Every four years there is a great deal of money spent on trying to predict who will win the U.S. Presidential election. Pundits examine the various segments of the population carefully and determine the issues that are most important for each group, who best addresses those issues (for the groups) and what the likelihood of that group voting will be. There are millions of dollars spent to predict who is likely to win the election. As the viewing public knows, there are many flaws to these preditions.
Allan J. Lichtman, professor of history at The American University in Washington, D.C. looks at the situation in a different way. He applied statistical pattern recognition algorithm from seismology to the question of who would be elected. Professor Lichtman began with nearly 200 questions, which were all binary ("yes" or "no") variables, and the algorithm picked those which displayed the greatest difference between the proportion of the time the variable was "yes" for years when the incumbent party won and the corresponding proportion for years when the challenging party won, using all U. S. elections starting with 1860 as the training set. Over time, he narrowed it to 13 keys. They are:
1. The incumbent party holds more seats in the U.S. House of Representatives after the midterm election than after the preceding midterm election.
2. There is no serious contest for the incumbent-party nomination.
3. The incumbent-party candidate is the current president.
4. There is no significant third-party or independent candidacy.
5. The economy is not in recession during the campaign.
6. Real (constant-dollar) per capita economic growth during the term equals or exceeds mean growth for the preceding two terms.
7. The administration has effected major policy changes during the term.
8. There has been no major social unrest during the term.
9. The incumbent administration is untainted by major scandal.
10. There has been no major military or foreign-policy failure during the term.
11. There has been a major military or foreign-policy success during the term.
12. The incumbent is charismatic or is a national hero.
13. The challenger is not charismatic and is not a national hero.
According to Dr. Lichtman’s models, if six or more of these statements are false, the incumbent party loses the popular vote. Using that criterion, the model has only been wrong twice, in 1876 and 1888. Of course, in the United States, it is the electoral vote, not the popular vote that determines the winner, so sometimes this method does not predict who will actually be in the White House.