Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.

Essays in revealed preference theory and behavioral economics

Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.

Four essays in behavioral economics

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

PRESENTATION. Experimental and behavioral economics. Theory, tools and topics

This note presents the special issue on Experimental and Behavioral Economics. The volume includes some recent contributions from these correlated disciplines –empirical the former and theoretical the latter– and their potential contribution to the intersection of Economics with Psychology and Sociology. The project “El papel de la comparación social en las decisiones económicas bajo incertidumbre” (Junta de Andalucía, P07-SEJ-03155)” provided us with inspiration and financial support to publish this volume.

Behavioral economics, wearable devices, and cooperative games: results from a population-based intervention to increase physical activity

Background: Health care literature supports the development of accessible interventions that integrate behavioral economics, wearable devices, principles of evidence-based behavior change, and community support. However, there are limited real-world examples of large scale, population-based, member-driven reward platforms. Subsequently, a paucity of outcome data exists and health economic effects remain largely theoretical. To complicate matters, an emerging area of research is defining the role of Superusers, the small percentage of unusually engaged digital health participants who may influence other members. Objective: The objective of this preliminary study is to analyze descriptive data from GOODcoins, a self-guided, free-to-consumer engagement and rewards platform incentivizing walking, running and cycling. Registered members accessed the GOODcoins platform through PCs, tablets or mobile devices, and had the opportunity to sync wearables to track activity. Following registration, members were encouraged to join gamified group challenges and compare their progress with that of others. As members met challenge targets, they were rewarded with GOODcoins, which could be redeemed for planet- or people-friendly products. Methods: Outcome data were obtained from the GOODcoins custom SQL database. The reporting period was December 1, 2014 to May 1, 2015. Descriptive self-report data were analyzed using MySQL and MS Excel. Results: The study period includes data from 1298 users who were connected to an exercise tracking device. Females consisted of 52.6% (n=683) of the study population, 33.7% (n=438) were between the ages of 20-29, and 24.8% (n=322) were between the ages of 30-39. 77.5% (n=1006) of connected and active members met daily-recommended physical activity guidelines of 30 minutes, with a total daily average activity of 107 minutes (95% CI 90, 124). Of all connected and active users, 96.1% (n=1248) listed walking as their primary activity. For members who exchanged GOODcoins, the mean balance was 4,000 (95% CI 3850, 4150) at time of redemption, and 50.4% (n=61) of exchanges were for fitness or outdoor products, while 4.1% (n=5) were for food-related items. Participants were most likely to complete challenges when rewards were between 201-300 GOODcoins. Conclusions: The purpose of this study is to form a baseline for future research. Overall, results indicate that challenges and incentives may be effective for connected and active members, and may play a role in achieving daily-recommended activity guidelines. Registrants were typically younger, walking was the primary activity, and rewards were mainly exchanged for fitness or outdoor products. Remaining to be determined is whether members were already physically active at time of registration and are representative of healthy adherers, or were previously inactive and were incentivized to change their behavior. As challenges are gamified, there is an opportunity to investigate the role of superusers and healthy adherers, impacts on behavioral norms, and how cooperative games and incentives can be leveraged across stratified populations. Study limitations and future research agendas are discussed.

Essays in behavioral economics

In this work we conduct an experimental analysis on different behavioral models of economic choice. In particular, we analyze the role of overconfidence in shaping the beliefs of economics agents about the future path of their consumption or investment. We discuss the relevance of this bias in expectation formation both from a static and from a dynamic point of view and we analyze the effect of possible interventions aimed to achieve some policy goals. The methodology we follow is both theoretical and empirical. In particular, we make large use of controlled economic field experiments in order to test the predictions of the theoretical models we propose. In the second part of the thesis we discuss the role of cognition and personality in affecting economic preferences and choices. In this way we make a bridge between established psychological research and novel findings in economics. Finally, we conduct a field study on the role of incentives on education. We design different incentive schemes and we test, on randomized groups of students, their effectiveness in improving academic performance.

