Framework Of Bounded Rationality Research Articles

Refining expected market return estimation: fusing multiple valuation models as an approach to reducing uncertainty

This paper presents a methodology aimed at reducing the uncertainty associated with estimating the expected market return within a bounded rationality framework. The proposed approach involves calculating the implicit rate of return using various valuation models and subsequently merging them using the Kalman Filter technique to minimize estimation errors. The contribution of this study lies in the application of the Kalman Filter, which enables the expected market return to be refined and provides a more accurate estimate by mitigating uncertainty. The ability to determine an accurately expected market return assumes critical significance in investment decision-making. Therefore, investors can utilize this methodology as a tool to enhance the precision of their investment choices. By reducing uncertainty in estimating the expected market return, this approach empowers investors to make more informed and confident decisions.

Bounded rational expectation: How it can affect the effectiveness of monetary rules in the open economy

Since the channel for agents’ expectations matters for the effectiveness of monetary policies, it is crucial for policy-makers to assess the degree to which economic agents are boundedly rational and understand how the bounded rationality affects the monetary rules in stabilising the economy. We investigate the empirical evidence for the bounded rationality in a small open economy model of the UK, and compare the results with those for the conventional rational expectations model. Overall, comparing the estimated models favours the bounded rationality framework. The results show that bounded rationality model helps to explain the hump-shaped dynamics of real exchange rate following monetary shocks, while the rational expectations model cannot. Also, we find that the exchange rate channel in the bounded rationality enlarges the effects of foreign mark-up shock, policymakers should send stronger signals over its target to the economics agents to combat the inflation. So the bounded rationality that can be found in the data still leaves scope for the forward guidance channel to work strongly enough to be exploited by policymakers.

Mixed messages & bounded rationality: The perverse consequences of real ID for immigration policy

AbstractPolicies concerning undocumented immigrants are inevitably ambivalent, creating uncertainty and confusion in the implementation process. We identify a clear example of this ambivalence —U.S. law setting standards for determining the credibility of asylum seekers—that resulted in an increase in asylum grants despite policymakers' intention to make it harder for individuals to obtain the status. We argue that this law, The REAL ID Act of 2005, sent mixed messages to immigration judges (IJs), street‐level bureaucrats who implement immigration policy. It increased IJ discretion, but set vague limits. We theorize that IJs, behaving in a bounded rationality framework, use their professional legal training as a short‐cut and look primarily to the courts for guidance. Our evidence supports our argument. After the passage of the REAL ID Act, IJ decision‐making is more closely aligned with the preferences of their political and legal principals, and, in the final score, the federal circuit courts are the winners.

Monetary and Macro-Prudential Mandates in a New Keynesian Behavioural Framework

This paper examines the conduct of optimal monetary and macro-prudential mandates in a behavioural bounded rationality framework with a financial friction in form of the collateral constraint. A mandate framework is designed where each macroeconomic regulator is assigned a distinct objective function, is instrument-independent and the welfare-optimal parameters of these delegated mandate are computed. Cooperative and non-cooperative mandates games between the monetary and macro-prudential regulation are studied and comparisons drawn between results for rational expectations (RE) and BR models. The main results are: first, in a Bayesian likelihood race the BR model easily outperforms the RE model. Second, the BR model has much larger region of determinacy compared with RE; i.e., the Taylor principle is easier to satisfy under BR. Third, forward guidance is much less powerful under the BR model; i.e., the “forward-guidance puzzle is resolved. Finally, we confirm a common result in this literature that monetary and macro-prudential cooperation is welfare reducing compared with non-cooperation.

Deciding to Apply for Federal Disaster Assistance: A Preliminary Investigation of Disaster Decision-Making using a Bounded Rationality Framework

AbstractAmong disaster victims, the decision to apply for assistance with the Federal Emergency Management Agency (FEMA) is not straight forward. It is typically affected a variety of factors beyond individual demographic characteristics. Using Texas in the aftermath of Hurricane Harvey, this study utilizes bounded rationality as a theoretical framework for exploring what may affect the decision to apply for individual assistance with FEMA. A representative sample of generally affected individuals and a subsample of individuals with home damage are used to investigate various factors thought to be important in decision-making and compare differences between the groups. As a byproduct of the analysis, it is observed that although the loss of employment and being able to rely on one’s immediate network is a significant predictor of applying for aid among individuals with home damage, these variables are not significant among those that were generally affected. Recommendations for future research are provided to enhance our understanding of decision-making in the aftermath of disasters.

Bounded Blame: The Effects of Victim-Perpetrator Relationship and Victimization History on Judgments of Sexual Violence.

Individuals often tend to irrationally blame victims for their plight. This research incorporated a bounded rationality framework to examine first-person perspectives (rather than third-person) of both victims' and nonvictims' perceptions and judgments of acquaintance and stranger sexual violence. Upon completing individual difference measures, including a just-world belief assessment, participants (N = 296) were randomly assigned to read a scenario in which the vignette victim was either acquainted with or had no prior relationship with the perpetrator. Then, taking the perspective of the vignette victim, participants offered four judgments: the likelihood of reporting the crime, self-blame, perceived control, and sympathy expected from others. Results showed that instances of acquaintance sexual violence were judged more negatively than instances of stranger sexual violence. Moreover, participants who had previously experienced sexual violence reported more negative judgments than nonvictims (except for sympathy expected from others). An exploratory path analysis indicated that as nonvictims', but not victims', just-world beliefs became stronger, they indicated a higher willingness to report the crime, perceived more control over the situation, and expected more sympathy from others. We end with a discussion of how the present research can advance our understanding of sexual violence by using a bounded rationality framework and discuss the practical implications that the observed effects have for professionals in the legal system, outside observers, and victims themselves.

