The Economy in the 2018 Congressional Election

Americans saw their real disposable personal incomes grow by a fairly average two percent over the past year.  With that mediocre rate of income growth, a “normal” President would have had an approval rating around forty-eight percent at the time of the election.  Donald Trump’s forty percent favorability probably cost his party at least four percent of the popular vote, or about half the Democrat’s popular-vote margin of just over eight percent.

The state of the economy was considered one of the few items on the positive side of the ledger for Congressional Republicans in 2018.  The stock market accelerated after Trump’s election in 2016; the new tax bill was expected to put cash in peoples’ pockets; and, incomes overall continued to rise as they had since 2010.  All of these should have helped Republicans this year.  The question is how much.

The effect of the stock market rise is somewhat easy to dismiss as only half of American adults own stocks.  And the market has experienced considerable volatility this year compared to the steady march upward during the first year of the Trump Administration.  So while the half of Americans with stock portfolios are certainly better off today than they were in November of 2016, the future looks more dicey.

However the evidence for a relationship between stock prices and presidential popularity is, at best, mixed. Back in 2009 Gallup found little correlation between the Dow-Jones Industrial Average and the popularity of recent Presidents.  Nate Silver at FiveThirtyEight also expresses skepticism about a stock-market effect.

The benefits of the Republican tax cut also have had limited effects when it comes to the broad voting populace. Some forecasts expected the cuts to stimulate investment and consumption and grow the overall economy. However, even supporters of the plan do not expect those broader benefits to appear for some years to come.  Meanwhile, critics of the plan focus on how most of the gains from the tax cut have been funneled into stock buy-back plans that boost companies’ share prices and executive compensation instead of investments in the real economy. “Perhaps that’s why voters aren’t enthusiastic about the tax cuts,” writes a columnist in Forbes. “People just aren’t getting any real economic benefits from the tax cuts and they know it.”

As I’ve discussed here before, political science research often treats changes in real per-capita disposable personal income as a useful shorthand for the economic welfare of an “average” American.  That measure turns out to have a weak, though measurable, influence on Presidential popularity.  This chart presents Gallup’s job-approval measure in the week or two before an election and the one-year change in real per-capita disposable income as reported by the Bureau of Economic Affairs. I use the third-quarter figure since it covers the period closest to an election.

The scatter around the line in this chart testifies to the weakness of the relationship. The R2 value measures the percentage of the variance in approval that can be accounted for by income changes; here it is about eleven percent.  The slope of the regression line, two, suggests that a one-percent increase in real disposable personal income is associated with, on average, a two-point improvement in a President’s popularity.

One thing made immediately clear by this chart is that average Americans saw no extraordinary growth in their incomes over 2018.  Real per-capita disposable income grew from $42,866 in the third quarter of 2017 to $43,718 at the end of September.  That gain of $852 was just short of a two-percent increase over the year before, and a bit below the 1944-2018 historical average of 2.25 percent.

Still, the chart shows that Trump was less popular than economic conditions would predict. Approval for a “typical” President presiding over an economy showing two-percent in growth should run a bit over 48 percent, not the 40 percent for Trump reported by Gallup in the week before the election.

Earlier this year I presented some results that tied together Presidential popularity and support for the President’s party on the so-called “generic-ballot” question.* We can use that model to imagine how the election might have transpired had Trump been a “normal” President and an economy with two-percent personal income growth.  In that model a one-percent change in “net approval,” the difference between the percent approving versus that disapproving of the President, improves the Democrats’ margin on the generic-ballot measure by about 0.3 percent.

Trump’s net-approval rating just before the election stood at 40-54, or -14, according to Gallup. A President with 48 percent approval will likely have an identical disapproval rating, 48-48, after accounting for the four percent or so who report having no opinion.  That makes the net approval for this hypothetical President zero, meaning Trump’s net approval is fourteen points below a normal President’s.  Trump running fourteen points behind a normal President on net approval probably expanded the Democrats’ margin in the popular vote for the House by about four percent (4.2 = 0.3 X 14).  That accounts for half the Democrats’ margin of victory in November, 2018.

