A thorough examination of the impact of campaign politics on presidential elections in the United States is presented in this book. Using actual election results and empirical evidence, the author also incorporates data on additional factors such as media coverage, the impact of nominating conventions on public opinion, presidential debates, and other events such as staff shake-ups, endorsements and scandals. In so doing, Holbrook develops a model for testing campaigns and proves how campaigns play a key role in shaping public opinion and, ultimately, influencing outcomes.
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By G.X. Larson
Format:Paperback
If you know anything about serious election forecasting (not the type done by pundits on television) then you know that they are easily predicted. In fact, anyone with access to Microsoft Excel can create their own reasonably good regression model based on as little as four variables. You could even generate a regression model with pencil and paper (and patience) using only (matrix) arithmetic. Economist Ray Fair (author of Predicting Presidential Elections and Other Things) has a well-known model that predicts the proportion of the two-party vote that the incumbent party will receive in an election based on three variables: 1) growth rate of real per capita GDP in the first 3 quarters of an election year; 2) growth rate of the GDP deflator; 3) number of quarters in the first 15 quarters of the incumbent party's term in which the growth rate of real per capita GDP is greater than 3.2 percent at an annual rate. Clearly Fair's hypothesis is that economic conditions shape election outcomes; or, "it's the economy, stupid". It goes without saying that his model can accurately predict the winner of an election even before the candidates have been selected. Other models may incorporate party strength, perceived economic conditions (subjective metrics of the economy, such as consumer sentiment, rather than objective measures used by Fair), party tenure (duration that an incumbent party has held the presidency), and actual measures of candidate popularity such as trial-heat poll data. Many models accurately predict the winner months in advance, which leads us to the question: if American presidential elections are so predictable, do campaigns matter?
The answer is yes and no. First, it is important to understand Holbrook's notion of equilibrium. Holbrook first uses a linear model to predict the winner of a presidential election based on data from no later than the month of May. His regression uses three variables: popularity (basically a preview of the November election), aggregate personal finances, and party tenure. This model is generally very accurate, accounting for roughly 84 percent of the data set's variability. The proportion of total vote a candidate receives as predicted by the model is that candidate's equilibrium. Since Holbrook's vote share regression is so indicative of the actual election outcome (and it is important to remember that it is based on data from no later than May of each election year) it is fairly obvious that there is actually something like "equilibrium" at play in nature.
The rest of the book investigates two key campaign events: the party convention and the debates. Holbrook's finding is that if a candidate's popularity is significantly greater than his estimated equilibrium, then that candidate will not receive a significant "bump" in the polls. However, if a candidate's popularity is significantly lower than her estimated equilibrium, then she will likely receive a significant bump in the polls. However, these bumps tend to smooth out as we step backward and look at the bigger picture: as Holbrook concludes, "although campaigns do matter and are relevant determinants of candidate support, national conditions carry more weight in determining the eventual outcome." However, if the estimated equilibrium indicates that each candidate (supposing a two party race) should expect roughly 50 percent of the electorate's support, then campaigns can make a huge difference if done right.
The answer is yes and no. First, it is important to understand Holbrook's notion of equilibrium. Holbrook first uses a linear model to predict the winner of a presidential election based on data from no later than the month of May. His regression uses three variables: popularity (basically a preview of the November election), aggregate personal finances, and party tenure. This model is generally very accurate, accounting for roughly 84 percent of the data set's variability. The proportion of total vote a candidate receives as predicted by the model is that candidate's equilibrium. Since Holbrook's vote share regression is so indicative of the actual election outcome (and it is important to remember that it is based on data from no later than May of each election year) it is fairly obvious that there is actually something like "equilibrium" at play in nature.
The rest of the book investigates two key campaign events: the party convention and the debates. Holbrook's finding is that if a candidate's popularity is significantly greater than his estimated equilibrium, then that candidate will not receive a significant "bump" in the polls. However, if a candidate's popularity is significantly lower than her estimated equilibrium, then she will likely receive a significant bump in the polls. However, these bumps tend to smooth out as we step backward and look at the bigger picture: as Holbrook concludes, "although campaigns do matter and are relevant determinants of candidate support, national conditions carry more weight in determining the eventual outcome." However, if the estimated equilibrium indicates that each candidate (supposing a two party race) should expect roughly 50 percent of the electorate's support, then campaigns can make a huge difference if done right.
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