Midterm Election Poll: Florida’s 26th District, Curbelo vs. Mucarsel-Powell

NYT Upshot / Siena College Poll

We polled voters in Florida’s 26th Congressional District.

This poll was conducted from Sept. 13 to Sept. 17.

A Democratic-leaning district represented by a Republican. We made 46010 calls, and 509 people spoke to us.

Carlos Curbelo, the Republican candidate, has a slight edge in our poll.

Given expectations, our poll is a decent result for Democrats. But remember: It’s just one poll, and we talked to only 509 people. Each candidate’s total could easily be five points different if we polled everyone in the district. And having a small sample is only one possible source of error.

Siena College Research Institute logo This survey was conducted by The New York Times Upshot and Siena College.

Where we called:

Each dot shows one of the 46010 calls we made.

Vote choice: Dem. Rep. Don’t know Didn’t answer

To preserve privacy, exact addresses have been concealed. The locations shown here are approximate.

Explore the 2016 election in detail with this interactive map.

About the race

  • Debbie Mucarsel-Powell is an immigrant from Ecuador who moved to the U.S. as a teenager. 19% favorable rating; 13% unfavorable; 68% don’t know

    Based on 509 interviews

  • Carlos Curbelo is the current representative and a Cuban-American. He voted to repeal the Affordable Care Act. 52% favorable rating; 27% unfavorable; 21% don’t know

    Based on 509 interviews

  • This strongly Hispanic South Florida district was created in 2012 and encompasses most of southern Miami-Dade County, Key West and all three of Florida's national parks.

  • Mr. Curbelo has disagreed with President Trump on some immigration issues. He initiated a seldom-used procedural maneuver to try to force the House to vote on a series of immigration proposals, a bold gesture that fell short by two votes.

  • Mr. Curbelo has also distanced himself from the president in other areas, calling the accumulation of Trump-related scandals a “sad chapter in our country’s politics.” But he voted for the G.O.P. tax overhaul; he helped draft the legislation as a member of the congressional tax-writing committee.

  • Ms. Mucarsel-Powell has said she was inspired to run for Congress the day that Mr. Curbelo voted to repeal the Affordable Care Act. She has worked as an associate dean at Florida International University and as a volunteer for a variety of environmental causes.

Other organizations’ ratings:

Cook Political Report Tossup
FiveThirtyEight Tossup
Center for Politics Lean Rep.
Inside Elections Tossup

Previous election results:

2016 President +16 Clinton
2012 President +12 Obama
2016 House +12 Rep.

It’s generally best to look at a single poll in the context of other polls:

Polls Dates Mucarsel-Powell Curbelo Margin
Siena College/New York Times n = 499 lv Oct. 19-24 45% 44% Even
Mason-Dixon Polling & Research, Inc. 625 lv Oct. 3-9 45% 46% Curbelo +1
GBA Strategies (D.) 500 lv Sept. 27-Oct. 1 50% 48% Mucarsel-Powell +2
Greenberg Quinlan Rosner (D.) 500 lv Sept. 23-27 49% 48% Mucarsel-Powell +1
Public Policy Polling (D.) 511 v Sept. 17-18 46% 45% Mucarsel-Powell +1
GBA Strategies (D.) 500 lv July 16-22 41% 48% Curbelo +7
DCCC Targeting Team (D.) 400 rv Mar. 17-22 40% 45% Curbelo +5

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How our poll result changed

As we reach more people, our poll will become more stable and the margin of sampling error will shrink. The changes in the timeline below reflect that sampling error, not real changes in the race.

One reason we’re doing these surveys live is so you can see the uncertainty for yourself.

If sampling error were the only type of error in a poll, we would expect candidates who trail by four points in a poll of 509 people to win about one out of every four races. But this probably understates the total error by a factor of two.

Our turnout model

There’s a big question on top of the standard margin of error in a poll: Who is going to vote? It’s a particularly challenging question this year, since special elections have shown Democrats voting in large numbers.

To estimate the likely electorate, we combine what people say about how likely they are to vote with information about how often they have voted in the past. In previous races, this approach has been more accurate than simply taking people at their word. But there are many other ways to do it.

Our poll under different turnout scenarios
Who will vote? Est. turnout Our poll result
The types of people who voted in 2014 157k Curbelo +7
Our estimate 179k Curbelo +4
People whose voting history suggests they will vote, regardless of what they say 182k Curbelo +4
People who say they will vote, adjusted for past levels of truthfulness 198k Curbelo +5
People who say they are almost certain to vote, and no one else 208k Curbelo +9
The types of people who voted in 2016 268k Curbelo +5
Every active registered voter 401k Curbelo +7

All estimates based on 509 interviews

Just because one candidate leads in all of these different turnout scenarios doesn’t mean much by itself. They don’t represent the full range of possible turnout scenarios, let alone the full range of possible election results.

