Economic Theory Of Choice Research Articles

A dopamine mechanism for reward maximization

Individual survival and evolutionary selection require biological organisms to maximize reward. Economic choice theories define the necessary and sufficient conditions, and neuronal signals of decision variables provide mechanistic explanations. Reinforcement learning (RL) formalisms use predictions, actions, and policies to maximize reward. Midbrain dopamine neurons code reward prediction errors (RPE) of subjective reward value suitable for RL. Electrical and optogenetic self-stimulation experiments demonstrate that monkeys and rodents repeat behaviors that result in dopamine excitation. Dopamine excitations reflect positive RPEs that increase reward predictions via RL; against increasing predictions, obtaining similar dopamine RPE signals again requires better rewards than before. The positive RPEs drive predictions higher again and thus advance a recursive reward-RPE-prediction iteration toward better and better rewards. Agents also avoid dopamine inhibitions that lower reward prediction via RL, which allows smaller rewards than before to elicit positive dopamine RPE signals and resume the iteration toward better rewards. In this way, dopamine RPE signals serve a causal mechanism that attracts agents via RL to the best rewards. The mechanism improves daily life and benefits evolutionary selection but may also induce restlessness and greed.

Pre-acquired Functional Connectivity Predicts Choice Inconsistency.

Economic choice theories usually assume that humans maximize utility in their choices. However, studies have shown that humans make inconsistent choices, leading to suboptimal behavior, even without context-dependent manipulations. Previous studies showed that activation in value and motor networks are associated with inconsistent choices at the moment of choice. Here, we investigated if the neural predispositions, measured before a choice task, can predict choice inconsistency in a later risky choice task. Using functional connectivity (FC) measures from resting-state functional magnetic resonance imaging (rsfMRI), derived before any choice was made, we aimed to predict subjects' inconsistency levels in a later-performed choice task. We hypothesized that rsfMRI FC measures extracted from value and motor brain areas would predict inconsistency. Forty subjects (21 females) completed a rsfMRI scan before performing a risky choice task. We compared models that were trained on FC that included only hypothesized value and motor regions with models trained on whole-brain FC. We found that both model types significantly predicted inconsistency levels. Moreover, even the whole-brain models relied mostly on FC between value and motor areas. For external validation, we used a neural network pretrained on FC matrices of 37,000 subjects and fine-tuned it on our data and again showed significant predictions. Together, this shows that the tendency for choice inconsistency is predicted by predispositions of the nervous system and that synchrony between the motor and value networks plays a crucial role in this tendency.

Phylogenetic Economics: Animal Models and the Study of Choice

AbstractWhile the investigation of non-human economic decision-making is increasingly popular, it is not clear exactly what role it can play in settling debates in economics. This paper argues that—contrary to recent claims otherwise—data on animal decision-making do not help in (dis–)confirming economic theories of choice. Rather, such data help in spelling out the representationally proper domains of models of choice. To play this role, though, these data must be placed into phylogenetic comparative analyses: correlations with specific environmental features need to be assessed, and these correlations need to be corrected for the presence of phylogenetic signals.

Estimating demand systems with corner solutions: the performance of Tobit-based approaches

ABSTRACT Since the introduction of the Tobit framework to perform estimation involving censored dependent variables, practitioners have been facing a clear trade-off between flexibility and theoretical plausibility in modelling consumers’ preferences in the presence of zero consumptions; the Kuhn-Tucker (or virtual price) approach is rigorously based on the economic choice theory but cannot be applied to complex and flexible demand systems, whereas the Tobit-based approach can be applied to any class of demand systems but is deficient in the theoretical foundations on the underlying preferences behind the observed choices. Hence, we assess the performance of three Tobit-based approaches (simple, correlated, and Amemiya-Tobin) and explore the extent of possible biases in elasticity estimates to provide reasonable criteria for model selection. Our analysis concludes that theoretical restrictions implied by the choice theory are essential to the Tobit model and improve its ability to capture the true underlying elasticities and mitigate overrejections. However, the performance of the Tobit models gradually deteriorates as the number of zero consumptions increases; the average rejection rate against the true elasticity values increases substantially as we have more zero consumptions. We illustrate the performance differences among the three Tobit models by applying them to the estimation of demand for fruits and vegetables.

Nudges, regulations, and behavioral public choice.

Chater & Loewenstein have done a service to the field by raising the fundamental issue of how the political process distorts well-intentioned efforts at behavioral public policy. We connect this argument to broader research on government failure, particularly public choice theory in economics. We further suggest ways that behavioral research can help identify and mitigate such failures.