Behavioral Economics and Physician Behavior

This study seeks to answer whether the availability heuristic leads physicians to utilize more medical care than is economically efficient. Do rare, salient events alter physicians' perceptions about the probability of patient harm? Do these events lead physicians to overutilize certain medical procedures? This study uses Pennsylvania inpatient hospital admissions data from 2009 aggregated at the physician level to investigate these questions. The data come from the 2009 Pennsylvania Health Care Cost Containment Council (PHC4). The study is divided into two parts. In Part I, we examine whether bad outcomes during childbirth (defined as maternal mortality, an obstetric fistula or a uterine rupture) lead physicians to utilize more cesarean sections on future patients. In Part II, we examine whether bad outcomes associated with appendicitis (defined as patient death, a perforated or ruptured appendix or sepsis) lead physicians to perform more negative appendectomies (appendectomies performed when the patient did not have appendicitis) on future patients. Overall the study does not find evidence to support the claim that the availability heuristic leads physicians to overutilize medical care on future patients. However, the study does find evidence that variations in health care utilization are strongly correlated with individual physician practice patterns. The results of the study also imply that physicians' financial incentives may be a source of variation in health care utilization.

Behavioral economics: Reunifying psychology and economics

“Behavioral economics” improves the realism of the psychological assumptions underlying economic theory, promising to reunify psychology and economics in the process. Reunification should lead to better predictions about economic behavior and better policy prescriptions.

Exploration in responsible business behavior: an exercise in behavioral economics.

Cover title.

Essays in behavioral and neuro-economics

This thesis examines foundational questions in behavioral economics—also called psychology and economics—and the neural foundations of varied sources of utility. We have three primary aims: First, to provide the field of behavioral economics with psychological theories of behavior that are derived from neuroscience and to use those theories to identify novel evidence for behavioral biases. Second, we provide neural and micro foundations of behavioral preferences that give rise to well-documented empirical phenomena in behavioral economics. Finally, we show how a deep understanding of the neural foundations of these behavioral preferences can feed back into our theories of social preferences and reference-dependent utility.

The first chapter focuses on classical conditioning and its application in identifying the psychological underpinnings of a pricing phenomenon. We return to classical conditioning again in the third chapter where we use fMRI to identify varied sources of utility—here, reference dependent versus direct utility—and cross-validate our interpretation with a conditioning experiment. The second chapter engages social preferences and, more broadly, causative utility (wherein the decision-maker derives utility from making or avoiding particular choices).

Decision making under pressure : a behavioural economics perspective

This research investigates the decision making process of individuals from revealed preferences in extreme environments or life-and-death situations, from a behavioral economics perspective. The empirical analysis of revealed behavioral preferences shows how the individual decision making process can deviate from the standard self-interested or “homo economicus” model in non-standard situations. The environments examined include: elite athletes in FIFA World and Euro Cups; climbing on Everest and the Himalaya; communication during 9/11 and risk seeking after the 2011 Brisbane floods. The results reveal that the interaction of culture and environment has a significant impact on the decision process, as social behaviors and institutions are intimately intertwined, which govern the processes of human behavior and interaction. Additionally, that risk attitudes are not set and that immediate environmental factors can induce a significant shift in an individuals risk seeking behaviors.

Using Behavioral Insights For a Better Understanding of Economic Decisions (Regarding Savings, Inequality and Dishonesty)

This dissertation consists of three essays on behavioral economics, with a general aim of enriching our understanding of economic decisions using behavioral insights and experimental methodology. Each essay takes on one particular topic with this general aim.

The first chapter studies savings behavior of the poor. In this project, partnering with a savings product provider in Kenya, we tested the extent to which behavioral interventions and financial incentives can increase the saving rate of individuals with low and irregular income. Our experiment lasted for six months and included a total of twelve conditions. The control condition received weekly reminders and balance reporting via text messages. The treatment conditions received in addition one of the following interventions: (1) reminder text messages framed as if they came from the participant’s kid (2) a golden colored coin with numbers for each week of the trial, on which participants were asked to keep track of their weekly deposits (3) a match of weekly savings: The match was either 10% or 20% up to a certain amount per week. The match was either deposited at the end of each week or the highest possible match was deposited at the start of each week and was adjusted at the end. Among these interventions, by far the most effective was the coin: Those in the coin condition saved on average the highest amount and more than twice as those in the control condition. We hypothesize that being a tangible track-keeping object; the coin made subjects remember to save more often. Our results support the line of literature suggesting that saving decisions involve psychological aspects and that policy makers and product designers should take these influences into account.