____________________

*The generic-ballot again did a pretty good job of predicting the actual margin of victory in the election for the House of Representatives.  The RealClearPolitics average of generic-ballot polls showed the Democrats with a lead of 7.3 percent.  Omitting the obvious Rasmussen outlier, which predicted a one-point Republican victory, brings the average up to 8.2 percent, nearly identical to the actual margin of 8.5 percent.

 

No, the “Blue Wave” did not wash away gerrymandering

Democrats have won, on average, about eight fewer seats in each election since 2010 than we would expect given their popular vote.  The surge in Democratic votes this year might have cut that deficit down to two, but it is more likely there was no effect at all.

Before the November election, some commentators argued that a surge in turnout could negate the effects of Republican gerrymandering after 2010.  Of course, this argument only makes sense if there were a larger increase in Democratic turnout than Republican turnout.  A proportional increase for both parties would leave the seat results unchanged.

It is certainly true that the Democratic vote for the House of Representatives was considerably greater in 2018 than it was in 2014.  In fact, Democrats cast nearly as many votes this month as they did for Hillary Clinton two years ago.  Compared to the 2014 midterm, the Democrats increased their vote by over fifty percent. Republicans also turned out in higher numbers, recording a vote for House candidates some 23 percent above their 2014 totals. (Figures for 2018 from Dave Wasserman of Cook Political Report.)

Was this surge in Democratic turnout sufficient to overcome the 2010 gerrymander?

To test this, I added a term for the 2018 election to my standard model of seats and votes described here and here.  I use the “logits” of Democratic seats and votes won with “dummy variables” to represent reapportionment periods.  The basic model, with 2018 included, produces this chart showing the number of Democratic seats won or lost compared to what we would expect based on the national popular vote won by that party.  Some periods, like 2002-2010, show no significant excess gains or losses.  Others like 1942-1950 and 2012-2018 show substantial effects.In the five elections beginning in 1942, Democrats routinely won nearly nine more House seats than their popular vote would predict.  Republicans picked up a number of state legislatures in the 1952 election and erased this deficit for the decade to follow.  From 1962 through 1990, Democrats were again advantaged, but by a diminishing margin over time.  The elections fought between 1992 and 2010 showed no systematic bias for either party  After the 2010 Census and the “shellacking” of Democrats in both national and state elections that year, Republicans were able to draw district maps that gave their party just short of eight “excess” seats in the House.

By adding another variable to represent just the 2018 election, it does indicate a diminished effect compared to the 2012-2018 average.  However this effect fails to reach any conventional level of statistical significance (t = 1.07).

One other question we might ask is what the 2018 outcome would have been had the neutral results for 1992-2010 continued on into elections held since the 2010 Census.  While the chart above shows that Democrats lost on average about eight seats to gerrymandering beginning in 2012, the estimated effect for this past election is just short of fourteen seats, the result of the Democrats’ substantial victory in the popular vote.

 

Governors and Gerrymandering: Update

Democratic governors in seven “red” states, and Republicans in two “blue” ones, will help insulate 81 likely Congressional seats from gerrymandering after 2020. Redistricting for another 61 seats will likely remain entirely in Republican hands compared to just seven seats in states with unified Democratic control.

Yesterday’s election helped limit potential gerrymandering after the 2020 Census in a half-dozen states but not, unfortunately, in the largest prizes.  Democrats appear to have failed in their bids to win the gubernatorial elections in Florida, Georgia, and Ohio, and in all three states Republicans maintained their control over the state legislatures as well.  Barring Democratic legislative victories, all three of those states will remain prospects for Republican gerrymanders in 2021.

Democrats did win or retain the governorships in Colorado, Connecticut, Illinois, Maine, Minnesota, Pennsylvania, and Wisconsin and will likely face either Republican or split legislatures when redistricting maps are redrawn after 2020.  Together those states will probably encompass 64 Congressional districts after reapportionment.  Two states, Maryland and Massachusetts, with a likely total of seventeen seats, will see Republican governors facing off against Democratic legislatures in 2021.  I would not be surprised to see a new Republican representative sent to Washington after the 2020 Census from both these states which now have uniformly Democratic Congressional delegations.

