Some folks you just can't reach: the genetic heritability of presidential approval.
Yet some questions remain unresolved. For instance, some argue that presidents can use rhetorical skill to manipulate public evaluations of presidential performance (Druckman and Holmes 2004; Jacobs and Shapiro 2000). Others are more pessimistic and think that public evaluations of presidential performance are stable and are less susceptible to political manipulation (Brace and Hinckley 1991; MacKuen 1983). Similarly, the individual-level mechanisms that influence how people evaluate the president are not clear. While some argue that prospective evaluations of the economy influence presidential approval (Erikson, MacKuen, and Stimson 2000; MacKuen, Erikson, and Stimson 1992), others think that retrospective evaluations of elites are more influential (Nadeau et al. 1999). From party identification (Fischle 2000; Gronke and Brehm 2002) to policy attitudes (Erikson, MacKuen, and Stimson 2002; Gronke 1999) and gender differences (Clarke et al. 2005; Gilens 1988), new approaches lead incrementally to a more complete understanding of how people evaluate the U.S. president. However, despite the growing literature that demonstrates the genetic heritability of political attitudes, ideologies, and behaviors, we do not know how one's genetic makeup might influence their evaluations of the president.
The behavioral revolution in political science emphasized the influence of social and family environments on the development of political values, beliefs, and attitudes (Campbell et al. 1960; Jennings and Niemi 1968; Jennings, Stoker, and Bowers 2009; Niemi and Jennings 1991), and we now know that much of this is genetically heritable (Alford, Funk, and Hibbing 2005; Hatemi et al. 201 la; Hatemi, Eaves, and McDermott 2012; Hibbing, Smith, and Alford 2013; Settle et al. 2010; Verhulst et al. 2012). Similarly, the study of presidential approval began with models developed using aggregate data, which were clarified once scholars began looking at individual variation (Druckman and Holmes 2004; Krosnick and Kinder 1990; Miller and Krosnick 2000; Mondak 1993). Yet, genetic differences explain significant variation in individual political attitudes. By exploring how genetic differences influence presidential approval evaluations, this article helps clarify previous research and refines our understanding of this concept.
The remainder of this article develops a model that explains both the long-term stability and the short-term fluctuations in presidential approval. Independent of other factors that explain attitude stability--such as party identification--our genes are strongly associated with stable attitude structures that tend not to shift dramatically (Eaves and Eysenck 1974; Hatemi, Eaves, and McDermott 2012; Hatemi, Funk et al. 2009; Martin et al. 1986). Insofar as genes influence individual evaluations of presidential performance, they likely cause stable views. This could be why presidential approval ratings tend to revert back to a baseline level following brief changes due to rally events, elections, and the like (Brace and Hinckley 1991; MacKuen 1983). Yet, our genetic makeup also predisposes us to react to our environment in particular ways (Hatemi 2015; Hibbing, Smith, and Alford 2013). The level of patriotism invoked in response to an attack on the United States is likely the result of genetic predispositions rather than social upbringing. As such, genes may explain short-term fluctuation in presidential approval ratings. Thus, both short-term fluctuations and long-term stability in public evaluations of presidential performance are the result of genetic rather than familial (social) differences.
Fluctuations in presidential approval have captured the attention of scholars since the mid-twentieth century. Initially, the dynamics of presidential approval were examined as an aggregate phenomenon (Kernell 1977; MacKuen 1983; MacKuen, Erikson, and Stimson 1992 Mueller 1973; Ostrom and Simon 1985; Stimson 1976). That is,
Mueller and others were interested in the national conditions that influence public evaluations of presidential performance. These studies noted the importance of national economic conditions, war, and national issues have on public approval of the president. In addition, these early studies identified a pattern that seems consistent in most presidential administrations. Presidential approval tends to peak at the beginning of a president's term in office, gradually declines until it bottoms out near the end of the term, and eventually rises again (though not to its original level) (Mueller 1973; Stimson 1976). These patterns and processes continue to influence presidential approval, though the explanations for them have become more nuanced.
Once attention focused on how individuals evaluate the president, the literature specified mechanisms and individual attributes that explained these initial observations. For instance, Edwards, Mitchell, and Welch (1995) demonstrated that only when national issues are salient do they influence individual evaluations of the president. Thus, it is not the objective importance of the national issues but the relative importance of the issue to an individual that influences presidential approval (Edwards, Mitchell, and Welch 1995). Similarly, Krosnick and Kinder (1990) showed that heightened media coverage of an issue increases the importance of that issue to individual evaluations of the president (Krosnick and Kinder 1990). In addition, Brody (1991) and Lee (1977) identified the mechanisms that caused people to modify their evaluations of the president during times of war. They demonstrated that political elites, the media, and patriotism influence how rally events influence presidential approval (Brody 1991; Lee 1977). Brace and Hinckley (1991) demonstrated that poor economic conditions have a negative influence on presidential approval. MacKuen, Erikson, and Stimson (1996) argued that the news media and economic elites influence public economic expectations, which influences presidential approval. The trend within the presidential approval literature is identification of broad patterns followed by exploration of the mechanisms that lead to the broader pattern.
On the whole, presidential approval seems to consist of one component that fluctuates in response to the everyday political world and another, more stable component (Bouchard and McGue 2003). As early as 1983, MacKuen attended to the rate at which public approval of the president recalibrated in response to political events. For instance, unemployment rates seemed to have a strong short-term influence on presidential approval, but the effect quickly dissipated. Inflation, however, had a smaller short-term impact, but the effect of inflation on presidential approval lasted longer, suggesting that it might have a stronger overall influence on presidential approval (MacKuen 1983). However, MacKuen also noted the importance of psychological motivations on presidential approval. At the time, MacKuen emphasized the president's ability to give people a sense of security by displaying his authority over public affairs (Edelman 1964) or demonstrating competence in public policy (Popkin et al. 1976). Mackuen found substantial evidence that these psychological influences were an "important component" of presidential approval and that they are "rarely altered" (1983, 184).
