Boundedly Rational Behavior Research Articles

Mechanisms of investors’ bounded rationality and market herding effect by the stochastic Ising financial model

The widespread herding effect prevalent in China’s stock market is caused by investors’ bounded rationality behavior. However, the underlying mechanisms are not fully understood. This article aims to use the stochastic Ising financial model, which explains this problem from the perspective of Econophysics. The probability density function and power-law distribution of return data simulated by the stochastic Ising financial model show sharp peaks and fat tails, similar to the stylized facts of real Chinese stock market data. Further, we use this financial model to simulate herding behavior in the market. The results show that when the degree of investor irrationality (represented by β) increases, the Herd Effect Index (HERDI) also rises. When β exceeds a critical point, the HERDI index fluctuates more violently. Through empirical analysis, we find that there is an interactive relationship between investors’ bounded rational behavior and market herding effects, and this model can effectively explain these two phenomena.

CEO Current and Prospective Wealth Option Compensation and Corporate Social Responsibility: The Behavioral Agency Model

This study examines the relationship between CEO options compensation and corporate social responsibility (CSR) based on the behavioral agency model (BAM). The BAM assumes that the CEO is bounded by loss-aversion behavior. Using constructs from the BAM, i.e., CEO current and prospective wealth from their options compensation, this study examines the differing effects of CEO current wealth and prospective wealth on firms’ CSR strengths, CSR concerns, institutional CSR and technical CSR. Based on a sample of 1565 U.S. firms during 1996 to 2018, the study finds that CEO current wealth is negatively related to firms’ CSR strengths and CSR concerns. The study also finds that CEO prospective wealth is positively related to firms’ CSR strengths but is unrelated to CSR concerns. CEO current wealth is negatively related to institutional CSR, whereas CEO prospective wealth is positively related to institutional and technical CSR. CEO current (prospective) wealth is more strongly and negatively (positively) related to institutional CSR than technical CSR. This study indicates that designing CEO option compensation to align top managers’ interests with the stakeholder interests requires a greater understanding of how CEO bounded rationality behavior toward loss aversion and risk taking is influenced by their option compensation.

Feed-in tariff or sheep farming subsidy? Implications of promoting photovoltaic energy by solar sheep raising

This paper theoretically establishes a solar sheep game model under three cases to capture the friction among the stockholders including the government, PV investors, and shepherds. Nash equilibrium has been revealed for analyzing the impact of different policies on the benefits of each player. The results show that the implementation of the feed-in tariff (FIT) policy can maximize the government’s revenue. However, when the government focuses on promoting poverty alleviation for shepherds, the sheep farming (SF) subsidy policy is more efficient than FIT if the positive effect of the PV panel on sheep raising is not enough. Besides, dynamic system models are established either to study the bounded rationality behavior during the decision process in the long run. Thresholds regarding speed of decision adjusting for each player are found. Results also show the system will lose stability if players adjust their decisions too frequently. Based on data from Talatan and Cascadilla, numerical analysis has been applied to illustrate the managerial implications from the proposed model.

Uncertainty in boundedly rational household adaptation to environmental shocks.

Despite the growing calls to integrate realistic human behavior in sustainability science models, the representative rational agent prevails. This is especially problematic for climate change adaptation that relies on actions at various scales: from governments to individuals. Empirical evidence on individual adaptation to climate-induced hazards reveals diverse behavioral and social factors affecting economic considerations. Yet, implications of replacing the rational optimizer by realistic human behavior in nature-society systems models are poorly understood. Using an innovative evolutionary economic agent-based model we explore different framings regarding household adaptation behavior to floods, leveraging on behavioral data from a household survey in Miami, USA. We find that a representative rational agent significantly overestimates household adaptation diffusion and underestimates damages compared to boundedly rational behavior revealed from our survey. This "adaptation deficit" exhibited by a population of empirically informed agents is explained primarily by diverse "soft" adaptation constraints-awareness, social influences-rather than heterogeneity in financial constraints. Besides initial inequality disproportionally impacting low/medium adaptive capacity households post-flood, our findings suggest that even under a nearly complete adaptation diffusion, adaptation benefits are uneven, with late or less-efficient actions locking households to a path of higher damages, further exacerbating inequalities. Our exploratory modeling reveals that behavioral assumptions shape the uncertainty of physical factors, like exposure and objective effectiveness of flood-proofing measures, traditionally considered crucial in risk assessments. This unique combination of methods facilitates the assessment of cumulative and distributional effects of boundedly rational behavior essential for designing tailored climate adaptation policies, and for equitable sustainability transitions in general.

