Category Archives: Hillary Clinton

The 2016 Electoral Map

The Aggregated 2016 Electoral Map

 

One week to go!

Hillary Clinton has a strong electoral lead — 347 to 191 — and she is close in a few states where Donald Trump leads, such as Georgia and Missouri.  Consistent with polls and the election narrative, Clinton is en route to handing Trump a resounding electoral loss.

Here’s the predicted 2016 electoral map:


Click the map to create your own at 270toWin.com

The below table shows current projections for battleground and other close states in the 2016 electoral map.

StateClintonTrumpJohnsonSteinClinton Chance of WinningTrump Chance of Winning
Arizona39.04%46.88%7.24%7.29%25.8%74.2%
Colorado46.62%40.04%9.48%3.56%92.1%7.9%
Florida49.11%46.06%4.63%1.48%70.0%30.0%
Georgia44.51%47.05%8.18%0.14%43.7%56.3%
Indiana40.48%47.15%11.72%0.78%10.20%89.80%
Iowa45.44%45.34%6.78%2.49%48.3%51.7%
Maine46.94%38.45%7.46%7.24%90.00%10.00%
Michigan49.64%39.56%7.36%3.51%91.90%8.10%
Minnesota47.75%39.91%5.82%6.52%81.40%18.60%
Missouri43.40%48.07%6.63%1.37%38.6%61.4%
North Carolina48.58%45.45%5.82%0.01%65.4%34.6%
New Hampshire48.16%41.25%8.49%2.88%93.0%7.0%
Nevada48.87%42.96%7.08%1.18%79.2%20.8%
Ohio46.88%44.99%6.40%1.82%69.1%30.9%
Pennsylvania50.15%42.96%5.16%1.78%87.8%12.2%
Virginia51.49%40.69%7.13%2.03%87.5%12.5%
Wisconsin49.86%41.61%5.86%2.60%66.3%33.7%


Structural Model Method

Independent of candidate characteristics, the Republican Party should fare well in 2016 due to Democratic Party fatigue (only once since 1952 has the same party held the White House for more than 8 years in a row).  However, Donald Trump’s historically low favorability ratings may very well cost him the presidency — including candidate favorability in the structural model hurts Trump to the tune of 60 electoral votes, enough to flip the election from a close Republican victory to a Clinton rout.

The structural model takes data from the 2000, 2004, 2008, and 2012 presidential elections to run a linear regression that determines the relationship between a handful of variables, including state demographics, and number of Democratic public officials, and the Democratic vote share.  It is developed by averaging two approaches: one which ignores candidate favorability and a second which includes in the regression the difference between Hillary Clinton and Donald Trump’s net favorability (the results from those models can be found here and here.  Clearly, Trump’s historically low favorability ratings could potentially cost him the election).

The structural model assesses the underlying electoral landscape separate from campaign actions.  By accounting for factors such as the state partisan voter index (developed by the Cook Political Report), the percent of House seats occupied by a Democrat, and region, we can understand how states are inclined to vote without campaign activities or candidate quirks.  Of course, considering Clinton and Trump have high unfavorable ratings, a pure structural analysis will likely miss the mark (hence averaging it with a structural model that includes favorability).  We have also developed a state battleground model to analyze poll results.

The structural model serves as a baseline.  We can expect these, or similar, results if the campaign ended today.  Between now and November 8, one variable will be adjusted: the difference between Clinton and Trump’s net favorabilities.  Numbers are from Gallup.

Overall, the model explains around 94 percent of the vote share variation during the four elections.

Predicting third party candidate vote shares is difficult because they fared poorly in previous elections, but polls indicate 2016 will be different.  Regression models won’t work.  Instead, using a Libertarian and Green Voter Index, vote shares for Gary Johnson and Jill Stein can be modeled.  The voter indices approximate each state’s inclination to vote for a Libertarian/Green Party candidate by taking state results from the past four elections and dividing them by the LP/GP national result.  This index can then be multiplied by Johnson and Stein’s national polling average to estimate their vote share in any given state.

An example should clarify the method (the following numbers are all made up): Say in Alabama the Libertarian candidate received 0.5% in 2000, 0.25% in 2004, 1% in 2008, and 2% in 2012.  Nationally, that candidate earned 1% in 2000, .50% in 2004, 1.5% in 2008, and 3% in 2012.  The index for each year is 0.5, 0.5, .67, and .67.  Averaging the four, Alabama would have a Libertarian Vote Index value of 0.59.  To estimate Gary Johnson’s 2016 vote share in Alabama, I multiple 0.59 by his national polling average (which I have weighted to account for pollster accuracy and date).

