Democrats remember 2014 in which lassitude among their core voters helped propel Larry Hogan into office. They’re hoping that the electorate will look more like 2016 in which Hillary Clinton carried the state by a large margin.

Using data from the State Board of Elections, the above table presents the percentage of people by party who took advantage of early voting at the end of the sixth day. It also shows changes from both 2014, the previous gubernatorial election, and 2016, the presidential election.

The statistics suggest that the 2018 electorate is unlikely to resemble closely the 2014 electorate. Democrats are joyful that early voting turnout is up a full 6.3% from 2014. Even better for Team Blue, Democratic turnout is up by even more at 7.5%.

Republicans are also turning out 5.5% higher but the lower increase means that the GOP has fallen behind. While Democratic and Republican turnout at this point in early voting was equal in 2014, Democrats have pulled into the lead this year.

Comparisons with 2016 are less favorable for Democrats. Early voting turnout  this year is 4.0% down from 2016. Democratic turnout is down by even more at 5.1%. Republican turnout has decreased much less at 2.1%. However, Republicans start from a much lower base as the EV electorate in 2016 was much more lopsidedly Democratic in that year than in 2014.

The bottom line is that the early voting electorate this year is much more favorable to Democrats than 2014. But it’s also not nearly as favorable to them as the 2016 electorate.

Of course, we have to wait and see the impact, if any, on total turnout. Early voting can simply replace Election Day voting. Nevertheless, the idea suggested by the data that total turnout will end higher than 2014, not a banner year for voting or when Trump polarized and mobilized people, but not reach presidential year turnout is intuitively appealing.

Earlier today, I published a piece arguing that there is no blue wave based on the early voting statistics. One reader pointed out on twitter that information about whether there was a wave could be better gauged by comparison with the past. After all, young voters could have closed the gap even if they remain behind older voters.

In order to provide a better basis for examination, I calculated early voting rates at the end of the fifth day of early voting for 2014, 2016 and 2018, which are shown in the above table. I used the same method as described in the post earlier today.

I suppose an optimistic reader might point out that early voting among 18-24 and 25-44 voters is three times higher than the abysmal turnout of 2014, a year when Democrats were unmotivated and demobilized.

That comparison seems a bit facile when you consider that the absolute turnout rates remain low. Three times more of a very small number is a slightly less small number. As of now, it means 8,111 18-24 year olds have voted than in 2014.

Comparisons with 2016 are less favorable. The share of early voters in the two youngest cohorts is only around 60% as large as at the same time during early voting in 2016. That was a presidential year, so we naturally expect turnout to be higher despite the absence of the panoply of state and local offices up at midterm.

At the same time, when Ben Jealous said Democrats needed a more progressive candidate to inspire higher turnout, I don’t think that the former co-chair of Bernie Sanders’s campaign was suggesting that he could do about 60% as well as Hillary Clinton.

Moreover, the older cohorts are much closer to turning out at 2016 rates than the younger cohorts. The 45-64 cohort has so far turned out at 69% of the rate of 2016. Even more impressively, the 65 and older cohort has seen very little drop off. The share of voters among seniors who voted is 91% of 2016 rates.

While the other age cohorts turnout rates appear roughly in the middle of their 2014 and 2016 turnout rates, the rate for seniors is clearly far closer to the much higher 2016 rates. Don’t forget that this group also a had a far higher bar to meet.

Comparing the difference between turnout rates for the oldest and youngest cohorts tells a similar story. In percentage points, older voters participated in early voting 8.6% more in 2014, 17.3% more in 2016, and 17.0% more in 2018.

The changes from 2014 to 2018 are even more dramatic. Yes, the youngest voters increased their turnout from 0.7% to 2.2%. But older voters jumped from 9.3% to 19.2%. That’s a gain of 9.9% as opposed to a gain of 1.4%.

In short, the evidence doesn’t support the conclusion that young Maryland voters are highly “energized” and eager to vote compared to other age cohorts, as claimed by the Jealous campaign. In early voting, it’s not the young but the old who are showing the way.

It’s not a youthful blue wave. It’s a senior tsunami.

At the end of yesterday, 9.3% of registered Maryland voters had taken part in early voting. Talbot continues to lead the early voting pack as over one-fifth of its registered voters have now cast ballots. Allegany trails at the end with just 3.6% having participated in early voting. Indeed, all Western Maryland counties lag in early voting.

Most counties with hot executive races – Howard, Baltimore County and Anne Arundel – continue to have above average turnout but Frederick continues to be an exception. Montgomery has very average turnout despite its comparatively unusual three-way contest.