Shedding Light on the “Eclipse” Narrative: Some Notes on Pragmatism in the Twentieth Century

Shedding Light on the “Eclipse” Narrative: Some Notes on Pragmatism in the Twentieth Century

Preferences for nutrients and sensory food qualities identify biological sources of economic values in monkeys

Value is a foundational concept in reinforcement learning and economic choice theory. In these frameworks, individuals choose by assigning values to objects and learn by updating values with experience. These theories have been instrumental for revealing influences of probability, risk, and delay on choices. However, they do not explain how values are shaped by intrinsic properties of the choice objects themselves. Here, we investigated how economic value derives from the biologically critical components of foods: their nutrients and sensory qualities. When monkeys chose nutrient-defined liquids, they consistently preferred fat and sugar to low-nutrient alternatives. Rather than maximizing energy indiscriminately, they seemed to assign subjective values to specific nutrients, flexibly trading them against offered reward amounts. Nutrient-value functions accurately modeled these preferences, predicted choices across contexts, and accounted for individual differences. The monkeys' preferences shifted their daily nutrient balance away from dietary reference points, contrary to ecological foraging models but resembling human suboptimal eating in free-choice situations. To identify the sensory basis of nutrient values, we developed engineering tools that measured food textures on biological surfaces, mimicking oral conditions. Subjective valuations of two key texture parameters-viscosity and sliding friction-explained the monkeys' fat preferences, suggesting a texture-sensing mechanism for nutrient values. Extended reinforcement learning and choice models identified candidate neuronal mechanisms for nutrient-sensitive decision-making. These findings indicate that nutrients and food textures constitute critical reward components that shape economic values. Our nutrient-choice paradigm represents a promising tool for studying food-reward mechanisms in primates to better understand human-like eating behavior and obesity.

Stated Preferences for the Adoption of IFRS and UK GAAP: Case Study Vignettes

Our aim is to see if the adoption of International Financial Reporting Standards (IFRS) is beneficial. Our methodology involved both quantitative methods (with non-parametric tests) and qualitative methods (with case study vignettes) in a complementary way, as in the ‘mixed method’. Our objective was to use a formal metric, adapted from economic choice theory, to analyze choosing behavior in firms over financial reporting standards, using calculated ratio and net utilities. Our evidence and analysis are based on a random sample of twenty-one UK firms. From these firms, primary source data were collected, using questionnaires and fieldwork interview tools, to enable the testing of our hypothesis that the adoption of IFRS was beneficial. Using robust non-parametric statistical tests, we found that public firms which had to adopt IFRS, as a matter of necessary policy compliance, often perceived this imposed choice to be unbeneficial, refuting our null hypothesis. This finding is highly statistically significant. The implication of our qualitative evidence was that this perception of lack of benefit in adopting IFRS created a voice for regulatory change.

Anterior Cingulate Cortex Lesions Abolish Budget Effects on Effort-Based Decision-Making in Rat Consumers.

Demand theory can be applied to analyze how animal consumers change their selection of commodities in response to changes in commodity prices, given budget constraints. Previous work has shown that demand elasticities in rats differed between uncompensated budget conditions in which the budget available to be spent on the commodities (e.g., the finite number of discrete operants to "purchase" rewards in two-alternative fixed-ratio schedules) was kept constant, and compensated budget conditions in which the budget was adjusted so that consumers could potentially continue to obtain the original reward bundles. Here, we hypothesized that rat anterior cingulate cortex (ACC) was necessary to produce this budget effect on demand elasticities. We applied excitotoxic or sham lesions to ACC in rats performing an effort task in which the prices of liquid vanilla or chocolate rewards (the effort required to obtain rewards) and the budget (the total number of operants) was manipulated. When reward prices changed, and the budget was compensated, all rats adjusted their demand for chocolate and vanilla accordingly. In sham-lesioned rats, changes in demand were even more pronounced when the budget was not compensated for the price changes. By contrast, ACC-lesioned animals did not show this additional budget effect. An in-depth comparison of the rats' choice patterns showed that, unlike sham rats, ACC-lesioned animals failed to maximize session-bundle utility after price/budget changes, revealing deficits in higher-order choice-strategy adaptations. Our results suggest a novel role of ACC in considering purchasing power during complex cost-benefit value computations.SIGNIFICANCE STATEMENT Anterior cingulate cortex (ACC) is important for allocating effort in cost-benefit calculations in animals and humans. Economic theory prescribes that the value of the costs in cost-benefit analyses not only depends on the net nominal costs required to purchase a reward, but also on the available budget resources, i.e., on the budget's "purchasing value." We asked whether ACC, a region implicated in effort-based decision-making and reward comparisons, is required for computing the value of effort relative to a budget constraint. Applying demand theory to describe rat choices in a rodent effort allocation task with varying effort prices and budgets, we show that ACC integrity was necessary for computing purchasing power, a core variable in economic choice theory.