With a Libertarian and Green Party candidate included, Clinton and Trump vote shares need to be adjusted.  To determine how much to subtract from each, I find the difference in polling averages between the weighted Clinton vs. Trump average and the weighted Clinton vs. Trump vs. Johnson vs. Stein polling averages.  From there, I divide the difference between each candidate’s polling average by the total number of percentage points lost between Clinton and Trump.  Their initial vote share estimates are then subtracted from the difference quotient multiplied by expected Johnson and Stein vote shares.

These values will obviously change as Johnson and Stein’s poll numbers fluctuate and the difference between the two polling averages changes.  As such, this model will be updated weekly (assuming new polls are released during the week).

State Poll Method

This model is developed through a simple process: Take the cross-tabs of each state poll and look at response by race, gender, and party identification.  Those results are multiplied by inferred electoral composition of each group (determined by a linear extension of the trends displayed in 2004, 2008, and 2012).  Demographic breakdown (race, gender, and party ID) is averaged and then multiplied by pollster rating (numeric values assigned based on the 538 assessment of polling outlets) and 1 divided by the days until the election from the poll’s end (this means that recent polls are weighted more than older polls).  Results are then multiplied so the numbers are sensible (ie, so that when added together, the numbers are equal to the sum of poll values in the RealClearPolitics average).

Aggregate Model

This model aggregates and weights the structural and state poll maps.  Initially, the two are weighted equally, but as states are polled more and election day nears, the battleground states model is dynamically given a larger say in the aggregate.  The structural model without candidate favorability sheds weight faster than does the structural model that includes candidate favorability.

To determine win probabilities, each state’s expected vote tally is simulated 1,000,000 times, varying candidate strength among different races, gender, party, and expected third party vote.  Doing so allows the model to account for polling error — by varying strength among demographic subgroups, the model analyzes what might happen if Clinton or Trump fares, for instance, unexpectedly well with black voters (an outcome that could flip Georgia to Clinton or allow Trump to win Pennsylvania).

 

*Old Updates*

July 20 Update: Our model continues to favor Hillary Clinton though polls, national and state, are beginning to tighten.  The structural model, which accounts for candidate favorability, gives Clinton a large edge.  Clinton’s unfavorable ratings have risen whereas Trump, with the aid of the Republican National Convention, saw his favorable ratings rise a couple of points.  However, Clinton’s margins in state polls, while shrinking, when combined with the structural model yields a comfortable lead.  Neither candidate is consistently crossing 45% in state polls, a clear sign that voters are dissatisfied with their choices this November.

Is Indiana in play?  The model saw Clinton’s chances in Indiana skyrocket this past week.  Can she actually compete in the traditionally red state?  Most likely not, though Trump’s selection of Indiana Governor Mike Pence as his running mate and joint rally in that state, plus his commitment to spending money defending the state’s 11 electoral votes, indicates that the Trump campaign might not be comfortable in its slim lead there.  Indiana’s past proclivity to vote for a libertarian candidate leads to a high expected result for Gary Johnson in the state.  Our models show that when Johnson is included in national polls, Trump loses slightly more support than does Clinton.  Those two instances intimate a close race in Indiana, one which might not bear fruit in November.  State polls are needed.

How might the RNC affect the race?  It’s too soon for polls to reflect Trump gains from the RNC, though his net favorability, tracked by Gallup, has risen throughout the week.  Polls released over the weekend and the beginning of the next week will likely show a closer race, with the Democratic National Convention next week similarly giving Clinton a bump.  In the weeks after the conventions polls should stabilize and begin to reflect the true nature of the race.

June 29 update: In the last week, Donald Trump’s net favorability numbers rose by around 4 points while Hillary Clinton’s fell by the same amount.  That net differential helped Trump gain a couple of points in the structural model, narrowing Clinton’s lead in Florida, Ohio, and Iowa and allowing Trump to expand his margin in Indiana and Missouri to double digits.

