive margin, however small and however large the MOE, is still indicative of a slight advantage (more values above 0 than below).

Until next time…

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This is an addendum started at 12:13 am on June 21, 2017.

According the New York Times, Handel beat Ossoff by 3.8 percentage points, 51.9 to 48.1%. My polling average (Ossoff+1.4) was thus off by -5.2 percentage points. That is a sizable polling error. RealClearPolitics (RCP) was somewhat closer (-3.6 percentage points), while HuffPostPollster (HPP) was the most dramatically different (-6.2 percentage points).

Why such a stark difference? And why was EVERY pollster off (the best Handel did in any poll was +2 percentage points, twice)?

I think the answer can be found in a simple difference in aggregation methods. RCP used four polls in its final average, with starting dates of June 7, June 14, June 17 and June 18, and their final average was Handel+0.2. HPP, however, included no polls AFTER June 7, and their final average was Ossoff+2.4, a difference of 2.6 percentage points in Handel’s favor.

Moreover, Handel’s final polling average was 2.1 percentage points higher in RCP (49.0 vs. 46.9%), while Ossoff’s final polling average was only 0.5% lower (48.8 vs. 49.3%).

In other words, over the last week or so of the race, Handel was clearly gaining ground, while Ossoff was fading slightly.

What could have caused this shift?

On the morning of June 14, 2017, a man named James T. Hodgkinson opened fire on a group of Republican members of Congress, members of the Capitol Police and others on an Alexandria, Virginia baseball diamond. Mr. Hodgkinson, who claimed to have volunteered on Senator Bernie Sanders’ 2016 presidential campaign, appeared to be singling out Republicans for attack; he had posted violent anti-Trump and anti-Republican screeds on his Facebook page.

When this ad, brazenly (and absurdly) tying Ossoff to the left-wing rage and violence deemed responsible for the Alexandria shooting, started playing in Georgia’s 6th Congressional District, I thought it was a despicable and desperate attempt to save Handel from a certain loss.

But the overarching message of “blame the left” appears to have resonated with district residents who otherwise may not have voted. The final poll of the campaign found that “…a majority of voters who had yet to cast their ballots said the recent shootings had no effect on their decision. About one-third of election-day voters said the attack would make them ‘more likely’ to cast their ballots, and most of those were Republican.”

It is conceivable that this event changed a narrow Ossoff win into a narrow loss, as disillusioned Republicans decided to cast an election-day ballot for Handel in defense of their party. While Ossoff won the early vote by 5.6 percentage points (and 9,363 votes), he lost the election day vote by a whopping 16.4 percentage points (and 19,073 votes).

Ossoff may well have lost anyway, for other reasons: his non-residence in the district, the difference between Republican opposition to Trump and support for mainstream Republicans, the amount of outside money which flowed into the district (making it harder for Ossoff to cast himself as a more centrist, district-friendly Democrat; the Democrat in the most expensive U.S. House race in history lost by a larger margin [3.8 percentage points vs. 3.2 percentage points] than the Democrat in the barely-noticed South Carolina 5th Congressional District special election held the same day) and his inexperience as a politician.

But the fact that Handel herself cited the Alexandria shooting in her victory speech (starting at 03:23) speaks loudly about why SHE thinks she won the election.

Until next time…again…

[1] Itself usually calculated as standard deviation divided by the square root of the sample population.

[2] Other recency weighting schemes yielded similar results.

Jon Ossoff, Ed Markey, and the (near-)future of the Democratic Party

The runoff special election for Georgia’s 6th Congressional District (CD) is June 20, 2017. Democrat Jon Ossoff won the first round of voting on April 19, 2017, but with only 48.1% of the vote. Rather than have separate party primaries, all candidates in Georgia run in a single “jungle primary.” If nobody receives more than 50% of the vote, the top two candidates meet in a runoff. Thus, Ossoff will be facing Republican Karen Handel (19.8%) in eight days.

This election is occurring because Republican Representative Tom Price resigned to become President Donald Trump’s Secretary of Health and Human Services on February 10, 2017. What makes Ossoff’s performance on April 19 so surprising is that Price had won his seven Georgia CD-6 elections by an average of 53.0 percentage points (excluding the 2004 and 2010 races, when Price ran unopposed, drops the average to 34.3%), although he had won in 2016 by “only” 23.4 percentage points.

