5.2 Using markov random fields for election prediction

Introduction

The importance of predicting the United States Presidential Election cannot be understated because of the impact the U.S. president has on national policy. The U.S. President holds the veto power, which can make it very difficult for the Congress to pass legislation without his approval. In addition, the president appoints all federal judges, most notably the justices of the Supreme Court. While all nominees must be confirmed by the Senate, the confirmation process is usually a rubber stamp and few nominees are turned down, with some notable exceptions (such as Ronald Reagan's failed appointment of Robert Bork). Also, the U.S. President is the Commander in Chief of the U.S. military and can go to war unilaterally and then ask for Congressional approval 48 hours later under the War Powers Resolution of 1973. Lastly, presidents use the executive order to carry out their wishes, perhaps outside the constraints of the Constitution, to choose which laws they want to enforce. For example, President Obama does not enforce neither Defense of Marriage Act nor the deportation of illegal immigrants under the age of 30, Harry Truman ended racial segregation of the military, and Jimmy Carter created the Federal Emergency Management Agency (FEMA). Clearly the U.S. president has enormous power in the U.S. and abroad. Therefore, a company or an individual making decisions that demand foresight about the political state of the country would benefit knowing who the next president is.

Despite the large demand for predicting elections, most existing methods are either unscientific or unreliable. Unscientific judgements include evaluations of a candidate's character or analysis of a candidate's rhetoric. It is not wrong to say that one candidate will win over another because he has more charisma or more appeal to the party base. Such statements are meaningful because political intangibles like charisma and appeal to the base are vital aspects for any politician. The problem is that such intangibles lack some sort of reliable measuring stick, something that can be viewed objectively rather than through the lens of political opinion, in which people may view candidates as they want to see them rather than as they really are.

The most common answer to the measuring stick problem is using public opinion polls. However, public opinion polls are unreliable. Polls are no doubt useful for a first approximation to predicting an election, but they contain many pitfalls for the election forecaster. For example, national polls may not be able to predict who will win the electoral college. The electoral college evolved to limit direct democracy, and an important consequence of the electoral college is that a president can win a presidential election without winning the popular vote. Four U.S. presidents have done so: John Quincy Adams in 1824, Rutherford B. Hayes in 1876, Benjamin Harrison in 1888, and most recently George W. Bush in 2000 [link] . Furthermore, national polls include voters from states of no consequence in that they are solidly Republican or Democratic states (i.e. Democratic voters from Texas or Republican voters from Massachusetts or New York). For these reasons, state level polls are more accurate.