Because the Democrats failed to win the governors’ races in Florida, Georgia, and Ohio, all three states will be prime targets for Republican gerrymanders in 2021.  (Iowa, with its four Members of Congress, matters much less.)  Ohio and Florida accounted for three to five “excess” Republican seats after the 2010 Census, and Georgia may have added another.  Because the Democrats fared less well in these larger states, the GOP will be drawing district lines for 61 of the 149 seats in “trifecta” states where they control both the governor’s mansion and the two houses of the state legislature.

 

1Both Michigan and New York appeared in the earlier version of this chart.  However both states will be using nonpartisan redistricting commissions in 2021 and have been excluded from the analysis here.

Governors and Gerrymanders in 2021

Elections this fall may limit the extent of gerrymandering for some 200 House seats after the 2020 Census.

Americans will elect thirty-four governors to four-year terms this fall, giving them all a say in how their states’ Congressional and legislative districts will be drawn after the 2020 Census.1

In 2010, Republicans took control of many state legislatures and governors’ offices, which offered them the opportunity to draw district maps that favored their party. During 2011-2012 when those maps were drawn, Republicans controlled both the executive and legislative branches in nineteen states and appear to have won fourteen percent more House elections in those states than we might expect based on historical data.  Democrats controlled just eight states and won four percent more seats than expected.  In thirteen states partisan control was split between the branches, and there the partisanship of the governor appears to have been the controlling factor. In split control settings, the governor’s party won about six percent more House seats after 2010 than expected.

The election in November has the potential for influencing how dozens of Congressional district lines will be drawn in the aftermath of the 2020 Census.  In a number of states Democrats are poised to break the Republicans’ lock on control of government by taking back the governor’s mansion.

I have categorized the governors’ races by their competitiveness using the most recent ratings for those races as compiled at Wikipedia.  Since the next redistricting will involve the results of the 2020 Census, I have used state-level population projections to estimate the number of seats each state will be awarded after reapportionment.  Most states’ representation in Congress will not change, but a few states like Texas are projected to add seats, while Rhode Island may lose one of its two representatives in the House.  Forecasting the results of state legislative races this fall, and more importantly two years hence, is obviously a dicey proposition.  I have instead assumed that all legislatures will be controlled by the same parties that control them now.  Based on these data I estimate that redistricting for some 188 seats, or 43 percent of the House, may be affected by the results of this year’s gubernatorial elections.

An “S” (“split”) code in the legislative column indicates that the two houses of the state legislature are held by different parties.

The first two columns of this table present the likely outcome of this fall’s race for governor in each of these states.  The “Consensus Rating” is based on translating each prognosticator’s ratings like “Safe Republican” or “Likely Democrat” into a numerical score and averaging them.  I also present the most recent ratings for each race from the well-known site, FiveThirtyEight.com.

In these more competitive states Democratic candidates for governor appear to be well-positioned to win back these offices from the Republicans.  Only in Massachusetts and Maryland are we likely to see Republican governors winning re-election while their states’ legislatures remain in Democratic hands.  In ten states from Georgia to Michigan to New Mexico, Democratic candidates are poised to oust Republican governors even if their states’ legislatures do not change hands.  As my results from the post-2010 redistricting showed, governors appear to have most of the clout in redistricting battles, reducing the chances of gerrymandering in places like Michigan, Ohio and Florida, all of which had an “excess” number of Republican seats beginning with the 2012 election.

 

 

 

1Governors in New Hampshire and Vermont serve two-year terms.

Governors Hold the Cards in Congressional Redistricting

In “split-control” states, Republicans won 6.2 percent more seats than expected when they held the governorship; when Democrats held that office, Republicans won 6.5 percent fewer seats than expected.

Americans will elect thirty-four governors to four-year terms this fall.  They will still be in office after the 2020 Census and will have a say in how states redraw their Congressional and legislative district plans. All states where legislatures draw district lines except North Carolina grant the governor the power to veto any plan.  In states where control over the branches is split between the parties, this process should lead to compromises acceptable to both parties.  As well see, however, the evidence from the redistricting after the 2010 Census suggests governors hold all the cards.

