Journal of Happiness Studies

, Volume 19, Issue 2, pp 587–606 | Cite as

We Are Happier than We Realize: Underestimation and Conflation in Measuring Happiness

Research Paper

Absract

The study evaluates a very common question designed to measure happiness: “Taken all together, how would you say things are these days–would you say that you are very happy, pretty happy, or not too happy?” Through five representative survey experiments, we show that (1) this survey item underestimates the level of happiness with one’s life; (2) this is because the measure is more likely to reflect satisfaction with the state of the world rather than personal life; (3) this measures is more susceptible to priming; (4) the addition of three words “in your life” to the item greatly reduces priming and question order effects; and (5) the addition of these three words produces results that are very similar to life satisfaction measures that include “in your life” and are more positively associated with income. These results provide evidence that a simple correction better measures personal happiness. Furthermore, our findings reassess the foundation of a considerable volume of scholarship about how politics and income is associated happiness.

Keywords

Survey methods Happiness measurement Question wording Experiments 

1 Introduction

Happiness matters. Happiness can be a useful indicator of a healthy society or of the impact of a policy, and perhaps is even more useful than traditional measures such as GDP (Frey and Stutzer 2010; Layard 2005; Diener et al. 2012). Oswald (1997, p. 1815) notes that “No-one is concerned in a genuine sense about the level of gross national product”. While serving as Federal Reserve Chairman, Ben Bernanke devoted much of a university commencement address to the importance of the social scientific study of happiness, and notes “happiness is nature’s way of telling us we are doing the right thing.”1 As Aristotle argued material wealth is a means, not an end. Wealth is useful in that it allows us to do things that make us happy (Helliwell 2003; Ryff 1989). And happiness is arguably one of the most important goals, or even the ultimate goal for both individuals and society (Frey and Stutzer 2002; Veenhoven 1995; Lyubomirsky and Lepper 1999). When Jefferson articulated a set of goals for government in the United States Declaration of Independence he outlined those goals as life, liberty and the pursuit of happiness (Frey and Stutzer Frey and Stutzer 2002; Lyubomirsky and Lepper 1999).

Recognizing the social importance of happiness, researchers have increasingly examined the concept in the past two decades (Ferrer-i-Carbonell and Frijters 2004; Frey and Stutzer 2010). Within this body of work the debate over how to measure happiness is arguably the most central issue in this growing field (Abdel-Khalek 2006). Happiness is among the most difficult concepts to define and measure in social science. The complexity of happiness is perhaps only surpassed by the concept of love, yet even that concept is frequently measured in numerous surveys (Graham 2011). As Veenhoven (1991) suggests, these measurement difficulties may lead one to conclude that “happiness is both an evasive and inconsequential matter” for serious researchers. Furthermore, Cummins (1995) argues, “the absence of a ‘gold standard’ for subjective well-being has severely hampered the interpretation of results from different studies.” The different measures of happiness are often used interchangeably, yet some believe that “empirical findings often depend critically on which particular measure of happiness is analyzed” (Huang 2010, p. 405).

We evaluate a very common question designed to measure happiness to see if a small variation in wording is associated with how respondents answer and interpret the question: “Taken all together, how would you say things are these dayswould you say that you are very happy, pretty happy, or not too happy?” We test how the addition of three words, “in your life,” to the standard survey item is associated with differences in overall levels of happiness and why these differences emerge. Through five population based survey experiments, we show rather than measuring happiness within one’s own life, the oft-cited happiness question is far more likely to reflect a respondent’s assessment of the state of the world. Besides eliciting different responses regarding levels of happiness, we show that adding three words to the survey (“in your life”) to the survey item has important implications when modeling the determinants of happiness. The strength of the relationship between happiness and political or economic conditions may depend on whether the wording of the question causes the respondent to reflect on their personal life or reflect upon the world in general. Findings reassess the foundation of a considerable volume of scholarship, especially in regards to how politics and income are associated with happiness.

2 The State of Happiness Measurement

Scholars conceptualize and measure happiness in multiple ways. Single-item measures of subjective well-being attempt to capture the “global” nature of happiness (Van Praag et al. 2003; Lyubomirsky and Lepper 1999; Diener et al. 2012). Numerous indexes and scales, both short and long, attempt to capture multiple dimensions of mental, emotional, physical, and environmental well-being (Hills and Argyle 2002). These measures are administered in a variety of ways: telephone survey (Connolly 2013), face to face interviews (Brickman et al. 1978), self-administered survey (Schwarz et al. 1991), online surveys (Howell et al. 2010). Others collect information on happiness through a diary method (Krueger and Schkade 2008). Most research relies on self-reports of happiness (Diener 2000), but a few studies have used external evaluations of an individual’s well-being (Sandvik et al. 1993).2

The diversity of these measures reflects the diversity of how scholars conceptualize happiness. Happiness is sometimes conceived as being part of a broader concept of “subjective well-being” (Scott 1958). Some scholars treat happiness and satisfaction with life as interchangeable (Frey and Stutzer 2000; Veenhoven 1991), others maintain distinction between the two concepts (Cummins 1995; Haller and Hadler 2006). A few suggest that happiness is a personality trait, while others argue that it is a more malleable state of being (Schimmack et al. 2002; Stones et al. 1995). There is evidence that happiness changes over time in association with age, income, health, marital status. However, other findings suggest that an individual’s subjective well-being is rather stable (Pavot and Diener 1993) and even linked to genetics (Huppert 2009; Weiss et al. 2008; Røysamb et al. 2014).

