Exercise 5. Personal Financial Situation and the Presidential Vote

Step A. Create and interpret Table 5A

Individuals’ perceptions about the state of the economy and their assessments of their personal financial situation can be important influences on voting behavior. In 2020, the COVID-19 pandemic affected the U.S. economy nationally. Unemployment rates increased significantly across the country. Many businesses closed. With the nation in an economic recession, many Americans experienced personal financial difficulties. In past elections, those who have experienced declines in their personal financial situation sometimes assign blame for this to the incumbent presidential administration. For these individuals, a vote for “change” (i.e., a vote for the presidential candidate challenging the incumbent administration) becomes more likely. To test for such a relationship in the 2020 presidential election, start by creating Table 5A, utilizing an individual’s assessment of his or her personal financial situation over the past year (F01) and the variable for the individual’s presidential vote. For the reasons suggested in exercise 1, you should use the recoded version of A02 that you created for that exercise, so that you examine only the major-party vote (i.e., only the Biden and Trump voters).

If you ran Table 5A as suggested, you should have a table with five columns and two rows. Personal financial situation (the independent variable) should be on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) should be on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). In reading your table, take care to interpret the percentages properly, remembering that they are column percentages, not row percentages.

You should attempt to answer these questions to see if you are able to read the table and interpret the data correctly:

  1. What percentage of the voters who felt that their personal financial situation was much better than it was a year ago cast a ballot for Trump? What percentage of the voters who felt that their personal financial situation was much worse than it was a year ago cast a ballot for Trump? How did those in between these two extremes vote? Overall, how strong of a relationship is there between these two variables?
  2. Did most voters feel that their financial situation had improved over the past year? If voter assessments of their financial situation had been slightly more positive, would it have affected the outcome of the election?

Step B. Create and interpret Table 5B

Table 5A shows how personal economic situation was related to the vote, and it appears that those who felt that they were worse off were more likely to vote for Biden. Another perspective would be to look at how the vote was influenced by the voter’s evaluation of the economic performance of the Trump administration. It is likely that those who thought highly of Trump’s performance would be more likely to vote for him. To examine this relationship, create Table 5B, showing how an individual’s assessment of President Trump’s handling of the economy (E02) was related to the individual’s presidential vote (use your recoded version of A02 that has only major-party voters).

If you ran Table 5B as suggested, you should have a table with four columns and two rows. Assessment of Trump?s handling of the economy (the independent variable) should be on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) should be on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). In reading your table, take care to interpret the percentages properly, remembering that they are column percentages, not row percentages.

You should attempt to answer these questions to see if you are able to read the table and interpret the data correctly:

  1. What percentage of the voters who strongly approved of Trump?s handling of the economy cast a ballot for Trump? What percentage of the voters who strongly disapproved of Trump?s handling of the economy cast a ballot for Trump? How did those in between these two extremes vote? Overall, how strong of a relationship is there between these two variables?
  2. Did most voters feel that Trump had done a good job of managing the economy? If voter assessments of the Trump administration had been significantly more positive, would it have affected the outcome of the election?

Step C. Create Table 5C

Tables 5A and 5B raise the question of exactly which feelings about the economy influence presidential voting and how these feelings are related. Do people vote simply based on their personal economic situation (what some analysts call pocketbook voting) or do they rely on their views of how the nation’s economy is being managed? How are these two attitudes related to each other?

We can explore this question by considering the concept of intervening variables. Intervening variables are those that are influenced by the independent variable and in turn affect the dependent variable. They are the linkage through which one variable affects another. In this case, we might consider assessments of Trump’s handling of the economy (E02) as a potential intervening variable between personal economic situation (F01) and the vote. That is, it seems likely that one’s personal financial situation could influence how one evaluated Trump’s economic performance. In comparison, it seems unlikely that how one evaluated Trump’s economic performance would influence one’s perceived financial situation. The likely causal path, if there is one, would run from personal financial situation to evaluation of Trump’s economic management to the presidential vote in 2020.

To examine a potential intervening variable, you should run the original two-variable relationship (personal financial situation and the presidential vote) with the potential intervening variable as a control variable. This will produce a separate sub-table for each category of the intervening variable (Create Table 5C).

For information on how to create a three-variable table using SDA, see Exercise 3 or Exercise 4.

F01 has five categories and E02 has four categories. While this is fine for the two-variable tables that you created, if you use both variables together to predict the vote, the result will be a three-variable table that may be a little too complex to interpret. Also, the resulting three-variable table will have too few respondents in some of the sub-table columns, making the percentages unreliable estimates. To solve these problems, you should recode both variables so that each has fewer categories.