The types of people we reached

Even if we got turnout exactly right, the margin of error wouldn’t capture all of the error in a poll. The simplest version assumes we have a perfect random sample of the voting population. We do not.

People who respond to surveys are almost always too old, too white, too educated and too politically engaged to accurately represent everyone.

How successful we were in reaching different kinds of voters
Called Inter-
viewed
Success
rate
Our
respon­ses
Goal
18 to 29 2942 67 1 in 44 13% 10%
30 to 64 15906 298 1 in 53 59% 58%
65 and older 5502 144 1 in 38 28% 32%
Male 9697 253 1 in 38 50% 45%
Female 14659 256 1 in 57 50% 55%
White 3674 140 1 in 26 28% 22%
Nonwhite 20212 357 1 in 57 70% 76%
Cell 18183 408 1 in 45 80%
Landline 6173 101 1 in 61 20%

Based on administrative records. Some characteristics are missing or incorrect. Many voters are called multiple times.

Pollsters compensate by giving more weight to respondents from under-represented groups.

Here, we’re weighting by age, party registration, gender, likelihood of voting, education and region, mainly using data from voting records files compiled by L2, a nonpartisan voter file vendor.

But weighting works only if you weight by the right categories and you know what the composition of the electorate will be. In 2016, many pollsters didn’t weight by education and overestimated Hillary Clinton’s standing as a result.

Here are other common ways to weight a poll:

Our poll under different weighting schemes
Our poll result
Don’t weight by education, like many polls in 2016 Curbelo +2
Our estimate Curbelo +4
Weight using census data instead of voting records, like most public polls Curbelo +7
Don’t weight by party registration, like most public polls Curbelo +11

All estimates based on 509 interviews

Just because one candidate leads in all of these different weighting scenarios doesn’t mean much by itself. They don’t represent the full range of possible weighting scenarios, let alone the full range of possible election results.

Undecided voters

About 9 percent of voters said that they were undecided or refused to tell us whom they would vote for. On questions about issues, these voters most closely resembled Democrats.

If they were to break 2 to 1 in favor of Democrats, that alone would be enough to change the lead in our poll, assuming we did everything else perfectly. (We could also be wrong on turnout or our sample could be unrepresentative. Or other voters could change their minds.)

Issues and other questions

We’re asking voters here several questions about immigration, including whether they’d like to eliminate Immigration and Customs Enforcement (an agency known as ICE), whether it bothers them to hear immigrants speaking a foreign language in public places and whether they think illegal immigrants living in the United States are more likely than American citizens to commit serious crimes.

Do you approve or disapprove of the job Donald Trump is doing as president?
ApproveDisapp.Don’t know
Voters n = 509 39% 54% 7%
Would you prefer Republicans to retain control of the House of Representatives or would you prefer Democrats to take control?
Reps. keep HouseDems. take HouseDon’t know
Voters n = 509 43% 50% 7%
Do you favor abolishing ICE, the Immigration and Customs Enforcement Agency?
SupportOpposeDon’t know
Voters n = 509 32% 60% 8%
Do you support a bill that would reduce legal immigration and provide funds for a wall along the U.S.-Mexican border?
SupportOpposeDon’t know
Voters n = 509 39% 57% 4%
Do you support or oppose a federal ban on the sale of assault-style guns and high-capacity magazines?
supportopposeDon’t know
Voters n = 509 58% 38% 4%
Are iIllegal immigrants living in the United States more likely than American citizens to commit serious crimes?
agreedisagreeDon’t know
Voters n = 509 21% 74% 5%
Does it bother you to hear immigrants speak a foreign language in a public place?
agreedisagreeDon’t know
Voters n = 509 17% 80% 2%
Are there places in your area, say within a mile of where you live, where you're afraid to walk alone at night?
agreedisagreeDon’t know
Voters n = 509 26% 72% 2%
How concerned are you that you, your family or other people that you know will suffer due to the effect climate change may have on the area where you live?
Not or not veryVery or somewhatDon't know
Voters n = 509 28% 70% 1%

Percentages are weighted to resemble likely voters.

What different types of voters said

Voters nationwide are deeply divided along demographic lines. Our poll suggests divisions too. But don’t overinterpret these tables. Results among subgroups may not be representative or reliable. Be especially careful with groups with fewer than 100 respondents, shown here in stripes.