Not surprisingly, the diversity in measures has caused a sizable debate as to the most appropriate method of measuring happiness. Much attention has been focused on the reliability and validity of various measures. Many scholars have concluded that most of these measures are reliable, valid, and relatively stable (Cummins 1995; Lyubomirsky and Lepper 1999; Lucas and Donnellan 2012; Cheung and Lucas 2014), while others have highlighted the sensitivity of measures to conversational context (Strack et al. 1988), question order (McClendon and O’Brien 1988), and interview format (Smith 1979). Such debates clearly points to the merits of and need for further research on the measurement of happiness.

3 Evaluating Measures of Happiness

Lyubomirsky and Lepper (1999) note that “every student of happiness and well-being has had to tackle the problem of how to measure levels of individual happiness.” This problem is complicated by the fact there is no “gold standard” measure out there, but a range of measures that have been developed to meet different needs and goals (Cummins 1995). These different measures have been vigorously tested and retested. Numerous studies compare results from different items (Lyubomirsky and Lepper 1999), apply different response categories (Kalmijn et al. 2011) or change question ordering (Smith 1990) to test both the reliability and validity of these measures. Less research focuses on how a small modification of a question’s wording may change how respondents interpret and thus respond to a survey question.

Tourangeau et al. (1991) is among a few studies that have modified a common happiness question to explore how respondents interpret a survey item. The scholars modified the General Social Survey item by adding one of the following two phrases: “aside from your marriage” and “including your marriage.” The authors observed that adding the two different phrases caused respondents to assess different parts of their life. Similarly, Schwarz et al. (1991) provided some respondents with instructions to evaluate specific aspects of their life, and then “leaving aside the life-domain(s) that you already told us about, how satisfied are you currently with other aspects of your life?” Both Tourangeau et al. (1991) and Schwarz et al. (1991) show respondents can be directed to think about specific information and, resultantly, can change responses.3

Like Tourangeau et al. (1991) this study is interested in how the wording of a question is associated with a respondent’s interpretation of the concept of happiness. Fundamentally a “good question” is one where all respondents interpret the question in a consistent manner (Fowler 1995). Many scholars believe that respondents draw on a wide range of information and experiences when asked to judge their subjective well-being (Schwarz and Strack 1999). Individuals may evaluate their level of happiness by comparing their circumstances to others, some may recall past experiences, and others may think to what the future holds for them (Frey and Stutzer 2002). Ross et al. (1986) examined what type of information respondents were accessing by asking them why they responded to the subjective well-being question. They found the most common reason mentioned referred to their present state or circumstances, followed by references of future or anticipated events or states of being, followed by references of past events. All of these reasons cited by Ross et al. (1986) involve personal reasons. This study is interested in how some respondents draw on non-personal reasons, or more specifically, societal level conditions, such as the overall condition of the economy or the direction the country is heading politically.

Most studies assume that individuals are using information about their own lives, but depending on the question wording or order they may be prompted to make “intraindividual comparisons” (e.g., comparing your present life circumstances with your past or your expected circumstances) or interindividual comparisons (e.g., comparing your current life circumstances with those around you) (Schwarz and Strack 1999). Much of the literature on happiness highlights the difficultly in identifying what type of information the respondent is accessing when asked about happiness. When respondents review their life or conditions, their reviews may not be systematic, but arbitrary or incomplete (Krueger and Schkade 2008) or primed by preceding questions (Pavot and Diener 1993).

We suggest that one of the most common measures of happiness actually causes many respondents to reference the state of the world, not their own personal circumstances. This is especially true if questions preceding the happiness question reference societal conditions (i.e., the state of the economy, approval of the President). The idea underpinning this article began from observations from the pretesting of a questionnaire that contained the standard GSS happiness question. While asking this question to individuals that were expected to be happy based on our personal knowledge, we were surprised to find test subjects responding with “not very happy.” When prompted as to why they were unhappy, test subjects frequently mentioned political, economic, or societal problems, not personal conditions specific to the subject’s life.

Several scholars have found that individuals who state they are happy are likely to have knowledgeable informants (friends or family members) describe the individual in the same manner (Moskowitz 1986; Sandvik et al. 1993; Pavot and Diener 1993). Finding subjects in the pre-test that we expected to be happy but found responding as unhappy suggested the measure was not performing as expected. However, pre-tests of surveys are not based on large or random samples. Our qualitative observations of pre-testing could have been an anomaly, an artifact of question ordering, or shaped by the political or economic events in the news that week; or we may simply have misjudged expected levels of happiness of our pre-test subjects. We subsequently developed a series of population-based survey experiments to refine these observations by introducing a modified question specifically referencing a person’s life.