In nine states, politicians play no direct role as redistricting is left up to nonpartisan commissions.  Courts, too, can override the lines drawn by legislatures.  This year’s dramatic redrawing of the lines in Pennsylvania follows similar judicial interventions in Florida and New York.  The New York decision affects my analysis since it applied to elections beginning with 2012.  (The other decisions have yet to come into force.)  I have added New York to the commission list, but have analyzed it, and California, separately as well.

I have also excluded the seven states which have only one Congressional district like Wyoming and Alaska since gerrymandering is not possible with no lines to draw.  That leaves 43 states which can be categorized as follows:

  • maps drawn by nonpartisan commissions or courts (8 states);
  • maps drawn by Republican legislatures facing Republican governors (16 states)
  • maps drawn by Democratic legislatures facing Democratic governors (6 states); and,
  • maps drawn when either the houses of the legislature were held by opposing parties, or where the legislature had unified control but faced a governor of the opposite party (13 states).

To avoid relying too heavily on a single year, I have added together the votes cast for Republican and Democratic House candidates in each group of states for the 2012-2016 elections.  I have applied the same method to seats won, again summing up the number of Republican and Democratic seats won across all three elections.  That method produces these results:

House Votes and Seats Won 2012-2016 by Redistricting Method

 

 

 

 

 

 

 

 

 

 

The first column reports the Republican percent of the total two-party popular vote summed across the three elections, 2012, 2014, and 2016.  In the sixteen states where Republicans held both houses of the state legislature and the governorship, they won 56.5 percent of the two-party House vote and 71.7 percent of the seats.  In solidly Democratic states the Republicans won both a minority of the popular vote and of the seats awarded.  The results for commissions and courts is complex; I will deal with it in a later article.

In various articles here I have described the natural inflation of the proportion of seats won due to the operation of our first-past-the-post electoral system.  As parties win larger and larger proportions of the vote, they gain an ever-increasing share of seats.  I have estimated this inflation factor using both biennial election results back to 1946, and across states in 2012.  Both methods produce equivalent results, for instance.

To estimate the share of seats awarded you need only square1 the value of the ratio (Republican Votes)/(Democratic Votes) to get the ratio (Predicted Republican Seats)/(Predicted Democratic Seats).  This approach gives rise to the third column in the table, the proportion of seats that are predicted to be won by the Republicans after applying this “square law” rule.2 In the entry for Republican control, that party’s 56 percent share of the House vote should produce a share of about 63 percent of seats.  In practice, the Republicans won nearly 72 percent of the seats.  The final column measures the over- or under-representation of the Republicans in the House as a percentage gain or loss compared to the predicted share.  In this case, the Republican’s 72 percent is about 14 percent higher than the expected 63 percent. This figure provides a criterion for evaluating how over- or under-advantaged a party was compared to expectations.

The normal expectations for states with unified control are confirmed:  Republicans win a disproportionate share of seats in states where they controlled the redistricting process, and won disproportionately fewer seats than expected in states where the Democrats were in control.  Notice that the size of Republican advantage in states that party controlled is larger than the disadvantage the Republicans faced in states controlled by Democrats, +14 percent versus -4 percent.

By this measure states with some form of split party control show hardly any partisan advantage at all.  Republicans won a share of the seats awarded in these states nearly equal to their expected share.  However, it turns out this overall result hides a lot of significant variation.

We can identify two different forms of split control:

  • ones where both chambers of the state legislature are held by one party but the governor is of the opposite party; and,
  • ones where the chambers of the state legislature are held by different parties.

As it turns out there are nearly equal number of each type of split control; in seven states unified legislatures faced an opposition governor, while in six states the chambers themselves were split.  Once we break out these various patterns, the power of governors becomes clear.  In both types of split control, the governor’s party is disproportionately advantaged during redistricting.  In fact, if we group these split-control states together simply by the partisanship of the governor, Republicans were over-represented in seats awarded by 6.2 percent where they held the governorship; when Democrats held that office, Republicans were under-represented by 6.5 percent.