The second chapter is related to views towards inequality. In this project, we investigate how the perceived fairness of income distributions depends on the beliefs about the process that generated the inequality. Specifically, we examine how two crucial features of this process affect fairness views: (1) Procedural justice - equal treatment of all, (2) Agency - one's ability to determine his/her income. We do this in a lab experiment by varying the equality of opportunity (procedural justice), and one's ability to make choices, which consequently influence subjects’ ability to influence their income (agency). We then elicit ex-post redistribution decisions of the earnings as a function of these two elements. Our results suggest both agency and procedural justice matter for fairness. Our main findings can be summarized as follows: (1) Highlighting the importance of agency, we find that inequality resulting from risk is considered to be fair only when risk is chosen freely; (2) Highlighting the importance of procedural justice, we find that introducing inequality of opportunity significantly increases redistribution, however the share of subjects redistributing none remain close to the share of subjects redistributing fully revealing an underlying heterogeneity in the population about how fairness views should account for inequality of opportunity.

The third chapter is on morality. In this project, we study whether religious rituals act as an internal reminder for basic moral principles and thus affect moral judgments. To this end, we conducted two survey experiments in Turkey and Israel to specifically test the effect of Ramadan and Yom Kippur. The results from the Turkish sample how that Ramadan has a significant effect on moral judgments to some extent for those who report to believe in God. Those who believe in God judged the moral acceptability of ten out of sixty one actions significantly differently in Ramadan, whereas those who reported not to believe in God significantly changed their judgments only for one action in Ramadan. Our results extends the hypothesis established by lab experiments that religious reminders have a significant effect on morality, by testing it in the field in the natural environment of religious rituals.

This thesis is part of a broader collaborative research agenda with both colleagues and advisors. The programming, analyses, and writing, as well as any errors in this work, are my own.

Present bias predicts participation in payments for environmental services: evidence from a behavioral experiment in Uganda

Farmers are necessary agents in global efforts to conserve the environment now that croplands and pastures together constitute the largest terrestrial system on Earth – covering some 48% of ice-free land surface. Whereas standard economic models predict that farmers will participate in conservation programs so long as they are profitable, empirical findings from behavioral economics point to a number of normally unobservable preferences that may influence the decision-making process. This study tests, for the first time, whether heterogeneity in behavioral preferences correlates with decisions to participate in Payments for Environmental Services (PES) programs. We elicit individual trust and time preferences using economic experiments and link resulting measures to household survey data and participation decisions in a Ugandan PES program. We find that farmers who exhibit a preference for proximate gains – present-biased preferences – are 47.7% more likely to participate in the program than those who show time-consistent or future-biased preferences. This result has implications for ongoing and planned PES programs involving farmers, particularly in Africa, by highlighting a potential relationship between payment timing and participation, and further validates the use of behavioral experiments in explaining real-world decisions.

A study of behavioral finance: background, theories and application

Behavioral finance, or behavioral economics, consists of a theoretical field of research stating that consequent psychological and behavioral variables are involved in financial activities such as corporate finance and investment decisions (i.e. asset allocation, portfolio management and so on). This field has known an increasing interest from scholar and financial professionals since episodes of multiple speculative bubbles and financial crises. Indeed, practical incoherencies between economic events and traditional neoclassical financial theories had pushed more and more researchers to look for new and broader models and theories. The purpose of this work is to present the field of research, still ill-known by a vast majority. This work is thus a survey that introduces its origins and its main theories, while contrasting them with traditional finance theories still predominant nowadays. The main question guiding this work would be to see if this area of inquiry is able to provide better explanations for real life market phenomenon. For that purpose, the study will present some market anomalies unsolved by traditional theories, which have been recently addressed by behavioral finance researchers. In addition, it presents a practical application of portfolio management, comparing asset allocation under the traditional Markowitz’s approach to the Black-Litterman model, which incorporates some features of behavioral finance.