Nonhuman Primates Satisfy Utility Maximization in Compliance with the Continuity Axiom of Expected Utility Theory.

Expected Utility Theory (EUT), the first axiomatic theory of risky choice, describes choices as a utility maximization process: decision makers assign a subjective value (utility) to each choice option and choose the one with the highest utility. The continuity axiom, central to Expected Utility Theory and its modifications, is a necessary and sufficient condition for the definition of numerical utilities. The axiom requires decision makers to be indifferent between a gamble and a specific probabilistic combination of a more preferred and a less preferred gamble. While previous studies demonstrated that monkeys choose according to combinations of objective reward magnitude and probability, a concept-driven experimental approach for assessing the axiomatically defined conditions for maximizing utility by animals is missing. We experimentally tested the continuity axiom for a broad class of gamble types in 4 male rhesus macaque monkeys, showing that their choice behavior complied with the existence of a numerical utility measure as defined by the economic theory. We used the numerical quantity specified in the continuity axiom to characterize subjective preferences in a magnitude-probability space. This mapping highlighted a trade-off relation between reward magnitudes and probabilities, compatible with the existence of a utility function underlying subjective value computation. These results support the existence of a numerical utility function able to describe choices, allowing for the investigation of the neuronal substrates responsible for coding such rigorously defined quantity.SIGNIFICANCE STATEMENT A common assumption of several economic choice theories is that decisions result from the comparison of subjectively assigned values (utilities). This study demonstrated the compliance of monkey behavior with the continuity axiom of Expected Utility Theory, implying a subjective magnitude-probability trade-off relation, which supports the existence of numerical utility directly linked to the theoretical economic framework. We determined a numerical utility measure able to describe choices, which can serve as a correlate for the neuronal activity in the quest for brain structures and mechanisms guiding decisions.

Covid‐19: Where We Are, What Got Us Here, and Where We Are Likely to Be Going—A Review Essay*

Covid‐19: Where We Are, What Got Us Here, and Where We Are Likely to Be Going—A Review Essay*

Izazovi racionalne teorije izbora u savremenoj ekonomskoj nauci

In the focus of the paper there are some basic insights and ideas of rational choice theory, that is the "core" of contemporary economic theory. Also, rational choice theory is the "center" of modern political science and is used in various other scientific disciplines, such as: sociology, philosophy, political science, psychology, and the like. There are two main goals of this paper. One is to point out the limitations of rational choice theory as one of the theories of economic behavior (and decision making). The second goal is to analyze certain problems detected during the application of the rational choice theory in economics and to adequately consider the importance of alternative concepts, models, and theories from the point of view of improving the understanding of economic, social, political, and other processes in the economy and society as a whole.

Mathematical Proof of the Ordinal Marginal Preference Theory

The model in which an individual maximizes the ordinal or cardinal total utility subject to her budget constraint has long been the paradigm of individual choice theory in economics. The ordinal total utility theory has the advantage of utility immeasurability, but the disadvantage of being inconsistent with common sense such as the principle of diminishing marginal utility. The cardinal total utility theory is consistent with the aforementioned common sense, but suffers from the problem of utility measurability. This leads to a dilemma when one develops a utility-maximization model: she either needs to abandon common sense, or needs to postulate measurability for utility. This puzzling riddle, as of today, is still unsolved. The purpose of this paper is to present a new theory — the ordinal marginal utility theory — to solve this puzzle, and offers a complete formal axiomatic proof.

Eye-tracking and economic theories of choice under risk

We examine the ability of eye movement data to help understand the determinants of decision-making over risky prospects. We start with structural models of choice under risk, and use that structure to inform what we identify from the use of process data in addition to choice data. We find that information on eye movements does significantly affect the extent and nature of probability weighting behavior. Our structural model allows us to show the pathway of the effect, rather than simply identifying a reduced form effect. This insight should be of importance for the normative design of choice mechanisms for risky products. We also show that decision-response duration is no substitute for the richer information provided by eye-tracking.