Price’s dominance makes the performance of Ossoff (and of all five Democrats, who combined for 49% of the vote overall) remarkable, though it should be noted that 2016 Democratic presidential nominee Hillary Clinton lost Georgia CD-6 by only 1.5 percentage points to Trump, after Republican presidential nominees Mitt Romney (2012) and John McCain (2008) had won the CD by an average of 21 percentage points.

Currently, Ossoff is leading in the non-partisan polls (which should be taken with a box of salt) by either 4.8 or 6.9 percentage points. Even a narrow win would be a small political earthquake, because Georgia CD-6, in suburban Atlanta, houses precisely the sort of highly-educated suburban population I argue Democrats need to target.

Thus, on the one hand, a Democratic victory in a historically Republican CD would bode well for their chances of recapturing the U.S. House of Representatives (House) in 2018. On the other hand, Ossoff is running a centrist campaign targeting local district needs, eschewing a more ideologically progressive message, and that is probably why he is winning.

As this article makes clear, Ossoff is opposed to raising taxes (even on the wealthy), is not ready to entertain a single-payer health plan, has not said whether he would support California Representative Nancy Pelosi as the Democratic leader in the House, and thinks it is too soon to discuss impeaching President Trump.

And I would still vote for him if I lived in Georgia CD-6, for the simple reason that for Democrats to regain the House in 2018 and have any chance of acting toward progressive goals, they will need to let more moderate/non-ideological Democratic candidates run campaigns suited to their individual states and CDs.

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On June 1, 2017, I attended Massachusetts Senator Ed Markey’s town hall event at the beautifully-restored Paramount Theater in Boston. To my mind, Markey is a progressive hero, particularly on the environment, even if he has been described as “moderate left of center.”

IMG_3107

Markey was introduced by Boston Mayor Marty Walsh and Democratic Congressman Michael Capuano, and then he spoke for about 15 minutes, primarily about the dangers posed by a President Trump and the need to defend the Patient Protection and Affordable Care Act (ACA), before taking questions.

The first few questions were about the ACA repeal and replace process. With the second overall question, I asked the Senator whether he could convince any fellow Republican Senators to break with pressure from their own party to vote against any ACA repeal/replace bill. He answered that he could, citing his long history of getting bills passed with bipartisan support.

The next two questions were by members of LaRouche PAC, about which the less said, the better (I had to leave the town hall early, and the two questioners were proselytizing outside; I MAY have had a few choice words for them).

And then came the single-payer questions.

Actually, these were more demands than questions.

They were demands that Markey not merely support a single-payer healthcare system (which he does, having introduced legislation to that effect in the past), but that he do so NOW, without equivocation, to the exclusion of all else.

Markey doggedly explained after each such question that he would support such a system again, but for now, the goal needs to be to save the Affordable Care Act. To my practical-progressive mind, what he was saying was “I would love to perform massive gorgeous renovations to our shared house, but right now the house is on fire, and I think we should put that out first.”

That sound about right to me. I support a Medicaid-for-all plan (or a similar variant), but I also recognize that we need to prevent repeal/replace of the ACA first.

One woman kept insisting (from her chair, after she had already asked her single-payer question, which struck me as the sort of rudeness I would never tolerate in my own daughters) that the public now supports a single-payer healthcare system.

The most recent poll I can find that specifically addresses this is a Kaiser Family Foundation poll from December 2015 (1,202 adults nationwide, +/-3%). When asked, “Now, please tell me if you favor or oppose having a national health plan in which all Americans would get their insurance through an expanded, universal form of Medicare-for-all,” 58% were in favor, 34% were opposed, and 8% were unsure or refused to answer the question.

I will admit that I expected the favor/opposed percentages to be much closer, and I am pleasantly surprised that support for a single-payer healthcare system is that high.

Still, here is the current political reality.

We live in a political universe in which the ACA is more popular (47.0% vs. 41.5%) than unpopular, while the AHCA is highly unpopular (17%-31% approval vs. 55-65% disapproval, in recent polling)…and the Republican-controlled U.S. Senate is still doing its darnedest to replace the former with the latter (or a related alternative), with the AHCA having already passed the House by just two votes. Republicans, beholden to their most right-wing voters and their own promises, are blatantly ignoring these data.

