The U.S. 2009 Tobacco Control Act opened the door for new antismoking policies by giving the Food and Drug Administration broad regulatory authority over the tobacco industry. We develop a behavioral welfare economics approach to conduct cost-benefit analysis of FDA tobacco regulations. We use a simple two-period model to develop expressions for the impact of tobacco control policies on social welfare. Our model includes: nudge and paternalistic regulations; an excise tax on cigarettes; internalities created by period 1 versus period 2 consumption; and externalities from cigarette consumption. Our analytical expressions show that in the presence of uncorrected internalities and externalities, a nudge or a tax to reduce cigarette consumption improves social welfare. In sharp contrast, a paternalistic regulation might either improve or worsen social welfare. Another important result is that the social welfare gains from new policies do not only depend on the size of the internalities and externalities, but also depend on the extent to which current policies already correct the problems. We link our analytical expressions to the graphical approach used in most previous studies and discuss the information needed to complete cost-benefit analysis of tobacco regulations. We use our model as a framework to reexamine the evidence base for strong conclusions about the size of the internalities, which is the key information needed.
PURPOSE This study exploits differences in the implementation of welfare reform across states and over time in the United States in the attempt to identify causal effects of welfare reform on youth arrests for drug-related crimes between 1990 and 2005, the period during which welfare reform unfolded. METHODOLOGY Using monthly arrest data from the U.S. Federal Bureau of Investigation's Uniform Crime Reports, we estimate the effects of welfare reform implementation on drug-related arrests among 15-17 year olds in the United States between 1990 and 2005. We use a difference-in-differences (DD) approach that exploits the implementation of welfare reform across states and over time to estimate effects for teens exposed to welfare reform. FINDINGS The findings, based on numerous different model specifications, suggest that welfare reform had no statistically significant effect on teen drug arrests. Most estimates were positive and suggestive of a small (3%) increase in arrests. ORIGINALITY/VALUE This study investigated the effects of a broad-based policy change that altered maternal employment, family income, and other family characteristics on youth drug arrests.
Unemployment insurance (UI) reduces the opportunity cost of leisure, but it is unknown whether this additional leisure time is physically active. To obtain unbiased estimates of the effect of UI on physically active leisure participation, I exploit changes in UI program legislation across US states and time. Using nationally representative monthly data between 2003 and 2010 from the Behavioral Risk Factor Surveillance System (BRFSS) and the American Time Use Survey (ATUS), I find evidence that both state UI eligibility expansions and increases in maximum allowable state UI benefits coincide with greater probability of physical activity among the recently unemployed. Based on point estimates, state UI eligibility expansions increased the probability of physical activity participation by 8-10 percentage points among the unemployed with less than a high school education, while a 10% increase in the maximum allowable state UI benefit increased the probability of physical activity by 0.3 to 0.6 percentage points among the unemployed who have completed high school or some college.
Child immunization is widely recognized as a cost-effective preventive medicine. Unfortunately, in India about 50% of the eligible children aged 12-23 months miss some essential vaccination. Though a positive association between maternal education and markers of child health like immunization has been long established, the literature has struggled to find a causal relationship, mainly because education is inextricably correlated with other socioeconomic variables like income. In this chapter, I propose a new instrument for women's education in India using the following facts. First, due to lack of sanitary facilities in schools, particularly rural schools, large number of girls drop out of school once they reach puberty. Second, age at menarche is largely determined by biological factors and not social factors. Together, age at menarche can explain variations in schooling, yet be independent of outcome variables like child immunization. I find that additional years of maternal schooling (conditional on strictly positive years of schooling) do increase the probability of complete immunization of children.
I investigate the well-known educational gradient in smoking. It is well established that, at least in recent decades, people with higher levels of education are less likely to smoke and, conditional on being a smoker, are more likely to quit than are people with less education. Using longitudinal data on lifetime smoking histories, I explore whether the educational gradient changes when one accounts for differences in the amount of information smokers have about the health risks associated with smoking. At the core of the analysis is a new way to measure not only the flow of information a person receives but also a person's stock of information in any year. I construct measures of the stock and flow of information with consumer magazine articles that discuss cigarette smoking and health. To calculate exposure, I predict individuals' reading of particular magazines and link predicted exposure to data on individual smoking status in every year of life. The analysis sample includes many individuals who started smoking in the 1930s and 1940s - well before scientific evidence had accumulated. After replicating the education gradient in terms of smoking cessation, I show that it is mostly explained by the interaction between educational attainment and the stock of knowledge individuals possess. The findings suggest that education affects whether and how a stock of health risk information induces people to quit smoking.
