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Content archived on 2024-06-18

Identification, Estimation and Implementation of Structural Economic Models

Objective

Structural economic models are getting increasingly complex. This complicates their implementation. In particular, for many models, (i) identification of the relevant components from data is still unresolved; (ii) estimation and testing procedures tend to be somewhat ad hoc and with no theoretical underpinning; (iii) the implementation of model and estimators often require numerical approximations since model solutions are not available on closed form.

The proposed research aims at addressing these three issues, (i)-(iii), by developing new methods and results for identification, estimation, testing and implementation of structural models. Particular emphasis is put on the use of nonparametric techniques. Many of the projects involve empirical applications where the proposed methods will be taken to data.

The individual projects making up the proposal are: Identification and inference in discrete choice models; identification and inference in continuous choice models; Implementation and estimation of parametric structural models; Filtering and likelihood inference in dynamic latent variable models; Bandwidth selection in estimation and testing of non- and semiparametric models.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Call for proposal

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ERC-2012-StG_20111124
See other projects for this call

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.

ERC-SG - ERC Starting Grant

Host institution

UNIVERSITY COLLEGE LONDON
EU contribution
€ 1 067 000,00
Total cost

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No data

Beneficiaries (1)

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