When the ACA was being written, inclusion of a “public option” (allowing consumers to buy into the Medicare program, a first step toward single-payer healthcare) was debated. It was ultimately rejected, even though Democrats had supermajorities of 59 Senate seats and 259 House seats (59.5%).

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My point is not that public opinion or election victories do not matter. They absolutely do.

My point is not that the Democrats should reject the progressive fervor of their energized and mobilized base. They absolutely should. The Democratic Party needs greater clarity in what precisely it stands for, and this is a great place (though not the only place) to start.

My point is that the primary goal for Democrats needs to be winning elections. The most progressive platform in the world will get you nothing if you are not in a position to enact it. If the Jon Ossoff’s of the world need to run centrist campaigns to win in traditionally Republican areas like Georgia (or Arizona or Texas or North Carolina), then so be it.

A separate-but-related point is that progressive and moderate Democrats alike need to be supportive of our current elected officials, from progressive champions like Massachusetts Senator Elizabeth Warren to moderates like West Virginia Senator Joe Manchin, who faces a tough reelection race next year.  Not blindly supportive, but not antagonistic either.

These folks are on the side of progressives, broadly speaking, and they all need our support.

Until next time…

Democrats need to capitalize on gubernatorial election opportunities in 2017 and 2018

Having previously analyzed Democratic prospects in the 2018 midterm elections for U.S. House (House; here and here) and Senate (Senate; here), I now examine what I think are the most important elections for both parties in 2017 and 2018—those for governor.

In an age of increasing partisan polarization and Congressional gridlock, governors have emerged as crucial policy leaders far from Washington DC. On the conservative side are recent innovations by Republican Governors such as Sam Brownback of Kansas, Scott Walker of Wisconsin (prompting an unsuccessful 2012 recall election) and Rick Snyder of Michigan. Governors could choose whether or not to accept Medicaid expansion under the Affordable Care Act, as Republican Governor John Kasich of Ohio continues to note.

More recently, Democratic Governors have attempted to block Trump Adminstration actions. Washington’s Jay Inslee was a key leader in blocking iterations of the travel ban. California’s Jerry Brown has emerged as a leader on climate change, especially after President Trump announced the withdrawal of the United States from the Paris Climate Accord.

Currently, there are 16 Democratic governors, 33 Republican governors and one Independent governor (Bill Walker of Alaska). Thus, of the 38 elections for governor scheduled for 2017 (New Jersey, Virginia) and 2018 (36, including New Hampshire and Vermont, who hold gubernatorial elections every two years), 27 are currently held by Republicans, offering a potentially target-rich opportunity for Democrats.

2018govraces

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Just bear with me while I review some recent electoral history.

When Barack Obama won his first presidential election in 2008, Democrats also netted one governor’s mansion, giving them a 29-21 edge.

On January 21, 2009, Arizona’s Democratic governor, Janet Napolitano, became Secretary of Homeland Security. She was succeeded, under the Arizona Constitution, by the Republican Secretary of State, Jan Brewer. That November, in a further ominous sign of things to come, Democrats lost governorships in New Jersey (Republican Chris Christie unseated Democrat Jon Corzine) and Virginia (Republican Bob McDonnell won an open seat).

Democrats 26, Republicans 24.

During the 2010 midterm elections, as Republicans were recapturing the House, Democrats lost six governorships, while Republicans gained five and Independents gained one (Lincoln Chafee in Rhode Island).

Republicans 29, Democrats 20, Independent 1.

Over the next three years, there was no net change in the partisan distribution of governorships. The four gubernatorial elections in 2011 were a wash: both Republican seats stayed Republican, and both Democratic seats stayed Democratic. In 2012, Republicans netted one governorship, as Republican Pat McCrory won an open seat in North Carolina from retiring Democratic governor Bev Perdue. And in 2013, while Christie cruised to reelection by 22.1 percentage points, Democrat Terry McAuliffe edged out Republican Ed Gillespie by 2.5 percentage points (Virginia governors are limited to a single four-year term).