These results are rather striking.  They suggest that opposite-party governors can force a redistricting map that is actually more favorable to the governor’s party than to the legislature’s.  Similarly when the two legislative chambers are held by opposite parties, it is again the governor who appears to determine which map wins approval.  It appears the governor’s veto is a more powerful weapon in the fight over Congressional district lines than the legislature’s control over drawing the lines themselves.  This fact could weigh heavily over redistricting fights in states like Colorado, Michigan, Florida and Georgia where Democratic governors may win election and end up facing Republican legislatures.  In Massachusetts and Maryland the reverse will likely hold true.

 


1The longitudinal estimate was 2.04; the cross-sectional estimate was 2.08. For simplicity I have rounded down to two, which is well within the confidence intervals for each estimate of beta.

2The tendency for first-past-the-post systems to disproportionately advantage the winning party was first observed in elections in the United Kingdom. There the coefficient reached three, giving rise to the name “cube law” rule, since cubing the ratio (Labour Votes)/(Conservative Votes) does a good job of predicting the ratio (Labour Seats/Conservative Seats). Following this tradition, I have named the US version of this relationship the “square law” rule.

How Well Do Generic-Ballot Polls Predict House Elections?

I have compiled the results of generic-ballot polls taken near to an election and compared them to the actual division of the Congressional vote.  The table below presents the margin between support for the President’s party and support for the opposition.  For each election I have used about half-a-dozen polls from different agencies taken just before voting day.  Averaging the differences between these two quantities shows that these polls have fared rather well since 2002.  The average deviation in the four midterm elections is 0.6 percent; in Presidential years that falls to 0.1 percent.

Still these averages hide some fairly wide fluctuations.  In four of the eight elections the difference between the polls and the election results exceeds two percent.  The error was especially egregious in 2006 when the polls predicted nearly a fourteen-point Democratic margin compared to 8.6 percent in the election itself.

In the most recent election, 2016, the polls predicted a slight positive swing in favor of the Democrats, but the outcome went slightly in the opposite direction.  All the cases where the polls erred in picking the winner occurred in Presidential years and usually when the polling margin was close.  The four polls taken during midterm years all predicted the correct winner, though the size of the victory was off by more than three points in two of those elections.

 

The Election in Pictures

Some data updated through September 2.

Sunday, July 29th, marked the point when there are just 100 days left until the November midterm.  In this post I will try to pull together my various writings and predictions for both the 2018 House and Senate elections.  I begin with the most important factor that influences both types of races, the President’s job-approval figures.

Presidential Approval

The President’s job-approval rating is an important predictor of midterm election results in both my model for Senate elections and the one for House elections.  The Democratic advantage on the “generic-ballot” question about voting in House elections has waxed and waned as Donald Trump’s approval rating first fell after he was inaugurated then rose again over the past few months.

Donald Trump enters the 2018 election with about the same level of public support Barack Obama had in 2010. Though Obama was much more popular when he was inaugurated, that goodwill faded over the following eighteen months. In the 2010 midterm that followed, the Democrats were “shellacked,” losing sixty-three seats in the House of Representatives. Support for Trump also ebbed away during 2017, but he has rebounded slightly from his nadir last December.


Though Trump’s overall approval rating heading into the first midterm is largely identical to Obama’s, Trump is more intensely disliked.  Pew reported that the proportion of people saying they “strongly” disapproved of Obama’s performance in office grew from 18 percent in April, 2009, to 32 percent by September, 2010.  For Trump, CNN found that he took office with over forty percent of Americans already strongly disapproving, a figure that has remained relatively unchanged.  In its June, 2018, poll CNN reports a “strongly disapprove” figure of 45 percent.