Preferences and Intentions of Seafood Consumers in Oman: An Empirical Analysis

This study examines the influence of product attributes and socio-economic, demographic, cultural, psychological, and market-related factors on “preferences” and “intention” of seafood consumers in Oman using the classical economic choice theory, the theory of planned behavior (TPB), and their hybrid form. Primary data were collected using questionnaires administered through online and face-to-face survey. A total of 906 responses were received from the online (N = 778), hypermarkets (N = 93), and fish market (N = 35) sources. Descriptive and empirical analyses were performed to the survey data. Findings from the preference model suggest that nationality, habit, freshness (perceived as quality), taste, household size, income, and education are significantly influencing the purchasing frequency of seafood. While consumer attitudes and control beliefs (i.e., facilitating conditions) are significant in the intention model, the hybrid model identifies additional significant variables such as past and current consumption behavior that influence consumers’ intention of seafood purchase. The findings will enable seafood firms and the concerned authorities to formulate appropriate management and marketing strategies.

Ordinal Marginal Preference Theory

The model in which an individual maximizes his total ordinal or cardinal utility subject to his budget constraint is a paradigm of individual choice theory in economics. The advantage of ordinal utility theory is that utility is immeasurable, but it is inconsistent with common sense, for example, as in the principle of diminishing marginal utility and complementarity defined by cross-derivatives of utility. The advantage of cardinal utility theory is its consistency with common sense, but its problem is that utility is measurable. This leads to a dilemma whenever an economist creates a utility maximization model, as they must either abandon common sense or postulate that utility is measurable. The conundrum of how to develop a utility theory that is immune to this dilemma has remained unsolved until today. This paper presents an ordinal marginal utility theory that solves this puzzle.

Visualizing aggregate movement in cities.

We argue here that despite the focus in cities on location and place, it is increasingly clear that a requisite understanding of how cities evolve and change depends on a thorough understanding of human movements at aggregate scales where we can observe emergent patterns in networks and flow systems. We argue that the location of activities must be understood as summations or syntheses of movements or flows, with a much clearer link between flows, activities and the networks that carry and support them. To this end, we introduce a generic class of models that enable aggregated flows of many different kinds of social and economic activity, ranging from the journey to work to email traffic, to be predicted using ideas from discrete choice theory in economics which has analogies to gravitation. We also argue that visualization is an essential construct in making sense of flows but that there are important limitations to illustrating pictorially systems with millions of component parts. To demonstrate these, we introduce a class of generic spatial interaction models and present two illustrations. Our first application is based on transit flows within the high-frequency city over very short time periods of minutes and hours for data from the London Underground. Our second application scales up these models from districts and cities to the nation, and we demonstrate how flows of people from home to work and vice versa define cities and related settlements at much coarser scales. We contrast this approach with more disaggregate, individual studies of flow systems in cities that we consider an essential complement to the ideas presented here.This article is part of the theme issue ‘Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour’.

Applied Choice Analysis, 2nd edn, by David AHensher, John MRose and William HGreene. Published by Cambridge University Press, Cambridge, UK, 2015, pp. 1188, ISBN: 9781107092648 (Hardback), 9781107465923 (Paperback), AUD$155 (Paperback)