North Carolina remains in Trump’s corner by a couple points.  Georgia and Arizona, two states Clinton supporters think might turn blue this cycle, both favor Trump by 9 points.  Here the state polls differ from the structural model: Our state poll model shows Trump three points in the Copper State, but the structural model gives him a larger edge.

July 6 update: The holiday weekend meant few polls released this past week.  National numbers continue to strongly favor Hillary Clinton and state polls largely back up that data (though more are needed).  This next week will be interesting as polls will capture the effects of Donald Trump’s latest Twitter snafu and the potential fallout from Clinton’s email investigation conclusion.  

North Carolina is currently anyone’s game, as evidenced by Clinton campaigning there with President Barack Obama and Trump holding a rally in the state that same night.  Other efforts to expand the electoral map, for both campaigns, are not yet looking good.  Arizona and Georgia, two states in which some Clinton folks believe she will be competitive, still strongly back Trump; Wisconsin and Pennsylvania, states Trump believes he can flip, are pro-Clinton at this time.  Ohio remains very close and Nevada, while still favoring Clinton, is showing a very tight race in state polls.

Gary Johnson is still forecasted to do well for a third-party candidate.  His national numbers are approaching double digits, though his state polling is rather low (or non-existent — a number of surveys fail to include his name).  Currently, third-party candidates actually hurt Clinton more than Trump, perhaps indicating that a few points of her support comes strictly from people voting against Trump (not for Clinton).   

July 13 update: North Carolina has flipped from slightly favoring Donald Trump to favoring Hillary Clinton by a percentage point.  The state’s 15 electoral votes put Clinton at 347 and Trump at 191.  Aside from Indiana, which has tightened this week as Trump (and Clinton’s) favorability dipped, this map is the same as the 2008 electoral map.  

In recent days, national and state polls have reflected a close race.  Contemporary Quinnipiac University polls show tight, if not tied, races in Ohio, Pennsylvania, and Florida.  Our models, which look at weighted and aggregated polls, still show Clinton with a slim lead in those states and a likely victory.  That said, if the polls continue to show a close race in said states, our model will quickly reflect the new reality.

Heading into Cleveland, Trump must try to further unite his party.  He currently receives between 70 and 90% of the Republican vote in most states whereas Clinton generally receives 80-95% of the Democratic vote.  Trump must boost his numbers among Republicans; he still has room to grow in that area.  Clinton has yet to reach her ceiling among independents, a number of whom likely supported Bernie Sanders in the primary and are still making their way to the Clinton camp.  Sanders’ recent endorsement of Clinton may hasten that process.

Some fallout from Clinton’s email scandal has been noted.  Her favorability numbers declined this week and polls post-James Comey’s decision not to recommend charges have shown her shedding a couple of points to Trump.  However, it doesn’t seem like Trump successfully capitalized on the announcement.  Time will tell whether he can keep salient Clinton’s email scandal.

The Republican Convention will likely boost Trump’s poll numbers a little bit.  That likely won’t be reflected next week, but rather during the week of the Democratic National Convention.  Trump unveiling his vice-president might also pad his numbers among Republicans.  As summer wears on, the excitement continues — check back next week for the updated model!

Election 2016: State Polls Model

Assessing State Polls

*June 29 Update*  Hillary Clinton has narrowly pulled ahead in North Carolina.  Her leads in other states have slightly expanded in the past week, largely following the trend in national polls.  The gender gap is currently favoring Clinton — though Donald Trump tends to do well with men, Clinton does even better with females.  Trump is still struggling to consolidate Republican support.  He’s polling in the high 70s to low 80s with Republicans throughout the states, bleeding some support to Gary Johnson (LP) and Clinton.  To win, he’ll need to earn their support.

The PoliticalEdu state polls model uses polling data to analyze individual states in the 2016 presidential race.  It accompanies the structural model and is combined with it in the aggregated 2016 electoral map model.

This model is developed through a simple process: Take the cross-tabs of each state poll and look at response by race, gender, and party identification.  Those results are multiplied by inferred electoral composition of each group (determined by a linear extension of the trends displayed in 2004, 2008, and 2012).  Demographic breakdown (race, gender, and party ID) is averaged and then multiplied by pollster rating (numeric values assigned based on the 538 assessment of polling outlets) and 1 divided by the days until the election from the poll’s end (this means that recent polls are weighted more than older polls).  Results are then multiplied so the numbers are sensible (ie, so that when added together, the numbers are equal to the sum of poll values in the RealClearPolitics average).