Thus, psychological motivations can influence both the short-term and long-term fluctuations in presidential approval. Psychological motivations might cause short-term fluctuations in presidential approval by changing the way people interpret the information that they encounter (Gilens 1988; Kriner and Schwartz 2009; Lebo and Cassino 2007; Mondak 1993). In addition, cognitive differences in the ability to process information mediate the relationship between media coverage and presidential approval (Althaus and Kim 2006). People who do not attend to politics are less susceptible to altering their short-term evaluations of the president based on information possessed only by the most politically sophisticated (Zaller 1992). By contrast, individual emotional needs (Edelman 1964) or the need for security might influence long-term evaluations of presidential performance (MacKuen 1983). What we lack is a complete picture of what causes people to attend to politics, impose their emotional needs on to political actors (like the president), or develop a need for security. Psychological and socialization theory has yielded promising avenues of exploration, but the most complete explanation will likely include biological and genetic influences.
Genetic Heritability of Political Attitudes and Behaviors
Until we understand the role that our genes play in evaluations of presidential performance, our models will be incomplete. Other fields of inquiry now incorporate genetic factors into their theoretical models with promising results. For example, scholars once thought that ordinary citizens' political attitudes lacked the stability, consistency, and constraint required to develop political ideology (Converse 1964). Yet, among the strongest, most consistent findings is the genetic heritability of political ideology. Using a classic twin design, Alford, Funk, and Hibbing (2005) estimated that 31% of the variation in political ideology was due to genetic factors. Though the initial findings and method were sharply criticized (Beckwith and Morris 2008; Charney 2008), subsequent research identified particular genetic base pairs related to political ideology and their locations on specific chromosomes (Hatemi, Gillespie et al. 2011) and in some cases specific genes (Settle et al. 2010).
For instance, some argue that variations in the DRD4 gene interacts with environmental conditions to influence political views (Settle et al. 2010). However, the process through which this occurs is diverse. Those with the long form allele (7R) of DRD4 (one of five subsets of dopamine receptors) are more likely to seek out novel experiences. When people with DRD4-7R have many friends, their genetic predispositions for novel experiences influences them to seek out the political views of their associates. In time, the exposure to a wider variety of political views may lead some to adopt liberal political views. By contrast, those with the short form DRD4 and many friends may be less interested in the diversity of political views shared by their social network, or those with DRD4-7R and few friends will not encounter the diversity of views in their social network. In either of these instances, being born with DRD4-7R would not lead to forming liberal political views (Settle et al. 2010). Thus, genetic exploration yielded insights that completely changed the dominant paradigm regarding political ideology (Hatemi, Eaves, and McDermott 2012; Jost 2006).
Our genetic makeup influences both our long-term stable attitudes and the attitudes we form in response to the everyday political environment we encounter. The dominant explanation for the marked family resemblance in political attitudes has been that they result from social learning, the social background, or the social environment (Campbell et al. 1960; Converse 1964; Jennings and Niemi 1968; Jennings, Stoker, and Bowers 2009; Niemi and Jennings 1991). Utilizing longitudinal survey data, Niemi and Jennings (1991) report a strong correlation between the party identification of the respondent's parents and the respondent's own party identification and political ideology decades later. Jennings, Stoker, and Bowers (2009) replicated these findings with the children of the original respondents and found strikingly similar results. Parents with consistent political values tend to pass those on to their children and people show remarkable attitude consistency from the moment they leave home throughout adulthood. The socialization hypothesis argues that both the stability in political attitudes and the correspondence between parent/ child views into adulthood result from familial socialization.
In contrast, recent work suggests that both attitude stability and parent/child attitude correspondence are likely due to shared parent/child genetic material rather than familial socialization. Nearly three decades ago, Martin et al. (1986) argued that attitudes had a strong genetic component and suggested that assortative mating explained the marked familial resemblance in political attitudes. According to this view, people choose reproductive mates who share similar social, political, and religious perspectives. Because these attitudes are genetically heritable, parents pass political and religious views to their offspring primarily through genetic rather than social pathways. Alford et al. (2011) argue that genetic attitudinal similarities influence mate selection. They demonstrate that spouses are more similar to each other attitudinally (particularly among attitudes that are highly heritable) than they are physically, suggesting that attitudinal similarity strongly influences mate selection.
Hatemi et al.'s (2009) analyses of longitudinal data collected on twins throughout childhood and adolescence show that the family social environment influences childhood political attitudes up until early adulthood. However, after children move out of the home (around age 20), the influence of their home environment on political attitudes significantly declines. From this point on, genetic influences account for nearly half of the variation in political ideology. By age 50, the environment in which a respondent is raised does not explain any of the variation in political ideology--it is strictly influenced by personal experiences and genetic components. This suggests that parental transmission of political attitudes occurs via genetic rather than social pathways. The long-term, stable political views people hold from early adulthood throughout their life are genetically transmitted.
In addition, genes influence the way that people respond to their everyday world. Genes exert their influence on political views in the background influencing attitude structures rather than particular attitude items (Hatemi, Eaves, and McDermott 2012, 362). Genes influence broad individual characteristics such as inclination toward ingroup members or aversion to social order that can be adapted to a wide variety of circumstances depending on time, place, and culture. Thus, our genes predispose us to particular responses to our environment. To a greater or lesser degree, people control how they deal with these predispositions; however, the manifestation of genetic heritability in political views, ideologies, or behaviors is a function of the environment and how people respond to their environment.