4 Reconsidering the Dominant Happiness Question

In this study we focus on the single-item, global question: “Taken all together, how would you say things are these days—would you say you are very happy, pretty happy, or not to happy?” This question, and ones that are almost identical to this question, are used in many surveys (e.g., General Social Survey; Gallup; European Social Survey, World Values Survey, Americans’ Changing Lives study, National Survey of Families and Households, Social Capital Community Benchmark Survey). As noted by many scholars, single-item questions are the most commonly used method of measuring happiness (Smith 1979; Diener 2000; Krueger and Schkade 2008; Abdel-Khalek 2006; Kalmijn et al. 2011) and this version is the most widely used single-item happiness measure. Andrews and Robinson (1991, p. 71) note “Happiness has been assessed in numerous other ways. None, however, has seemed markedly better than the measures presented above and none has as long a history of observation in the United States (or anywhere else).” Schwarz and Strack (1999) note that “hundreds of thousands of survey respondents around the world have been asked questions like ‘Taking all things together, how would you say things are these days—would you say that your are very happy, pretty happy, or not too happy?’” The GSS online document archive shows 433 publications relying on this question.4

Although some may caution on the use of a single item in measuring subjective well-being, several studies have shown that a single measure can accurately measure this concept (Abdel-Khalek 2006; Wanous and Reichers 1996; Cummings 1995; Cheung and Lucas 2014). In practical terms, unless a survey is specifically designed to study happiness, it is unlikely to contain more than one item. General purpose surveys, such as the General Social Survey, are interested in hundreds of concepts, happiness being only one of them. Therefore surveys often cannot dedicate numerous items to explore happiness in all of its complexity and ambiguity. Instead, surveys typically rely on a single-item global measure that is more cost-effective (Abdel-Khalek 2006).

The question we are testing has been tested and retested for decades. What new can be uncovered by examining this question again? Although numerous studies compare single-item measures with indexes or scales, or compare continuous measures with discrete measures (Studer 2012), far less research has been devoted to examining how slight modifications in wording can change the way a respondent interprets a question. Several potential factors explain the lack of research. Subjective well-being questions have been asked for decades and changing the question would compromise comparisons across certain time periods. Our goal is not to lobby for changing the traditional single-item global measure, but to better understand how respondents are interpreting this commonly used survey item.

4.1 Hypotheses

Our theory suggests four questions and five associated hypotheses. The remainder of this manuscript is organized around these questions and hypotheses. We elaborate details of each below.
Question 1

How will happiness questions differ when “in your life” is added to the traditional question? Our theory suggests that directing respondents to reflect on their “life” rather than society will lead to more positive assessments of happiness. H1 is derived from this expectation

H1

Receiving a treatment question adding “in your life” to the traditional happiness question will be positively associated with reporting high levels of happiness

Question 2

Does “in your life” actually lead respondents to reflect on their life rather than society? If so, the causal mechanism suggested by our theory and implied in question 1 has some support

H2

Receiving a treatment question adding “in your life” to the traditional happiness question will be positively associated with respondents referencing personal circumstances when asked to elaborate on their response

Question 3

Because many responses to the traditional wording of happiness involve respondents reflecting on the state of society rather their own lives, evaluations of society, politics in particular, should be associated with happiness in that wording. When respondents reflect on their own lives, the association between politics and self-reports of happiness should diminish. Inducing respondents to reflect on their own lives could be done through a prime antecedent to the happiness question or through a modification to the happiness question itself. This intuition leads to both Hypotheses 3 and 4

H3

Political satisfaction will have a stronger positive association with the traditional measure of happiness than with the modified “in your life” question

H4

Priming a respondent with a political satisfaction question before measuring happiness will have a stronger effect on the standard measure than a question references a person’s life

Question 4

A corollary to the logic behind Question 3 is that individuals more reflective on their own lives and less reflective on society will likely not simply deemphasize society (politics). These individuals will also enhance emphasis on aspects on their own lives. Personal household income is one such personal life aspect. Lucas and Schimmack (2009, 75) note that the association between income and subjective well-being have been found to be small in most studies, and frequently been “dismissed as unimportant.” This finding could, in part, derive from societal rather than personal reflection. This leads to our final hypothesis

H5

The positive association between income and happiness will be larger when question wording contains references to a person’s own life

5 Data and Methods

We tested the above hypotheses through a series of five population-based survey experiments.5 Four of the experiments were conducted using a Computer Assisted Telephone Interview (CATI) system to conduct a live-interview dual-frame (cell phone and land-line) telephone survey of residents or registered voters in North Carolina. An additional experiment tests uses a nonprobability quota sample of online respondents living in North Carolina. Table 1 provides a list of the experiments, hypotheses, statistical method and associated survey data.6
Table 1

List of experiments

Study

University poll

Hypothesis

Statistical test

Experiment 1

Aug’12; Oct’12; Feb’13

H1:Treatment (modified wording) group will be happier

t tests

Experiment 2

Feb’13

H2: Treatment group will mention personal circumstances more frequently; control group will mention societal

t test

Experiment 3

Oct’12

H3: Political satisfaction is more strongly associated with standard question wording

Ordered probit

Experiment 4

Sept’14

H4: Societal prime has larger association with standard question wording

t tests

Experiment 5

Sept’14 (online)

H5: Income is more highly correlated with modified survey question

Ordered probit

Most surveys on happiness are conducted with national samples. Fewer studies look at a specific region or state. Studying a single state offers several advantages.7 The climate and weather is more likely to be similar throughout a state than an entire country, and weather has a potentially biasing effect on responses to happiness questions (Connolly 2013; Rehdanz and Maddison 2005). More importantly for this study, it is useful that residents of a single state have the same president, governor and two U.S. Senators as their elected officials. If residents lived among various states they would be exposed to various state policies and political leaders. The lack of variation benefits our study by exposing both the control group and treatment group to similar political stimuli and allows the survey to ask about those political conditions. By focusing on a single state and asking more specific questions relevant to that state’s politics the “black-box” can be opened and the mechanisms of how politics is associated with happiness can be explored in greater detail (Haller and Hadler 2006). Furthermore, the state of this study, North Carolina is populous and diverse. As a “swing state,” North Carolina very roughly approximates a “typical” state in the United States.

