Rational Inattention Theory Research Articles

Pricing model of ride-hailing platform considering rationally inattentive passengers

ABSTRACT The ride-hailing services are booming in our daily lives, but it is unclear that how the platforms should set prices to maximize their profits when facing one kind of rationally inattentive passengers in a two-sided market. To fill this gap, we establish a profit maximization model for the ride-hailing platform based on queuing theory and rational inattention theory and analyze the properties of the model. Numerical examples are presented to demonstrate the impacts of perceived high and low service levels, information cost and prior belief on the optimal price and commission rate of the ride-hailing platform. The results show that (1) for different cities, there is always an optimal pricing strategy to maximize the profit of the platform. (2) To ensure maximum profit, the platform should disclose the service information of ride-hailing as much as possible, but also maintain the unknownness of ride-hailing services appropriately.

Rational inattention in neural coding for economic choice.

Mental operations like computing the value of an option are computationally expensive. Even before we evaluate options, we must decide how much attentional effort to invest in the evaluation process. More precise evaluation will improve choice accuracy, and thus reward yield, but the gain may not justify the cost. Rational Inattention theories provide an accounting of the internal economics of attentionally effortful economic decisions. To understand this process, we examined choices and neural activity in several brain regions in six macaques making risky choices. We extended the rational inattention framework to incorporate the foraging theoretic understanding of local environmental richness or reward rate, which we predict will promote attentional effort. Consistent with this idea, we found local reward rate positively predicted choice accuracy. Supporting the hypothesis that this effect reflects variations in attentional effort, richer contexts were associated with increased baseline and evoked pupil size. Neural populations likewise showed systematic baseline coding of reward rate context. During increased reward rate contexts, ventral striatum and orbitofrontal cortex showed both an increase in value decodability and a rotation in the population geometries for value. This confluence of these results suggests a mechanism of attentional effort that operates by controlling gain through using partially distinct population codes for value. Additionally, increased reward rate accelerated value code dynamics, which have been linked to improved signal-to-noise. These results extend the theory of rational inattention to static and stationary contexts and align theories of rational inattention with specific costly, neural processes.

Fusing Repeated Cross-Sectional Revealed Preference Datasets based on Rational Inattention Theory: Accounting for Changing Modal Preferences

To address the methodological limitation of cross-sectional studies and the data constraints of longitudinal/panel studies, this paper presents a model-based method to fuse repeated cross-sectional travel survey data based on the theory of rational inattention (RI) in discrete choice modeling. In the proposed framework, older cross-sectional data are used to model the prior probability of choice alternatives, and more recent cross-sectional data are used to capture conditional heterogeneous choices. The fusion method is theoretically more robust and computationally less burdensome than existing data pooling techniques. The method is empirically tested using data from two cycles of a large-sample post-secondary student travel survey in the Greater Toronto and Hamilton Area to investigate the commuting mode choices of post-secondary students. Parameter estimates of the RI-based multinomial logit (MNL) model indicate that the proposed method can generate behaviorally consistent results. Validation of the estimated model using a holdout sample indicates its improved forecasting performance compared with the classical random utility maximizing MNL model. The fusion method can be extended to more than two cycles of repeated cross-sectional data by updating the prior probabilities whenever new cross-sectional data become available. Thus, the study presents a continuous framework for fusing information from multiple time points using repeated cross-sectional datasets to capture preference evolution better and enhance the forecasting robustness of discrete choice models.

What can analyst forecasts tell us about imperfect information?

We used two imperfect information models, taking analyst as representatives of informed investors, quantifying the potential information constraints of the financial market and different companies, and found that China's financial market has more serious information friction than the United States, which means that people update the information set every seven to eight months on average or people's weight on new information is only 0.37. At the same time, we also found evidence consistent with cognitive constraints or rational inattention theory, that the more volatile a company's and industry performance, the slower analysts are to respond to that company's information.