Naturally, this model only applies to states that have been polled.  Many have not, leading to a number of grey “undecided” states.  Those will hopefully be filled in as the election approaches and more states are polled.

The model’s results, shown below, are favorable to Hillary Clinton.  Thus far, she is faring well in state polls; however, it is still early and much can change between now and November.


Click the map to create your own at 270toWin.com

Poll-based states’ predicted results:

StateClintonTrumpJohnsonStein
Arkansas36.90%47.84%5.26%0.00%
Arizona41.11%44.95%3.47%0.00%
Florida45.40%41.20%3.47%0.97%
Georgia41.08%44.23%3.72%0.00%
Iowa45.81%41.66%0.00%0.00%
Michigan44.89%39.89%14.03%0.00%
North Carolina44.42%44.01%4.35%1.07%
New Hampshire46.57%40.40%0.00%0.00%
Ohio45.00%40.03%3.19%1.02%
Pennsylvania47.04%42.33%3.44%1.21%
Texas33.20%41.53%0.00%0.00%
Virginia42.28%39.63%3.82%0.00%
Wisconsin48.26%40.44%4.28%0.60%

(You’ll notice these numbers do not add up to 100% — the polls released have options for “don’t know/other” and “wouldn’t vote,” thus preventing the candidates from adding to 1.  The number of “don’t know” respondents should decrease as election day approaches.)

This post will be updated as more polls are released!

Structural Model Regression Output

Democratic Vote Share Structural Model
Dependent variable:
dem.vote.share
dem.nom.fav0.005***
(0.001)
dem.8-0.04***
(0.01)
atlantic.coast0.04***
(0.01)
new.england0.05***
(0.01)
west.coast0.02*
(0.01)
midwest0.03***
(0.01)
great.plains0.005
(0.01)
mountain.west0.01
(0.01)
state.gdp0.0000
(0.0000)
south0.002
(0.01)
dem.reps-0.01
(0.01)
rep.nom.fav-0.0003
(0.001)
net.rep.fav
net.dem.fav
mood
percent.minority0.10***
(0.02)
dem.senators0.004
(0.003)
st.pvi-0.01***
(0.0004)
Constant0.39***
(0.02)
Observations204
R20.95
Adjusted R20.94
Residual Std. Error0.03 (df = 188)
F Statistic222.02*** (df = 15; 188)
Note:*p<0.1; **p<0.05; ***p<0.01

Electoral Map 2016 — Structural Model

Electoral Map 2016: The Structural Model

PoliticalEdu is developing three electoral models for 2016.  The first, the structural model, takes data from the 2000, 2004, 2008, and 2012 presidential elections to run a linear regression that determines the relationship between a handful of variables, including state demographics, and number of Democratic public officials, and the Democratic vote share.  It is developed by averaging two approaches: one which ignores candidate favorability and a second which includes in the regression the difference between Hillary Clinton and Donald Trump’s net favorability (the results from those models can be found here and here.  Clearly, Trump’s historically low favorability ratings could potentially cost him the election).

The structural model assesses the underlying electoral landscape separate from campaign actions.  By accounting for factors such as the state partisan voter index (developed by the Cook Political Report), the percent of House seats occupied by a Democrat, and region, we can understand how states are inclined to vote without campaign activities or candidate quirks.  Of course, considering Clinton and Trump have high unfavorable ratings, a pure structural analysis will likely miss the mark (hence averaging it with a structural model that includes favorability).  We have also developed a state battleground model to analyze poll results.

The structural model serves as a baseline.  We can expect these, or similar, results if the campaign ended today.  Between now and November 8, one variable will be adjusted: the difference between Clinton and Trump’s net favorabilities.  Numbers are from Gallup.

Overall, the model explains around 94 percent of the vote share variation during the four elections.

Predicting third party candidate vote shares is difficult because they fared poorly in previous elections, but polls indicate 2016 will be different.  Regression models won’t work.  Instead, using a Libertarian and Green Voter Index, vote shares for Gary Johnson and Jill Stein can be modeled.  The voter indices approximate each state’s inclination to vote for a Libertarian/Green Party candidate by taking state results from the past four elections and dividing them by the LP/GP national result.  This index can then be multiplied by Johnson and Stein’s national polling average to estimate their vote share in any given state.