Formulation and solution for calibrating boundedly rational activity-travel assignment: An exploratory study

Parameter calibration of the traffic assignment models is vital to travel demand analysis and management. As an extension of the conventional traffic assignment, boundedly rational activity-travel assignment (BR-ATA) combines activity-based modeling and traffic assignment endogenously and can capture the interdependencies between high dimensional choice facets along the activity-travel patterns. The inclusion of multiple episodes of activity participation and bounded rationality behavior enlarges the choice space and poses a challenge for calibrating the BR-ATA models. In virtue of the multi-state supernetwork, this exploratory study formulates the BR-ATA calibration as an optimization problem and analyzes the influence of the two additional components on the calibration problem. Considering the temporal dimension, we also propose a dynamic formulation of the BR-ATA calibration problem. The simultaneous perturbation stochastic approximation algorithm is adopted to solve the proposed calibration problems. Numerical examples are presented to calibrate the activity-based travel demand for illustrations. The results demonstrate the feasibility of the solution method and show that the parameter characterizing the bounded rationality behavior has a significant effect on the convergence of the calibration solutions.

Exploring Lithuanian Real Estate Crowdfunding Investors’ Rationality

Abstract The research aims to assess how rational investors are in making real estate crowdfunding investment decisions and weather similar rationality investors share common individual-level characteristics. The research data was collected through an online survey and investors’ rationality was assessed according to risk & return and behavioral biases criteria. Results revealed that 18% of the respondents were rational and as much as 78.1% of them demonstrated bounded rationality behavior. Further clustering of bounded rationality investors identified three distinct clusters and suggested that bounded rationality proved to be largely based on established behavioral biases rather than on failing to understand and apply risk and return criteria. In terms of individual-level characteristics, rationality of real estate crowdfunding investors significantly related to their financial knowledge, but not to their age, sex, income level, education, occupation, residence and interface with finance sector.

Computing Quantal Stackelberg Equilibrium in Extensive-Form Games

Deployments of game-theoretic solution concepts in the real world have highlighted the necessity to consider human opponents' boundedly rational behavior. If subrationality is not addressed, the system can face significant losses in terms of expected utility. While there exist algorithms for computing optimal strategies to commit to when facing subrational decision-makers in one-shot interactions, these algorithms cannot be generalized for solving sequential scenarios because of the inherent curse of strategy-space dimensionality in sequential games and because humans act subrationally in each decision point separately. We study optimal strategies to commit to against subrational opponents in sequential games for the first time and make the following key contributions: (1) we prove the problem is NP-hard in general; (2) to enable further analysis, we introduce a non-fractional reformulation of the direct non-concave representation of the equilibrium; (3) we identify conditions under which the problem can be approximated in polynomial time in the size of the representation; (4) we show how an MILP can approximate the reformulation with a guaranteed bounded error, and (5) we experimentally demonstrate that our algorithm provides higher quality results several orders of magnitude faster than a baseline method for general non-linear optimization.

A macro traffic flow model with headway variation tendency and bounded rationality

The rapid adoption of sensor technology has upgraded the vehicular communication capacity, which enables the drivers to predict the traffic state (e.g. headway variation tendency (HVT)) based on the current traffic information. Meanwhile, in practice, the drivers would exhibit bounded rationality behavior in that they often perceive and respond to acceleration/deceleration only when the headway variation exceeds a certain threshold. The collective effect may greatly affect the driving behavior and traffic flow performance. In this study, we innovatively model the traffic flow macroscopically considering HVT and bounded rationality effect in the context of continuum model. Based on the linear stability theory, the stability condition of the above model is obtained. The KdV-Burgers equation of the model is derived to describe traffic jam propagation mechanism near the neutral stability line by applying the reductive perturbation method in nonlinear stability analysis. Results show that the HVT and bounded rationality behavior have a great impact on the traffic congestion and energy consumption.

