2016 Presidential Elections Forecast Update August 2015: Time-Tested Model Says Democrats Will Win
Based on a prediction model used by Moody's Analytics, it will be another win for the Democrats in the 2016 U.S. Presidential Election. Moody's Analytics, a subsidiary of Moody's Corporation, recently came out with its forecast for the elections.
The prediction model is only able to predict which party will take the White House, and not the nominee who will be seated as the next President. The report said that this model has been used by Moody's to predict election outcomes and it has been able to make accurate predictions since it predicted Ronald Reagan's win in 1980.
The next President will reportedly be a Democrat and it will be a tight race. The model is said to be able to predict the results of the Electoral College, indicating which party will win in every state, so individual nominees are not part of the equation.
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The Democratic nominee is expected to get 270 electoral votes, which is not a majority win as it is only the required minimum number of votes needed. The Republican nominee is said to be getting a close 268 votes.
In the 2012 election, the model reportedly predicted each state correctly and previous to this, had a 90 percent success rate for each state since the 1980 elections.
Moody's Analytics' model is a model that is based on economics, according to a report in CNN Money. It looks at the state of the economy in every state, particularly focusing on three variables that have the "best" predictors, namely family or household income, home values and gas prices. According to Moody's, if these three variables are going up, this is favorable for the party in power. Otherwise, it means people want to see some change.
"The economy's performance strongly favors the Democratic nominee for president," said Moody's.
Household incomes are seen to be continually rising and may continue to do so until Election Day.
"The only missing ingredient is stronger wage growth, which is expected to pick up in the coming months as the job market approaches full employment," they continued.
