Objective
"This research project aims to contribute to advances in the research on semiparametric and nonparametric econometric methods by developing novel estimation and inference approaches in a variety of contexts and applying them to important empirical problems in economics.
The project is divided into four parts. The first part develops a Bayes procedure for the moment condition model. A likelihood function is constructed by employing an information theoretic projection from space of nonparametric prior distributions on data to space of distributions satisfying the moment conditions. Posterior sampling methods and asymptotic theory for the posterior are developed.
The second part focuses on the moment condition model but from a different perspective, robustness of decision methods. By focusing on local perturbations within shrinking topological neighborhoods, this part develops a framework to evaluate robustness of inference methods for the moment condition model. It is found that there is a computationally convenient method that achieves optimal minimax robust properties under local perturbations without losing asymptotic equivalence to GMM under correct specification.
The third part develops nonparametric regression techniques for extremal or tail behaviors. This part develops asymptotic theory for nonparametric quantile regression when the quantile drifts to 0 or 1 as the sample size increases. Based on the theory, a new inference method for extremal behaviors is developed.
The fourth part extends the empirical likelihood approach to a variety of empirical problems in economics. This part develops empirical likelihood inference methods for regression discontinuity designs, continuity or discontinuity of probability density functions, volatility measurement in high frequency financial data, and testing for partially identified moment inequality models. Also new concepts of nonparametric likelihood are developed by extending the likelihood theory on parametric models."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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.
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
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
ERC-2013-CoG
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.
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.
Host institution
WC2A 2AE London
United Kingdom
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.