In 2014, however, the wheels really came off for Democrats, as they lost nine Senate seats, and control of the Senate, while losing 12 additional House seats. They also lost a net of two governorships: Republicans Asa Hutchinson, Larry Hogan and Charlie Baker won open Democratic-held governor’s mansions in Arkansas, Maryland and Massachusetts, respectively, while Republican Bruce Rauner defeated incumbent Democratic governor Pat Quinn in Illinois. On the flip side, Democrat Tom Wolf defeated incumbent Republican Tom Corbett in Pennsylvania, and Democrat Gina Raimondo won an open seat in Rhode Island (Independent Chafee did not seek reelection), while Walker defeated incumbent Republican governor Sean Parnell in Alaska.

Republicans 31, Democrats 18, Independent 1.

The three gubernatorial elections in 2015 were again a wash, with open seats in Kentucky flipping Republican (Matt Bevin) and Democratic in Louisiana (Jon Bel Edwards). Finally, in 2016, Republicans netted an additional two governor’s mansions, winning open seats in Missouri (Eric Greitens), New Hampshire (Chris Sununu) and Vermont (Phil Scott), while Democrat Roy Cooper upset McCrory in North Carolina.

Republicans 33, Democrats 16, Independent 1

In other words, since Obama assumed the presidency on January 20, 2009, Democrats have lost 13 governorship (Republicans +12, Independents +1), as well as 62 House and 11 Senate seats.

Ouch.

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For Democrats simply to break even in governor’s mansions (or pull within one, if Alaska reelects Walker in 2018), they would need to net nine of them (or Republicans would have to lose eight of them).

That is a tall order for a single two-year election cycle, but there is every reason to believe Democrats can make up substantial ground in the 2017 and 2018 gubernatorial elections.

 Table 1: Governor Elections in 2017 and 2018

Current Governor State Open Seat? 3W-RDM Ave. Margin Prior 2 Races, Incumbent Party Net Approval*
DEMOCRATS
David Ige HI No 34.3 14.7% 8%
Jerry Brown CA Yes 23.2 16.4% 24%
Andrew Cuomo NY No 21.6 21.6% 31%
Gina Raimondo RI No 18.0 -3.0% 3%
Dannell Malloy CT ? 12.8 1.6% -37%
Kate Brown†† OR No 8.7 6.5% 27%
John Hickenlooper CO Yes 2.2 9.0% 33%
Terry McAuliffe VA Yes 1.5 -7.4% 21%
Mark Dayton MN Yes 1.5 3.0% 23%
Tom Wolf PA No -0.4 0.4% 5%
 

INDEPENDENT

Bill Walker AZ No -19.2 -9.6% -10%
 

REPUBLICANS

Phil Scott VT No 27.7 3.7% 52%
Larry Hogan MD No 22.6 -5.3% 57%
Charlie Baker MA No 22.1 -2.3% 58%
Bruce Rauner IL No 14.7 1.5% -7%
Chris Christie NJ Yes 12.0 12.8% -46%
Susana Martinez NM Yes 6.5 10.6% -5%
Paul LePage ME Yes 5.9 3.3% -1%
Rick Snyder MI Yes 2.2 11.1% -14%
Brian Sandoval NV Yes 2.0 29.2% 42%
Scott Walker WI No 0.7 6.1%††† -5%
Chris Sununu NH No 0.1 -1.3% 33%
Rick Scott FL Yes -3.4 1.1% 21%
Kim Reynolds†† IA No? -4.7 15.7% N/A
John Kasich OH Yes -5.8 16.3% 26%
Nathan Deal GA Yes -9.6 9.0% 38%
Doug Ducey AZ No -9.7 11.8% 25%
Greg Abbott TX No -15.3 16.5% 40%
Henry McMaster†† SC No -15.7 9.5% N/A
Sam Brownback KS Yes -23.4 17.4% -39%
Pete Ricketts NE No -25.8 32.9% 31%
Dennis Daugaard SD Yes -25.8 34.0% 45%
Bill Haslam TN Yes -25.8 39.7% 40%
Asa Hutchinson AR No -28.2 -8.4% 45%
Kay Ivey†† AL ? -28.4 21.5% N/A
C.L. “Butch” Otter ID Yes -34.2 20.6% 26%
Mary Fallin OK Yes -38.1 17.9% -11%
Matt Mead WY Yes -45.7 37.4% 33%

   * From a Morning Consult poll of 85,000+ respondents in all states (except South Carolina), January to March 2017.

