This paper shows that, consistent with a signaling-by-consuming model à la Veblen, income elasticities can be predicted from the visibility of consumer expenditures. We outline a stylized conspicuous consumption model where income elasticity is endogenously predicted to be higher if a good is visible and lower if it is not. We then develop a survey-based measure of expenditure visibility, ranking different expenditures by how noticeable they are to others. Finally, we show that our visibility measure predicts up to one-third of the observed variation in elasticities across consumption categories in U.S. data.

A growing literature explores differences in subjective well-being across demographic groups, often relying on surveys with high nonresponse rates. By using the reported number of call attempts made to participants in the University of Michigan's Surveys of Consumers, we show that comparisons among easy-to-reach respondents differ from comparisons among hard-to-reach ones. Notably, easy-to-reach women are happier than easy-to-reach men, but hard-to-reach men are happier than hard-to-reach women, and conclusions of a survey could reverse with more attempted calls. Better alternatives to comparing group sample averages might include putting greater weight on hard-to-reach respondents or even extrapolating trends in responses.

How high is unemployment? How low is labor force participation? Is obesity more prevalent among men? How large are household expenditures? We study the sources of the relevant official statistics—the Current Population Survey, the Behavioral Risk Factor Surveillance System, and the Consumer Expenditure Survey—and find that the answers depend on whether we look at easy- or at difficult-to-reach respondents, measured by the number of call and visit attempts made by interviewers. A challenge to the (conditionally-)random-nonresponse assumption, these findings empirically substantiate the theoretical warning against making population-wide estimates from surveys with low response rates.

How should a survey-based measure of well-being be implemented? How could it be constructed in a systematic and politically neutral way? These questions should be approached by economists with the same level of care that has been taken in the theoretical and practical development of GDP. We focus on two essential requirements for implementation: formulating a list of different aspects of well-being that is theoretically valid and can be measured accurately via surveys, and choosing and interpreting the survey response scales. We discuss progress to date on these issues, remaining challenges, and some possible approaches to overcoming them.

This paper proposes foundations and a methodology for survey-based tracking of well-being. First, we develop a theory in which utility depends on "fundamental aspects" of well-being, measurable with surveys. Second, drawing from psychologists, philosophers, and economists, we compile a comprehensive list of such aspects. Third, we demonstrate our proposed method for estimating the aspects' relative marginal utilities-a necessary input for constructing an individual-level well-being index-by asking ~4,600 U.S. survey respondents to state their preference between pairs of aspect bundles. We estimate high relative marginal utilities for aspects related to family, health, security, values, freedom, happiness, and life satisfaction.

We survey 561 students from US medical schools shortly after they submit choice rankings over residencies to the National Resident Matching Program. We elicit (i) these choice rankings, (ii) anticipated subjective well-being (SWB) rankings, and (iii) expected features of the residencies (such as prestige). We find substantial differences between choice and anticipated-SWB rankings in the implied trade-offs between residency features. In our data, evaluative SWB measures (life satisfaction and Cantril's Ladder) imply trade-offs closer to choice than does affective happiness (even time-integrated), and as close as do multimeasure SWB indices. We discuss implications for using SWB data in applied work. (JEL D12, I31)

We propose a social choice rule for aggregating preferences elicited from surveys into a marginal adjustment of policy from the status quo. The mechanism is: (i) symmetric in its treatment of survey respondents; (ii) ordinal, using only the orientation of respondents' indifference surfaces; (iii) local, using only preferences in the neighborhood of current policy; and (iv) what we call “first-order strategy-proof,” making the gains from misreporting preferences second order. The mechanism could be applied to guide policy based on how policy affects responses to subjective well-being surveys.

Would people choose what they think would maximize their subjective well-being (SWB)? We present survey respondents with hypothetical scenarios and elicit both choice and predicted SWB rankings of two alternatives. While choice and predicted SWB rankings usually coincide in our data, we find systematic reversals. We identify factors-such as predicted sense of purpose, control over one's life, family happiness, and social status-that help explain hypothetical choice controlling for predicted SWB. We explore how our findings vary by SWB measure and by scenario. Our results have implications regarding the use of SWB survey questions as a proxy for utility.