For example, Hatemi (2015) explored how life events--like losing a job--interact with genes to influence support (opposition) for economic policies. The results suggest that both life events and genes have a strong influence on short-term support (opposition) for economic policies. Generally speaking, losing a job causes a person to be more supportive of expanding unemployment benefits, but genes also account for a substantial proportion of individual differences. Situational triggers influence policy attitudes, while genes influence individual sensitivity to the event. Over the long term, however, life events continue to influence policy positions while genetic influence dampens. Thus, to the extent that genes influence policy support in the long term, it is likely reflected in a person's default position (Hatemi 2015).
The extant research on the genetic heritability of political attitudes suggests that people cannot be persuaded to adopt political views contrary to their core value system. In fact, quite the opposite seems to occur. Genetic differences cause individualized predisposed responses to various stimuli in the political world, and these subconscious, automatic, predisposed response tendencies shape our political views (Hibbing, Smith, and Alford 2013; Lodge and Taber 2013; Porges 2004). Once these predispositions exist, people organize their political world to conform to these dispositions rather than the other way around (Cohen 2003; Gaines et al. 2007; Jost et al. 2003). This assertion does not imply or suggest that people are incapable of resisting political predispositions; rather it suggests that most people follow their predispositions most of the time (Haidt 2012).
Genetic Heritability and Presidential Approval
Presidential performance evaluations comprise two distinct components. The first is expectations of what a president should do, and the second is evaluations of how well the president meets those expectations. Based on the findings presented in the previous section, we should expect genes to have a strong influence on both of these. While some might expect a president to be tough on crime, serve as a moral example for the nation, proactively work for social change, be a visible foreign policy leader, and promote economic growth, others might have exactly the opposite expectations of the president. Regardless, individual views about these issues are more strongly influenced by genes than the social environment (Hatemi and McDermott 2012; Hatemi, Dawes et al. 2011). In addition, our genes influence how we translate our everyday expectations into evaluations of how well the president meets our expectations. Interest in politics, political sophistication, and political ideology--each of which has been shown to influence presidential performance evaluations--is more than 50% genetically heritable. This suggests that, not only are individual responses to political information genetically predisposed, but whether or not people are aware of the political world around them is highly dependent on their genetic makeup.
The portion of presidential approval that is stable, resistant to change, and tends to recalibrate (MacKuen 1983) might have a genetic rather than a familial basis. This is because genes seem to be associated with the stable, less malleable portions of socialized attitudes. As such, genes create a baseline level of political attitudes. While these attitudes may change in response to life events, they are also likely to return to a baseline level, which is influenced by one's genetic makeup. Much of the stability in political attitudes we once attributed to family upbringing is actually genetically heritable, not the result of family socialization. Political sophistication, social trust, interest in politics, voter participation, and racial attitudes all have a strong genetic component and are weakly associated with familial socialization (Hatemi and McDermott 2012). Similarly, we should expect that the portion of presidential approval that is stable, resistant to change, and tends to recalibrate is the result of genetic rather than familial socialization components.
Short-term individual differences in how people evaluate the president are the result of individual responses to events like war (Brody 1991; Lee 1977), economic conditions (Clarke et al. 2005; MacKuen, Erikson, and Stimson 1992), honeymoon periods, and other administration-specific events (Brace and Hinckley 1991). Yet, genetic variation influences how a person responds to a particular event. The mechanisms through which a poorly performing economy influence individual evaluations of the president will vary depending on one's genetic predispositions to (1) care about the economy and (2) evaluate a president using that criterion. In this way, everyday political events can be the dominant explanation for variation in presidential approval evaluations, and genetic factors can be the dominant explanation for individual differences (Hibbing, Smith, and Alford 2013). Genes influence short-term presidential approval evaluations by predisposing individual responses to these events.
Yet, we know that partisanship influences presidential performance evaluations (Kriner and Schwartz 2009). All things being equal, Republicans are more likely to approve of a Republican president and Democrats are more likely to approve of a Democrat. Though it is tempting to include partisanship into the theoretical model, the extant literature does not support its inclusion. Despite preliminary findings to the contrary (Alford, Funk, and Hibbing 2005), thorough examinations of the genetic heritability of partisanship find a very low genetic component and a strong familial socialization component (Hatemi, Alford et al. 2009; Hatemi and McDermott 2012), which is consistent with early conceptualizations of partisanship (Campbell et al. 1960). When contrasted with the strong genetic heritability of political ideology, this presents a bit of a theoretical puzzle. Political ideology and partisanship so often predict similar variation in many of our empirical models that many think of the two as interchangeable. However, for the purposes of this study, the two concepts remain theoretically distinct. To the extent that partisanship influences presidential approval evaluations, its influence will be present in the common or unique environment components of the empirical model, whereas political ideology is more likely to influence the genetic component of the model.
Figure 1 uses a Venn diagram to illustrate the hypothesized sources of variation in presidential approval (Kennedy 1992). The upper-middle circle represents all of the potential variation in presidential approval. The plain white portions of the circle represent variation in presidential approval unexplained by the theoretical model. A substantial proportion of the long-term, stable component of presidential approval is likely due to genetic factors. This is because genes may influence our sensitivity to situational triggers, but genetic influence of political attitudes tends to return to the baseline condition
(Hatemi 2015). In addition, a portion of the variation in presidential approval explained by short-term factors like economic performance and rally effects is genetically heritable. This is because genetic predispositions influence how people react to situational triggers. Much of the variation in presidential approval that is not genetically heritable is likely influenced by partisanship. This is because partisanship has a strong, nongenetic influence on individual evaluations of presidential performance. Thus, while presidential approval itself fluctuates substantially both within and across presidencies, a significant proportion of that variation could result from genetic factors influencing how people respond to their environment. If so, we should expect a substantial portion of presidential approval evaluations to be genetically heritable and a small portion to be influenced by family socialization.
