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Modeling Misspecification: Incorporating Information Processing Biases into Economic Models

Project description

Modelling information biases in decision-making

Differences in how individuals interpret information significantly impact societal decision-making. However, many economic models assume that people not only interpret information correctly but also agree on its meaning. In this context, the ERC-funded ModelMisspec project seeks to address this gap by developing a unified framework for modelling information processing biases. The project has three key components: theoretical, empirical and applied. First, it will create a transparent framework linking common approaches to modelling biases. Then, through experiments and surveys, it will explore real-world implications of these biases, such as in price dynamics and reputation. Ultimately, the project aims to provide new tools for analysing and understanding the effects of biases on decision-making in various economic contexts.

Objective

Differences in how individuals interpret the same information have proven to play an important role in societal decision making. Yet, most economic models assume individuals not only interpret information correctly but fundamentally agree on how information should be interpreted. In ModelMisspec, I will develop a unified framework that links two approaches to modeling information processing biases. I plan to (i) develop a unified framework to model information processing biases, (ii) develop tools, both theoretical and empirical, that can be applied to the analysis of problems this framework, and (iii) bring this framework to bear on applied models to study to the role of biases in price dynamics, learning, reputation and other applications.

The proposed project has theoretical, empirical and applied components. In the theory part, I will develop a unified framework that bridges two common approaches to modeling biases. This approach provides a transparent and general framework for modeling information processing biases. I'll then use this framework to explore the implications of information processing biases for decision making.

In the second part, I study misspecification empirically. In the first empirical component, I will experimentally elicit a key part of this framework, the forecast. This object is an key piece of decision making, that has gone unstudied. I also will study misspecification in the field, through a survey of Finnish drivers' beliefs about the penalty schedule for speeding. This section will focus on both developing tools for studying misspecification empirically, and its implications for decision making.

Finally, I plan to explore the economic applications of this framework, including timing games, social learning, reputation, markets, etc.

Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2024-STG

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Host institution

AALTO KORKEAKOULUSAATIO SR
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 487 820,00
Address
OTAKAARI 1
02150 Espoo
Finland

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Region
Manner-Suomi Helsinki-Uusimaa Helsinki-Uusimaa
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 487 820,00

Beneficiaries (1)

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