Objective
In recent years, there has been an increased availability of economic datasets that are characterised by a non-negligible amount of time-series information, as well as a large cross-section dimension. Unfortunately, in many cases, although the time-series dimension is not small anymore, it is not large enough for accurate estimation either. Examples of such datasets can be found in a variety of literatures: growth data, firm data (e.g. studies of insider trading activity), earnings studies (the popular Panel Study of Income Dynamics) and hedge fund returns, to name a few. Such panels are generally designated as short panels in the literature. Intuitively, the problem with short panels is a time-series finite-sample bias. This project’s main aim is to conduct a systematic theoretical and empirical research programme on modelling short panels in the presence of unknown and complex types of dependence across both time and cross-section. Inclusion of cross-section dependence is the central novelty of this project. This is motivated by my doctoral research where I showed that this type of dependence introduces new bias terms. The central theoretical objectives are to develop bias correction methods for (i) the Dynamic Autoregressive and Dynamic Probit/Logit models which are quite popular in applied research and (ii) the multivariate nonlinear and dynamic panel data models. The main empirical objectives are to a large extent concerned with univariate and multivariate volatility modelling using panels of financial data. As such, this project will contribute to the theoretical panel data and volatility modelling literatures, as well as the statistics literature, where the outlined small-sample bias has a long research tradition. In addition, as this project is concerned with modelling and understanding macro and financial panels, this project also has a significant potential to contribute to the key policy area “Connect to compete: building tomorrow’s networks today.”
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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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.
FP7-PEOPLE-2013-CIG
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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.
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.
MC-CIG - Support for training and career development of researcher (CIG)
Coordinator
06800 Bilkent Ankara
Türkiye
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.