Project acronym ATTENTION
Project Economics of Inattention
Researcher (PI) Filip Matejka
Host Institution (HI) NARODOHOSPODARSKY USTAV AKADEMIE VED CESKE REPUBLIKY VEREJNA VYZKUMNA INSTITUCE
Country Czechia
Call Details Consolidator Grant (CoG), SH1, ERC-2020-COG
Summary This proposal outlines an agenda that aims to improve 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.
In the first part of the agenda, we will 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. We will address the question of endogenous model uncertainty by sidestepping the largely statistical nature of previous work. Our agents learn about a model directly, i.e., all information on the details of the correct model is readily available. The envisioned implications can speak to issues such as the expectations formation and formation of narratives, polarization of opinions, and demand for public policy.
In the second part, we will study how a government optimally intervenes in markets if it finds it costly to get the necessary information. On one hand, a government does not possess the local information of decentralized markets. On the other, markets on their own often generate suboptimal social outcomes. We will explore what information the government should collect, how to use it for regulation, and when instead it should leave markets unaffected.
In the third part, we will leverage recent theories of attention allocation and use uniquely detailed data on attention and treatment choices by hospital personnel (including physicians and nurses). This will allow 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.
Summary
This proposal outlines an agenda that aims to improve 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.
In the first part of the agenda, we will 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. We will address the question of endogenous model uncertainty by sidestepping the largely statistical nature of previous work. Our agents learn about a model directly, i.e., all information on the details of the correct model is readily available. The envisioned implications can speak to issues such as the expectations formation and formation of narratives, polarization of opinions, and demand for public policy.
In the second part, we will study how a government optimally intervenes in markets if it finds it costly to get the necessary information. On one hand, a government does not possess the local information of decentralized markets. On the other, markets on their own often generate suboptimal social outcomes. We will explore what information the government should collect, how to use it for regulation, and when instead it should leave markets unaffected.
In the third part, we will leverage recent theories of attention allocation and use uniquely detailed data on attention and treatment choices by hospital personnel (including physicians and nurses). This will allow 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.
Max ERC Funding
1 162 664 €
Duration
Start date: 2021-04-01, End date: 2026-03-31
Project acronym BEHAVFRICTIONS
Project Behavioral Implications of Information-Processing Frictions
Researcher (PI) Jakub STEINER
Host Institution (HI) NARODOHOSPODARSKY USTAV AKADEMIE VED CESKE REPUBLIKY VEREJNA VYZKUMNA INSTITUCE
Country Czechia
Call Details Consolidator Grant (CoG), SH1, ERC-2017-COG
Summary BEHAVFRICTIONS will use novel models focussing on information-processing frictions to explain choice patterns described in behavioral economics and psychology. The proposed research will provide microfoundations that are essential for (i) identification of stable preferences, (ii) counterfactual predictions, and (iii) normative conclusions.
(i) Agents who face information-processing costs must trade the precision of choice against information costs. Their behavior thus reflects both their stable preferences and the context-dependent procedures that manage their errors stemming from imperfect information processing. In the absence of micro-founded models, the two drivers of the behavior are difficult to disentangle for outside observers. In some pillars of the proposal, the agents follow choice rules that closely resemble logit rules used in structural estimation. This will allow me to reinterpret the structural estimation fits to choice data and to make a distinction between the stable preferences and frictions.
(ii) Such a distinction is important in counterfactual policy analysis because the second-best decision procedures that manage the errors in choice are affected by the analysed policy. Incorporation of the information-processing frictions into existing empirical methods will improve our ability to predict effects of the policies.
(iii) My preliminary results suggest that when an agent is prone to committing errors, biases--such as overconfidence, confirmatory bias, or perception biases known from prospect theory--arise under second-best strategies. By providing the link between the agent's environment and the second-best distribution of the perception errors, my models will delineate environments in which these biases shield the agents from the most costly mistakes from environments in which the biases turn into maladaptations. The distinction will inform the normative debate on debiasing.
Summary
BEHAVFRICTIONS will use novel models focussing on information-processing frictions to explain choice patterns described in behavioral economics and psychology. The proposed research will provide microfoundations that are essential for (i) identification of stable preferences, (ii) counterfactual predictions, and (iii) normative conclusions.
