When Trump first took office, his net approval rating in Louisiana was a whopping 31 percent, 59 to 28 percent approval. Today, based upon the December net approval poll numbers, that positive differential has sunk to 54% to 41% or 13 net approval.
This is a margin of 18% drop since January 2017 which is one of the highest drops nationally.
Yet, Louisiana is still one of the top Trump states. West Virginia gives him a 36% net approval while Wyoming competes with 32%.
As expected Trump scores poorly in New England with a high net disapproval of 39% in Vermont. Also, as expected, he is doing poorly in the far west with a California -29%, Oregon -22% and Washington -23% net disapproval.
Possibly one of the more startling statistics comes out of Texas. When he first took office, his net approval was 21% which has now dropped to 4%, a 17% fall. In Florida, he was approved by 22% of the voters in 2017 whereas now, Trump has dropped into the negative, sporting a -3% number, a drop of a whopping 25%. Another key state, Illinois, gives him a drop of 17%, going from 14 to a -3%. Pennsylvania, a state that he won in 2016 scores him now at a -6 % percent while in January 2017, the incoming president rating was a positive 10%.
The 13% approval in Louisiana is still a glowing endorsement at this moment. It will be interesting to see how much sway he will have November 2019 when the candidates for Governor, legislators and other governmental seats are at issue.
Also, the Morning Consult polled only registered voters, not likely voters, a population that normally helps conservatives and Republicans since likely voters are generally older.
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Below are representations made by Morning Consult that explain the polling process and results:
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 2012 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 100 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 5 percentage points in the smaller population size of Alaska