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Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition


Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition
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Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition


Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition
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Author : Hrishikesh D Vinod
language : en
Publisher: World Scientific
Release Date : 2022-04-08

Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition written by Hrishikesh D Vinod and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-08 with Business & Economics categories.


How to learn both applied statistics (econometrics) and free, open-source software R? This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics. No other text provides software snippets to learn so many new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying. The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.The second edition's preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows' Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.



Hands On Intermediate Econometrics Using R Templates For Extending Dozens Of Practical Examples With Cd Rom


Hands On Intermediate Econometrics Using R Templates For Extending Dozens Of Practical Examples With Cd Rom
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Author : Hrishikesh D Vinod
language : en
Publisher: World Scientific Publishing Company
Release Date : 2008-10-30

Hands On Intermediate Econometrics Using R Templates For Extending Dozens Of Practical Examples With Cd Rom written by Hrishikesh D Vinod and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-30 with Business & Economics categories.


This book explains how to use R software to teach econometrics by providing interesting examples, using actual data applied to important policy issues. It helps readers choose the best method from a wide array of tools and packages available. The data used in the examples along with R program snippets, illustrate the economic theory and sophisticated statistical methods extending the usual regression. The R program snippets are not merely given as black boxes, but include detailed comments which help the reader better understand the software steps and use them as templates for possible extension and modification.



Hands On Intermediate Econometrics Using R


Hands On Intermediate Econometrics Using R
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Author : Hrishikesh D. Vinod
language : en
Publisher:
Release Date : 2010

Hands On Intermediate Econometrics Using R written by Hrishikesh D. Vinod and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.


This book explains how to use R software to teach econometrics by providing interesting examples, using actual data applied to important policy issues. It helps readers choose the best method from a wide array of tools and packages available. The data used in the examples along with R program snippets, illustrate the economic theory and sophisticated statistical methods extending the usual regression. The R program snippets are not merely given as black boxes, but include detailed comments which help the reader better understand the software steps and use them as templates for possible extension and modification.



Hands On Intermediate Econometrics Using R


Hands On Intermediate Econometrics Using R
DOWNLOAD
Author : Hrishikesh D. Vinod
language : en
Publisher: World Scientific
Release Date : 2008

Hands On Intermediate Econometrics Using R written by Hrishikesh D. Vinod and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.


This book explains how to use R software to teach econometrics by providing interesting examples, using actual data applied to important policy issues. It helps readers choose the best method from a wide array of tools and packages available. The data used in the examples along with R program snippets, illustrate the economic theory and sophisticated statistical methods extending the usual regression. The R program snippets are not merely given as black boxes, but include detailed comments which help the reader better understand the software steps and use them as templates for possible extension and modification.



Financial Macro And Micro Econometrics Using R


Financial Macro And Micro Econometrics Using R
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Author :
language : en
Publisher: North Holland
Release Date : 2020-01-20

Financial Macro And Micro Econometrics Using R written by and has been published by North Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-20 with Mathematics categories.


Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.



Conceptual Econometrics Using R


Conceptual Econometrics Using R
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Author :
language : en
Publisher: Elsevier
Release Date : 2019-08-20

Conceptual Econometrics Using R written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-20 with Mathematics categories.


Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. - Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society - Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art



Applied Econometrics With R


Applied Econometrics With R
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Author : Christian Kleiber
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-10

Applied Econometrics With R written by Christian Kleiber 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 2008-12-10 with Business & Economics categories.


R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.



Time Series Econometrics


Time Series Econometrics
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Author : John D. Levendis
language : en
Publisher: Springer Nature
Release Date : 2023-12-23

Time Series Econometrics written by John D. Levendis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-23 with Business & Economics categories.