6 Experiment 1/Hypothesis 1: We Are Happier than We Realize

Figure 1 depicts results from three different telephone surveys conducted in North Carolina. The first was conducted in August 2012. The second study was conducted in October of 2012. The third study was conducted in February 2013. In all three surveys respondents were randomly assigned into a control group or treatment group. The control group was given the standard question wording: “Taken all together, how would you say things are these days—would you say that you are very happy, pretty happy, or not too happy?” The treatment group was given the modified question: “Taken all together, how would you say things are these days in your life–would you say that you are very happy, pretty happy, or not too happy?”
Fig. 1

Mean Self-Reported Happiness by Question Type. Independent sample t-tests. 3-point variable. 0, Not too happy; 2, Very Happy. Treatment group wording includes “in your life”; control group does not.

Source: University Poll

Both happiness questions (control and treatment) have three response options ranging from “very happy” (2) to “pretty happy” (1) to “not too happy” (0). The mean happiness level for control group subjects was 0.768 in August 2012, 0.752 in October 2012, and 0.764 in February 2013. In contrast, subjects in the treatment group receiving the “in your life” addition reported substantially higher mean happiness: 1.153 in August 2012, 1.172 in October 2012 and 1.176 in February 2013. The maximum effect of the treatment ranged from 0.38 in August 2012 to 0.41 in February 2013. Results are statistically significant at the 0.0001 level for each of the three experiments. Furthermore, the results are remarkably similar over time, implying consistent effects of the treatment.8 For comparison purposes, to put a 0.4 difference in context, the mean happiness difference was 0.27 in August 2012 between subjects with household incomes of less than $25,000 and those with incomes over $75,000. Question wording was associated with a bigger difference than a 300 percent increase in respondent income. This experiment supports Hypothesis 1.

7 Experiment 2/Hypothesis 2: Finding the Meaning Behind “In Your Life”

We hypothesize that the reason why “in your life” elicits happier responses is because by a respondents are more likely to reflect on personal conditions rather than societal conditions. In the February 2013 survey we design a test related to this hypothesis. We followed the happiness question (in both randomized control and treatment forms) with a follow-up question asking respondents to explain why they gave a particular answer. This was an open-ended question that read, “What is one reason why you answered that you are…(very happy; pretty happy, not too happy)?” We then coded open-ended responses into the following 5 point scale, 1 = definitely personal, 2 = mostly personal, 3 = neither personal or societal, 4 = mostly societal, 5 = definitely societal.9 Examples we recorded of highly personal responses (code 1) include, “Husband and myself have saved lots of money to retire” and “broken shoulder.” Examples we recorded of highly societal responses (code 5) recorded include, “because I think the politicians are making stupid decisions” and “There are a lot of unsettling things in America.”

Figure 2 shows an independent sample t test resulting from this mechanism experiment. Subjects who received the ubiquitous wording in the control group were much more likely to respond to the follow up question with a societal reason in the follow-up question than those in the treatment group. The mean response in the control group was 2.625 compared to 1.718 in the treatment group. This result is statistically significant (t = 8.8; p < 0.0001) and supports our prediction in Hypothesis 2.
Fig. 2

Results of Open-Ended Question “What is one reason why you answered that you are…(very happy; pretty happy, not too happy)?” Independent sample t tests. t = 8.8. p <0.0001. Value is based on open-ended responses coded on 5 point scale. 1. Definitely personal. 5. Definitely societal. Treatment group recieved “in your life” question prior to the open-ended followup. The control group recieved the standard wording in advance.

Source: Elon University Poll, Feb. 2013. N = 886

Also noteworthy is that reported happiness tends to drop precipitously as the reason for the response becomes more societal (Kendall’s tau-b = −0.4412; p < 0.01). For instance, the mean happiness was 1.234 for respondents in both control and treatment groups who offered a definitely personal reason for their happiness. In contrast, mean happiness dropped to 0.339 among respondents offering a definitely societal explanation for their response.

8 Experiment 3/Hypothesis 3: Happiness and Politics

For many years studies of happiness were almost entirely produced in the field of psychology (Frey and Stutzer 2002). The field of economics, although slow to see the usefulness of studying happiness, has seen tremendous growth in the number of studies focusing on happiness (Ferrer-i-Carbonell and Frijters 2004; Frey and Stutzer 2002; MacKerron 2012). Political science, has been even slower to recognize the importance of happiness, but in recent years a number of studies have examined how political factors influence subjective well-being (e.g., Alvarez-Diaz et al. 2010; Gerber and Huber 2010; Gerber et al. 2013; Tavits 2008; Pacek and Radcliff 2008a, b; Weitz-Shapiro and Winters 2011).

For the most part, studies exploring the relationship between happiness and political conditions and institutions have concluded that politics does matter (Easterlin 2013; Diener et al. 2012; Wills-Herrera et al. 2011; Flavin et al. 2014). Orviska et al. (2014) finds that countries or regions that have populations that are satisfied with democracy also have populations that are happy and satisfied with life in general. Similarly, some scholars have found government performance, as measured by level of corruption, level of democracy, and level of service provision, is associated with the happiness of citizens (Helliwell and Huang 2008; Tavits 2008; Rodríguez-Pose and Maslauskaite 2012; Veenhoven 1995). A number of studies found respondents are happier when the party in power shares their political ideology (Alvarez-Diaz et al. 2010; Di Tella and MacCulloch 2005; Gerber and Huber 2010; Gerber et al. 2013; Tavits 2008).

