Look to Wall Street to find out who our next president will be
By Jonathon M. Trugman
The New York Post
The New York Post
April 11, 2016
Next week is primary week in the capital of the world, New York.
All of the candidates are here, but they are staying far away from Wall Street because none dares to acknowledge the economic models that have an almost perfect record predicting presidential political outcomes.
Today, most of Wall Street’s predictive models call for a GOP victory in November, based on the anemic gross domestic product growth.
Interestingly, the primary modalities of predictive analysis are each done differently, but the major ones all do have at least one common thread: economic growth.
Ray Fair, economics professor at Yale and author of “Predicting Presidential Elections and Other Things,” has one of the leading economic models predicting elections, and has been doing it the longest — since 1978.
The model he uses has the enviable record of correctly forecasting all but three presidential races since 1916. One instance when it was incorrect was in 2012, when Barack Obama beat Mitt Romney.
Fair’s model relies on three primary points of analysis: the per capita growth rate of gross domestic product in the three quarters before an election, inflation over the entire presidential term, and the number of quarters during the presidential term in which growth per capita exceeded 3.2 percent.
Moody’s has the Dems in the lead in the fall. But it seems to be an outlier with obviously flawed reason, in my opinion.
The Moody’s report — which came out last week from economist Dan White — for the first time ever weighs the sitting president’s approval rating, even though neither he nor his veep are up for election.
Strangely, the economists over at Moody’s — whose model hasn’t missed an election since it was created in 1980 — chose to tinker with success by adding a volatile variable that sometimes can be personality-driven and completely devoid of economics.
But, hey, Moody’s will get its report card come November.
Next week is primary week in the capital of the world, New York.
All of the candidates are here, but they are staying far away from Wall Street because none dares to acknowledge the economic models that have an almost perfect record predicting presidential political outcomes.
Today, most of Wall Street’s predictive models call for a GOP victory in November, based on the anemic gross domestic product growth.
Interestingly, the primary modalities of predictive analysis are each done differently, but the major ones all do have at least one common thread: economic growth.
Ray Fair, economics professor at Yale and author of “Predicting Presidential Elections and Other Things,” has one of the leading economic models predicting elections, and has been doing it the longest — since 1978.
The model he uses has the enviable record of correctly forecasting all but three presidential races since 1916. One instance when it was incorrect was in 2012, when Barack Obama beat Mitt Romney.
Fair’s model relies on three primary points of analysis: the per capita growth rate of gross domestic product in the three quarters before an election, inflation over the entire presidential term, and the number of quarters during the presidential term in which growth per capita exceeded 3.2 percent.
Moody’s has the Dems in the lead in the fall. But it seems to be an outlier with obviously flawed reason, in my opinion.
The Moody’s report — which came out last week from economist Dan White — for the first time ever weighs the sitting president’s approval rating, even though neither he nor his veep are up for election.
Strangely, the economists over at Moody’s — whose model hasn’t missed an election since it was created in 1980 — chose to tinker with success by adding a volatile variable that sometimes can be personality-driven and completely devoid of economics.
But, hey, Moody’s will get its report card come November.
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