As a newcomer to the world of choice modelling, I sometimes get lost in the complicated world between economic choice theory, econometrics and statistics. Applied Choice Analysis Second Edition is a light to help you find your way. Though the reading itself is certainly not ‘light’, it is a substantially sized reference book that accidently ended up as an epic stand for my computer screen. However, it was quickly upgraded to prime position as a key reference because it provides a clear and comprehensive coverage of the theory and econometrics of choice modelling. This book is of interest both to the novice choice modeller and to the more experienced practitioner. The authors are prominent choice analysts and have developed this reference book while teaching graduate courses – and it shows. They explain all things choice modelling, without unnecessary technical language or jargon. This second edition was written in response to feedback on their first edition Applied Choice Analysis A primer and includes advances made since writing the first edition in 2004. The authors added numerous new sections, including generalised mixed logit, latent class analysis and a whole new chapter on more advanced topics. I notice that this Second Edition has a more relaxed conversational writing style (which is impressive given the technical nature of the content) and uses more examples to demonstrate theory and techniques. I also prefer the new formatting to increase readability and I particularly appreciate the overhanging chapter titles that makes finding sections easier. The book is generally structured by first introducing the relevant theory and concepts followed by using Nlogit as the software to demonstrate applications of the theory. The book is presented in three parts. Part I ‘Getting started’ covers topics in choice and utility, types and estimation of discrete choice models, experimental design and statistical inference. This first part provides 384 pages of choice modelling theory for your enjoyment, providing extensive background reading for any beginner or essential reference material for experienced practitioners. Towards the end of this section, there is an historical overview of the evolution of experimental design theory which more experienced users may find interesting. The next shorter section, Part II ‘Software and data’, moves into the more technical side of data analysis using the software Nlogit. This section introduces Nlogit and the software language and details the data set-up requirements for analysing discrete choice data sets in Nlogit. Part III ‘The suite of choice models’ is described by the authors as a ‘journey’, beginning with the multinominal logit model (the ‘workhorse’ of the choice modeller) through to more complex model specifications, such as nested, mixed and latent class logit models. This third part may be challenging for the novice reader, but essential material if you want to learn about the variety in choice models that is (or has been) used in the literature. The final Part IV ‘Advanced Topics’ is a new section that highlights some of the recent advancements to choice modelling, covering nonlinearity in parameter estimates, process heuristics and group decision-making. If you were lost in Part III, then you may need rescuing now. However, this is an interesting and important additional chapter as it begins to detail the frontiers of choice modelling and will be particularly useful for more advanced researchers and practitioners. The authors claim that this book is usable for the beginner, as I consider myself to be. Evidently, the authors assume you might be a beginner to choice modelling and not to econometrics or statistics, as for this second edition they have removed the introductory chapter on the Basic notions of statistics. This may not be a problem for most users who will have some background. Furthermore, the authors make every effort to bring you along regardless of your level by explaining concepts from the beginning, using examples and clear accessible language. While extremely useful for most choice modellers, the close integration with Nlogit software language and examples may provide some frustrations for practitioners who prefer different software. For example, preparing raw choice data for analysis can be a serious source of confusion. This book provides specific guidance for setting up data for use in Nlogit, which may be incomplete for researchers who are using other software. Despite the fact that I use different software, I find myself referring to this key reference book regularly on all topics from utility theory to complex model specifications, and I should probably refer to it more often. Finally, on the days when I cannot face any equations, I still find this text surprisingly readable and useful. I recommend this book to anyone, either beginning their choice modelling journey or looking to deepen their knowledge.

From the Firm to Economic Policy: The Problem of Coase's Cost

One of Ronald Coase's insights was to extend the economic theory of choice to include the policy choice among institutional arrangements, which had to be analyzed with the same framework as the producer's choice. Both choices, he argued, are amenable to an opportunity-cost approach. The similarity he points to, however, is somewhat limited: while some of his articles from the 1930s stressed the subjectivity of producers' decisions, his later criticisms of standard policies, as well as the method he suggests for the design of policy, are based on the idea that costs are objective and measurable. Are the subjective aspects of the production decision reconcilable with the objective aspects of the policy decision in Coase's analysis? I shall argue that the framework he adopts is objectivist or subjectivist depending on the nature of the criticism he is leveling against standard theory and on the type of decision he is studying. Eventually he did propose a univocal analysis—an objectivist one—of the producer's decision between making and buying and the policy decision among institutional arrangements. This essay initiates a study of Coase's theory of decision. It returns to his subjectivist account of choice and contributes to solving the apparent contradiction between the subjectivist young Coase and the more mature objectivist scholar. It thereby sets out the diversity of the criticisms that Coase levels against standard theory and shows the evolution of his strategy. Ultimately, the problem of the difference between Coase's analyses of production decisions and policy decisions is more subtle than simply being an apparent contradiction: it turns on the subjectivity of individual decisions having no consequence for his analysis of policy.

Neuronal Reward and Decision Signals: From Theories to Data.

Rewards are crucial objects that induce learning, approach behavior, choices, and emotions. Whereas emotions are difficult to investigate in animals, the learning function is mediated by neuronal reward prediction error signals which implement basic constructs of reinforcement learning theory. These signals are found in dopamine neurons, which emit a global reward signal to striatum and frontal cortex, and in specific neurons in striatum, amygdala, and frontal cortex projecting to select neuronal populations. The approach and choice functions involve subjective value, which is objectively assessed by behavioral choices eliciting internal, subjective reward preferences. Utility is the formal mathematical characterization of subjective value and a prime decision variable in economic choice theory. It is coded as utility prediction error by phasic dopamine responses. Utility can incorporate various influences, including risk, delay, effort, and social interaction. Appropriate for formal decision mechanisms, rewards are coded as object value, action value, difference value, and chosen value by specific neurons. Although all reward, reinforcement, and decision variables are theoretical constructs, their neuronal signals constitute measurable physical implementations and as such confirm the validity of these concepts. The neuronal reward signals provide guidance for behavior while constraining the free will to act.