In order simplify the tables and to ensure that you have a sufficient number of respondents in each column of each sub-table, you should recode E02 and F01.

For F01, a logical recoding would be to combine the “much better” and the “better” categories into one group and to combine the “worse” and “much worse” categories. This will produce a new version of the variable with just three categories: those who felt that their financial situation was better than it was a year ago, those who felt that their financial situation was about the same, and those who felt that it was worse.

E02 has four categories: strongly approve, approve, disapprove, and strongly disapprove. A logical recoding would be to dichotomize the variable into those who approved and those who disapproved of Trump?s handling of the economy.

Step D. Interpret Table 5C

If you ran Table 5C as suggested, you should have a table that consists of two sub-tables. Each sub-table should have three columns and two rows. Each sub-table should have a recoded version of personal financial situation (the independent variable) on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). There should be one sub-table for those who approved of Trump’s handing of the economy, and one for those who disapproved. In reading your sub-tables, take care to interpret the percentages properly, remembering that they are column percentages, not row percentages.

You should attempt to answer these questions to see if you are able to read the table and interpret the data correctly:

  1. For those who approved of Trump’s handing of the economy, is there a relationship between how the voter felt about his or her personal financial situation and which presidential candidate the voter cast a ballot for?
  2. For those who disapproved of Trump’s handing of the economy, is there a relationship between how the voter felt about his or her personal financial situation and which presidential candidate the voter cast a ballot for?
  3. How do the relationships within each of the two sub-tables compare to the original relationship that you examined? What interpretation do you have for the difference between the original two-variable relationship and what you find in the three-variable table?

In this three-variable table, there is a moderate relationship between personal economic situation and the vote. In the first sub-table, those who approved of Trump’s handling of the economy and were better off were 9 points more likely to vote for Trump than were those who similarly approved of Trump’s handling of the economy but were worse off. Thus, the original relationship between these two variables does not disappear entirely when we introduce the control variable, but it is much weaker than what we found in the original two-variable relationship. This indicates that we have identified an intervening variable between personal economic situation and presidential vote. However, it also is worth noting one additional result from the table. Among those who did not approve of Trump’s handling of the economy, there are no real differences in voting behavior regardless of whether one reported being better off or worse off financially than a year earlier.

In this example, the relationship between personal financial situation and presidential vote is much weaker after we control for assessment of Trump’s handling of the economy. This tells us that whatever effect that personal financial situation has on the presidential vote is due largely to the effect that one’s personal financial situation has on how the voter assesses the president’s handling of the economy. If the original two-variable relationship had remained just as strong in the three-variable table, then we would conclude that the control variable was not an intervening variable in this relationship and that personal financial situation directly affected the vote. If the original bivariate relationship had completely disappeared in the three-variable table, then we would conclude that all the effect of personal financial situation on the vote was through the assessment of the president’s handling of the economy. In this case, we have something between a completely direct effect and a completely indirect effect through the control variable

Suggested Additional Analysis

Generate a table that shows the relationship between the voter’s personal financial situation and his or her assessment of Trump’s handling of the economy (think about which should be the independent variable and which should be the dependent variable). Does this table help you understand the relationships among the three variables in this exercise?

In exercises 3 and 4, you explored possible confounding variables. As exercise 3 illustrated, if the original relationship between the independent and dependent variable vanishes when the possible confounding variable is controlled for, then you should conclude that the control variable really is a confounding variable and that the original relationship was a spurious one.

In this exercise, you examined a possible intervening variable. Because the original relationship between the independent and dependent variable became much weaker when the possible intervening variable was controlled for, you concluded that the control variable really was an intervening variable that helped to explain the link between the independent and dependent variables.

It is important to understand the difference between the analysis in this exercise compared to the analyses in the previous two exercises. In those exercises, the control variable was a potential confounding variable, one that might produce a spurious association between the independent and dependent variables. In such a situation, if the original relationship disappears when the control is applied, then we would conclude that the original relationship was spurious. In this exercise, we are controlling for a potential intervening variable. If the original relationship disappears, or even greatly weakens, then we would conclude that we have identified a mechanism or path through which the independent variable affects the dependent variable.

If controlling for a variable makes the original relationship disappear or greatly weaken, how do you know whether the control variable is a confounding variable or an intervening variable? The answer is that you must theoretically interpret the results. You must decide whether the control variable is affected by the independent variable (which would make the control variable an intervening variable) or whether it affects the independent variable (which would make it a confounding variable). It is not just a matter of reading the table percentages. It also is a matter of interpreting the results, which requires you to think about how the variables might affect each other.