Misinterpretation of a negative test results in health screening may initiate less preventive effort and more future lifestyle-related disease. We predict that misinterpretation occurs more frequently among individuals with a low level of education compared with individuals with a high level of education. The empirical analyses are based on unique data from a randomized controlled screening experiment in Norway, NORCCAP (NORwegian Colorectal Cancer Prevention). The dataset consists of approximately 50,000 individuals, of whom 21,000 were invited to participate in a once only screening with sigmoidoscopy. For all individuals, we also have information on outpatient consultations and inpatient stays and education. The result of health behaviour is mainly measured by lifestyle-related diseases, such as COPD, hypertension and diabetes type 2, identified by ICD-10 codes. The results according to intention-to-treat indicate that screening does not increase the occurrence of lifestyle related diseases among individuals with a high level of education, while there is an increase for individuals with low levels of education. These results are supported by the further analyses among individuals with a negative screening test.
Virtually all parents want their children to succeed academically. How to achieve this goal, though, is far from clear. Specifically, the temporal spacing between adjacent births has been shown to affect educational outcomes. While many of these studies have produced substantial and statistically significant results, these results have been relatively narrow in their application due to data limitations. Using Colorado birth certificates matched to schooling outcomes, we investigate the relationship between birth spacing and educational attainment. We instrument birth spacing with a previous pregnancy that did not result in a live birth. We find no overall effect of spacing on either the first or second children’s grade 3–10 test scores. Stratifying by the sexes of the children, we find that when the first child is a boy and the second a girl, an extra year of spacing increases the first child’s math, reading, and writing test scores by 0.07–0.08 SD, while there is no impact on the second child. This is the first study to do such an analysis using matched large-scale birth and elementary to high school administrative data, and to leverage a very large dataset to stratify our results by the sexes of the children.
Empirical studies show that years of schooling are positively correlated with good health. The implication may go from education to health, from health to education, or from factors that influence both variables. We formalize a model that determines an individual’s demand for knowledge and health based on the causal effects, and study the impacts on the individual’s decisions of policy instruments such as subsidies on medical care, subsidizing schooling, income tax reduction, lump-sum transfers, and improving health at young age. Our results indicate that income redistribution policies may be the best instrument to improve welfare, while a medical care subsidy is the best instrument for longevity. Subsidies to medical care or education would require large imperfections in these markets to be more welfare improving than distributional policies.
Past neuroeconomics studies using neurophysiology methods (mainly fMRI) have revealed the neural basis of "boundedly rational" or "irrational" decision-making that violates normative economics theory. It is expected that the field of neuroeconomics will be merged with neurotransmitter research and clinical neuroscience. Here, we provide an overview of recent molecular neuroimaging studies to understand how central monoamine transmission is related to "irrational" decision-making. Empirical evidence suggests that central dopamine transmission might be related to distortion of subjective reward probability and noradrenaline and serotonin transmission might influence aversive emotional reaction to financial loss. Positron emission tomography (PET) is a powerful tool to understand the neurochemical basis of decision-making in vivo in human. This approach seems to be a promising direction to understand the neurobiology of impaired decision-making in neuropsychiatric disorders and may help to develop novel pharmacotherapy for them.
People display rich heterogeneity in decision-making, but from where do these individual differences originate? And what are the processes that underlie decision-making heterogeneity? In this chapter, we explore a 'neural trait approach' in which neuroscience measures of meaningful dispositional differences are used to illuminate the sources of variability in decision-making. We begin by outlining the neural trait approach, with a focus on two methods: resting state electroencephalography and structural magnetic resonance imaging. Next, we review innovative studies that have used these methodologies to explore time and social preferences in decision-making. We then outline future research considerations and close by discussing certain opportunities and challenges afforded by this research and the neural trait approach in general.