The House of Representatives

As the first chart shows, the president’s job-approval rating bears directly on the “generic-ballot” question.  Based on polls through September 2nd, the Democrats’ lead on the generic ballot has grown slowly since Inauguration Day and inversely with Presidential job approval.  The grey area in the chart below represents the likely range of outcomes.  Since April, Donald Trump’s net approval rating has ranged from about -8 to -14.  Those values define the left and right sides of the shaded region.  When I include estimates of any methodological or unique “house effects,” I find that polls conducted over the Internet show a pro-Republican tilt of about 2.6 percent.  Gallup’s polling shows an ever greater Republican edge of nearly five percentage points.  I use the values for live polling, which are most favorable to Democrats, and those from the much-less favorable Gallup, to define the height of the grey area.

Notice that, according to these results, even if Trump were to achieve a net approval rating of zero, Democrats are still predicted in live polling to lead on the generic ballot by about six points on Election Day. That reflects the slow growth in support for Democratic House candidates over Trump’s presidency from about four points on Inauguration Day to a predicted six points this November. In past elections the margin of victory in generic-ballot polls has proven to be a pretty accurate predictor of the actual division of the vote.

An earlier version of this model showed a small, marginally significant positive boost for Democrats in polls of likely voters.  That difference has disappeared as the number of polls has increased.  Since Democrats are generally disfavored in likely-voter polls, especially ones conducted in midterm years, a finding of no difference between registered and likely voters is actually positive news for Democrats.

One other major problem for House Republicans has been the historically large number of their Members who are leaving, or have left, the House.  Forty Republicans will not be returning to the House next January creating an excess number of more vulnerable open seats on that side of the aisle.  Only 18 Democrats are leaving the chamber.  With 22 more retirements than the opposition, the largest midterm gap since the New Deal, the Republicans face a loss of 39 seats based on the historical relationship between the two measures.

The Senate

There is no national generic-ballot question for Senate elections because only two-thirds of the states have a Senate race in any given year.  Looking back historically over Senate elections, the fate of the President’s party depends directly on his job-approval rating and, unlike for House elections, the state of the economy as measured by the growth in real disposable personal income per capita.  Any plausible combination of approval for Donald Trump and income growth predicts that the Republicans will fail to win a majority of the popular vote for Senate in November.  One reason is that the popular vote for Senate candidates of the President’s party runs four points lower when the President is not on the ballot.


Much has been made of the 4.1 percent increase in Gross Domestic Product reported for the second quarter of the year.  That figure represents the growth in nominal GDP; after adjusting for inflation the figure is 2.8 percent. Unfortunately for the Republicans little of that growth appears to be “trickling down” to ordinary Americans.  Here are the recent trajectories for both real GDP and real per-capita disposable personal income.

Personal income has hovered around a two-percent growth rate for the last three quarters, while real GDP grew more quickly.  If voters respond to changes in the amount of money in their pockets, then the economy will not be sufficient to power the Republicans to victory in the fall.  From the chart above, a two-percent growth rate in per-capita income and even a 45 percent approval rating for Donald Trump still leaves Republican candidates short of a majority in the national popular vote for Senate.

From Votes to Seats: The House

Americans became much more cognizant of the word “gerrymander” after the redistricting that followed the publication of the 2010 Census.  Drawing lines for partisan advantage has become easier as voters have segregated themselves geographically by party.  Together the two forces have combined to create a Republican “bulwark” in the House. Democrats need to win the popular vote by more than fifty percent to take half the seats in the body.  How much more is subject to debate, but most estimates put the needed margin of victory in the range of six-to-eight percentage points, or an election where the Democrats win somewhere between 53 and 54 percent of the popular vote.

For instance, The Economist currently projects the Democrats to win 54.3 percent of the popular vote, or a margin of 8.6 percent, but take just 51.3 percent of the seats in the House.  Both Dave Wasserman at the Cook Political Report and Nate Cohn at the New York Times cite a seven-point margin as the minimum required for a slim Democratic win. My model agrees.  It uses historical voting data back to 1940 to estimate the relationship between seats and votes. I include adjustments for redistricting after each Census and for the decline in political competition since the 1994 “Contract with America” midterm. Using those data I estimate the Democrats need at least 53 percent of the national popular two-party vote to win a majority in the House of Representatives.