Gender
Dem.Rep.Und.
Female n = 256 / 54% of voters 46% 44% 10%
Male 253 / 46% 41% 51% 8%
Age
Dem.Rep.Und.
18 to 29 n = 67 / 10% of voters 52% 34% 14%
30 to 44 80 / 16% 44% 46% 9%
45 to 64 218 / 41% 43% 46% 10%
65 and older 144 / 33% 42% 53% 5%
Race
Dem.Rep.Und.
White n = 158 / 25% of voters 47% 43% 10%
Black 42 / 10% 87% 5% 8%
Hispanic 292 / 61% 35% 57% 8%
Asian 4 / 1% 16% 22% 62%
Other 7 / 2% 61% 39%
Race and education
Dem.Rep.Und.
Nonwhite n = 345 / 74% of voters 43% 49% 8%
White, college grad 87 / 11% 58% 37% 6%
White, not college grad 71 / 15% 39% 48% 13%
Education
Dem.Rep.Und.
H.S. Grad. or Less n = 68 / 28% of voters 37% 55% 8%
Some College Educ. 168 / 33% 41% 49% 10%
4-year College Grad. 132 / 26% 51% 39% 10%
Post-grad. 135 / 13% 54% 40% 5%
Region
Dem.Rep.Und.
Monroe n = 108 / 18% of voters 49% 45% 7%
North Miami-Dade 226 / 46% 36% 54% 9%
South Miami-Dade 175 / 37% 51% 40% 9%
Party
Dem.Rep.Und.
Democrat n = 179 / 38% of voters 81% 10% 9%
Republican 178 / 35% 6% 92% 2%
Independent 133 / 24% 42% 41% 17%
Another party 11 / 2% 32% 58% 9%
Party registration
Dem.Rep.Und.
Democratic n = 197 / 40% of voters 77% 13% 10%
Republican 197 / 36% 9% 87% 4%
Other 115 / 24% 39% 45% 15%
Intention of voting
Dem.Rep.Und.
Almost certain n = 294 / 60% of voters 43% 51% 5%
Very likely 136 / 26% 52% 40% 8%
Somewhat likely 36 / 8% 29% 47% 23%
Not very likely 18 / 2% 21% 51% 28%
Not at all likely 19 / 2% 47% 33% 20%

Percentages are weighted to resemble likely voters; the number of respondents in each subgroup is unweighted. Undecided voters includes those who refused to answer.