The study of eye movements may provide a "window to the soul", that is, a unique opportunity to investigate the mind and brain of humans and animals. In this chapter we argue that the study of eye movements may also be of use in neuroeconomics research. We first describe the types of eye movements that are of relevance in this context and outline their neural correlates. We then outline the key oculographic methods that are likely to be applied in neuroeconomics experiments and point out the advantages of oculomotor research over manual motor experiments. We address the long researched issue of the association between eye movements and visual attention. That research supports the benefit of studying eye movements as a concurrent level of analysis in addition to manual responses in order to better understand the temporal and spatial features of attention. We then review key literature on the pupil, which shows a close relationship between pupil dynamics and various cognitive and affective states. Finally, we summarise some important findings from oculomotor research in the field of neuroeconomics. It is concluded that the study of eye movements represents a convenient, objective and reliable method that may yield important additional data to better understand economic decision-making processes as well as their neurophysiological correlates.
All decision-making takes place under uncertainty, even in controlled laboratory circumstances. The Bayesian brain hypothesis, a widely accepted theoretical framework of brain function, prescribes that the brain uses probability distributions to store parameter values, rather than point estimates, and is thus able to use uncertainty on various parameters. This allows for investigating value-based decision-making under natural circumstances when information needs to be extracted from noisy input, and it may also impact on decisions based on propositional information. In this chapter, I present experimental approaches to neural representations of uncertainty in value-based decision-making.
Functional magnetic resonance imaging (fMRI) is undoubtedly one of the most common techniques used in the cognitive neurosciences and neuroeconomics. The methods section of fMRI papers are oftentimes filled with jargon. We hope to clarify this jargon by defining and explaining the most fundamental concepts. The present chapter has been written to target a broad audience of scholars and students and explains the principles of fMRI: The reader will learn what signals are measured in fMRI, how this measure relates to neural activity, and how fMRI data are most commonly analyzed. This includes a brief summary of physical, physiological, and statistical ideas. We further present a comprehensive step by step guide through a typical fMRI data analysis to provide scholars and students with the appropriate knowledge to understand basic fMRI methodology in research papers and to judge whether the presented analysis is meaningful and appropriately protected against the most common pitfalls in the field of neuroimaging.
Recent neuroscientific research on economic behaviour of consumers explores how individuals translate information into value in their brain, and what mechanisms underlie this process. The typical aim of this research is to establish how single attributes are valued and combined into a single utility, neglects findings in multi-attribute utility theory on how utility is achieved when both costs and benefits are involved. This chapter argues that it is important to consider how the marginal utility of costs and benefits changes in the respective presence of one another. This point is discussed by reviewing behavioural and brain imaging data that illuminate this interplay, with a focus on the implications on econometric models of consumer behaviour.
This study examined the neural basis of framing effects using life-death decision problems framed either positively in terms of lives saved or negatively in terms of lives lost in large group and small group contexts. Using functional MRI we found differential brain activations to the verbal and social cues embedded in the choice problems. In large group contexts, framing effects were significant where participants were more risk seeking under the negative (loss) framing than under the positive (gain) framing. This behavioral difference in risk preference was mainly regulated by the activation in the right inferior frontal gyrus, including the homologue of the Broca's area. In contrast, framing effects diminished in small group contexts while the insula and parietal lobe in the right hemisphere were distinctively activated, suggesting an important role of emotion in switching choice preference from an indecisive mode to a more consistent risk-taking inclination, governed by a kith-and-kin decision rationality.
Hormones are chemical messengers released into the body that change the probability of behavior. Because hormones are both measurable and manipulable they lend themselves to experimental methodology that can establish causal relationships. Neuroeconomics studies have shown hormones’ influence on decision-making using quantifiable treatment and outcome variables in economic and social contexts. This chapter provides background and methodology for hormonal research in neuroeconomics and reviews significant studies on how oxytocin, testosterone, arginine vasopressin, dopamine, serotonin, and stress hormones impact decisions, and how research can be used to improve decisions and the business of life.