While we do not dispute the aforementioned findings, we do posit that some findings about happiness’s relationship with politics may be biased to the extent that the wording of the most common happiness question causes respondents to reflect more acutely on societal conditions rather than their personal situation. This has important implications for studies that are examining how political and economic factors are associated with happiness. Question wording that draws attention to a respondent’s personal life may correlate less with political and economic factors, while wording that is interpreted in such a way as to include conditions outside the respondent’s personal life may be more strongly associated with various political variables.

As shown above, when respondents were asked why they responded the way they did to the traditional worded question, they were more likely to reference a societal, political or macroeconomic condition (e.g., I don’t like the President; the country is going downhill). When given the modified question respondents were more likely to reference a personal event or condition.

We test hypothesis 3 using data from a survey experiment conducted in October 2012. An ordered probit model with an interaction term is used to examine how perceptions of society may be associated with changes in a respondent’s reported level of happiness (see Table 2).10 The right hand side of the model includes a measure based on a survey item asking 1325 registered voters in North Carolina “Do you think things in the nation are generally headed in the right direction, or do you feel things are off on the wrong track?” The dependent variable Happiness was regressed on this dummy variable (wrong track = 0; right track = 1) along with a dummy variable for the treatment (treatment group = 1; control group = 0) and a multiplicative interaction term of the two (treatment × right track). The treatment group represents those respondents who were given the modified happiness question that included the words “in your life”.
Table 2

“Direction of Country” effect on happiness conditional on wording.

Source: University Poll, October 2012

 

Param. Est. (SE)

Treatment wording × right track

−0.397***

(0.127)

Right track

1.003***

(0.0928)

Treatment wording

0.889***

(0.0845)

Cut1

0.167**

(0.0623)

Cut2

1.610***

(0.0717)

Observations

1325

Pseudo R-squared

0.101

Likelihood ratio (LR) Chi2

281.5

Log likelihood

−1257.2

Prob > chi2

0.000

Dependent variable is happiness (0 not too happy; 1 pretty happy; 2 very happy)

Ordered probit. Registered Voters in NC. Independent variables range from 0 to 1

* p < 0.05; ** p < 0.01; *** p < 0.001

Figure 3 presents an interpretation of the estimates in Table 2 to visualize the effect of “right track/wrong direction” on happiness conditional on question wording. In the treatment, the probability of responding very happy is 45.4% if respondents said “right track” and 23.5% if “wrong direction.” In the control, the probability of saying very happy is 27.2% if respondents thought the country was on the “right track” and 5.3% if respondents said “wrong direction.” Both of these represent statistically discernable 22% effects of the track variable. However, in the control condition, the track question is much more powerful in terms of making people unhappy (“not too happy”). In the control question, moving from wrong direction to right track is associated with a 36 point drop in the probability of being unhappy from 56.6 to 20.1%. In the treatment, moving from wrong direction to right track is only associated with a 14 point decline in probability of responding as unhappy, a change from 23.5 to 9.2%.
Fig. 3

Marginal effect of political “track” on happiness conditional on question wording. Changes in predicted probabilities based on ordered probit in Table 2

When respondents think about themselves instead of society when they evaluate their happiness, they tend to be less sad. This finding may help explain some interesting anomalies in the happiness literature. For example Schlenker et al. (2012) found liberals were less happy than conservatives in the U.S. The authors use the General Social Survey (GSS) happiness global measure from 1972 to 2008. We suspect that part of this difference is because the GSS happiness measure is more likely to direct respondents to assess societal (and political) factors. Between 1972 and 2008 a Republican president was in office for 25 of those 37 years, and liberals were likely responding to that fact. A global measure that included “in your life” may have diminished the differences between liberals and conservatives.

In fact, survey results from February 2013 found that that slightly more conservatives (34%) said they were very happy compared to liberals (32%) when “in your life” was added. That changed when “in your life” was dropped from the survey item. Both liberals and conservatives were less happy, but conservatives were now less happy than liberals (14% very happy compared to 19%). We suspect that Barack Obama’s reelection may help explain this reversal, and the GSS measure frequently causes respondents to think about their social, economic, and political environment, rather than their personal conditions.11

9 Experiment 4/Hypothesis 4: Question Ordering Effects

The above experiment used regression analysis to examine how perceptions of the state of the country were associated with different levels of self-reported happiness depending on question wording. In this experiment we use both randomization in the assignment of respondents to the treatment or control group, as well as randomization of question ordering to test hypothesis 4. We predict that priming a respondent with a political question (right track/wrong track) will produce a larger bias for the control group than a group that received the modified happiness question.

Furthermore, we believe that it is the words “in your life” that is causing respondents to reflect on their personal conditions rather than societal conditions. Therefore we predict that a typical life satisfaction question that usually includes the words “your life” will also be less affected by a question priming respondents to think about national conditions. Several surveys use some variation of the following wording to measure life satisfaction: “All things considered, how satisfied are you with your life these days?”12 We modify this life satisfaction question so that it is similar to our modified happiness question: “Taken all together , how satisfied are you with your life these days?” Additionally, we modified the response categories of the two happiness questions so they conform to a 4 point scale (very happy/satisfied; pretty happy/satisfied; not too happy/satisfied; not at all happy/satisfied). We predict that because the life satisfaction question includes the words “your life” it will direct respondents to focus on their personal lives. Therefore, both our modified happiness question that includes “in your life” and the modified life satisfaction question should be less strongly associated with change following a societal prime.