(i) Agents who face information-processing costs must trade the precision of choice against information costs. Their behavior thus reflects both their stable preferences and the context-dependent procedures that manage their errors stemming from imperfect information processing. In the absence of micro-founded models, the two drivers of the behavior are difficult to disentangle for outside observers. In some pillars of the proposal, the agents follow choice rules that closely resemble logit rules used in structural estimation. This will allow me to reinterpret the structural estimation fits to choice data and to make a distinction between the stable preferences and frictions.
(ii) Such a distinction is important in counterfactual policy analysis because the second-best decision procedures that manage the errors in choice are affected by the analysed policy. Incorporation of the information-processing frictions into existing empirical methods will improve our ability to predict effects of the policies.
(iii) My preliminary results suggest that when an agent is prone to committing errors, biases--such as overconfidence, confirmatory bias, or perception biases known from prospect theory--arise under second-best strategies. By providing the link between the agent's environment and the second-best distribution of the perception errors, my models will delineate environments in which these biases shield the agents from the most costly mistakes from environments in which the biases turn into maladaptations. The distinction will inform the normative debate on debiasing.
Max ERC Funding
1 321 488 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
Project acronym INATTENTION
Project Behavioral and Policy Implications of Rational Inattention
Researcher (PI) Filip Matejka
Host Institution (HI) NARODOHOSPODARSKY USTAV AKADEMIE VED CESKE REPUBLIKY VEREJNA VYZKUMNA INSTITUCE
Country Czechia
Call Details Starting Grant (StG), SH1, ERC-2015-STG
Summary This proposal outlines agenda which aims to improve our understanding of policies in environments with cognitively limited agents. It seeks to extend and apply the theory of rational inattention developed in macroeconomics. Citizens are inattentive to details of tax codes, government bureaucrats cannot inspect all data about people in need, and voters are highly uninformed about politicians’ campaign platforms. The agenda is specifically targeted at applications where human inability to digest all available information has strong implications for public policy formation. It falls into three broad parts.
First (macroeconomics), the proposed research will develop a new model of risk-sharing in a typical modern-macro setting with heterogeneous agents. Instead of incentive constraints, the imperfections will be driven by the government’s or citizens’ inability to process all available information. What are the properties of the resulting system of redistribution? Why do taxes often take a simple form? Can minorities be left behind because they attract less of the government’s attention?
Second (behavioral economics), it will extend the rational inattention theory to model how agents simplify multidimensional features of the environment. Among many applications, the theory is likely to provide an alternative explanation for mental accounting, when people have separate budgets for different types of expenditures (critical to consumption decisions, especially of the poor), and for salience of different elements of the tax code.
Third (political economy), it will develop a unified framework to study implications of voters’ rational inattention (selective ignorance) for the outcomes of political processes, such as for popular demand for misguided policies, public good provision, and the complexity of announced platforms. Voters’ information acquisition and fragmented information processing will be studied in a field experiment.
Summary
This proposal outlines agenda which aims to improve our understanding of policies in environments with cognitively limited agents. It seeks to extend and apply the theory of rational inattention developed in macroeconomics. Citizens are inattentive to details of tax codes, government bureaucrats cannot inspect all data about people in need, and voters are highly uninformed about politicians’ campaign platforms. The agenda is specifically targeted at applications where human inability to digest all available information has strong implications for public policy formation. It falls into three broad parts.
First (macroeconomics), the proposed research will develop a new model of risk-sharing in a typical modern-macro setting with heterogeneous agents. Instead of incentive constraints, the imperfections will be driven by the government’s or citizens’ inability to process all available information. What are the properties of the resulting system of redistribution? Why do taxes often take a simple form? Can minorities be left behind because they attract less of the government’s attention?
Second (behavioral economics), it will extend the rational inattention theory to model how agents simplify multidimensional features of the environment. Among many applications, the theory is likely to provide an alternative explanation for mental accounting, when people have separate budgets for different types of expenditures (critical to consumption decisions, especially of the poor), and for salience of different elements of the tax code.
Third (political economy), it will develop a unified framework to study implications of voters’ rational inattention (selective ignorance) for the outcomes of political processes, such as for popular demand for misguided policies, public good provision, and the complexity of announced platforms. Voters’ information acquisition and fragmented information processing will be studied in a field experiment.
Max ERC Funding
950 424 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