Methods and Results
Heritability studies focus on genes that have different forms. The alternative forms of a particular gene are called alleles, and an individual's combination of alleles is called a genotype. We do not directly observe the genotype; rather we focus on the observed traits, called a phenotype. The theoretical model is examined using the Minnesota Twins Political Survey (MTPS) collected in 2008-2009- The survey was administered to a sample of twins selected from the Minnesota Twin Family Registry (National Science Foundation grant #SES-0721378; John R. Hibbing, Principal Investigator). The Minnesota Twin Family Registry comprises about 8,000 twin pairs born in the state of Minnesota between 1936 and 1955. The registry was compiled between 1983 and 1990. This survey is the first twin study devoted to political phenotypes. Data were mainly collected using a web-based survey instrument. The survey was fielded between July and December of 2008 with some supplementary data collected between July and October of 2009.
The sample is not, nor does it purport to be, a representative sample of the U.S. population. This sample is dissimilar from the general population in several specific, yet desirable ways. First, the sample comprises monozygotic (MZ) and dizygotic (DZ) twins, exclusively (n - 596 matched twin pairs). Second, only same-sex twin pairs were selected in the sampling phase (MZ males = 143 pairs, MZ females =213 pairs, DZ males = 86 pairs, DZ females =154 pairs). Third, the sample comes from a total of 744 families (MZ = 428, DZ = 316). Finally, the sample is age restricted. All of the respondents were between the age of 53 and 61 at the time of the interview. Yet, this sample is ideal for examining the genetic heritability of presidential approval; the next section explains why.
The conventional measurement approach (which dominates political science) seeks to explain variation in the dependent variable by references to another set of independent variables. By contrast, twin studies compare the phenotypes (any observed or measured trait) of twins who share 100% of their genetic material (identical or MZ) to those who, on average, share 50% of their genetic material (fraternal or DZ). This approach emphasizes the concordance between MZ twins relative to that of the DZ twins. If we assume that these different sets of twins share comparable environments, we can estimate the variance that results from shared environments (C) and separate that from the variance due to genetic factors (A) and individual experiences (E). This approach has been used by behavioral geneticists since the early 1920s, and the findings based on these methods have been largely confirmed as statistical tools have become more precise (Bouchard and McGue 2003; Visscher et al. 2012).
The basic quantitative model assumes that any given phenotype (P) is a function of genetic (G) and environmental (E) components. To generate the model estimates, we assume that variance in P is due to three factors: additive genetic factors (A), common environmental factors among twin pairs (C) or all nongenetic influences that twins share, and unique environmental factors or everything nongenetic that makes them different (E). Assuming no interaction between genes and environment, then this reduces to the simple model: P = A + C + E, typically referred to as the ACE model (DeFries and Fulker 1985; Smith and Hatemi 2013). Though we do not directly observe the environmental and genetic effects, we can estimate their effects using the covariance (Evans, Gillespie, and Martin 2002; Neale and Maes 1992).
Thus, while the MTPS sample is a poor approximation of the attitudes of U.S. adults, it is ideal for estimating genetic heritability because it contains a broad sample of both MZ and DZ twins with substantial life experience. As mentioned previously, the MTPS was the first study specifically designed to measure genetic variation in phenotypes that are politically relevant. Among the first questions asked of respondents was the typical presidential approval question. Respondents were asked, "Do you approve or disapprove of the way George W. Bush is handling his job as president?" and were given the options of approve, disapprove, and "strongly" approve and disapprove. The Gallup presidential approval rating for the period of time during data collection is relatively stable with 32% approving of the president's performance in July 2008 and 32% approving in December 2008. The lowest approval rating (25%) was registered in early October 2008. In this sample, 33.5% of respondents either approved (30.11%) or strongly approved (3.42%) of Bush's performance, while 65.7% either disapproved (32.6%) or strongly disapproved (33.1%) of the president's performance. To simplify data analysis, those who said that they either "strongly" or "somewhat" approve were coded as 1 and the rest were coded 0.
The Measurement Model
The data were analyzed using a structural equation model (SEM) for several reasons. First, the SEM framework corrects for missing data using full information maximum likelihood, which produces robust, unbiased estimates without imputing missing data (Enders and Bandalos 2001). Second, regression-based approaches can approximate the results from an SEM when the dependent variable is continuous (DeFries and Fulker 1985; Smith and Hatemi 2013), but a logistic regression approach has not been showed to yield unbiased estimates for dichotomous dependent variables in an ACE model. Finally, the ACE model discussed previously does not yield unbiased estimates when the dependent variable is not continuous, which necessitates the use of a threshold model, explained in the next paragraph.
Liability is a theoretical construct that we measure using the SEM framework. To measure the liability, we assume that the underlying variable (presidential approval) is continuous, but we have measured it in terms of a few ordered categories. The liability is a latent (unmeasured) variable with an arbitrary scale that is customarily assumed to have a standard normal distribution (or z in this case) with a mean of 0 and a standard deviation of 1. The observed ordinal measure (presidential approval) with two categories is related to the underlying continuous variable by means of one threshold. The probability that y is in category c is the area under the standard normal curve bounded by the two thresholds on the z scale, modeled below:
Probability of disapproving of the president is:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Probability of approving of the president:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
When the measured trait is dichotomous, we partition our observations into pairs concordant for the absence of the trait (disapproving of the president), pairs concordant for approving of the president, and discordant pairs in which one twin approves and the other does not (see Table 1). The joint liability is assumed to follow a bivariate normal distribution where both latent variables (Twin 1, Twin 2 approval) have a mean of 0 and a standard deviation of 1, but the correlation between them is variable. The joint probability of a certain response combination is the volume under the bivariate normal distribution surface bounded by the threshold. Thus, the probability that both twins approve of the president is:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Probability of both disapproving of the president is:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
And the probability of one twin approving of the president and the other disapproving is:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
When data on MZ and DZ twin pairs are available, we can estimate a correlation liability for each type of twin. However, we can also go further by fitting a model that explains these MZ and DZ correlations. We can decompose the liability correlation into A, C, and E, as we do for continuous traits with correlations determined by the path model. This allows us to estimate the genetic heritability of the dichotomous liability (Falconer 1965; Rijsdijk and Sham 2002). The first step in estimating the genetic heritability of a dichotomous trait (like presidential approval) is to generate a table displaying trait concordance between MZ and DZ twins. Table 1 displays the twin pair concordances for presidential approval.
