Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics published by Elsevier (http://www.journals.elsevier.com/econometrics-and-statistics/). It publishes research papers in all aspects of econometrics and statistics and comprises of two sections:
- Part A: Econometrics. Emphasis will be given to methodological and theoretical papers containing substantial econometrics derivations or showing a potential of a significant impact in the broad area of econometrics. Topics of interest include the estimation of econometric models and associated inference, model selection, panel data, measurement error, Bayesian methods, and time series analyses. Simulations are to be considered when they involve an original methodology. Innovative papers in financial econometrics and its applications will be considered. The topics to be covered include portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure. Interest will be focused as well on well-founded applied econometric studies that demonstrate the practicality of new procedures and models. Such studies should involve the rigorous application of statistical techniques, including estimation, inference and forecasting. Topics will include volatility and risk, credit risk, pricing models, portfolio management, and emerging markets. Innovative contributions in empirical finance and financial data analysis that use advanced statistical methods are encouraged. The results of the submissions should be replicable. Applications consisting only of routine calculations will not be of interest to the journal.
- Part B: Statistics. Papers providing important original contributions to methodological statistics inspired in applications will be considered for this section. Papers dealing, directly or indirectly, with computational and technical elements will be particularly encouraged. These cover developments concerning issues of high-dimensionality, re-sampling, dependence, robustness, filtering, and, in general, the interaction of mathematical methods, numerical implementations and the extra burden of analysing large and/or complex datasets with such methods in different areas such as medicine, epidemiology, biology, psychology, climatology and communication. Innovative algorithmic developments are also of interest, as are the computer programs and the computational environments that implement them as a complement.
The journal consists, preponderantly, of original research. Occasionally, review and short papers from experts are published, which may be accompanied by discussions. Special issues and sections within important areas of research are occasionally published.
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