An example should clarify the method (the following numbers are all made up): Say in Alabama the Libertarian candidate received 0.5% in 2000, 0.25% in 2004, 1% in 2008, and 2% in 2012.  Nationally, that candidate earned 1% in 2000, .50% in 2004, 1.5% in 2008, and 3% in 2012.  The index for each year is 0.5, 0.5, .67, and .67.  Averaging the four, Alabama would have a Libertarian Vote Index value of 0.59.  To estimate Gary Johnson’s 2016 vote share in Alabama, I multiple 0.59 by his national polling average (which I have weighted to account for pollster accuracy and date).

With a Libertarian and Green Party candidate included, Clinton and Trump vote shares need to be adjusted.  To determine how much to subtract from each, I find the difference in polling averages between the weighted Clinton vs. Trump average and the weighted Clinton vs. Trump vs. Johnson vs. Stein polling averages.  From there, I divide the difference between each candidate’s polling average by the total number of percentage points lost between Clinton and Trump.  Their initial vote share estimates are then subtracted from the difference quotient multiplied by expected Johnson and Stein vote shares.

These values will obviously change as Johnson and Stein’s poll numbers fluctuate and the difference between the two polling averages changes.  As such, this model will be updated weekly (assuming new polls are released during the week).

Including Johnson, this is the electoral map 2016:

 

electoral map 2016

 

The map belies the closeness of many states.  Here is a table of states that could very easily change the election.

Clinton +5-7.5Clinton +2.5-4.9Clinton +0-2.4
ColoradoIowaFlorida
New HampshireOhio
Pennsylvania
Wisconsin
Trump +0-2.4Trump +2.5-4.9Trump +5-7.5
North CarolinaIndiana
Missouri

This post will be updated!

can trump win

Can Trump Win? Yes, Very Easily

Can Trump Win the Presidency?

Democrats are convinced that Donald J. Trump will not be elected president.  And they have good reason for that belief: Trump has managed to insult many crucial demographic groups, most notably Latinos and women.  But Democratic thinking mimics that of Republican elites nearly 10 months ago.  Remember when all GOP candidates and many elected officials stated that Trump would not become the nominee?  Such cocksure statements ultimately proved to be false.  Trump wantonly attacked 2008 Republican nominee John McCain because he was captured in war, compared Ben Carson to a child molester, ceaselessly harassed Lindsey Graham, brazenly dismissed the last Republican president (George W. Bush), insinuated that Ted Cruz’s father took part in John F. Kennedy’s assassination, and assailed 2012 Republican nominee Mitt Romney.  Yet he won.

What makes Democrats so sure that Trump won’t win the general election?  Yes, he has a foot-in-mouth habit, flip-flops constantly, and puts forth absolutely no effort in learning public policy, but none of that has mattered.  No ideological attacks have changed his poll numbers.  No debate attacks over his conservative bona fides or outlandish policy ideas diminished his chances of winning the nomination.  In fact, through it all, Trump supporters — a true cult — fell deeper and deeper for their illiberal candidate.  Why would that change for the general election?  Better yet, why, given his many missteps and poor standing among Latinos and women, can Trump win?

All it takes is one event over the next 5.5 months and all those laughing when asked “can Trump win?” will spend election night pondering where they went wrong; all it takes for Trump to become president is one event.

That event is a domestic terrorist attack.

Prior to the Paris and San Bernardino attacks, Trump’s poll numbers had started to stagnate and even dip.  However, following the terrorist strikes and his Muslim ban proposal, his numbers rocketed.  The chart below shows his poll numbers from the beginning of November through the end of 2015 (he soared almost 10 points, or 40 percent, in that time frame).

trump poll numbers
Source: RealClearPolitics

For some reason, a man with no foreign policy experience — a man who touts being the Grand Marshall of a parade as pro-Israel credentials and has cited hosting beauty pageants in foreign countries as international experience — is viewed as tough on terrorism.  That’s true beyond just Republican voters.  A domestic terrorist attack could very well provide Trump with an irreversible boost in the polls, one which would flip the current electoral standing.

Here’s the scary part: ISIS has every reason to encourage a lone-wolf terror attack in the United States before the general election.  Trump is a boon to ISIS’s recruitment: ISIS thrives on an incorrect notion that the West is at war with Islam.  But Trump almost makes that idea correct.  His want to ban Muslims from the country and register Muslims citizens here (when asked about how that idea differed from Hitler’s Jew registry, Trump responded “you tell me”) lends weight to the (incorrect) idea that Western democrats and individuals despise Islam and want to see it eliminated.  Using Trump and his policy ideas in recruitment advertisements and videos will help ISIS find new members.