Table 1 reports the concordance in presidential approval between MZ and DZ twin pairs. Roughly 55% of the MZ twins that approved of President Bush in the survey had twin pairs that also approved of President Bush. In the DZ group, 52.8% of twins approving had twin pairs that also approved. The disapproval concordance seems to be much higher among MZ twins (75.9%) than among DZ twins (60.7%). On the whole, there appears to be greater concordance between MZ twin pairs than DZ pairs. Combining the percentages of (rows 1 and 2 of Table 1) shows 69% concordance in the approval ratings for MZ twin pairs compared to 55.8% concordance between the DZ twin pairs. This suggests that presidential approval may be genetically heritable, but it is possible that the concordance is due to twins sharing a common environment rather than genes. Next, we use this liability correlation information to estimate the amount of variation in presidential approval that is explained by common genetic material compared to environmental influences (see Table 2).
The results of the threshold ACE model suggest that 62% (P < 0.00) of the variance in presidential approval can be accounted for by genetic effects. The 99% confidence interval for the estimate is (37.2%, 87.2%), which indicates that we can reject the null hypothesis that genes do not contribute to variation in presidential approval. Moreover, the estimated size of the genetic effect is quite large relative to other political attitudes known to be genetically heritable. For example, the most genetically heritable political items are political knowledge ([h.sup.2] = 0.59) and political ideology ([h.sup.2] = 0.58), while the least genetically heritable political attitudes are party identification ([h.sup.2] = 0.04) and sense of civic duty ([h.sup.2] = 0.12). This suggests that presidential approval is more strongly influenced by one's genetic makeup than any other political attitude that has been measured to date.
In addition, the results from the threshold ACE model are consistent with broader genetic heritability estimates of political traits. When twins display a high degree of concordance on political traits, the commonality is usually the result of a combination of genetic similarities (A) and unique environmental influences (E); shared family environment (C) usually does not play a substantial role. The only significant deviation from this pattern is party identification, which is largely explained by the family environment (Hatemi and McDermott 2012). Yet, shared family experiences do not account for any of the variation in presidential approval, while unique personal experiences with the environment account for 37.8% (P < 0.00) of the variation in presidential approval. This suggests that evaluations of presidential performance primarily result from genetic and nonfamilial environmental effects.
This pattern of findings is consistent with the theoretical model presented in this article. Genes have a profound, strong, significant influence on individual evaluations of how well the president is handling his job. This does not suggest that presidential approval ratings are immovable, rigid, or not susceptible to change quickly in response to particular conditions. However, it does suggest that people are hardwired to interpret events in a particular manner, and the president may have less influence over how events are interpreted. In addition, these findings do not imply that the extant literature on presidential approval needs to be substantially revised. Genes likely influence the way that people respond to rally events (Brody 1991; Lee 1977) and the economy (Clarke et al. 2005; Clarke and Stewart 1994; MacKuen, Erikson, and Stimson 1992), which explains short-term variation in presidential approval. At the same time, genes influence long-term political dispositions like political ideology, political sophistication, and trust in authority, all of which might account for the human tendency to revert back to a baseline level of presidential approval (MacKuen 1983; Stimson 1976).
The influence of partisanship on presidential performance evaluations is likely limited to the 37.8% of the variation attributed to the unique personal environment. Party identification is more the result of family socialization than genetic heritability. Thus, people may be genetically predisposed through their political ideology to particular expectations of the president and to certain evaluations of presidential performance. However, partisanship can significantly strengthen, or alter, these evaluations. People might be predisposed to higher levels of political interest, which would cause them to have a more informed evaluation of presidential performance, but the strength of their partisan identification might bias the way that the individuals interpret political information. Thus, presidential performance evaluations have a substantial genetic component but are altered by individually unique, nongenetic components.
Political science is in the midst of a biological revolution. For decades we assumed that political attitudes and traits were the product of socialization and family environment, and we now know that much of this is genetically heritable. In part because we know so little about the mechanisms through which genes influence political attitudes, socialization models seem more intuitive. We simply have more experience in our social world, which makes models that imply that family upbringing influences political values, attitudes, and behaviors more sensible to us. Evidence that a political trait is genetically heritable simply means that an individual's biological features influence how that person will respond to the environment they encounter. As such, we expect a variety of biologically predictable individual differences in how people interpret, respond to, and value information. As the tools to estimate the influence of biological components on political attitudes become more precise, we should embrace the opportunity to identify the mechanisms through which biology influences politics
Family socialization has little to no influence on individual variation of presidential approval. If you and your sibling tend to agree about the president's current performance, this is more likely the result of your genetic similarity than it is a consequence of how you were raised. Genes are substantially more influential on individual evaluations of presidential performance than the particular political environment of the time; roughly 62% of the variation in presidential approval is genetically heritable. One reason that presidential approval is subject to short-term fluctuation, but tends to recalibrate back to the previous level, is that genes influence the development of stable political attitudes.