Rational inattention in discrete choice models: Estimable specifications of RI-multinomial logit (RI-MNL) and RI-nested logit (RI-NL) models

As opposed to the fully informed choice-making assumption in classical discrete choice models, the theory of Rational Inattention (RI)11RI is used interchangeably for ‘Rational Inattention’ or ‘Rationally Inattentive’ throughout the paper in discrete choice modelling has been recently proposed in the literature. Matějka and McKay (2015) proposed the RI-multinomial logit (RI-MNL), and Fosgerau et al. (2020) proposed the RI-nested logit (RI-NL) model. These models consider that choice makers are bayesian agents with prior probabilities of choices and process any further information assuming an information processing cost to have the updated/posterior choice probabilities. However, the proposed RI-MNL and RI-NL models are theoretical formulations without any estimable empirical specifications. This paper proposes econometric formulations of RI-MNL and RI-NL models that are estimable using classical maximum likelihood estimation methods and suitable for revealed crossectional choice data. The proposed models are estimated for commuting mode choices in the Greater Toronto and Hamilton Area (GTHA) using data from a household travel survey conducted in the region. Empirical investigation reveals that the induction of RI in the classical discrete choice models (MNL and NL) improves the model fit by large margins. While scale parameterization in classical MNL and NL does not make a better model, the scale parameterization better captures the choice heterogeneity within the RI framework. Between the RI-MNL and RI-NL, the RI-NL is proven to be the best. The RI-NL model can capture asymmetric (between increasing and decreasing values) elasticities of choice attributes.

Economic policy uncertainty, investor attention and post-earnings announcement drift

How the market incorporates information into stock price is a core issue in finance. This study focuses on the impact of economic policy uncertainty (EPU) on the stock prices information efficiency of China's A-share market and underlying role of investors' attention allocation mechanism. This study analyzes the information efficiency of stock prices using the sensitivity of stock cumulative abnormal return to earnings information across different windows following earnings announcement. Based on the earnings announcement events of listed companies in China's A-share market, this study presents an empirical study of the aforementioned issues using event study and regression analysis methods. The following results are seen: (1) EPU aggravates the underreaction of stock price earnings information and the post-earnings announcement drift in the A-share market. (2) Under highly uncertain economic policies, investors show a limited attention allocation pattern of devoting increasing attention to macroeconomic policies and decreasing attention to earnings information, which leads to a decrease in the information efficiency of stock price. This study also analyzes the heterogeneity of the influence of EPU on stock price information efficiency using the institutional shareholding ratio. The results show that increasing institutional shareholding does not reduce the adverse effects of EPU on the information efficiency of stock prices. This study not only provides empirical evidence for Brunnermeier, Sockin, and Xiong (2022) and rational inattention theory, but also reveals that institutional investors show similar behavioral characteristics to retail investors in China's stock market. The results of this study have policy significance for improving the information efficiency of stock market.

Rational Inattention: A Review

We review the recent literature on rational inattention, identify the main theoretical mechanisms, and explain how it helps us understand a variety of phenomena across fields of economics. The theory of rational inattention assumes that agents cannot process all available information, but they can choose which exact pieces of information to attend to. Several important results in economics have been built around imperfect information. Nowadays, many more forms of information than ever before are available due to new technologies, and yet we are able to digest little of it. Which form of imperfect information we possess and act upon is thus largely determined by which information we choose to pay attention to. These choices are driven by current economic conditions and imply behavior that features numerous empirically supported departures from standard models. Combining these insights about human limitations with the optimizing approach of neoclassical economics yields a new, generally applicable model. (JEL D83, D91, E71)

Queueing Systems with Rationally Inattentive Customers

Problem definition: Classical models of queueing systems with rational and strategic customers assume queues to be either fully visible or invisible, while service parameters are known with certainty. In practice, however, people only have “partial information” on the service environment, in the sense that they are not able to fully discern prevalent uncertainties. This is because assessing possible delays and rewards is costly, as it requires time, attention, and cognitive capacity, which are all limited. On the other hand, people are also adaptive and endogenously respond to information frictions. Methodology: We develop an equilibrium model for a single-server queueing system with customers having limited attention. Following the theory of rational inattention, we assume that customers optimize their learning strategies by deciding the type and amount of information to acquire and act accordingly while internalizing the associated costs. Results: We establish the existence and uniqueness of a customer equilibrium when customers allocate their attention to learn uncertain queue lengths and delineate the impact of service characteristics. We provide a complete spectrum of the impact of information costs on throughput and show numerically that throughput might be nonmonotone. This is also reflected in social welfare if the firm’s profit margin is high enough, although customer welfare always suffers from information costs. Managerial implications: We identify service settings where service firms and social planners should be most cautious for customers’ limited attention and translate our results to advisable strategies for information provision and service design. For example, we recommend firms to avoid partial hindrance of queue-length information when a low-demand service is not highly valued by customers. For a popular service that customers value reasonably highly, however, partial hindrance of information is particularly advisable. Academic/practical relevance: We propose a microfounded framework for strategic customer behavior in queues that links beliefs, rewards, and information costs. It offers a holistic perspective on the impact of information prevalence (and information frictions) on operational performance and can be extended to analyze richer customer behavior and complex queue structures, rendering it a valuable tool for service design. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.1032 .

