Midterm Election Poll: California’s 10th District, Denham vs. Harder (original) (raw)
Our poll shows a close race.
But remember: It’s just one poll, and we talked to only 501 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.
Where we called:
Each dot shows one of the 25803 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
- Josh Harder is a former venture capitalist who is now a business instructor at Modesto Junior College. 46% favorable rating; 41% unfavorable; 13% don’t know
Based on 501 interviews - Jeff Denham is the incumbent, elected in 2010. He voted for the Republican tax bill and to repeal the Affordable Care Act. 45% favorable rating; 45% unfavorable; 10% don’t know
Based on 501 interviews - The district, a patchwork of conservative farming communities and liberal-leaning cities east of San Jose, is nearly 45 percent Latino. Democrats have a slight registration edge, but have posted underwhelming results among Latinos in our polling so far.
- With his district greatly affected by immigration policy, Mr. Denham led an unsuccessful effort to pressure the House to vote on legislation to protect the young undocumented immigrants known as Dreamers.
- Mr. Denham, 51, is an Air Force veteran who owns a plastics company and a small almond farm.
- Mr. Harder, 32, is a political newcomer (and a newlywed) who beat a crowded primary field and has been endorsed by Barack Obama. He’s stressing job creation and expansion of health care.
- Mr. Harder says he’s “of the valley, for the valley,” but after attending Stanford and Harvard and working as a technology investor, he may be a bit of a mismatch with the working-class parts of this district.
Other organizations’ ratings:
Previous election results:
| 2016 President | +3 Clinton |
|---|---|
| 2012 President | +4 Obama |
| 2016 House | +3 Rep. |
It’s generally best to look at a single poll in the context of other polls:
| Polls | Dates | Harder | Denham | Margin |
|---|---|---|---|---|
| UC Berkeley n = 726 lv | Sept. 16-23 | 50% | 45% | Harder +5 |
| Garin-Hart-Yang Research Group (D.) 501 lv | June 27-July 1 | 48% | 48% | Even |
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 two points in a poll of 501 people to win about four out of every 13 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.
Assumptions about who is going to vote may be particularly important in this race.
Our poll under different turnout scenarios
| Who will vote? | Est. turnout | Our poll result |
|---|---|---|
| The types of people who voted in 2014 | 150k | Denham +1 |
| People whose voting history suggests they will vote, regardless of what they say | 167k | Harder +3 |
| Our estimate | 168k | Harder +2 |
| People who say they will vote, adjusted for past levels of truthfulness | 183k | Harder +4 |
| People who say they are almost certain to vote, and no one else | 216k | Harder +6 |
| The types of people who voted in 2016 | 230k | Denham +1 |
| Every active registered voter | 334k | Harder +9 |
All estimates based on 501 interviews
In these scenarios, higher turnout tends to be better for Democrats.
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 | Successrate | Ourresponses | Goal | |
|---|---|---|---|---|---|
| 18 to 29 | 2213 | 42 | 1 in 53 | 8% | 11% |
| 30 to 64 | 13808 | 271 | 1 in 51 | 54% | 57% |
| 65 and older | 5383 | 188 | 1 in 29 | 38% | 32% |
| Male | 8478 | 235 | 1 in 36 | 47% | 47% |
| Female | 12934 | 266 | 1 in 49 | 53% | 53% |
| White | 11230 | 306 | 1 in 37 | 61% | 59% |
| Nonwhite | 8883 | 161 | 1 in 55 | 32% | 34% |
| Cell | 14636 | 340 | 1 in 43 | 68% | — |
| Landline | 6776 | 161 | 1 in 42 | 32% | — |
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, race, 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 party registration, like most public polls | Harder +4 |
| Our estimate | Harder +2 |
| Weight using census data instead of voting records, like most public polls | Harder +2 |
| Don’t weight by education, like many polls in 2016 | Harder +1 |
All estimates based on 501 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 8 percent of voters said that they were undecided or refused to tell us whom they would vote for.
Issues and other questions
Do you approve or disapprove of the job Donald Trump is doing as president?
| Approve | Disapp. | Don’t know | |
|---|---|---|---|
| Voters n = 501 | 45% | 49% | 6% |
Would you prefer Republicans to retain control of the House of Representatives or would you prefer Democrats to take control?
| Reps. keep House | Dems. take House | Don’t know | |
|---|---|---|---|
| Voters n = 501 | 47% | 47% | 6% |
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 = 266 / 53% of voters | 54% | 37% | 9% |
| Male 235 / 47% | 40% | 54% | 6% |
Age
| Dem. | Rep. | Und. | |
|---|---|---|---|
| 18 to 29 n = 43 / 10% of voters | 69% | 23% | 8% |
| 30 to 44 98 / 20% | 47% | 46% | 7% |
| 45 to 64 177 / 38% | 42% | 50% | 8% |
| 65 and older 183 / 32% | 46% | 45% | 9% |
Race
| Dem. | Rep. | Und. | |
|---|---|---|---|
| White n = 298 / 58% of voters | 36% | 56% | 8% |
| Black 24 / 5% | 84% | 14% | 2% |
| Hispanic 115 / 24% | 66% | 25% | 9% |
| Asian 18 / 4% | 54% | 40% | 6% |
| Other 27 / 5% | 59% | 32% | 9% |
Race and education
| Dem. | Rep. | Und. | |
|---|---|---|---|
| Nonwhite n = 184 / 39% of voters | 66% | 26% | 8% |
| White, college grad 115 / 16% | 45% | 48% | 7% |
| White, not college grad 183 / 42% | 33% | 60% | 8% |
Education
| Dem. | Rep. | Und. | |
|---|---|---|---|
| H.S. Grad. or Less n = 78 / 30% of voters | 53% | 37% | 10% |
| Some College Educ. 230 / 41% | 42% | 52% | 7% |
| 4-year College Grad. 109 / 18% | 51% | 41% | 8% |
| Post-grad. 79 / 9% | 47% | 47% | 6% |
Party
| Dem. | Rep. | Und. | |
|---|---|---|---|
| Democrat n = 172 / 34% of voters | 89% | 6% | 5% |
| Republican 167 / 34% | 5% | 90% | 5% |
| Independent 139 / 27% | 52% | 37% | 11% |
| Another party 13 / 2% | 26% | 68% | 6% |
Party registration
| Dem. | Rep. | Und. | |
|---|---|---|---|
| Democratic n = 206 / 40% of voters | 80% | 9% | 11% |
| Republican 193 / 39% | 10% | 87% | 3% |
| Other 102 / 20% | 54% | 35% | 11% |
Intention of voting
| Dem. | Rep. | Und. | |
|---|---|---|---|
| Already voted n = 164 / 33% of voters | 48% | 45% | 7% |
| Almost certain 201 / 41% | 47% | 46% | 8% |
| Very likely 111 / 22% | 47% | 46% | 7% |
| Somewhat likely 10 / 2% | 65% | 23% | 13% |
| Not very likely 6 / 1% | 14% | 49% | 37% |
| Not at all likely 4 / 0% | 78% | — | 22% |
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
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 1.25. 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.
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.
By Michael Andre, Larry Buchanan, Matthew Bloch, Jeremy Bowers, Nate Cohn, Alastair Coote, Annie Daniel, Richard Harris, Josh Katz, Rebecca Lieberman, Blacki Migliozzi, Paul Murray, Adam Pearce, Kevin Quealy, Eden Weingart and Isaac White