Charging demand analysis framework for electric vehicles considering the bounded rationality behavior of users

A novel analytic framework is proposed for the charging demand of electric vehicles (EVs), which considers charging demand is primarily determined by the travel behavior. And the bounded rationality of the EV users in travel choices is focused in this paper. The activity-based analysis is expanded to divide the travel behavior of users into the transfer relationship between activity chains and the time-space transfer rule for each activity chain. The transfer relationship between different activity chains is established by the Bayesian method. Based on the cumulative prospect theory, we prioritize the bounded rationality of users in the selection of the travel mode, the departure time and the travel path. And the time-space transfer rule and the charging demand of EVs on each activity chain are described by combining the dynamic traffic assignment model. On this basis, the daily charging demand rule for EVs is revealed. Finally, a test traffic network and a real urban traffic network are used to study the travel behavior and daily charging demand of EVs. The simulation results show that the proposed method can effectively describe dynamic changes in the charging demands of EVs. In addition, the charging demand of EVs will be affected by the ownership rate of EVs, the service capacity of charging stations and the degree of the bounded rationality of users.

The Complexion of Multi-period Stackelberg Triopoly Game with Bounded Rationality

Stackelberg model is a dynamic model, in which two players with different scales and power players act sequentially. However, there are few literatures that apply complex oligopoly dynamics theory in this model. In this paper, based on a traditional Stackelberg model, we improve the model in Peng and Lu (Appl Math Comput 271:259–268, 2015) and construct a multi-period Stackelberg triopoly game model. One leader firm and two followers with bounded rationality behavior are considered. The leader’s decision-making variable, which is simplified as a constant in Peng and Lu’s paper, is observed by the followers in stage 1 in every period in this model. We arrive at the conclusion that the leader would have the first-move advantage even when the players adopt a gradient output adjustment process in a multi-period Stackelberg triopoly game model. The speeds of output adjustment form a three-dimensional stability region. In the equilibrium state, the outputs of the followers are one-third of the leader’s. With adjustment speed of the leader increasing, Stackelberg equilibrium would be broken at a certain point. The effect of adjustment speed on speed of convergence to equilibrium is also analyzed. Theoretical result and numerical simulation both demonstrate that the speed converging to equilibrium is slowing when the Lyapunov exponent increases. Strange attractor and the sensitivity on initial values are presented by numerical simulation, while feedback control method is used to eliminate chaos. Moreover, in the stage of periodic bifurcation outside the stability region, the increase of the adjustment speed of the leader could be incentive for choosing chaos. While in the chaos stage, the average profits of three firms are uncertain, which shows that the relative benefit is closely related to adjustment speed of bounded rationality.

Are People Subject to Persuasion Bias? Test of Degroot Model

Theoretical paper DeMarzo, Vayanos, and Zwiebel (2003) proposes a model of information aggregation in networks when individuals are subject to bias. The term persuasion refers to a particular form of boundedly rational behavior when individuals connected into a network do not account for repetition in the information they acquire. We argue that under the assumption that agents form their beliefs as a weighted average of all information available to them, the bias assumption is equivalent to a generalized version of the famous DeGroot model (DeGroot (1974)). We test the bias hypothesis against the (generalized) Bayesian updating model and find support for the bias hypothesis. We also found a positive correlation between how well a subject fits the generalized DeGroot model, compared to the alternative generalized Bayesian updating model, and their performance in the experiment. Data suggest that the generalized DeGroot model better accommodates other subjects' deviations from equilibrium, which explains the positive correlation.

Pareto-optimal matching allocation mechanisms for boundedly rational agents

Is the Pareto optimality of matching mechanisms robust to the introduction of boundedly rational behavior? To address this question I define a restrictive and a permissive notion of Pareto optimality and consider the large set of hierarchical exchange mechanisms which contains serial dictatorship as well as Gale’s top trading cycles. Fix a housing problem with boundedly rational agents and a hierarchical exchange mechanism. Consider the set of matchings that arise with all possible assignments of agents to initial endowments in the given mechanism. I show that this set is nested between the sets of Pareto optima according to the restrictive and the permissive notion. These containment relations are generally strict, even when deviations from rationality are minimal. In a similar vein, minimal deviations from rationality suffice for the set of outcomes of Gale’s top trading cycles with all possible initial endowments to differ from the set of outcomes of serial dictatorship with all possible orders of agents as dictators.