Optimal attention and heterogeneous precautionary saving behavior

This paper applies rational inattention theory proposed by Sims (2003) to study a puzzling empirical fact that wealthier individuals have a stronger precautionary saving motive. In the model, consumers face uninsured capital income risk but suffer from an information-processing capacity constraint. I solve for the optimal attention and consumption choices analytically in a Gaussian framework. I find that consumers with more initial wealth pay less attention to the capital income risk. As a result, wealthier consumers have higher perceived uncertainty about their future capital income and display a stronger precautionary motive by saving at higher rates.

Attention Trajectories Predict Brand Choice

Trajectories of attention during a complex brand choice task reflect the accumulation of utility and predict final choice before consumers implement it. Our findings reveal a “double attention lift” of the ultimately chosen brand towards the end of the choice task: it receives more attention than other brands do, and more of that attention is devoted to integrating information about the brand rather than to comparing it with other brands. Attention trajectories predict 85% of brand choices correctly out-of-sample, and 52% one period (29 secs.) before consumers reveal their brand choice. Attention during the choice task reflects sources of utility over and above those from brand ownership and knowledge effects. These results are obtained from a new multivariate attention-and-choice model, using K-fold Cross-Validation, and data from a large scale eye-tracking experiment among 325 regular consumers. The findings support notions from rational inattention theory, reveal the tight, potentially neurological, link between attention and utility accumulation, and have implications for consumer choice theory and managerial practice.

Rational Inattention: A Review

We review the recent literature on rational inattention, identify the main theoretical mechanisms, and explain how it helps us understand a variety of phenomena across fields of economics. The theory of rational inattention assumes that agents cannot process all available information, but they can choose which exact pieces of information to attend to. Several important results in economics have been built around imperfect information. Nowadays, many more forms of information than ever before are available due to new technologies, and yet we are able to digest little of it. Which form of imperfect information we possess and act upon is thus largely determined by which information we choose to pay attention to. These choices are driven by current economic conditions and imply behavior that features numerous empirically supported departures from standard models. Combining these insights about human limitations with the optimizing approach of neoclassical economics yields a new, generally applicable model.

Costly Consideration and Dynamic Choice Set Formation

Dynamic choices of cognitively constrained individuals have been ascribed, by the rational inattention theory, as being a filtering problem, in which the attentional intensity is consciously elected. Human attention, however, is not merely of voluntary intensity; it is rather of volitional placement nature. In this article, I study the implications of a dynamic theory of volitional attention describing individuals who choose among the alternatives that are induced by their attentional choices. Firstly, a consumer search application using US scanner data indicates that attentional choices are characterized by complementarities. Costs do not exclusively depend on the cardinality of consideration sets, but also on experience and similarities between considered items. Neglecting, thereby, attentional placement aspects potentially leads to misidentification of preference characteristics. Secondly, participation inertia in financial markets is revisited under the scope of volitional attention and a cultural-based argument of why it can be optimal not to participate is provided.

A Survey on Entropy and Economic Behaviour

Entropy plays a significant role in the study of games and economic behaviour in several ways. A decision maker faced with an n-fold repetition of a decision-making problem needs to apply strategies that become increasingly complex as n increases. When several players are involved in selecting strategies in interactive games, bounds on the memories and cognitive capacities of the players can affect possible outcomes. A player who can recall only the last k periods of history is said to have bounded recall of capacity k. We present here a brief survey of results of games played by players with different bounded recall capacities, in particular those indicating surprisingly strong relations between memory and entropy in the study of the min-max values of repeated games with bounded recall. In addition, we consider uses of entropy in measuring the value of information of noisy signal structures, also known as experiments. These are represented by stochastic matrices, with the rows representing states of the world and the columns possible signals. The classic ordering of experiments, due to David Blackwell and based on decision-making criteria, is a partial ordering, which has led to attempts to extend this ordering to a total ordering. If a decision maker has a prior distribution over the states, receipt of a signal yields a posterior. The difference between the entropy of a prior and the expected entropy of the set of possible posteriors has been proposed as a natural extension of the Blackwell ordering. We survey this alongside the theory of rational inattention, which posits that, since individuals have limited attention, they do not always follow every single piece of economic news in planning their economic behaviour. By modelling attention limits as finite channel capacity in the sense of Shannon, economists have developed a theory that explains a range of observed economic behavioural phenomena well.