This experiment is based on a September 2014 dual frame (cell phone and land line) telephone survey of 1078 residents of North Carolina. It employed a 3 × 2 factorial design producing six randomized groups. The first dimension of this design varied the question wording in three ways: the control group received the standard GSS wording while one treatment group received the “in your life” addition as detailed above. A third group received the modified life satisfaction question describe above.

The second dimension of the experiment varied the question ordering in two ways. Half of respondents received one of the three aforementioned questions directly after the survey item directing respondents to think about societal factors: “Do you think things in the nation are generally headed in the right direction?” The other randomized half of respondents received one of the three questions immediately after a standard demographic question about marital status, “Are you single, married, divorced, separated, or widowed?” The “right track” group was consequently primed to think about the state of the society. The marital status group was primed to think about their personal lives.

Table 3 presents mean response of all six groups. Groups 1a through 6a include all respondents. Groups 1b through 6b include only married respondents. Groups 1c through 6c include only non-married respondents (single, divorced, or widowed). The results support Hypothesis 4 and show the difference between receiving a societal question and a personal question is larger among the control happiness group than the treatment happiness group. Among all respondents, respondents receiving the standard wording increased reported happiness 0.29 points from 1.55 in the societal prime group (Group 1a) to 1.84 in the marital status prime group, Group 4a (t = 3.1). The t-score for this difference is modest, but statistically significant at the 0.01 level. This is likely because we are examining how each of the three measures are responding to the question ordering. The experiment creates six subgroups, reducing the sample size and therefore reducing statistical power.
Table 3

Happiness Measures and Life Satisfaction.

Source: University Poll, Telephone Survey, September 2014

Group

Prime

Question

Mean

SD

N

All respondents

 Group 1a

Societal prime

Std. happiness wording

1.55

0.93

186

 Group 2a

Societal prime

“In your life” happiness

2.11

0.74

180

 Group 3a

Societal prime

Life satisfaction

2.03

0.86

188

 Group 4a

Personal prime

Std. happiness wording

1.84

0.91

195

 Group 5a

Personal prime

“In your life” happiness

2.24

0.68

204

 Group 6a

Personal prime

Life satisfaction

2.20

0.77

177

Married respondents

 Group 1b

Societal prime

Std. happiness wording

1.57

0.95

104

 Group 2b

Societal prime

“In your life” happiness

2.24

0.70

94

 Group 3b

Societal prime

Life satisfaction

2.20

0.80

112

 Group 4b

Personal prime

Std. happiness wording

2.03

0.90

107

 Group 5b

Personal prime

“In your life” happiness

2.36

0.66

129

 Group 6b

Personal prime

Life satisfaction

2.30

0.79

106

Not married respondents

 Group 1c

Societal prime

Std. happiness wording

1.52

0.91

82

 Group 2c

Societal prime

“In your life” happiness

1.97

0.76

86

 Group 3c

Societal prime

Life satisfaction

1.79

0.90

76

 Group 4c

Personal prime

Std. happiness wording

1.61

0.88

88

 Group 5c

Personal prime

“In your life” happiness

2.03

0.68

75

 Group 6c

Personal prime

Life satisfaction

2.04

0.71

71

Mean responses. Four possible response range from 0 (Not at all happy/satisfied) to 3 (very happy/satisfied)

Changing the prime from a societal question to a marital status question also increased mean responses of the treatment happiness groups, but by a much smaller amount. Those in Group 2a received the modified happiness wording and the societal prime and reported a mean score of 2.11. Group 5a also received the modified happiness wording, but received the marital status prime and had a mean score of 2.24 (Difference: 0.13; t = 1.77). As expected the biasing effect of the societal prime is smaller for the modified happiness question.

Interestingly and consistent with our predictions, the aggregate effect of the marital status prime is driven in large part by married people. Previous research frequently finds married people to be happier people (Dolan, Peasgood and White 2008).13 Priming non-married people to think about their marital status instead of the state of world still makes them happier, but much less so than for married people. Married individuals given the political question before the standard happiness question (Group 1b), had a happiness score 0.46 points higher than married individuals given the marital status question before the standard happiness question (Group 4b; t = 3.62). This is five times larger than the statistically insignificant 0.09 increase in happiness between Group 1c and Group 4c in non-married respondents (t = 0.652). Asking individuals to think about their marriage instead of the state of the world makes them report high happiness levels in all groups, but the effect is much more pronounced among those receiving the standard happiness question and among those who are currently married.

Table 3 also shows that the scores for respondents receiving the modified happiness question are much closer to those who received the life satisfaction question. For example, when we compare the scores of respondents receiving the standard question wording with those receiving the life satisfaction question we find substantial differences. Specifically, the difference between Group 1a and Group 3a is 0.48 and the differences between Group 4a and Group 6a are 0.36 units apart. On the other hand, respondents receiving the modified happiness questions score very similarly to respondents receiving the life satisfaction question. The difference between Group 2a and Group 3a is only 0.08 units and the difference between Group 5a and Group 6a is only 0.04 units. The distance in means between the control happiness group and life satisfaction is six to nine times larger than the distance in means between the treatment happiness group and life satisfaction. Like the modified happiness question, the life satisfaction question is also less effected by the priming effects of a societal question. This provides some evidence that it is the reference to “your life” in both questions that causes respondents to reflect on personal rather than societal circumstance.