From Vote to Seats: The Senate

Unlike House districts, Senate seats cannot be gerrymandered because they constitute entire states.  That makes the Senate more competitive than the House.  There is no equivalent “bulwark” in the Senate; winning half the popular vote generally translates into about half the seats.  Since the model predicts that the Democrats will win a majority of the 2018 popular vote for Senate, we should expect the Democrats to win a majority of the 35 Senate seats at risk.  Winning 18 of those seats would not be enough to flip control of the Senate because of the Vice President’s tie-breaking vote.  Nineteen seats would give the Democrats control.


From Here to November

Can the Republicans rebound between now and election day?  Unfortunately, recent history suggests they will face even larger obstacles in November than they do todayPresidential approval generally declines as the election nears, and the opposition party’s advantage on the generic ballot grows.

Job approval for first-term presidents fell on average about five points between May/June and October of midterm election years.  Trump might see a smaller decay because his current popularity is historically low, around 42 percent.  Presidents whose approval was above fifty percent in May/June saw a 3.3 percent drop in approval; those who started below fifty percent in May/June saw their ratings fall an average of just 1.9 percent.


In off-year elections, generic ballot polls for both of Obama’s midterms fell as the election neared.  For George W. Bush in 2006, Republicans recovered slightly from their early summer deficit, then watched support for their candidates crater in October.  Most observers credit that sharp decline to the Mark Foley scandal that fall.

 

From Job Approval to the Ballot Box

“Generic-ballot” polls predict a nine or ten point Democratic victory in House elections this fall, enough to flip the chamber.

As most observers know, support for the Democrats on the so-called “generic-ballot” question has moved inversely to the public’s opinion about Donald Trump’s performance in office.


Can we use this link between support for the parties on the generic-ballot question and Trump’s job approval figures to forecast possible election results in November?

There are 228 generic-ballot polls in my current dataset covering the period from Inauguration Day, January 20, 2017, through June 9, 2018.  Of those 228 polls, 209 also collected data on presidential approval.  Those 209 polls constitute the sample for this analysis.

A weighted-least-squares model using my standard predictors — days in office, polling method, and polling sample — plus the net Trump job approval score “explains” about half the variance in the size of the Democrats’ lead on the generic-ballot question.  Overall, the Democrats’ lead has increased at a slow, but discernible pace since the Inauguration.  Even after taking Trump’s job approval into account, I find support for the Democrats grows about 0.3 percent every hundred days.  At that pace, the Democrats will have picked up about 2.2 percentage points by the time the election takes place on November 6th, some 655 days after Trump took office.

Two other factors influence the size of a poll’s Democratic lead.  The Democrats do about 2.2 percent worse in online polls than in ones conducted by telephone. On the other hand, polls restricted to “likely” voters show a marginally significant (p < 0.11) boost for the Democrats of 1.3 percent.  That might indicate a slight Democratic advantage in voter mobilization going into the fall, but the effect is still too small, and too variable, to be taken seriously at the moment.

These factors remain constant in the face of changes in Trump’s job approval and the passage of time.  We can thus set them at their values on Election Day and see how the margin in the generic House ballot varies with changes in Trump’s job-approval rating.  This chart presents the likely Democratic lead on the generic-ballot question in polls conducted with live interviewers on Election Day, November 6th. The dotted line represents the effect of adding the small, marginally-significant boost for polls of likely voters:


As of July 20, Trump’s net job approval (approve-disapprove) is averaging about -11 (42-53). My estimates indicate that difference translates into a Democratic margin of 8.8 percent in generic-ballot polls.  Notice that the remaining factors in the model predict a Democratic margin of about six to seven percent even if Trump’s net approval score is zero. That might be a decent estimate of the so-called “blue-wave.”

Models of the relationship between House votes won and House seats won find that, to take back the House, the Democrats will likely need to win by a margin of +7 or better to overcome gerrymandering and partisan geographic self-selection.  For instance, The Economist’s simulation model for the House midterms predicts that the Democrats will win 54.3 percent in November, or a margin of 8.6 percent.  In their model that gap translates into a Democratic seat margin of 224-211, enough to retake control of the House.

History suggests that both the President’s approval rating and support for the President’s party in the House are lower on election day than they are in the spring.