   For Rhode Island 2010, the margin is Democrat minus Republican, despite the victory of  Independent Chafee. For Colorado 2010, the margin is Democrat minus American  Constitution Party (who nominated former Republican Representative Tom Tancredo). For Alaska, the margins are Independent minus Republican (2014) and Democrat minus Republican (2010). New Hampshire and Vermont hold gubernatorial elections every two years, so this is the average of 2014 and 2016. For Maine 2010, the margin is Republican minus Independent, as LePage’s closest competitor was Independent Eliot Cutler.

   †† Brown became governor February 18, 2015 when John Kitzhaber resigned amid scandal, then won reelection in 2016. Reynolds became governor May 24, 2017 when Terry  Brandstad became Ambassador to China. McMaster became governor January 24, 2017 when Nikki Haley became Ambassador to the United Nations. Ivey became governor  April 10, 2017 when Robert Bentley resigned amid scandal.

    ††† Margin includes the regularly-scheduled 2010 and 2014 elections, as well as the June 2012 recall election

Table 1 (for which I am indebted, in part, to here) lists, for every governor’s race in 2017 (italicized) and 2018, whether an incumbent will be seeking reelection (if known; open seats tend to be closer), the average margin of victory in the previous two gubernatorial elections for the current governor’s party, and the net approval rating (percent approving minus percent disapproving) in an April 2017 Morning Consult poll[1].

The potential for Democratic governorship gains in 2017-18 is clear: Republicans are defending governor’s mansions in nine states which lean at least 2.0 points more Democratic than the nation[2] (using my 3W-RDM measure of how much more or less Democratic a state’s presidential vote has been than the national presidential vote over the last three elections, weighted for recency) and in an additional five[3] states no more than six points more Republican than the nation. Democrats, by contrast, are defending only one governor’s mansion in a state (Pennsylvania) less than 1.5 points more Democratic than the nation.

In the rest of this post, I will briefly analyze all 38 gubernatorial elections in 2017 and 2018, organized by party and from most to least vulnerable. This analysis is based solely upon the partisan lean of the state, previous winning margins and the incumbent governor’s popularity (or unpopularity), ignoring possible partisan “waves” and (for the most part) opposition candidate quality.

Republicans. Let’s get 2017 out of the way first. Christie is the least popular governor in the nation, with a -46% net approval rating. And while he won his two elections by a solid 12.8 percentage points, on average, New Jersey is a Democratic state (+12.0). Put it this way: if Democrats do NOT win the 2017 New Jersey governor’s race, they should disband as a political party.

There are four other 2018 gubernatorial elections in Democratic-leaning states in which a Republican governor is retiring: Maine (+5.9), Michigan (+2.2), Nevada (+2.0) and New Mexico (+6.5). In Maine, Michigan and New Mexico, the current Republican governors average a -7% net approval rating and won relatively close elections in very good Republican years (2010, 2014). These three states are thus probably the best opportunities for Democrats to win back governor’s mansions in 2018[4]. Nevada, by contrast, has a very popular governor in Brian Sandoval (+42), who won his two elections by an average of 29.2 percentage points, making it a harder pick-up for the Democrats than the state’s Democratic lean would suggest.

Six Republican governors will seek reelection in 2018 in Democratic-leaning or swing states, with five having won either a single close election (average margin 4.1 percentage points) or three relatively close elections (Walker, by an average 6.1 percentage points). Baker, Hogan and Scott govern very Democratic states (average=+24.1), but they are also remarkably popular (average=+56%), making them (at this point) likely favorites to win reelection[5]. On the flip side, however, are Bruce Rauner (Illinois, +14.7), Walker (+0.7) and Sununu (+0.1). While Rauner and Walker have an average net approval of -6%, Sununu is quite popular (+33%). Thus, Illinois and Wisconsin should also be at the top of the Democratic target list in 2018, while Maryland, Massachusetts, New Hampshire and Vermont have popular Republican incumbents who may be hard to beat in 2018.

Florida is the ultimate swing state, albeit one that leans Republican (-3.4) at the presidential level. Retiring Republican governor Rick Scott (net approval +21%) won both his 2010 and 2014 elections by only 1.1 percentage points (even as Republicans were winning the gubernatorial vote in 2013-14 by 4.4 percentage points and in 2009-10 by 1.3 percentage points). If I were a Democratic strategist, I would add Florida to Illinois, Maine, Michigan, New Mexico and Wisconsin as top targets to retake governor’s mansions (and I would certainly keep an eye on Maryland, Massachusetts, Nevada, New Hampshire and Vermont).