Yet, genes also influence how people respond to short-term political, economic, and social events. Genetic predispositions toward patriotism would lead some to respond favorably toward the executive during war periods, explaining rally effects. Others might be predisposed to ignore such events, which would lead them to maintain their baseline evaluations of the president. Similarly, those genetically predisposed to political conservatism will evaluate a president differently than someone predisposed toward politically liberal views. Our genetic makeup influences both how we perceive and interpret presidential behavior in the short term and our stable long-term attitudes about presidential performance. Thus, genetic heritability plausibly explains why rally events, honeymoon periods, and the economy influence short-term evaluations of presidential performance and why some presidential evaluations are impervious to change.
The sample used in these analyses is not representative of the U.S. population, and the measure of presidential approval represents a snapshot in time. This limits the present study's capacity to measure change in presidential approval. Though the results are consistent with the theoretical model, the data do not measure how respondents' evaluations of the president actually change in response to events. Another reason for caution is that the analyses presented here are based on twin data. In some cases, traits once thought to be highly heritable based on twin analyses have been shown to be much less genetically heritable using more advanced measurement techniques (Visscher et al. 2006, 2012). Yet, we should also be optimistic. Recent findings in behavioral genetics tend to confirm that which has been found in earlier twin studies that use the same methods as this article. Particularly when twin studies find high heritability levels, we can be confident that subsequent analyses will confirm the original findings while adding greater specificity (Rietveld et al. 2013; van Dongen et al. 2012).
This implies that subsequent research into the biological and genetic foundations of individual evaluations of the president will be productive. While subsequent estimates of the genetic heritability of presidential approval may decline, the strength of the estimated heritability reported in this article suggests that presidential approval is highly dependent on one's genetic makeup. As such, future work should find ways to include measures of presidential approval into existing twin registries to replicate the findings presented here. In addition, we should find ways to take advantage of the existing subject pools utilized by developmental psychologists, sociologists, and medical research facilities to identify the particular genes associated with presidential approval. Once we identify the genomes associated with presidential approval, we can begin to explain the precise mechanisms that cause human genes to influence individual evaluations of presidential performance.
Alford, John R., Carolyn L. Funk, and John R. Hibbing. 2005. "Are Political Orientations Genetically Transmitted?" American Political Science Review 99 (2): 153-67.
Alford, John R., Peter K. Hatemi, John R. Hibbing, Nicholas G. Martin, and Lindon J. Eaves. 2011. "The Politics of Mate Choice." The Journal of Politics 73 (2): 362-79.
Althaus, Scott L., and Young Mie Kim. 2006. "Priming Effects In Complex Information Environments: Reassessing The Impact of News Discourse on Presidential Approval." The Journal of Politics 68 (4): 960-76.
Beckwith, Jon, and Corey A. Morris. 2008. "Twin Studies of Political Behavior: Untenable Assumptions?" Perspectives on Politics 6 (4): 785-91.
Bouchard, Thomas J., and Matt McGue. 2003. "Genetic and Environmental Influences on Human Psychological Differences." Journal of Neurobiology 54 (1): 4-45.
Brace, Paul, and Barbara Hinckley. 1991. "The Structure of Presidential Approval: Constraints within and across Presidencies." The Journal of Politics 53 (4): 993-1017.
Brody, Richard A. 1991. Assessing the President: The Media, Elite Opinion, and Public Support. Stanford, CA: Stanford University Press.
Campbell, Angus, Philip E. Converse, Warren E. Miller, and Donald E. Stokes. 1960. The American Voter. New York: Wiley.
Canes-Wrone, Brandice. 2006. Who Leads Whom?: Presidents, Policy, and the Public. Chicago: University of Chicago Press.
Canes-Wrone, Brandice, and Scott de Marchi. 2002. "Presidential Approval and Legislative Success." The Journal of Politics 64 (2): 491-509.
Charney, Evan. 2008. "Genes and Ideologies." Perspectives on Politics 6 (2): 299-319.
Clarke, Harold D., and Marianne C. Stewart. 1994. "Prospections, Retrospections, and Rationality: The Bankers Model of Presidential Approval Reconsidered." American Journal of Political Science 38 (4): 1104-23.
Clarke, Harold D., Marianne C. Stewart, Mike Ault, and Euel Elliott. 2005. "Men, Women and the Dynamics of Presidential Approval." British Journal of Political Science 35 (1): 31-51.
Cohen, Geoffrey L. 2003. "Party Over Policy: The Dominating Impact of Group Influence on Political Beliefs." Journal of Personality and Social Psychology 85 (5): 808-22.
Converse, Phillip E. 1964. "The Nature of Belief Systems in Mass Publics." In Ideology and Discontent, ed. D. Apter. New York: Free Press of Glencoe, 206-61.
DeFries, John C., and David W. Fulker. 1985. "Multiple Regression Analysis of Twin Data." Behavior Genetics 15 (5): 467-73.
Druckman, James N., and Justin W. Holmes. 2004. "Does Presidential Rhetoric Matter? Priming and Presidential Approval." Presidential Studies Quarterly 34 (4): 755-78.
Eaves, Lindon J., and Hans J. Eysenck. 1974. "Genetics and the Development of Social Attitudes." Nature 249 (5454): 288-89.
Edelman, Murray J. 1964. The Symbolic Uses of Politics. Urbana: University of Illinois Press.
Edwards, George C., III, William Mitchell, and Reed Welch. 1995. "Explaining Presidential Approval: The Significance of Issue Salience." American Journal of Political Science 39 (1): 108-34.
Enders, Craig K., and Deborah L. Bandalos. 2001. "The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models." Structural Equation Modeling 8 (3): 430-57.
Erikson, Robert S., Michael B. MacKuen, and James A. Stimson. 2000. "Bankers or Peasants Revisited: Economic Expectations and Presidential Approval." Electoral Studies 19 (2-3): 295-312.
--.2002. The Macro Polity. New York: Cambridge University Press.