10 Experiment 5/Hypothesis 5: Income and Happiness

Our prior tests showed the standard happiness question frequently caused respondents to consider societal conditions when assessing their own subjective well-being. We concluded that the adding of the words “in your life” caused respondents to reflect on their personal circumstance rather than broader societal issues. If this is true we would also expect that the “in your life” would be more strongly associated with questions about their personal situation, especially their personal economic circumstances. Prior findings have found the life satisfaction question typically correlates higher with income than the typical happiness question (Graham 2012). Like the life satisfaction question, our modified happiness measure also includes “your life.” Therefore we also expect this measure to correlate more highly with income.

We test this prediction using data from an online survey of North Carolina residents conducted September 2014. This survey was used because all respondents were randomly given one of the three survey items (GSS happiness; modified happiness; and life satisfaction) at the exact same place in the survey (after 4 standard likely voter questions). In addition, the online survey contained a measure of income with a ten income categories; while all of the telephone surveys in this study contained a set of income questions that produced an income measure with only 4 income categories.14

The online survey was split into three subsamples, one for each of the three measures of subjective well-being (standard happiness wording; modified happiness; life satisfaction). Each subsample was analyzed using an ordered probit model with single independent variable---annual household income.15 The results from this analysis are presented in Table 4 and show that income is positively associated with all three measures of subjective well-being. But, the coefficient is noticeably smaller in Model 1 analyzing the subsample containing respondents given the standard happiness question. The relationship between income and subjective well-being is stronger for the subsample given the modified happiness question (Model 2) and the subsample given the life satisfaction survey item (Model 3).
Table 4

Ordered probit—subjective well-being and household income.

Source: University Poll- Online Survey Sept 5–9, 2014—Registered voters in North Carolina

 

HappyGSS

Happy Modified

Life Satisfaction

 

Model 1

Model 2

Model 3

 

Param. Est. (SE)

Param. Est. (SE)

Param. Est. (SE)

Annual Household Income

0.0543*

0.0803**

0.0815*

(0.0296)

(0.0309)

(0.0352)

Cut 1

−0.594***

−1.458***

−1.018***

(0.128)

(0.160)

(0.145)

Cut 2

0.370**

−0.273*

−0.0468

(0.127)

(0.127)

(0.134)

Cut 3

1.639***

1.417***

1.349***

(0.152)

(0.146)

(0.150)

Observations

307

294

278

Pseudo R-squared

0.004

0.011

0.008

Likelihood ratio (LR) Chi2

3.38

6.78

5.38

Log likelihood

−385.6

−310.6

−336.4

Prob > chi2

0.066

0.009

0.024

Dependent variable ranges from 0 to 3: 0 not at all happy/satisfied; 1 not too happy/satisfied; 2 pretty happy/satisfied; 3 very happy/satisfied. Income variable range from 1 to 10: 1 = less than $20,000; 10 = $180,000 or more

* p < 0.05; ** p < 0.01; *** p < 0.001

A z-test comparing differences in coefficients for the income variables in Table 4 Models 1-3 does not reach standard levels of statistical significance (Model 1 vs. Model 2 z = 0.61; Model 1 vs. Model 3 z = 0.59; Model 2 vs. Model 3 z = 0.03). This could, in part, be caused by the fact we divided the overall sample into three smaller subsamples to estimate the three models for comparison. We suggest, however, the substantive differences between models as respondents move from low income to high income are interesting nonetheless. The change in predicted probability of saying very happy for the standard wording as a simulated respondent moves from less than $20,000 in income to over $180,000 in income is 8% (5.7% lowest income respondents to 13.7% for highest income respondents). This change for the “in your life wording” is 17.9% (9.1 to 27.0%). For the life satisfaction wording it is 19.4% (10.3 to 29.7%). When “in your life” is added the relationship between income and happiness is similar to the relationship income has with the life satisfaction measure.

11 Conclusion

Researchers frequently treat single-item happiness questions and life satisfaction questions interchangeably (Graham 2012). This is partially because the two measures correlate so highly together. However, prior studies have found some consistent differences between the two measures. Among other things, life satisfaction measures typically tend to be more stable (Ryff 1989) and they typically correlate higher with personal income (Graham 2012). Our evaluation of the common single-item happiness question “Taken altogether, how would you say things are these days?” suggests why this might be the case. Through a series of 5 population-based survey experiments we found that adding “in your life” to the standard happiness question creates a measure that 1) causes respondents to more likely say they are happy and 2) causes respondents to more likely reflect on their personal situation rather than societal conditions. In the end, this modified question produces results very similar to the typical single-item life satisfaction question. The results here, suggest that the difference between the typical happiness question and the typical life satisfaction question is caused not by the difference in the adjective describing well-being (i.e., happy, satisfied, content, pleased) but rather the inclusion of the words “your life” which directs respondents to focus on their personal circumstances.