After that it gets…trickier. Donald Trump won Iowa and Ohio by 8.7 percentage points, on average, in 2016; these two states now average 5.2 percentage points more Republican than the nation in presidential elections. Kasich, who is term-limited, won his two elections by 16.3 percentage points, on average, just above the average 15.7% percentage point victory margin for Branstad, before becoming Ambassador to China in May 2017, elevating Lieutenant Governor Reynolds to governor. If Reynolds seeks reelection in 2018, she is probably a heavy favorite[6]. However, the open seat in Ohio should be in play for Democrats, even with Kasich’s current popularity (+26%).

Governor’s races in 2018 in Arizona and Georgia (average 3W-RDM=-9.7, though trending Democratic), will test the hypothesis that the future of the Democratic Party lies more in the Southeast and Southwest than in the Rust Belt/Midwest. Current Republican governors Doug Ducey (+25%) and Nathan Deal (+38%) are quite popular. However, Ducey is seeking reelection in Arizona, making him a likely favorite, while Deal is term-limited in Georgia, creating a better opportunity for Democrats. These elections may be more about narrowing Republican advantage than outright victory, but Georgia, at least, should be on the Democrats’ radar.

That leaves 11 additional 2018 gubernatorial elections in states with a Republican governor. These states average 27.9 percentage points more Republican than the nation in presidential elections, ranging from Texas (-15.3) and South Carolina (-15.7) to Wyoming (-45.7). As many as five of them will have incumbent governors seeking reelection, three of whom have an average net approval of +39% (Greg Abbott in Texas, Pete Ricketts in Nebraska, Asa Hutchinson in Arkansas). Of the six open seats, only two are of even the slightest interest to Democrats: Kansas, where outgoing governor Sam Brownback has a dismal -39% net approval rating (and only beat Democrat Paul Davis in 2014 by 3.7 percentage points), and Oklahoma, where outgoing governor Mary Fallin has a net approval rating of -11%. These two states would be the longest of long shots, but I would still stick a pin in them if I were a Democratic strategist.

Independent. The unpopular Walker (-10%) upset incumbent Republican Parnell in 2014 by 2.2 percentage points while Republicans were winning the national gubernatorial vote by 1.3 percentage points. Given the strong Republican lean of Alaska (-19.2), I would expect a decent Republican challenger to unseat Walker—though if a strong Democrat were to run[7], a three-way race could be anyone’s to win.

Democrats. Let’s start with 2017. McAuliffe, the popular (+21%) Democratic governor of Democratic-leaning Virginia (+1.5), cannot seek reelection, and in the commonwealth’s two previous gubernatorial elections, the average Democrat-minus-Republican margin was -7.4 percentage points. On paper, then, this election looks like a toss-up (maybe even slight lean Republican). That said, both Democrat candidates for governor—Lieutenant Governor Ralph Northam and former House Member Tom Perriello—have opened up double-digit polling leads against Gillespie.

Should he seek a third term, the most vulnerable incumbent Democrat is Dannell Malloy of Connecticut. His net approval is a dismal -37%, and he won his previous two elections (albeit in strong Republican years nationally) by only 1.6 percentage points, on average. The state’s solid Democratic lean (+12.8), which would benefit another Democratic candidate (even as Malloy’s unpopularity would weigh her/him down), probably would not save Malloy in 2018.

To the extent that any of the other eight Democratic-held governorships are likely to be won by Republicans in 2018, the next-most-vulnerable incumbent Democrat is Wolf, whose net approval is a middling +5%. Wolf defied Pennsylvania’s decades-long tradition of changing partisan control of the governor’s mansion every eight years[8] when he beat incumbent Republican Corbett by 9.9 percentage points (after Corbett had won an open seat in 2010 by 9.0 percentage points), even as Republicans were winning the national gubernatorial vote by 4.4 percentage points. Pennsylvania is a swing-state at the presidential level (-0.4), and Democrats have essentially tied the last two governor’s races (D+0.4 percentage points). Like Virginia, this looks like a toss-up on paper, but I would give Wolf the edge to win reelection.