The Rationally Inattentive Manager

We analyze the ordering decisions of a manager who acquires demand information to make inventory decisions. Human beings' cognitive ability in information acquisition is imperfect by nature. We adopt the rational inattention theory to model the information acquisition activity. By reformulating the rational inattention decision problem, we find that rational inattention theory resembles the free energy principle (Friston 2009, 2010) that is used to model brain activities. Therefore, rational inattention theory gets a neurocognitive foundation. We obtain closed-form solutions of the optimal action strategies, which is a discrete distribution although the states are continuous. The process of resulting the optimal action strategies shows that the essence of the process, as a neurocognitive activity, is to think until nothing to think. The optimal action strategies themselves show that an effective thinking is hard to obtain unless think one more step. We also study the impact on decisions once the primitive information is contaminated. If the primitive information is contaminated by, for example, data sampling errors, the acquired information will be eclipsed by the contamination and exhibit certain features that mistaken the ordering decisions by acquiring information if the primitive information were clean. The specific forms of the well-known one-to-one correspondence between action and signal are also restricted by the contamination. We propose an empirical approach to identify the optimal ordering quantities, and the approach works only if the information contamination is separated from the estimation of the unconditional optimal ordering strategies.

Rational Inattention and Analyst Forecast Accuracy

Facing limited attention constraints, financial analysts must strategically choose which information to pay attention to and which information to ignore when making earnings forecasts. I rely on rational inattention theory to develop and test hypotheses on factors that determine analyst attention and how analyst attention affects forecast accuracy. I construct a novel measure of attention that varies across stocks followed by the same analyst during the same fiscal period. I find that analyst attention is decreasing in the marginal cost of paying attention and that analysts allocate attention to firms with earnings that are difficult to forecast, suggesting that analysts suffer from a limited attention constraint. Importantly, I find that attentive analysts are more accurate, and the effect of attention is larger for inexperienced analysts and stocks with highly volatile earnings. Finally, I find that attentive analysts are less likely to revise forecasts upwards and are less optimistic even after controlling for firm information environment and analyst ability.

Opaque Queues: Service Systems with Rationally Inattentive Customers

Problem description: Classical models of queueing systems with rational and strategic customers assume queues to be either fully visible or invisible while service parameters are known with certainty. In practice, however, people only have “partial information” on the service environment in the sense that they are not able to fully discern prevalent uncertainties. This is because assessing possible delays and rewards is costly as it requires time, attention, and cognitive capacity which are all limited. On the other hand, people are also adaptive and endogenously respond to information frictions. Methodology: We develop an equilibrium model for a single-server queueing system with customers having limited attention. Following the theory of rational inattention, we assume that customers optimize their learning strategies by deciding the type and amount of information to acquire and act accordingly while internalizing the associated costs. Results: We establish the existence and uniqueness of a customer equilibrium and delineate the impact of service characteristics and information costs. We numerically show that when customers allocate their attention to learn uncertain queue length, limited attention of customers improves throughput in a congested system that customers value reasonably highly, while it can be detrimental for less popular services that customers deem rather unrewarding. This is also reflected in social welfare if the firm's profit margin is high enough, although customer welfare always suffers from information costs. Managerial implications: Our results shed light on optimal information provision and physical design strategies of service firms and social planners by identifying service settings where they should be most cautious for customers' limited attention. Academic/practical relevance: We propose a microfounded framework for strategic customer behavior in queues that links beliefs, rewards, and information costs. It offers a holistic perspective on the impact of information prevalence (and information frictions) on operational performance and can be extended to analyze richer customer behavior and complex queue structures, rendering it a valuable tool for service design.

