Nonparametric Methods in Econometrics
A special issue of Econometrics (ISSN 2225-1146).
Deadline for manuscript submissions: closed (31 May 2016) | Viewed by 19080
Special Issue Editor
Interests: econometrics: semiparametric and nonparametric estimation; time series econometrics: volatility and interest rates estimation; simulation and modelling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims at gathering the latest advances in nonparametric techniques within a variety of applications in economics and finance, in particular, but not exclusively, it will highlight the research in methodologies for time-varying parameter models. Acolytes of the motto “let data speak” have increased in the last decades as faster computer power permits a feasible treatment of large datasets with nonparametric techniques. More recently, researchers in nonparametrics are working on varying coefficient models. In the particular case of time series, economists have searched intensely for a way to include time variation in the coefficients and volatility. The reason for this is that economic processes evolve over time and their effects must be identified locally rather than globally. Despite the fact that these estimators adapt easily to situations of change, the lack of computer applications with this functionality makes them somewhat “unpopular” as it is difficult for the nonspecialized end-user to code them. This Special Issue also calls for computing code, when available, to be posted as part of the research contribution.
Dr. Isabel Casas
Guest Editor
Manuscript Submission Information
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Keywords
- nonparametric estimation
- varying coefficients
- time-varying parameters
- nonstationarity
- kernel smoothing
- smoothing spline
- forecasting
- rate of convergence