Periodic Reporting for period 2 - ATTENTION (Economics of Inattention)
Reporting period: 2022-10-01 to 2024-03-31
This project aims at improving our understanding of economies with inattentive agents. Attention to detail, not only to current news, but also to how the world works in general, is central to how we interact with the environment. How do agents internalize and potentially simplify complex models of the environment? How does a government intervene in markets if it finds it too costly to get the local information? How do people allocate their attention in the practical repetitive tasks they face, especially in medical decisions? Improving any public policy of practical decisions is subject to these questions.
There are three main objectives of the agenda. Frist, we study how agents come up with the simplified mental models they use in their decision-making. The aim is to provide a new alternative to rational expectations. In the second part, we study how a government optimally intervenes in markets if it finds it costly to get the necessary information. And in the third part, we leverage recent theories of attention allocation and use uniquely detailed data on attention and treatment choices by hospital personnel (including physicians and nurses). This allows us to explore in more detail than before what theories describe realistic choices well. Moreover, we will eventually aim at a very practical goal: how to help clinicians decrease their cognitive load and improve medical choices.
There are three main objectives of the agenda. Frist, we study how agents come up with the simplified mental models they use in their decision-making. The aim is to provide a new alternative to rational expectations. In the second part, we study how a government optimally intervenes in markets if it finds it costly to get the necessary information. And in the third part, we leverage recent theories of attention allocation and use uniquely detailed data on attention and treatment choices by hospital personnel (including physicians and nurses). This allows us to explore in more detail than before what theories describe realistic choices well. Moreover, we will eventually aim at a very practical goal: how to help clinicians decrease their cognitive load and improve medical choices.
The first section is partly finished. We completed and published a paper in the Journal of Economic Literature.
It summarizes ideas on how people deal with limited attention and how how it shapes the whole environment, i.e. markets and policy. The paper has already been widely cited and used as a teaching material at numerous institutions, too.
Another paper was published in Nature and also has already been successful. It focuses on simplified information provision to public during the covid times. It shows that sufficiently transparent information about doctors’ beliefs can help move the public’s beliefs in the direction of those of the physicians.
There are two other paper related to limited information provision, one published in the Journal of Economic Theory.
Moreover, we have been working on development of methods that could describe existing narratives empirically. We developed a large language model (LLM) that summarizes a scraped text and can answer questions such as “Is inflation caused by deficit or by low interest rates?” This is meant to describe beleifs of those writing the text on the internet.
Maćkowiak, Bartosz, Filip Matějka, and Mirko Wiederholt. "Rational inattention: A review." Journal of Economic Literature 61.1 (2023): 226-273.
Bartoš, Vojtěch, et al. "C ommunicating doctors’ consensus persistently increases COVID-19 vaccinations." Nature 606.7914 (2022): 542-549.
Matyskova, Ludmila, and Alfonso Montes. "Bayesian persuasion with costly information acquisition." Journal of Economic Theory (2023): 105678.
Rehák, Rastislav, and Maxim Senkov. "Form of Preference Misalignment Linked to State-pooling Structure in Bayesian Persuasion." CERGE-EI Working Paper Series 708 (2021).
In the second section we are still in the preparation stage. One area where we progressed quite a bit is study of the decentralized market via focusing on a taxi market where customers decide on which taxi to choose among those in the vicinity.
In the third section, we have been collecting data from the system of University of California in San Francisco and running initial analysis. Now we have a database of million of patient visits with detailed features in each visit. In the first stage we are focusing on “fatigue of doctors”, i.e. how their performance and working habits change as a function of already performed work and what type of patients they interacted with recently.
We do already have initial results, which we are starting to present at invited seminars these very days. We have slides, but there is no paper yet. The interaction between physicians’ performance and behavior, and past interactions is very interesting. We see that they make vastly different choices if they interacted with complicated patients in recent past.
It summarizes ideas on how people deal with limited attention and how how it shapes the whole environment, i.e. markets and policy. The paper has already been widely cited and used as a teaching material at numerous institutions, too.
Another paper was published in Nature and also has already been successful. It focuses on simplified information provision to public during the covid times. It shows that sufficiently transparent information about doctors’ beliefs can help move the public’s beliefs in the direction of those of the physicians.
There are two other paper related to limited information provision, one published in the Journal of Economic Theory.
Moreover, we have been working on development of methods that could describe existing narratives empirically. We developed a large language model (LLM) that summarizes a scraped text and can answer questions such as “Is inflation caused by deficit or by low interest rates?” This is meant to describe beleifs of those writing the text on the internet.
Maćkowiak, Bartosz, Filip Matějka, and Mirko Wiederholt. "Rational inattention: A review." Journal of Economic Literature 61.1 (2023): 226-273.
Bartoš, Vojtěch, et al. "C ommunicating doctors’ consensus persistently increases COVID-19 vaccinations." Nature 606.7914 (2022): 542-549.
Matyskova, Ludmila, and Alfonso Montes. "Bayesian persuasion with costly information acquisition." Journal of Economic Theory (2023): 105678.
Rehák, Rastislav, and Maxim Senkov. "Form of Preference Misalignment Linked to State-pooling Structure in Bayesian Persuasion." CERGE-EI Working Paper Series 708 (2021).
In the second section we are still in the preparation stage. One area where we progressed quite a bit is study of the decentralized market via focusing on a taxi market where customers decide on which taxi to choose among those in the vicinity.
In the third section, we have been collecting data from the system of University of California in San Francisco and running initial analysis. Now we have a database of million of patient visits with detailed features in each visit. In the first stage we are focusing on “fatigue of doctors”, i.e. how their performance and working habits change as a function of already performed work and what type of patients they interacted with recently.
We do already have initial results, which we are starting to present at invited seminars these very days. We have slides, but there is no paper yet. The interaction between physicians’ performance and behavior, and past interactions is very interesting. We see that they make vastly different choices if they interacted with complicated patients in recent past.
In the first stream the main progress has been in the general ideas and methods. We are expecting that we succeed in developing the method to build a database of narratives from the text data and also that we dive deeper in the theory of narrative formation beyond the one based on rational expectation. One other direction on which we currently work related to mis-specified models.
In the second stream we expect that the study of decentralized taxi market as a very interesting case will yield insightful results. The novel approach is that it takes advantage of unique data of a decentralized system of auctions run each time a customer is waiting for a taxi.
And the third stream already delivers novel and important results regarding the effect of fatigue of doctors. In this stream, there is a whole universe of additional questions to explore and we are looking at many of them.
In the second stream we expect that the study of decentralized taxi market as a very interesting case will yield insightful results. The novel approach is that it takes advantage of unique data of a decentralized system of auctions run each time a customer is waiting for a taxi.
And the third stream already delivers novel and important results regarding the effect of fatigue of doctors. In this stream, there is a whole universe of additional questions to explore and we are looking at many of them.