Evans, David M., N. A, Gillespie, and N. G. Martin. 2002. "Biometrical Genetics." Biological Psychology 61 (1): 33-51.
Falconer, Douglas S. 1965. "The Inheritance of Liability to Certain Diseases, Estimated from the Incidence Among Relatives." Annals of Human Genetics 29 (1): 51-76.
Fischle, Mark. 2000. "Mass Response to the Lewinsky Scandal: Motivated Reasoning or Bayesian Updating?" Political Psychology 21 (1): 135-59.
Gaines, Brian J., James H. Kuklinski, Paul J. Quirk, Buddy Peyton, and Jay Verkuilen. 2007. "Same Facts, Different Interpretations: Partisan Motivation and Opinion on Iraq." The Journal of Politics 69 (4): 957-74.
Gilens, Martin. 1988. "Gender and Support For Reagan: A Comprehensive Model of Presidential Approval." American Journal of Political Science 32 (1): 19-49.
Gronke, Paul. 1999. "Policies, Prototypes, and Presidential Approval." Presented at the Annual Meeting of the American Political Science Association, Atlanta, GA.
Gronke, Paul, and John Brehm. 2002. "History, Heterogeneity, and Presidential Approval: A Modified ARCH Approach." Electoral Studies 21 (3): 425-52.
Haidt, Jonathan. 2012. The Righteous Mind: Why Good People are Divided by Politics and Religion. New York: Random House.
Hatemi, Peter K. 2015. "The Influence of Major Life Events on Economic Attitudes in a World of Gene-Environment Interplay." American Journal of Political Science 57 (4): 987-1007.
Hatemi, Peter K., and Rose McDermott. 2012. "The Genetics of Politics: Discovery, Challenges and Progress." Trends in Genetics 28 (10): 525-3.3.
Hatemi, Peter K., Carolyn L. Funk, Sarah E. Medland, Hermine M. Maes, Judy L. Silberg, Nicholas G. Martin, and Lindon J. Eaves. 2009- "Genetic and Environmental Transmission of Political Attitudes over a Life Time." The Journal of Politics 71 (3): 1141-56.
Hatemi, Peter K., Christopher T. Dawes, Amanda Frost-Keller, Jaime E. Settle, and Brad Verhulst. 2011. "Integrating Social Science and Genetics: News from the Political Front." Biodemography and Social Biology 57 (1): 67-87.
Hatemi, Peter K., John R. Alford, John R. Hibbing, Nicholas G. Martin, and Lindon J. Eaves. 2009. "Is There a 'Party' in Your Genes?" Political Research Quarterly 62 (3) 584-600.
Hatemi, Peter K., Lindon Eaves, and Rose McDermott. 2012. "It's the End of Ideology as We Know It." Journal of Theoretical Politics 24 (3): 345-69
Hatemi, Peter K., Nathan A. Gillespie, Lindon J. Eaves, Brion S. Maher, Bradley T. Webb, Andrew C. Heath et al. 2011. "A Genome-Wide Analysis of Liberal and Conservative Political Attitudes." The Journal of Politics 73 (1): 271-85.
Hibbing, John R., Kevin B. Smith, and John R. Alford. 2013. Predisposed: Liberals, Conservatives, and the Biology of Political Differences. New York: Routledge.
Jacobs, Lawrence R., and Robert Y. Shapiro. 2000. Politicians Don't Pander: Political Manipulation and the Loss of Democratic Responsiveness. Chicago: University of Chicago Press.
Jennings, M. Kent, and Richard G. Niemi. 1968. "The Transmission of Political Values from Parent to Child." American Political Science Review 62 (1): 169-84.
Jennings, M. Kent, Laura Stoker, and Jake Bowers. 2009. "Politics across Generations: Family Transmission Reexamined." The Journal of Politics 71 (3): 782-99.
Jost, John T. 2006. "The End of the End of Ideology." American Psychologist 61 (7): 651-70.
Jost, John T., Brett W. Pelham, Oliver Sheldon, and Bilian Ni Sullivan. 200.3. "Social Inequality and the Reduction of Ideological Dissonance on Behalf of the System: Evidence of Enhanced System Justification among the Disadvantaged." European Journal of Social Psychology 33 (1): 1.3-36.
Kennedy, Peter. 1992. A Guide to Econometrics. 3rd ed. Cambridge, MA: MIT Press.
Kernel), Samuel. 1977. "Presidential Popularity and Negative Voting: An Alternative Explanation of the Midterm Congressional Decline of the President's Party." American Political Science Review 71 (1): 44-66.
--. 1986. Going Public: New Strategies of Presidential Leadership. Washington, DC: CQ Press.
Kriner, Douglas, and Liam Schwartz. 2009. "Partisan Dynamics and the Volatility of Presidential Approval." British Journal of Political Science 39 (3): 609-31.
Krosnick, Jon A., and Donald R. Kinder. 1990. "Altering the Foundations of Support for the President through Priming." American Political Science Review 84 (2): 497-512.
Lebo, Matthew J., and Daniel Cassino. 2007. "The Aggregated Consequences of Motivated Reasoning and the Dynamics of Partisan Presidential Approval." Political Psychology 28 (6): 719-46.
Lee, Jong R. 1977. "Rallying around the Flag: Foreign Policy Events and Presidential Popularity." Presidential Studies Quarterly 7 (4): 252-56.
Lodge, Milton, and Charles S. Taber. 2013. The Rationalizing Voter. Cambridge, UK: Cambridge University Press.
MacKuen, Michael B. 1983. "Political Drama, Economic Conditions, and the Dynamics of Presidential Popularity." American Journal of Political Science 27 (2): 165-92.
