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Some published conclusionspublished conclusions from a 2016 paper signed off by dozen [or so] researchers/pollsters [of course, alway too late to get much votes here]:

There are a number of reasons as to why polls under-estimated support for Trump. The explanations for which we found the most evidence are:

  • Real change in vote preference during the final week or so of the campaign. [...]
  • Adjusting for over-representation of college graduates was critical, but many polls did not do it. [...]

  • Some Trump voters who participated in pre-election polls did not reveal themselves as Trump voters until after the election, and they outnumbered late-revealing Clinton voters. This finding could be attributable to either late deciding or misreporting (the socalled Shy Trump effect) in the pre-election polls. A number of other tests for the Shy Trump theory yielded no evidence to support it.

Less compelling evidence points to other factors that may have contributed to under-estimating Trump’s support:

  • Change in turnout between 2012 and 2016 is also a likely culprit, but the best data sources for examining that have not yet been released. [...]
  • Ballot order effects may have played a role in some state contests, but they do not go far in explaining the polling errors. [...]

There is no consistent partisan favoritism in recent U.S. polling. In 2016 national and statelevel polls tended to under-estimate support for Trump, the Republican nominee. In 2000 and 2012, however, general election polls clearly tended to under-estimate support for the Democratic presidential candidates. The trend lines for both national polls and state-level polls show that – for any given election – whether the polls tend to miss in the Republican direction or the Democratic direction is tantamount to a coin flip.

[...]

A proposal for addressing the performance of state-level polling. As this report documents, the national polls in 2016 were quite accurate, while polls in key battleground states showed some large, problematic errors. It is a persistent frustration within polling and the larger survey research community that the profession is judged based on how these often under-budgeted state polls perform relative to the election outcome. The industry cannot realistically change how it is judged, but it can make an improvement to the polling landscape, at least in theory. AAPOR does not have the resources to finance a series of high quality state-level polls in presidential elections, but it might consider attempting to organize financing for such an effort. Errors in state polls like those observed in 2016 are not uncommon. With shrinking budgets at news outlets to finance polling, there is no reason to believe that this problem is going to fix itself. Collectively, well-resourced survey organizations might have enough common interest in financing some high quality state-level polls so as to reduce the likelihood of another black eye for the profession.

Some published conclusions from a 2016 paper signed off by dozen [or so] researchers/pollsters [of course, alway too late to get much votes here]:

There are a number of reasons as to why polls under-estimated support for Trump. The explanations for which we found the most evidence are:

  • Real change in vote preference during the final week or so of the campaign. [...]
  • Adjusting for over-representation of college graduates was critical, but many polls did not do it. [...]

  • Some Trump voters who participated in pre-election polls did not reveal themselves as Trump voters until after the election, and they outnumbered late-revealing Clinton voters. This finding could be attributable to either late deciding or misreporting (the socalled Shy Trump effect) in the pre-election polls. A number of other tests for the Shy Trump theory yielded no evidence to support it.

Less compelling evidence points to other factors that may have contributed to under-estimating Trump’s support:

  • Change in turnout between 2012 and 2016 is also a likely culprit, but the best data sources for examining that have not yet been released. [...]
  • Ballot order effects may have played a role in some state contests, but they do not go far in explaining the polling errors. [...]

There is no consistent partisan favoritism in recent U.S. polling. In 2016 national and statelevel polls tended to under-estimate support for Trump, the Republican nominee. In 2000 and 2012, however, general election polls clearly tended to under-estimate support for the Democratic presidential candidates. The trend lines for both national polls and state-level polls show that – for any given election – whether the polls tend to miss in the Republican direction or the Democratic direction is tantamount to a coin flip.

[...]

A proposal for addressing the performance of state-level polling. As this report documents, the national polls in 2016 were quite accurate, while polls in key battleground states showed some large, problematic errors. It is a persistent frustration within polling and the larger survey research community that the profession is judged based on how these often under-budgeted state polls perform relative to the election outcome. The industry cannot realistically change how it is judged, but it can make an improvement to the polling landscape, at least in theory. AAPOR does not have the resources to finance a series of high quality state-level polls in presidential elections, but it might consider attempting to organize financing for such an effort. Errors in state polls like those observed in 2016 are not uncommon. With shrinking budgets at news outlets to finance polling, there is no reason to believe that this problem is going to fix itself. Collectively, well-resourced survey organizations might have enough common interest in financing some high quality state-level polls so as to reduce the likelihood of another black eye for the profession.