ISIS leaders are not dumb.  They understand politics and surely know that a Trump presidency would strengthen their standing.  And I have to imagine they realize that the best way of electing Trump would be to launch or encourage a domestic terror attack.

As seen in Brussels, terrorist strikes are frighteningly easy.  There are many vulnerable points in American mass-transit systems.  A strike in any of those spots would result in numerous casualties and surely would succeed in terrorizing the nation, pushing undecided voters into Trump’s camp given his (horrendously flawed) image as a tough man.

One terrorist attack and an illiberal politician whose policies could well push America on a road to proto-fascism may be swept into the Oval Office.

We need to defeat Trump early — Democrats need to destroy his candidacy before he destroys them (and the country).  That means super PACs need to front-load advertisements; the Clinton campaign needs to do the same.  Bernie Sanders, if he insists on staying in the race, needs to focus his ire on Trump, not Clinton.  Rank and file Democrats need to volunteer and donate to the party and its presumptive nominee early so the party can destroy Trump’s poll numbers and standing with voters.

Trump needs to be put down right away; otherwise, the uncertainty of the next 5.5 months might be a boon to his candidacy.

So, can Trump win?  Yes, and very easily.

wisconsin democratic primary predictions

Wisconsin Democratic Primary Predictions

We’re back with our Democratic prediction model, which fared very well during Western Saturday (it correctly predicted the winner in each of the Alaska, Hawaii, and Washington caucuses and its vote share estimates also fell close to the actual results).  While those results likely did not change the trajectory of the race, they have certainly infused Bernie Sanders with momentum: In the past week, Wisconsin polls flipped from having Clinton up 6 points to Sanders being up an average of 5 points.

Our Wisconsin Democratic primary predictions show two different (and simultaneously expected) results.  The table below depicts win probabilities for the two candidates.  It largely aligns and mimics the polls — Sanders has a clear advantage and is indubitably favored, but not overwhelmingly so (a win probability one would expect with a candidate leading the polls by just more than the margin of error).

Hillary Clinton Win Probability


Bernie Sanders Win Probability


Wisconsin42%58%

However, the vote share model tells a different story.  The vote share Wisconsin Democratic primary predictions point to a decisive, landslide victory for Sanders.  Our vote share model relies heavily on demographics and those of Wisconsin trend favorably to Sanders — the state is overwhelmingly white (82 percent) with a very small African American and Hispanic population (6 and 5.6 percent, respectively).  These demographics are similar to those of Minnesota, a neighboring state which Sanders handily won (with 62 percent of the vote; Minnesota also favored Sanders because it was a caucus).  Sanders fares very well with white voters and their large presence in the state’s electorate leads to the model advantaging him in the primary.  In other words, if he’s to make up the delegate gap, Wisconsin is very favorable terrain to net a large number of them.

Hillary Clinton Vote Share


Bernie Sanders Vote Share


Wisconsin47%53%

Will our predictions bear out?  Based on polls, it seems so, though given Sanders’ recent momentum and financial resources (which could fund a substantial last-minute ad blitz), it would not be surprising to see Sanders win by slightly larger margins.  Considering that Wisconsin is 82 percent white, the predicted margin is actually rather disappointing for Sanders – favorable demographics in a medium sized state offer him an increasingly rare opportunity to pick up a large amount of delegates and begin to meaningfully close his deficit.  We predict the below delegate allocation:

Hillary Clinton Delegate Expectation


Bernie Sanders Delegate Expectation


Wisconsin4046

These targets, again, seem reasonable given the polls.  If Sanders earns more than 46 delegates from the primary, it will be a good day for him.  If he passes 50, it will be a very good day for Sanders (though, unless indicative of beating polls and expectations, the single victory here will not alter any race dynamics).

As always, take these numbers with grains of salt as they reflecting underlying electoral conditions, not the campaigns or the candidates or momentum or news, etc.  These estimates may well be wrong (we fully admit that) and in the case they are, we’ll go right back to the drawing board to refine and edit our models.  Any comments about these forecasts or our models are welcomed!

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