Most counties in CD 1 are also voting at high rates. Dorchester and Cecil continue to lag with Wicomico just below average but closing the gap with the state average compared to yesterday. It’s interesting to see Somerset in the above average category as this relatively poor county often has low turnout.

At the end of the fourth day of early voting, age appears heavily correlated with participation in early voting. According to the raw data released by the State Board of Elections, here are the number of people who early voted by age cohort:

18-24: 9,588.
25-44: 41,586.
45-64: 117,992.
65 and older: 101,787
unknown: 7,818.

Looking simply at the raw numbers, the old are casting early voting ballots in massively higher numbers than the young. For example, the 45-64 cohort had 284% more voters than the 25-44 cohort. Both cover 20 year periods (i.e. one generation).

What does it look like if you consider the rate of turnout rather than absolute numbers? I used the 2015 Maryland Department of Planning population estimates to gauge the size of each cohort’s population. (It’s not perfect as it includes non-citizens but gives a rough indicator. Age is reported in five-year groups, so I estimated the 18 and 19 year olds as 40% of all people ages 15-19.)

Here are the resulting estimates of early voting turnout rates:

18-24: 1.7%
25-44: 2.7%
45-64: 7.4%
65 and older: 14.4%

If anything, I suspect that this understates age differences. Remember that among Latinos and Asian Americans, two groups with large immigrant populations, kids are far more likely to be citizens than their parents because many were born in the U.S. and are citizens and eligible voters by right. As a result, the older cohorts likely includes higher shares of non-citizens.

Some might ascribe especially low rates among 18-24 year olds due to many people this age being away at college. This may indeed depress turnout figures somewhat but turnout rates among 25-44 year olds are also very low.

The Ben Jealous campaign has argued that the polls showing Hogan leading him handily are wrong because, among other reasons, they “undercount young people” who are “energized” about voting this year. So far, the early voting data suggest that no blue wave of young voters has arrived yet.

Earlier today, I presented data on the share of people who have voted early for each Maryland county. At the end of the fourth day of early voting, 7.1% of registered Marylanders had voted. The share across counties varies much more widely from 2.8% in Allegany to 15.5% in Talbot.

What explains the variation?

St. Mary’s Political Science Professor Todd Eberly suggested on Twitter that he thought there were signs of higher turnout in counties that (1) have competitive executive races, and (2) are in the First Congressional District. Is he right?

Two other hypotheses occurred to me: (3) turnout might be higher in counties with more older residents as age is associated with participation, and (4) race might also be associated with voting. In particular, Latinos and Asian Americans tend to vote at lower rates than whites or African Americans.

I created multivariate models of turnout at the end of the fourth day of early voting in order to test these hypotheses. The models allow one to assess the probable impact of one factor while controlling for others. However, the relatively small number of units in Maryland (24) precludes including too many variables.

So where are more people voting? Increasing the share of the population over age 50 by 2% raises the predicted share of early voters in a county by an estimated 0.59% (p = .02 for the statistically minded who are familiar with OLS models).

Counties in the First CD also seem to be participating at higher rates, though the effect is small. In counties in which 100% of registered voters live in CD 1, turnout is an estimated 0.02% higher than elsewhere in the state (p = .04). Though perceived as a safe Republican seat, voters there seem energized this year.

Counties with hot executive races (defined here as Anne Arundel, Baltimore County, Frederick and Howard) are seeing much higher early voting turnout. The estimated impact of close exec contest on the share of early voters at the end of day 4 is 2.75% (p = .04). Including Montgomery as a hot race causes the effect to vanish, suggesting that our unusual three-way race is not motivating EV turnout in the same way in MoCo.

Contrary to my expectation due to historically lower rates of Latino and Asian turnout, counties with more non-Hispanic whites seem to have fewer early voters. Increasing their share of the population by 2% is estimated to reduce EV turnout at the end of day 4 by 0.10%. However, the effect is marginal as statistical significance is normally assessed (p = .09) and I would interpret with especial caution.

Closer examination of the data reveals that any impact is driven by the presence of Latinos and that changes in the share of blacks have no real impact on EV turnout. Only Montgomery and Prince George’s have relatively high shares of Latinos (and MoCo also has the highest share of Asians), so I suspect that what is being captured by the model is that these two counties have relatively high turnout once you consider that they are not in CD 1, don’t have tight exec races, and the age of their populations.

In case you were counting, Todd Eberly wins the hypothesis prediction race. Both of his panned out while one of my two turned out to be a turkey-and Thanksgiving isn’t quite here yet.