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When Waiting Is Not an Option: Learning Options With a Deliberation Cost

Recent work has shown that temporally extended actions (options) can be learned fully end-to-end as opposed to being specified in advance. While the problem of how to learn options is increasingly well understood, the question of what good options should be has remained elusive. We formulate our answer to what good options should be in the bounded rationality framework (Simon, 1957) through the notion of deliberation cost. We then derive practical gradient-based learning algorithms to implement this objective. Our results in the Arcade Learning Environment (ALE) show increased performance and interpretability.

Surviving Information Overload: How Elite Politicians Select Information

Information in politics is overabundant. Especially elite politicians are bombarded with information. Politicians must be selective to stay on top of the information torrent. Aggregate‐level work within the bounded rationality framework showed that information selection is at the core of decision making. Yet, an answer to the question as to how individual elite politicians go about selecting information is lacking. We know that they unavoidably do, but how exactly they perform this selection task remains largely unknown. The article draws on interviews with 14 party leaders and ministers in Belgium about their information processing. We present a typology, and a funnel, of consecutive information selection mechanisms and attitudes. Politicians partially outsource their information selection to procedures and/or staffers, they personally apply rigorous rules of thumb about what to attend to and what not, and they compensate the pressure and constant risk of messing up with a large dose of self‐confidence.

Modeling networked systems using the topologically distributed bounded rationality framework

In networked systems research, game theory is increasingly used to model a number of scenarios where distributed decision making takes place in a competitive environment. These scenarios include peer‐to‐peer network formation and routing, computer security level allocation, and TCP congestion control. It has been shown, however, that such modeling has met with limited success in capturing the real‐world behavior of computing systems. One of the main reasons for this drawback is that, whereas classical game theory assumes perfect rationality of players, real world entities in such settings have limited information, and cognitive ability which hinders their decision making. Meanwhile, new bounded rationality models have been proposed in networked game theory which take into account the topology of the network. In this article, we demonstrate that game‐theoretic modeling of computing systems would be much more accurate if a topologically distributed bounded rationality model is used. In particular, we consider (a) link formation on peer‐to‐peer overlay networks (b) assigning security levels to computers in computer networks (c) routing in peer‐to‐peer overlay networks, and show that in each of these scenarios, the accuracy of the modeling improves very significantly when topological models of bounded rationality are applied in the modeling process. Our results indicate that it is possible to use game theory to model competitive scenarios in networked systems in a way that closely reflects real world behavior, topology, and dynamics of such systems. © 2016 Wiley Periodicals, Inc. Complexity 21: 123–137, 2016

‘Milk is Milk’: Organic Dairy Adoption Decisions and Bounded Rationality

Bounded rationality is an especially appropriate framework for organic dairy adoption decisions as it recognizes internal and external constraints which are critical in understanding complex farm decision making. Farmers use of, and access to, information is examined using interview data gathered from organic, conventional, managed graziers, and Amish dairy farmers in Southwestern Wisconsin at a time when organic milk prices offered a 50% premium over conventional prices. Focusing on certain aspects and impressions of organic dairy, such as the sentiment that “milk is milk”, may lead to information satisficing where farmers do not take full advantage of the information available to them. Organic farmer interviews reveal the challenges they faced with bounded rationality constraints and how they countered these challenges with the help of social networks, as well as how situational factors such as economic and health crises may have motivated them to adopt organic dairy. The interview data from organic and conventional farmers alike also reveals how many conventional dairy farmers utilized information strategies which did not fully consider the pros and cons of the organic system. A bounded rationality framework could enlighten policy makers and educators as they tailor sustainable agricultural policy design and information dissemination strategies to serve the diversity of farmers on the landscape.

Bounded Rationality and the Diffusion of Modern Investment Treaties

Given the considerable sovereignty costs involved, the adoption of modern investment treaties by practically all developing countries presents somewhat of a puzzle. Based on a review of leading explanations of investment treaty diffusion, the article advances a new theory using behavioral economics insights on cognitive heuristics. In line with recent work on policy diffusion, it suggests that a bounded rationality framework has considerable potential to explain why, and how, developing countries have adopted modern investment treaties. To illustrate the potential of this approach, the case of South Africa is studied in depth.

Route switching behavior on freeways with the provision of different types of real-time traffic information

This study investigates route switching behavior on freeways in reaction to the provision of different types of real-time traffic information. The experimental design of the stated preference survey is based on four types of real-time information provided to travelers who were randomly selected at rest areas. The four types of real-time information defined in this paper are qualitative, quantitative, qualitative guidance, and quantitative guidance. The bounded rationality framework, also known as indifference band approach, is applied to model the freeway route switching behavior. Two important variables, travel time and travel cost, are included in the indifference band. In this study, the best route switching rule, travelers’ current routes as compared to the best route, is investigated to further provide valuable insights into freeways travelers’ route switching behavior with the provision of different types of real-time traffic information.

A bounded rationality framework for property investment behaviour

This paper attempts to explain the motivations of residential rental property investors in New Zealand in terms of the behavioural assumption of bounded rationality. Commencing with a rejection of the more standard neo‐classical economics view of rationality as an explanation of investment behaviour, the paper seeks to both examine the extent to which bounded rationality applies to the investment behaviour encountered and to elaborate on that behaviour. The discussion is underpinned by the findings of a postal survey of a large nationwide sample of private residential rental property owners, and is directly based on a study of a smaller sample of investors using in‐depth interview techniques. Qualitative analysis overlays the quantitative data, to enable better exploration of the constraints within which individual investors operate.