 

Update on Family Separations

Some 1,500 children remain separated from their parents and in government custody.  Only 63 percent of children whose cases have been officially been reviewed have been reunited with their parents.

The Federal Government has provided new figures concerning the migrant children separated from their parents at the border as part of the proceeding before Judge Dana Sabraw.  I have used these figures, along with my previous accounting, to develop estimates of the number of children reunited with their parents, and those not yet reunited for a variety of reasons. I start with the total of 4,954 separated children I estimated earlier including both children separated during the “zero-tolerance” period and those separated during the “pilot program.”  There are three official sources of information on reunifications.  The first is a “fact sheet” from DHS which reported that 538 children had been reunited with their parents “as part of the Zero Tolerance initiative.” Some number of these children may have been separated before zero tolerance, but we have no way of knowing how many.  The “Fact Sheet” also fails to mention the number of children whose cases were processed but who remain in government custody.  I will estimate that number below.

The other two sources of data on reunifications comes from the filings made by the government in the case of Ms. L.v. ICE before Judge Dana Sabraw.  On June 26th Judge Sabraw ordered that the government must reunite all separated children.  The government has since submitted two filings to the court reporting on its progress.  The first, filed July 12th, concerned the disposition of the supposed 103 children in custody who were under five years of age.  (This figure of 103 remains suspiciously low.)  Late this past Thursday, July 19th, the government reported on its progress with the older children in its custody.

The government could only identify and clear the parents of 57 of the youngest children.  The other 46 remain in government custody because it determined the child might be subject to abuse, the parents were in custody or had criminal records, the associated adult was not the child’s parent, or, in twelve cases, the parent(s) had already been deported.  The clearance rate was higher for the older children.  364 of them were reported to be reunited with parents, and in another 848 cases the parent(s) were identified and cleared, but the reunification had yet to take place.  However the government also identified another 908 children whose parent(s) were either declared ineligible or whose eligibility was still unresolved.

The one remaining piece of the puzzle concerns the number of children separated before zero tolerance began who were subsequently reunited with their parent(s).  If we assume that their cases were disposed of at the same rate as cases during zero-tolerance, we can estimate the number of reunited children from that earlier period.  Combining together the 57 reunited young children with their 364 older reunited peers, and counting the 848 children awaiting reunification, gives us a total of 1,269 children either reunited or awaiting reunification.  In comparison 46 young children and 229 older ones remain separated because their parents were not cleared.  If we add to that the 908 children who may also be ineligible, we get a total of 1,183 children whose cases have been reviewed without reunification,  Applying the same “clearance rate” to the period before zero tolerance gives us an estimate of 502 children from that period who remain ineligible for reunification.


The rate at which parents are declared ineligible should be a major source of concern.  Of the 3,492 separated children whose cases I estimate were resolved by July 19th, only 1,807, or just 52 percent, were reunited or awaiting reunification with their parents. If we rely solely on official reports, 1,045 children were ineligible or uncleared.  Even that more conservative figure results in a reunification rate of just 63 percent.

 

Tracking Family Separations

How the number of separated children grew to nearly 4,300, and why many more than 103 of them must be under five years of age.

In the last post I offered a simple bookkeeping model using reported figures from DHS and plausible extrapolations to estimate the number of children separated from their parents at the border since October, 2016.  Here is the time track of the number of children in custody. The solid lines connect points based on DHS reports; the dotted lines are estimates.


The black lines represent the period of “zero tolerance,” during which nearly 3,000 children were taken from their parents.  Since then DHS has reported 538 reunifications that span zero-tolerance and maybe earlier.  I estimate another 126 children were reunited with parents between the end of family separations on June 20th and July 5th when DHHS Secretary Azar told reporters the number of children in custody numbered “fewer than 3,000.”

Much attention has been paid to the 103 children under five who were supposed to be reunited with their parents last week.  A rate of 103 children under five from a population of  “fewer than 3,000” separated children is entirely preposterous.  About one in three children living in the countries from which most families migrate is under five years of age.  There must be hundreds more “tender-aged” children in custody than the government has accounted for so far.