Essays On Nonlinear Transformations Of Nonstationary Time Series
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Essays On Nonlinear Transformations Of Nonstationary Time Series
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Author : Chien-Ho Wang
language : en
Publisher:
Release Date : 2003
Essays On Nonlinear Transformations Of Nonstationary Time Series written by Chien-Ho Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Economics categories.
Essays In Honor Of Joon Y Park
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Author : Yoosoon Chang
language : en
Publisher: Emerald Group Publishing
Release Date : 2023-04-24
Essays In Honor Of Joon Y Park written by Yoosoon Chang and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-24 with Business & Economics categories.
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Essays In Nonlinear Time Series Econometrics
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Author : Niels Haldrup
language : en
Publisher: OUP Oxford
Release Date : 2014-06-26
Essays In Nonlinear Time Series Econometrics written by Niels Haldrup and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-26 with Business & Economics categories.
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Dissertation Abstracts International
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Author :
language : en
Publisher:
Release Date : 2005
Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Dissertations, Academic categories.
Essays In Forecasting Stationary And Nonstationary Stochastic Processes
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Author : Norman R. Swanson
language : en
Publisher:
Release Date : 1994
Essays In Forecasting Stationary And Nonstationary Stochastic Processes written by Norman R. Swanson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Forecasting categories.
Macroeconomic Forecasting In The Era Of Big Data
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Author : Peter Fuleky
language : en
Publisher: Springer Nature
Release Date : 2019-11-28
Macroeconomic Forecasting In The Era Of Big Data written by Peter Fuleky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Business & Economics categories.
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Essays In Mathematical Economics In Honor Of Oskar Morgenstern
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Author : Martin Shubik
language : en
Publisher: Princeton University Press
Release Date : 2015-12-08
Essays In Mathematical Economics In Honor Of Oskar Morgenstern written by Martin Shubik and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Business & Economics categories.
Professor Morgenstern's deep interests in economic time series and problems of measurement are represented by path-breaking articles devoted to the application of modern statistical analysis to temporal economic data. Originally published in 1967. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Nonlinear And Multisectoral Macrodynamics
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Author : Kumaraswamy Velupillai
language : en
Publisher: Springer
Release Date : 1990-06-18
Nonlinear And Multisectoral Macrodynamics written by Kumaraswamy Velupillai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-06-18 with Business & Economics categories.
A collection of essays concerned with nonlinear and multisectoral macrodynamics written in honour of Richard Goodwin which includes discussion of Goodwin's contribution and ideas in comparison with other theories.
Model Free Prediction And Regression
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Author : Dimitris N. Politis
language : en
Publisher: Springer
Release Date : 2015-11-13
Model Free Prediction And Regression written by Dimitris N. Politis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-13 with Mathematics categories.
The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality. Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, computer-intensive methods such as the bootstrap and cross-validation freed practitioners from the limitations of parametric models, and paved the way towards the `big data' era of the 21st century. Nonetheless, there is a further step one may take, i.e., going beyond even nonparametric models; this is where the Model-Free Prediction Principle is useful. Interestingly, being able to predict a response variable Y associated with a regressor variable X taking on any possible value seems to inadvertently also achieve the main goal of modeling, i.e., trying to describe how Y depends on X. Hence, as prediction can be treated as a by-product of model-fitting, key estimation problems can be addressed as a by-product of being able to perform prediction. In other words, a practitioner can use Model-Free Prediction ideas in order to additionally obtain point estimates and confidence intervals for relevant parameters leading to an alternative, transformation-based approach to statistical inference.
Recent Advances And Future Directions In Causality Prediction And Specification Analysis
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Author : Xiaohong Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-01
Recent Advances And Future Directions In Causality Prediction And Specification Analysis written by Xiaohong Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-01 with Business & Economics categories.
This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.