Popular Democratic incumbents Mark Dayton (+23%) and John Hickenlooper (+33%) are term-limited in the Democratic-leanings states of Minnesota (+1.5) and Colorado (+2.2). These two governors defied the strong Republican performances of 2010 and 2014, winning their four combined elections in those years by an average 6.0 percentage points. I would expect Democrats to prevail in close elections in both states in 2018.

That leaves five current Democratic governors in Democratic states. Oregon is the least Democratic of the five (+8.7), but Governor Kate Brown has a solid +27% net approval rating. California’s equally popular Jerry Brown (+24%) is term-limited (for a second time; the eternally-young 79-year-old also served as California’s governor from 1975-1983), but at +23.2, California is one of the nation’s most Democratic states. Hawaii’s David Ige is only marginally popular (+8%), but Hawaii (+34.3) is the most Democratic state in the country, and Ige won his first election by 12.4 percentage points. By contrast, Rhode Island’s Raimondo is not especially popular (+3%) and she only won in 2014 by 4.5 percentage points, but the state’s strong Democratic lean (+18.0) is likely sufficient for her to win reelection. And, finally, New York’s highly popular governor Andrew Cuomo (+31%) won his previous two elections by 21.6 percentage points, on average, while New York is heavily Democratic (+21.6); Cuomo is a safe bet to win reelection.

Bottom line. The dream scenario for Democrats is this. All 10 governor’s mansions currently held by Democrats stay in Democratic hands, while Democrats not only upset Walker in Alaska, they also defeat Rauner and Walker in Illinois and Wisconsin, respectively, while capturing open seats in New Jersey, Maine, Michigan, New Mexico, Florida, Ohio, Kansas and Oklahoma. Democratic gubernatorial candidates also prevail in states with popular incumbent Republican governors: Maryland, Massachusetts, Nevada, New Hampshire, Vermont, and even Iowa. This scenario would result in a net pickup of 17 governor’s mansions, which while (barely) within the realm of possibility, is EXTREMELY unlikely.

The nightmare scenario for Democrats is that Republicans win the New Jersey and Virginia governor’s races in 2017, recapture governor’s mansions in Connecticut and Pennsylvania (as well as Colorado and Minnesota), and do not lose any other currently Republican governorship in 2018. This scenario would result in a net gain for Republicans of five governor’s mansions. This, too, is (even more barely) within the realm of possibility, and even more EXTREMELY unlikely.

The most likely outcome is that Democrats net somewhere between one (lose VA, CT, PA while winning half of NJ, MI, ME, NM, IL, WI, FL, OH and none of MD, MA, NV, NH, VT, KS, OK) and nine-ten governorships (hold VA, CT, PA and win all of NJ, MI, ME, NM, IL, WI, FL, OH as well as one or two of MD, MA, NV, NH, VT, KS, OK).

Simply put, the opportunity for Democrats to make substantial progress towards parity in governorships is there, if they can take advantage of it.

Until next time…

[1] I assume more unpopular governors will have a harder time winning reelection or being succeeded by a member of the same party, and that higher popularity will make it easier to win reelection, while contributing little otherwise.

[2] This is still a reasonable proxy for the general partisan lean of a state, despite the fact that governor’s races do not always align neatly with presidential voting.

[3] Seven, if you count Democratic-trending Arizona and Georgia.

[4] A wild card is Maine. If Republican Senator Susan Collins runs for governor in 2018, she is probably a heavy favorite to win, though from a policy perspective, replacing the Trump-like LePage with the far more moderate Collins would be a moral victory for Democrats.

[5] Heck, I am a lifelong Democrat, and I might vote for Charlie Baker in 2018!

[6] It should be noted, however, that Branstad had only a +2 net approval rating in April 2017.

[7] Former Democratic Senator (and Anchorage Mayor) Mark Begich lost his 2014 reelection bid by only 2.1 percentage points, even as Republicans were winning nationally by 6.7 percentage points. Were Begich to run for governor…

[8] I’m not kidding. Democrat Ed Rendell was governor from 2003-2011. Republican Tom Ridge was governor from 1995-2003. Democrat Bob Casey Sr. was governor from 1987 to 1995. Republican Richard Thornburgh was governor from 1979 to 1987. Democrat Milton Shapp was governor from 1971 to 1979. And so forth.