Revised and updated for the second edition, this textbook allows students to work through classic texts in economics and finance, using the original data and replicating their results. In this book, the author rejects the theorem-proof approach as much as possible, and emphasizes the practical application of econometrics. They show with examples how to calculate and interpret the numerical results. This book begins with students estimating simple univariate models, in a step by step fashion, using the popular Stata software system. Students then test for stationarity, while replicating the actual results from hugely influential papers such as those by Granger & Newbold, and Nelson & Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot & Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. Finally, students estimate static and dynamic panel data models, replicating papers by Thompson, and Arellano & Bond. The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful. “How to best start learning time series econometrics? Learning by doing. This is the ethos of this book. What makes this book useful is that it provides numerous worked out examples along with basic concepts. It is a fresh, no-nonsense, practical approach that students will love when they start learning time series econometrics. I recommend this book strongly as a study guide for students who look for hands-on learning experience." --Professor Sokbae "Simon" Lee, Columbia University, Co-Editor of Econometric Theory and Associate Editor of Econometrics Journal.



Advanced Econometric Methods


Advanced Econometric Methods
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Author : Thomas B. Fomby
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advanced Econometric Methods written by Thomas B. Fomby 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 2012-12-06 with Business & Economics categories.


This book had its conception in 1975in a friendly tavern near the School of Businessand PublicAdministration at the UniversityofMissouri-Columbia. Two of the authors (Fomby and Hill) were graduate students of the third (Johnson), and were (and are) concerned about teaching econometrics effectively at the graduate level. We decided then to write a book to serve as a comprehensive text for graduate econometrics. Generally, the material included in the bookand itsorganization have been governed by the question, " Howcould the subject be best presented in a graduate class?" For content, this has meant that we have tried to cover " all the bases " and yet have not attempted to be encyclopedic. The intended purpose has also affected the levelofmathematical rigor. We have tended to prove only those results that are basic and/or relatively straightforward. Proofs that would demand inordinant amounts of class time have simply been referenced. The book is intended for a two-semester course and paced to admit more extensive treatment of areas of specific interest to the instructor and students. We have great confidence in the ability, industry, and persistence of graduate students in ferreting out and understanding the omitted proofs and results. In the end, this is how one gains maturity and a fuller appreciation for the subject in any case. It is assumed that the readers of the book will have had an econometric methods course, using texts like J. Johnston's Econometric Methods, 2nd ed.



Reproducible Econometrics Using R


Reproducible Econometrics Using R
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Author : Jeffrey S. Racine
language : en
Publisher: Oxford University Press
Release Date : 2018-12-24

Reproducible Econometrics Using R written by Jeffrey S. Racine and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-24 with Business & Economics categories.


Across the social sciences there has been increasing focus on reproducibility, i.e., the ability to examine a study's data and methods to ensure accuracy by reproducing the study. Reproducible Econometrics Using R combines an overview of key issues and methods with an introduction to how to use them using open source software (R) and recently developed tools (R Markdown and bookdown) that allow the reader to engage in reproducible econometric research. Jeffrey S. Racine provides a step-by-step approach, and covers five sets of topics, i) linear time series models, ii) robust inference, iii) robust estimation, iv) model uncertainty, and v) advanced topics. The time series material highlights the difference between time-series analysis, which focuses on forecasting, versus cross-sectional analysis, where the focus is typically on model parameters that have economic interpretations. For the time series material, the reader begins with a discussion of random walks, white noise, and non-stationarity. The reader is next exposed to the pitfalls of using standard inferential procedures that are popular in cross sectional settings when modelling time series data, and is introduced to alternative procedures that form the basis for linear time series analysis. For the robust inference material, the reader is introduced to the potential advantages of bootstrapping and the Jackknifing versus the use of asymptotic theory, and a range of numerical approaches are presented. For the robust estimation material, the reader is presented with a discussion of issues surrounding outliers in data and methods for addressing their presence. Finally, the model uncertainly material outlines two dominant approaches for dealing with model uncertainty, namely model selection and model averaging. Throughout the book there is an emphasis on the benefits of using R and other open source tools for ensuring reproducibility. The advanced material covers machine learning methods (support vector machines that are useful for classification) and nonparametric kernel regression which provides the reader with more advanced methods for confronting model uncertainty. The book is well suited for advanced undergraduate and graduate students alike. Assignments, exams, slides, and a solution manual are available for instructors.