Affective shifts are critical factors in our decision-making with respect to all our survival concerns, including high cognitive ones such as those related to our economic investments and divestments. A critical emotional system, not commonly considered in neuroeconomics, is our primary process subcortical SEEKING system that regulates our exploratory-investigatory urges, including the eager anticipations of our higher mental processes. In economic decision-making, our SEEKING urge motivates us to consider the diverse opportunities and risks that are inherent in life-supportive decision-making. This state of mind, at normal levels of activity, energizes focus on cognitive details that can promote opportunities for success as well as avoid costly mistakes. However, excessive activity in this system may also promote faulty (addictive?) decision-making that is common in gambling, when hopes outweigh consideration of risks (as might be mediated by the cognitive representatives of FEAR and PANIC system). It is well known that all drug addictions are mediated by the feelings of euphoria that the SEEKING system can promote. Clearly, the ancient emotional systems of the brain need to be considered as motivators of neuroeconomic decisions, but they also need to be understood as primal motivations which need to be disciplined by higher decision-making capacities that emerge developmentally as a function of the losses and gains that have resulted from the vicissitudes of living in at times predictable but also unpredictable social (and physical) worlds. Without developmentally emergent cognitive discipline, the SEEKING system can promote delusional thinking.
We present an outline of a model for how the subjective experience of time influences decision-making. First, an individual's time perspective determines how strongly attention is directed to time. A stronger emphasis on the present perspective at the expense of the future perspective—as seen in impulsive individuals—leads to a stronger focus on the passage of time in waiting situations. This in turn causes longer estimates of duration. In intertemporal decisions, a relative overestimation of duration can lead to the perception of delayed rewards lying too far in the future. As a consequence, the value of a future commodity is discounted and more immediate but less valuable rewards are preferred. We present empirical evidence on the relationship between time perception and intertemporal decision-making and discuss these findings within the respective psychological and neural models.
Approaches from neuroeconomy have recently received increased attention in the investigation of mental disorders. In this chapter, we will give an overview of concepts and paradigms from neuroeconomics that have been applied in different mental disorders and summarize first results in this emerging field. We focus, thereby, on 'social decision-making' which constitutes one of the main concepts of neuroeconomy. First findings suggest that these approaches may prove to be promising research tools in the investigation of social functioning, which is a prominent symptom domain in many mental disorders. In contrast to self-and observer-based questionnaires that have provided information on how interaction behaviour is subjectively perceived by the patients themselves or their social environment, the variety of exchange games from behavioural economy allow for a direct and, thus, unbiased assessment of interaction behaviour. So far, findings suggest that neuroeconomic tools are suited to uncover alterations in social interaction behaviour in mental disorders, such as anxiety disorders, depression, borderline personality disorder, attention-deficit/hyperactivity disorder, but also schizophrenia and autism. However, the investigation of social interaction behaviour in mental disorders poses particular challenges. Deficits in basal or complex cognitive functions, such as working memory, deficits in basal social cognitive processes, such as the recognition of emotional facial expressions and a lower socioeconomic status due to long periods of illness and unemployment can be assumed to affect interaction behaviour. These have to be disentangled for the purpose of characterizing social decision-making in mental disorders and understanding the causes underlying its alterations. The combination of neuroeconomic approaches and their elaborated quantitative models with methods from experimental psychology und cognitive neurosciences seems a promising avenue to achieve this goal.
Diffusion Tensor Imaging is a Magnet Resonance Imaging-technique that allows for the non-invasive in vivo assessment and delineation of white matter tracts. TheMagnetResonance signal is sensitized to the natural diffusion process of protons and a tensor model is fitted to the resulting data. By following the direction of the diffusion maximum across the brain, the process of tractography yields three-dimensional reconstructions of white matter tracts, which may be microstructurally analyzed by means of diffusivity parameters. Before the advent of Diffusion Tensor Imaging, studies of connectional anatomy in humans could only be conducted post-mortem. Diffusion Tensor Imaging has shifted neuroscientific attention from single brain regions to the networks connecting them. This, however, has not only extended our knowledge on brain networks but also on single loci being part of these networks. Although the biological substrates of Diffusion Tensor Imaging-derived parameters remain unclear to a certain extent, Diffusion Tensor Imaging and tractography have successfully informed many studies in the field of age-or training-related neuronal changes. In addition, it has been found to be applicable in clinical settings. However, Diffusion Tensor Imaging studies covering the fields of neuroeconomics and behavioral psychology are sparse. Two pioneer studies from these fields have successfully related personality characteristics of interest to Diffusion Tensor Imaging-and tractography-derived measures. This chapter tries to give an introduction to themechanisms ofDiffusion Tensor Imaging and will work to explain its utilization while highlighting limitations of Diffusion Tensor Imaging as well as examples of its successful applications.
