Objective
Constructing accurate predictions on different macroeconomic variables is a key issue for any central bank and other policy making institutions. For example, obtaining accurate inflation forecasts is important for setting interest rates. These institutions typically rely on a set of models to construct their forecasts and the question that often arises is which of these models performs the best in terms of predictive ability. The purpose of this project is to show that, when strong identification on these models is lost (an issue that is prevalent in many models used for prediction), our inference based on standard tests, that compare these models' predictive accuracy, can be misleading. A policy maker could thus falsely conclude that a particular model outperforms some other models in her set of competing models. This project will answer thus the question of how to perform correct inference about predictions in the setting in which the models are affected by identification deficiencies. To this end, I propose methods that make the standard predictive ability tests robust to this issue, while appropriately accounting for the parameter estimation error. The asymptotic distribution of the statistic will be derived under loss of strong identification. Bootstrap inference will be developed in order to obtain correct critical values. Monte Carlo simulations will analyze the finite sample properties of bootstrap critical values. Empirical studies will illustrate the consequences of using a standard vs. a bootstrap critical value. Results emerging from this project, will be of interest to a large academic community, central banks and other governmental organizations - that could take-up the new knowledge for policy making, as well as businesses that produce predictions - that could improve their forecast evaluation methodologies.
Fields of science (EuroSciVoc)
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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.
(opens in new window) H2020-MSCA-IF-2017
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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.
3062 PA Rotterdam
Netherlands
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.