Quick response in fashion supply chains with retailers having boundedly rational managers

AbstractIn fashion retailing, inventory decisions are usually made by a human manager who is not necessarily perfectly rational. In this situation, the inventory decisions made may not always be optimal. At the same time, with advances in technology, fashion retailers have access to the latest market information and can implement the quick response (QR) system that is very helpful to systematically deal with market disruptions. In this paper, we explore the value of QR with the consideration of a boundedly rational human manager in the fashion retailing company. We show that for both cases, with and without QR, the human retail manager's level of bounded rationality significantly hurts the expected profits of the retailer and supply chain, but it does not hurt the manufacturer's expected profit. In addition, for both cases, with and without QR, we indicate how a minimum ordering quantity (MOQ) measure can be imposed by the manufacturer on the retailer, so that the manufacturer can benefit (in terms of expected profit) from the retailer's bounded rationality behavior. We further prove that if the manufacturer sets the MOQ to be the same as the retailer's theoretical optimal ordering quantity, the manufacturer will enjoy a higher profit with 50% chance, if the retailer is boundedly rational.

Discrete Choice and Rational Inattention: A General Equivalence Result

This note establishes a general equivalence between discrete choice and rational inattention models. We exploit convex-analytic properties of these models to show that the choice probabilities emerging from any additive random utility discrete choice model can be rationalized from a class of suitably generalized rational inattention models, and vice versa. Thus any discrete choice model can be given an interpretation in terms of boundedly rational behavior.

Formulation, existence, and computation of boundedly rational dynamic user equilibrium with fixed or endogenous user tolerance

This paper analyzes dynamic user equilibrium (DUE) that incorporates the notion of boundedly rational (BR) user behavior in the selection of departure times and routes. Intrinsically, the boundedly rational dynamic user equilibrium (BR-DUE) model we present assumes that travelers do not always seek the least costly route-and-departure-time choice. Rather, their perception of travel cost is affected by an indifference band describing travelers’ tolerance of the difference between their experienced travel costs and the minimum travel cost. An extension of the BR-DUE problem is the so-called variable tolerance dynamic user equilibrium (VT-BR-DUE) wherein endogenously determined tolerances may depend not only on paths, but also on the established path departure rates.This paper presents a unified approach for modeling both BR-DUE and VT-BR-DUE, which makes significant contributions to the model formulation, analysis of existence, solution characterization, and numerical computation of such problems. The VT-BR-DUE problem, together with the BR-DUE problem as a special case, is formulated as a variational inequality. We provide a very general existence result for VT-BR-DUE and BR-DUE that relies on assumptions weaker than those required for normal DUE models. Moreover, a characterization of the solution set is provided based on rigorous topological analysis. Finally, three computational algorithms with convergence results are proposed based on the VI and DVI formulations. Numerical studies are conducted to assess the proposed algorithms in terms of solution quality, convergence, and computational efficiency.

Efficiency or bounded rationality? Drivers of firm diversification strategies in Vietnam

Considering the case of diversified firms within a developing/transition country such as Vietnam, this paper investigates diversification relatedness while taking into account both firm- and industry-specific components. The high volatility of the dynamics of diversification observed in Vietnam suggests the hypothesis that firms decide to enter into new industries following a trial and error process, initiated by boundedly rational herding behaviors, i.e., firms follow the most commonly observed business combinations. Using a survivor-based (SB) measure of relatedness, we test the hypothesis of boundedly rational behavior. We find that both the probability of exit and the different performance measures (Return on sales and Total factor productivity) are not or are negatively correlated with SB-related diversification. This is in contrast to what has been observed in developed countries. However, using the SIC distance approach, we obtain the expected positive relationship between performance and relatedness in diversified firms. The conflicting result between these two relatedness indices therefore suggests there has been a trend in follow-up among inexperienced firms that imitate the direction and intensity of the diversification of dominating players within the industry (herd behavior). However, diversified firms gain experience over time and choose more efficient business combinations in subsequent entries. When we use the classical SIC-based approach, we find that greater diversification raises profitability, but only to an optimum relatedness point, beyond which the positive effect fades away. To control for the endogeneity of diversification relatedness and the serial correlation in error terms, we adopt an instrumental-variable two-stage least-squares estimation approach (IV-2SLS) with GMM treatment.