Other districts where we’ve completed polls

California 48 Orange County Sept. 4-6
Illinois 12 Downstate Illinois Sept. 4-6
Illinois 6 Chicago suburbs Sept. 4-6
Kentucky 6 Lexington area Sept. 6-8
Minnesota 3 Minneapolis suburbs Sept. 7-9
Minnesota 8 Iron Range Sept. 6-9
West Virginia 3 Coal Country Sept. 8-10
Virginia 7 Richmond suburbs Sept. 9-12
Texas 23 South Texas Sept. 10-11
Wisconsin 1 Southeastern Wisconsin Sept. 11-13
Colorado 6 Denver Suburbs Sept. 12-14
Maine 2 Upstate, Down East Maine Sept. 12-14
Kansas 2 Eastern Kansas Sept. 13-15
Florida 26 South Florida Sept. 13-17
New Mexico 2 Southern New Mexico Sept. 13-18
Texas 7 Houston and suburbs Sept. 14-18
California 25 Southern California Sept. 17-19
New Jersey 7 Suburban New Jersey Sept. 17-21
Iowa 1 Northeastern Iowa Sept. 18-20
California 49 Southern California Sept. 18-23
Texas 32 Suburban Dallas Sept. 19-24
Pennsylvania 7 The Lehigh Valley Sept. 21-25
Kansas 3 Eastern Kansas suburbs Sept. 20-23
California 45 Southern California Sept. 21-25
New Jersey 3 South, central New Jersey Sept. 22-26
Nebraska 2 Omaha area Sept. 23-26
Washington 8 Seattle suburbs and beyond Sept. 24-26
Michigan 8 Lansing, Detroit suburbs Sept. 28-Oct. 3
Virginia 2 Coastal Virginia Sept. 26-Oct. 1
Arizona 2 Southeastern Arizona Sept. 26-Oct. 1
Iowa 3 Southwest Iowa Sept. 27-30
Ohio 1 Southwestern Ohio Sept. 27-Oct. 1
Minnesota 2 Minneapolis suburbs, southern Minn. Sept. 29-Oct. 2
Michigan 11 Detroit suburbs Oct. 1-6
Illinois 14 Chicago exurbs Oct. 3-8
North Carolina 9 Charlotte suburbs, southern N.C. Oct. 1-5
New York 1 Eastern Long Island Oct. 4-8
Texas 31 Central Texas, Round Rock Oct. 1-5
North Carolina 13 Piedmont Triad Oct. 3-8
Pennsylvania 16 Northwestern Pa. Oct. 5-8
Texas Senate The Lone Star State Oct. 8-11
Tennessee Senate The Volunteer State Oct. 8-11
Nevada Senate The Silver State Oct. 8-10
Pennsylvania 1 Delaware Valley Oct. 11-14
Arizona 6 Northeastern Phoenix suburbs Oct. 11-15
Minnesota 8 Iron Range Oct. 11-14
Virginia 10 Northern Virginia Oct. 11-15
Colorado 6 Denver Suburbs Oct. 13-17
Washington 3 Southwest Washington Oct. 14-19
Texas 23 South Texas Oct. 13-18
West Virginia 3 Coal Country Oct. 14-18
Kansas 3 Eastern Kansas suburbs Oct. 14-17
Arizona Senate The Grand Canyon State Oct. 15-19
Florida 27 South Florida Oct. 15-19
Maine 2 Upstate, Down East Maine Oct. 15-18
New Jersey 11 Northern New Jersey suburbs. Oct. 13-17
Pennsylvania 8 Wyoming Valley Oct. 16-19
Florida 15 Tampa Exurbs Oct. 16-19
Virginia 5 Central, southern Virginia Oct. 16-22
California 39 East of Los Angeles Oct. 18-23
Illinois 12 Downstate Illinois Oct. 18-22
Virginia 2 Coastal Virginia Oct. 18-22
California 49 Southern California Oct. 19-24
Florida 26 South Florida Oct. 19-24
Texas 7 Houston and suburbs Oct. 19-25
Illinois 13 Downstate Illinois Oct. 21-25
New Mexico 2 Southern New Mexico Oct. 19-23
Illinois 6 Chicago suburbs Oct. 20-26
Ohio 1 Southwestern Ohio Oct. 20-24
California 10 Central Valley farm belt Oct. 21-25
New Jersey 3 South, central New Jersey Oct. 21-25
Pennsylvania 10 South, central Pennsylvania Oct. 23-26
New York 11 Staten Island, southern Brooklyn Oct. 23-27
Florida Senate The Sunshine State Oct. 23-27
Florida Governor The Sunshine State Oct. 23-27
Utah 4 South of Salt Lake City Oct. 24-26
New York 27 Western New York Oct. 24-29
Iowa 3 Southwest Iowa Oct. 25-27
California 25 Southern California Oct. 25-28
California 45 Southern California Oct. 26-Nov. 1
Pennsylvania 1 Delaware Valley Oct. 26-29
North Carolina 9 Charlotte suburbs, southern N.C. Oct. 26-30
Kansas 2 Eastern Kansas Oct. 27-30
New Jersey 7 Suburban New Jersey Oct. 28-31
Georgia 6 Northern Atlanta suburbs Oct. 28-Nov. 4
Iowa 1 Northeastern Iowa Oct. 28-31
Texas 32 Suburban Dallas Oct. 29-Nov. 4
California 48 Orange County Oct. 29-Nov. 4
Virginia 7 Richmond suburbs Oct. 30-Nov. 4
Illinois 14 Chicago exurbs Oct. 31-Nov. 4
Washington 8 Seattle suburbs and beyond Oct. 30-Nov. 4
Iowa 4 Northwestern Iowa Oct. 31-Nov. 4
Michigan 8 Lansing, Detroit suburbs Oct. 31-Nov. 4
Kentucky 6 Lexington area Nov. 1-4
New York 19 Catskills, Hudson Valley Nov. 1-4
New York 22 Central New York Nov. 1-4

About this poll

  • Most responses shown here are delayed about 30 minutes. Some are delayed longer for technical reasons.
  • The design effect of this poll is 1.37. That’s a measure of how much weighting we are doing to make our respondents resemble all voters.
  • Read more about the methodology for this poll.
  • Download the microdata behind this poll.

This survey was conducted by The New York Times Upshot and Siena College.

Siena College Research Institute logo

Data collection by Reconnaissance Market Research, M. Davis and Company, the Institute for Policy and Opinion Research at Roanoke College, the Survey Research Center at the University of Waterloo, the University of North Florida and the Siena College Research Institute.