For years, Morning Consult's approach to political polling has provided insight into the evolving political landscape at a scale and speed unmatched in the industry.
With the growing demand to modernize political data, we are excited to debut our newest data intelligence product, Morning Consult Political Intelligence. Morning Consult Political Intelligence delivers daily polling data on elected officials, critical elections and top issues at national, state and congressional levels by surveying over 5,000 registered voters in the United States. Learn how you can get access to daily political polling data – Learn More.
Use the slider to track how Trump’s net approval has shifted over time.
Select a state to view the trend data.
A breakdown of which demographic groups are more or less likely to approve of Trump. Each of the below groups are sub-demographics among potential GOP primary voters:
This page was last updated on March 3, 2020.
About Morning Consult Political Intelligence
On a daily basis, Morning Consult surveys over 5,000 registered voters across the United States. Along with 2020 presidential election data, Political Intelligence tracks the approval ratings for all governors, senators, House members, the president and more at the national, state and congressional district level.
About the state-level data:
Morning Consult conducted more than 4 million surveys with registered U.S. voters from January 20, 2017, through February 29, 2020, to determine the approval ratings for President Donald Trump in each of the 50 states and Washington, D.C., for each month. These results use a statistical technique called multilevel regression with post-stratification (MRP) to estimate state-level public opinion from the national survey data for a specific month.
In each poll, Americans indicated whether they approve or disapprove of the job performance of Trump. For each question, they could answer strongly approve, somewhat approve, somewhat disapprove, strongly disapprove, or don’t know/no opinion. The surveys also included about 30 demographic questions.
Responses to the Trump approval question are modeled via multilevel regression as a function of both individual-level and state-level variables. Our models use age, gender, education and race as individual-level predictor variables. For our state-level variables, we chose variables that may influence state-level vote choice such as the percent change in state gross domestic product (GDP), state unemployment rates, state median household income and state-level outcomes from the 2016 presidential election.
Morning Consult obtained population parameters for registered voters from the November 2016 Current Population Survey. We applied post-stratification weights at the state level based on gender, age, educational attainment and race using the American Community Survey (ACS).
Standard errors for our estimates for each state were calculated by taking 50 bootstrap samples with replacement from our full national dataset for each hypothetical matchup and then assessing this empirical distribution at the state level. The distribution of these predictions at the state level allows us to construct a predictive interval, which gives us a sense of the spread of MRP estimates. The 95 percent predictive intervals range from 1 percentage point in larger states such as California, Florida, New York, Pennsylvania and Texas, to 4 points in states with sparser populations such as Alaska.
The margin of error in each state for the last month is available here.
About the demographic approval data:
The “Trump’s Approval With GOP Primary Voters” section has a different methodology than the above sections. This section is reported based on 61,609 interviews with registered voters who indicated they may vote in the Republican primary or caucus in their state. The interviews were collected from Feb. 1-29, 2020, and have a margin of error of plus or minus 1 point. Each demographic group listed is based on at least 3,031 interviews over that same time frame. The margin of error for each group is either plus or minus 1 or 2 points.