Pricing When Customers Have Limited Attention

We study the optimal pricing problem of a monopolistic firm facing customers with limited attention and capability to process information about the value (quality) of a single offered product. We model customer choice based on the theory of rational inattention in the economics literature, which enables us to capture not only the impact of true quality and price, but also the intricate effects of customer’s prior beliefs and cost of information acquisition and processing. We formulate the firm’s price optimization problem assuming that the firm can also use the price to signal the quality of the product to customers. To delineate the economic incentives of the firm, we first characterize the pricing and revenue implications of customer’s limited attention without signaling, and then use these results to explore perfect Bayesian equilibria of the strategic pricing signaling game. As an extension, we consider heterogeneous customers with different information costs as well as prior beliefs. We discuss the managerial implications of our key findings and prescribe insights regarding information provision and product positioning. This paper was accepted by Gad Allon, operations management.

Tax Rate Biases in Tax Planning Decisions: Experimental Evidence

Contrary to standard economic theory, recent empirical findings suggest that firms do not always engage in economically optimal tax planning. We conduct a laboratory experiment and find robust evidence that decision biases offer a behavioral explanation for suboptimal tax planning. When facing time pressure in an intra-group cross-border financing decision, subjects apply heuristics based on the salience of statutory tax rates. This stirs decision makers to underestimate the effects of tax-base changes and causes economically suboptimal decisions. We find that tax-planning behavior is largely unaffected by subjects' work experience or education in accounting, taxation, and/or finance. However, we observe an overconfidence bias in subjects with work experience. In line with the theory of rational inattention, an increasing tax-burden difference between two tax-planning strategies weakly mitigates the use of heuristics. Taken together, our findings suggest that tax-information salience drives tax-planning decisions. This effect might cause decision biases and contribute to the undersheltering puzzle.

Pricing When Customers Have Limited Attention

We study the optimal pricing problem of a firm facing customers with limited attention and capability to process information about the value (quality) of the offered products. We model customer choice based on the theory of rational inattention in the economics literature, which enables us to capture not only the impact of true qualities and prices, but also the intricate effects of customer’s prior beliefs and cost of information acquisition and processing. We formulate the firm’s price optimization problem and characterize the pricing and revenue implications of customer’s limited attention. We test the robustness of our results under various modelling generalizations such as prices signaling quality and customer heterogeneity, and study extensions such as multiple products, competition, and joint inventory and pricing decisions. We also show that using alternative pricing policies that ignore the limited attention of customers or their ability to allocate this attention judiciously can potentially lead to significant profit losses for the firm. We discuss the managerial implications of our key findings and prescribe insights regarding information provision and product positioning.

Macropudential Policy in a Knightian Uncertainty Model with Credit-, Risk-, and Leverage Cycles

We study the impact of uncertainty on financial stability and the business cycle. We extend the work of Boz and Mendoza (2014) by endogenizing credit production, modifying learning mechanism into an adaptive set-up, as well as including financial and monetary policies. In our model households are (intrinsically) rational but take economic decisions under incomplete information. The incompleteness is not caused by their cognitive limitations, as in rational inattention theory (Sims, 2003). Households `learn by doing' and once a sufficient number of realizations of the state variable have materialized, and the incomplete information set is completed. This learning set-up is incorporated into a New Keynesian model with credit market frictions, extended to include uncertainty, where a share of households needs external financing to consume. Because of limited enforceability of financial contracts, households are required to provide collateral for their loans, and so the relationship between the bank and household is tightened for many periods ahead. We find in our framework the build up of risk, leverage, increase in consumption and price of collateral takes longer than in other DSGEs with standard financial friction models. We also find that both the frequency and the amplitude of expansions and contractions are asymmetric - recessions are less frequent and deeper than expansions. Moreover, we find that boom-bust cycles occur as rare events. Using the Cogley and Sargant's (2008) definition of a severe(or systemic) crisis, we find on average two such events per century. We also find that, different from standard boom-bust cycles, a systemic crisis can be followed by a sequence of subsequent contractions, as it makes the economy more unstable. The result is asymmetric distributions of key macroeconomic and financial variables, with high skewness and fat tails. Lastly, we also find that, by reducing the amount of borrowing and leverage in upturns, the LTV-ratio regulation is effective in smoothing the cycles and reducing the effects of a deep contraction on the real-financial variables. We also discuss the role of macroprudential policy in reducing information incompleteness by generating information that helps the agent learn faster the new environment, or provide a smoother transition to the new economic environment.