Some published conclusions from a 2016 paper signed off by dozen [or so] researchers/pollsters [of course, alway too late to get much votes here]:

There are a number of reasons as to why polls under-estimated support for Trump. The explanations for which we found the most evidence are:

  • Real change in vote preference during the final week or so of the campaign. [...]
  • Adjusting for over-representation of college graduates was critical, but many polls did not do it. [...]

  • Some Trump voters who participated in pre-election polls did not reveal themselves as Trump voters until after the election, and they outnumbered late-revealing Clinton voters. This finding could be attributable to either late deciding or misreporting (the socalled Shy Trump effect) in the pre-election polls. A number of other tests for the Shy Trump theory yielded no evidence to support it.

Less compelling evidence points to other factors that may have contributed to under-estimating Trump’s support:

  • Change in turnout between 2012 and 2016 is also a likely culprit, but the best data sources for examining that have not yet been released. [...]
  • Ballot order effects may have played a role in some state contests, but they do not go far in explaining the polling errors. [...]

There is no consistent partisan favoritism in recent U.S. polling. In 2016 national and statelevel polls tended to under-estimate support for Trump, the Republican nominee. In 2000 and 2012, however, general election polls clearly tended to under-estimate support for the Democratic presidential candidates. The trend lines for both national polls and state-level polls show that – for any given election – whether the polls tend to miss in the Republican direction or the Democratic direction is tantamount to a coin flip.

[...]

A proposal for addressing the performance of state-level polling. As this report documents, the national polls in 2016 were quite accurate, while polls in key battleground states showed some large, problematic errors. It is a persistent frustration within polling and the larger survey research community that the profession is judged based on how these often under-budgeted state polls perform relative to the election outcome. The industry cannot realistically change how it is judged, but it can make an improvement to the polling landscape, at least in theory. AAPOR does not have the resources to finance a series of high quality state-level polls in presidential elections, but it might consider attempting to organize financing for such an effort. Errors in state polls like those observed in 2016 are not uncommon. With shrinking budgets at news outlets to finance polling, there is no reason to believe that this problem is going to fix itself. Collectively, well-resourced survey organizations might have enough common interest in financing some high quality state-level polls so as to reduce the likelihood of another black eye for the profession.

1
source | link

Some published conclusions from a 2016 paper signed off by dozen [or so] researchers/pollsters [of course, alway too late to get much votes here]:

There are a number of reasons as to why polls under-estimated support for Trump. The explanations for which we found the most evidence are:

  • Real change in vote preference during the final week or so of the campaign. [...]
  • Adjusting for over-representation of college graduates was critical, but many polls did not do it. [...]

  • Some Trump voters who participated in pre-election polls did not reveal themselves as Trump voters until after the election, and they outnumbered late-revealing Clinton voters. This finding could be attributable to either late deciding or misreporting (the socalled Shy Trump effect) in the pre-election polls. A number of other tests for the Shy Trump theory yielded no evidence to support it.

Less compelling evidence points to other factors that may have contributed to under-estimating Trump’s support:

  • Change in turnout between 2012 and 2016 is also a likely culprit, but the best data sources for examining that have not yet been released. [...]
  • Ballot order effects may have played a role in some state contests, but they do not go far in explaining the polling errors. [...]

There is no consistent partisan favoritism in recent U.S. polling. In 2016 national and statelevel polls tended to under-estimate support for Trump, the Republican nominee. In 2000 and 2012, however, general election polls clearly tended to under-estimate support for the Democratic presidential candidates. The trend lines for both national polls and state-level polls show that – for any given election – whether the polls tend to miss in the Republican direction or the Democratic direction is tantamount to a coin flip.

[...]

A proposal for addressing the performance of state-level polling. As this report documents, the national polls in 2016 were quite accurate, while polls in key battleground states showed some large, problematic errors. It is a persistent frustration within polling and the larger survey research community that the profession is judged based on how these often under-budgeted state polls perform relative to the election outcome. The industry cannot realistically change how it is judged, but it can make an improvement to the polling landscape, at least in theory. AAPOR does not have the resources to finance a series of high quality state-level polls in presidential elections, but it might consider attempting to organize financing for such an effort. Errors in state polls like those observed in 2016 are not uncommon. With shrinking budgets at news outlets to finance polling, there is no reason to believe that this problem is going to fix itself. Collectively, well-resourced survey organizations might have enough common interest in financing some high quality state-level polls so as to reduce the likelihood of another black eye for the profession.