Because the ubiquitous GSS happiness measure is so broad in scope of reference, it is likely to cause respondents to reflect on societal conditions rather than themselves. This leads to lower reported levels of happiness. Moreover, it decreases the measured effect of household income while increasing the measured effect of political satisfaction. Are these effects a problem? The answer depends on whether a study is attempting to examine how happy individuals are with current societal conditions or if they are happy with their personal lives. The paradox of growing unhappiness in the face of increasing resources observed by various scholars (Easterlin 1995; Lane 2000) is likely due, in part, to how respondents differentiate between personal circumstances and societal conditions and how different measures will capture one interpretation more than another. The traditional GSS measure better captures evaluations of societal conditions. Porta and Scazzieri (2007, p. 96) write that once a person’s basic needs are met, happiness is a “cognitive state associated with beliefs and opportunities.” However, those beliefs might not always be the personal well-being of the respondent but instead might be driven by perceptions of society, causing some doubt about the popularized notions that happiness is unresponsive to income after a certain threshold.

One critique of the single-item, global measure of happiness is that it is too general and respondents must think of something specific to answer the question (McClendon and O’Brien McClendon and O’Brien 1988; Schwarz and Strack 1991). Much of the debate in the literature is about what personal experiences or conditions are being referenced (marriage, job, income, etc.). In this study we show that instead of referencing personal phenomena, respondent are referencing some societal event or condition.

Creating and evaluating techniques to address this bias, though beyond the scope of this paper, is a promising area for future research given the large number of publications dependent on single item happiness measures without personal life references. The findings here suggest future research should reconsider some established conclusions about the precursors of happiness. Furthermore, future studies of happiness should also consider multiple measures of happiness instead of relying on a single survey item without an explicit and personalized life reference. Additional research could also expand upon the results here by expanding the geographic sample area, especially outside of the U.S., given that happiness self-reports may be culturally dependent. Experiment 4 also cautions researchers to be cognizant of question ordering’s potential to prime responses to happiness questions.

Many researchers have concluded that the concept of happiness can be measured in a meaningful and reliable way, both at the individual and aggregate level (Easterlin 2013; Frey and Stutzer 2002). Furthermore, some scholars have downplayed the effects of different wording, suggesting that different subjective well-being items are often highly correlated with one another and typically stable across time and context (Diener et al. 2012). Yet there is clear evidence from numerous studies that some uncertainty remains about exactly how respondents interpret a question and what cognitive process generates that answer. We hesitate to offer a “gold standard” for a happiness measure, but a good question is one where respondent interpret the question in a similar way (Fowler 1995). The evidence presented here suggests that the traditional single-item, global happiness measure used in hundreds of studies is often not interpreted as “how happy am I” but rather “should I be happy given what the world is like today”? This measurement error has likely led to overestimation of some societal variables’ effects on happiness, such as level of democracy, level of corruption, or national economic conditions. It has also likely led to the underestimation of the effects of some individual attributes, such as personal income. Future studies should revisit existing scholarship on happiness reliant on on single item measures.

Footnotes

  1. 1.

    http://www.federalreserve.gov/newsevents/speech/bernanke20100508a.htm---It should be noted that in this speech Bernanke specifically cites the survey item we evaluate in this study.

  2. 2.

    The advantage of using external evaluations of happiness is that one can avoid problems stemming from common-source bias. Researchers have observed that when two self-reported measures are obtained from the same source, such as a single survey, the association between the two measures is often inflated (Favero and Bullock 2015; Meier and O’Toole 2010).

  3. 3.

    Additionally, Smith (1979) investigated the slight difference between the National Opinion Research Center (NORC) wording and the Survey Research Center, University of Michigan (SRC) wording of a single item happiness question and finds noticeable differences in responses but suggests that much of this may be due to question ordering in the two surveys.

  4. 4.

    GSS variable name HAPPY. A Google Scholar search of the exact question revealed 628 results. Document counts accessed on 9/19/2015.

  5. 5.

    Mutz (2011) argues that “population-based survey experiments provide a means of establishing causality that is unmatched by any large-scale survey data collection effort, no matter how extensive.”

  6. 6.

    Details of each survey is presented in Table 5 in the Online Supporting Materials.

  7. 7.

    See Nicholson-Crotty and Meier (2002) for a defense of single-state studies.

  8. 8.

    The results were also consistent across survey mode. In an online, web-based survey we found that the modified happiness question produced happier responses than the standard question wording.

  9. 9.

    To assess accuracy of coding, we coded responses with multiple coders. Intercoder reliability was 0.71. Other scales could be used for this coding.

  10. 10.

    We estimate a parsimonious model. However, results are consistent with additional right-hand side variables.

  11. 11.

    A content analysis of the February 2013 open-ended responses to the questions asking why a respondent was happy or unhappy found that 8 percent of respondents mentioned "government" when "in your life" wasn't in the wording. This is compared to only 1 percent when "in your life" was included in question. In addition, only 3 respondents mentioned the president or his name in the "in your life" survey item, while 14 referenced the president when those words were dropped from the question.

  12. 12.

    For example, the World Values Survey; European Social Survey, and European Quality of Life Survey use such a measure.

  13. 13.

    Although Fry and Stutzer (2005) question the causal direction of this relationship and find that for some age groups happy people are more likely to get married.

  14. 14.

    We replicated the analysis with each of the four telephone surveys containing the 4 category income measure and found in every case our modified happiness measure was more strongly correlated with income than the standard happiness measure.

  15. 15.

    We estimate a parsimonious model. However, results are consistent with additional right-hand side variables.

Supplementary material

10902_2016_9831_MOESM1_ESM.docx (17 kb)
Supplementary material 1 (DOCX 17 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Elon UniversityElonUSA
  2. 2.College of Southern NevadaLas VegasUSA

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