MacKuen, Michael B., Robert S. Erikson, and James. A. Stimson. 1992. "Peasants or Bankers? The American Electorate and the US Economy." American Political Science Review 86 (3): 597-611.
Martin, Nicholas G., Lindon J. Eaves, Andrew C. Heath, Rosemary Jardine, Lynn M Feingold, and Hans J. Eysenck. 1986. "Transmission of Social Attitudes." Proceedings of the National Academy of Sciences 83 (12): 4364-68.
Mayer, Kenneth R. 1999. "Executive Orders and Presidential Power." The Journal of Politics 61 (2): 445-66.
Miller, Joanne M., and Jon A. Krosnick. 2000. "News Media Impact on the Ingredients of Presidential Evaluations: Politically Knowledgeable Citizens are Guided by a Trusted Source." American Journal of Political Science 44 (2): 301-15.
Mondak, Jeffery J. 1993. "Source Cues and Policy Approval: The Cognitive Dynamics of Public Support for the Reagan Agenda." American Journal of Political Science 37 (1): 186-212.
Mueller, John E. 1973. War, Presidents, and Public Opinion. New York,: Wiley.
Nadeau, Richard, Richard G. Niemi, David P. Fan, and Timothy Amato. 1999. "Elite Economic Forecasts, Economic News, Mass Economic Judgments, and Presidential Approval." The Journal of Politics 61 (1): 109-35.
Neale, Michael C., and Hermine H. M. Maes. 1992. Methodology for Genetic Studies of Twins and Families. Dordrecht, Netherlands: Kluwer Academic Publishers.
Niemi, Richard G., and M. Kent Jennings. 1991. "Issues and Inheritance in the Formation of Party Identification." American Journal of Political Science 35 (4): 970-88.
Ostrom, Charles W., Jr., and Dennis M Simon. 1985. "Promise and Performance: A Dynamic Model of Presidential Popularity." American Political Science Review 79 (2): 334-58.
Porges, Stephen W. 2004. "Neuroception: A Subconscious System for Detecting Threats and Safety." Zero to Three 24 (5): 19-24.
Rietveld, Cornelius A., Sarah E. Medland, Jaime Derringer, Jian Yang, Tonu Esko, Nicolas W. Martin et al. 2013. "GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment." Science 340 (6139): 1467-71.
Rijsdijk, Fruhling V., and Pak C. Sham. 2002. "Analytic Approaches to Twin Data Using Structural Equation Models." Briefings in Bioinformatics 3 (2): 119-33.
Settle, Jaime E., Christopher T. Dawes, Nicholas A. Christakis, and James H. Fowler. 2010. "Friendships Moderate an Association Between A Dopamine Gene Variant and Political Ideology." The Journal of Politics 72 (4): 1189-98.
Smith, Kevin B., and Peter K. Hatemi. 2013. "OLS Is AOK for ACE: A Regression-Based Approach to Synthesizing Political Science and Behavioral Genetics Models." Political Behavior 35 (2): 383-408.
Stimson, James A. 1976. "Public Support for American Presidents: A Cyclical Model." Public Opinion Quarterly 40 (1): 1-21.
van Dongen, Jenny, P. Eline Slagboom, Harmen H. M. Draisma, Nicholas G. Martin, and Dorret I. Boomsma. 2012. "The Continuing Value of Twin Studies in the Omics Era." Nature Reviews Genetics 13 (9): 640-53.
Visscher, Peter M., Matthew A. Brown, Mark I. McCarthy, and Jian Yang. 2012. "Five Years of GWAS Discovery." American Journal of Human Genetics 90 (1): 7-24.
Visscher, Peter M., Sarah E. Medland, Manuel A. R. Ferreira, Katherine I. Morley, Gu Zhu, Belinda K. Cornes et al. 2006. "Assumption-Free Estimation of Heritability from GenomeWide Identity-by-Descent Sharing between Full Siblings." Plos Genetics 2 (3): e41.
Yates, Jeff, and Andrew Whitford. 1998. "Presidential Power and the United States Supreme Court." Political Research Quarterly 51 (2): 539-50.
Zaller, John R. 1992. The Nature and Origins of Mass Opinion. New York: Cambridge University Press.
MATTHEW R. MILES
Brigham Young University, Idaho
Matthew Miles is a professor of political science at Brigham Young University, Idaho. His research on presidentialpress relations has appeared in the International Journal of Press/Politics, the Journal of Political Science, and some edited volumes.
TABLE 1 Within-Pair Concordance of Presidential Approval No. (%) of Subjects Total Approve (President) Co-Twin Monozygotic Dizygotic Yes Yes 59 (55.1)/107 38 (52.8)/72 No No 189 (75.9)/249 102 (60.7)/168 Yes No 48 (44.9)/107 34 (47.2)112 No Yes 60 (24.1)/249 66 (39.3)/168 TABLE 2 Summary of Model Results Additive Genetic Common Unshared Effects Environment Environment a c e Presidential 0.683 0.00 0.533 Approval (0.583, 0.784) (-1.158, 1.158) (0.395, 0.670) Heritability [h.sup.2] = [a.sup.2] / ([a.sup.2] + [c.sup.2] [chi square] + [e.sup.2]) (df) Presidential 0.622 11.673 Approval (0.431, 0.812) (3) Note: Model estimated using MPlus version 6. ACE models estimate a parameter for additive genetics (A), common environment (C), and unique environment (E). Ninety-five percent confidence intervals of the estimate in parentheses. The overall genetic heritability is calculated using by squaring a, c, and e, summing them and dividing a-squared by that number.
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||Polls and Elections|
|Author:||Miles, Matthew R.|
|Publication:||Presidential Studies Quarterly|
|Date:||Dec 1, 2015|
|Previous Article:||Public opinion toward presidential power.|
|Next Article:||Barack Obama and the clemency power: real reform on the way?|