Learning to bid in sequential Dutch auctions

We propose an agent-based computational model to investigate sequential Dutch auctions with particular emphasis on markets for perishable goods and we take as an example wholesale fish markets. Buyers in these markets sell the fish they purchase on a retail market. The paper provides an original model of boundedly rational behavior for wholesale buyers׳ behavior incorporating learning to improve profits, conjectures as to the bids that will be made and fictitious learning. We analyze the dynamics of the aggregate price under different market conditions in order to explain the emergence of market price patterns such as the well-known declining price paradox and the empirically observed fact that the very last transactions in the day may be at a higher price. The proposed behavioral model provides alternative explanations for market price dynamics to those which depend on standard hypotheses such as diminishing marginal profits. Furthermore, agents learn the option value of having the possibility of bidding in later rounds. When confronted with random buyers, such as occasional participants or new entrants, they learn to bid in the optimal way without being conscious of the strategies of the other buyers. When faced with other buyers who are also learning their behavior still displays some of the characteristics learned in the simpler case even though the problem is not analytically tractable.

Boundedly-Rational vs. Optimization-Based Behavior: A Distinction Without a Difference

We prove that every well-defined behavioral rule can be interpreted as being optimization-based. Therefore, the categorical distinction between boundedly-rational behavior and optimization-based behavior asserted by Harstad and Selten (2013) does not entail a substantive difference.

Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets

Boundedly rational user equilibria (BRUE) represent traffic flow distribution patterns where travellers can take any route whose travel cost is within an ‘indifference band’ of the shortest path cost. Those traffic flow patterns satisfying the above condition constitute a set, named the BRUE solution set. It is important to obtain all the BRUE flow patterns, because it can help predict the variation of the link flow pattern in a traffic network under the boundedly rational behavior assumption. However, the methodology of constructing the BRUE set has been lacking in the established literature. This paper fills the gap by constructing the BRUE solution set on traffic networks with fixed demands. After defining ε-BRUE, where ε is the indifference band for the perceived travel cost, we formulate the ε-BRUE problem as a nonlinear complementarity problem (NCP), so that a BRUE solution can be obtained by solving a BRUE–NCP formulation. To obtain the BRUE solution set encompassing all BRUE flow patterns, we propose a methodology of generating acceptable path set which may be utilized under the boundedly rational behavior assumption. We show that with the increase of the indifference band, the acceptable path set that contains boundedly rational equilibrium flows will be augmented, and the critical values of indifference band to augment these path sets can be identified by solving a family of mathematical programs with equilibrium constraints (MPEC) sequentially. The BRUE solution set can then be obtained by assigning all traffic demands to the acceptable path set. Various numerical examples are given to illustrate our findings.

Understanding Behavioral Antitrust

Behavioral antitrust – the application to antitrust analysis of empirical evidence of robust behavioral deviations from strict rationality – is increasingly popular and hotly debated by legal scholars and the enforcement agencies alike. This Article shows, however, that both proponents and opponents of behavioral antitrust frequently and fundamentally misconstrue its methodology, treating concrete empirical phenomena as if they were broad hypothetical assumptions. Because of this fundamental methodological error, scholars often make three classes of mistakes in behavioral antitrust analyses: First, they fail to appreciate the variability and heterogeneity of behavioral phenomena; second, they disregard the concrete ways in which markets, firms, and other institutions both facilitate and inhibit rational behavior by antitrust actors; and, third, they erroneously equate all deviations from standard rationality with harm to competition. After establishing the central role of rationality assumptions in present-day antitrust and reviewing illustrative behavioral analyses across the field – from horizontal and vertical restraints, through monopolization, to merger enforcement practices – the Article examines the three classes of mistakes, their manifestation, and their consequences in antitrust scholarship. It concludes by offering two sets of essential lessons that the behavioral approach already can offer to make antitrust law and policy more realistic and effective in protecting competition: One concerning the value of case-specific evidence in antitrust adjudication and enforcement, the other showing how antitrust law can and should account for systematic and predictable boundedly rational behavior that is neither constant nor uniform.