Modern Series Methods In Econometrics And Statistics
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Introduction To Modern Time Series Analysis
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Author : Gebhard Kirchgässner
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-17
Introduction To Modern Time Series Analysis written by Gebhard Kirchgässner 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 2007-08-17 with Business & Economics categories.
This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series. It also covers modeling volatilities of financial time series with autoregressive conditional heteroskedastic models.
Modern Series Methods In Econometrics And Statistics
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Author : CHAOHUA. GAO DONG (JITI.)
language : en
Publisher:
Release Date : 2025
Modern Series Methods In Econometrics And Statistics written by CHAOHUA. GAO DONG (JITI.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Methods For Estimation And Inference In Modern Econometrics
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Author : Stanislav Anatolyev
language : en
Publisher: CRC Press
Release Date : 2011-06-07
Methods For Estimation And Inference In Modern Econometrics written by Stanislav Anatolyev and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-07 with Business & Economics categories.
This book covers important topics in econometrics. It discusses methods for efficient estimation in models defined by unconditional and conditional moment restrictions, inference in misspecified models, generalized empirical likelihood estimators, and alternative asymptotic approximations. The first chapter provides a general overview of established nonparametric and parametric approaches to estimation and conventional frameworks for statistical inference. The next several chapters focus on the estimation of models based on moment restrictions implied by economic theory. The final chapters cover nonconventional asymptotic tools that lead to improved finite-sample inference.
Computational Methods In Statistics And Econometrics
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Author : Hisashi Tanizaki
language : en
Publisher: CRC Press
Release Date : 2004-01-21
Computational Methods In Statistics And Econometrics written by Hisashi Tanizaki and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-21 with Mathematics categories.
Reflecting current technological capacities and analytical trends, Computational Methods in Statistics and Econometrics showcases Monte Carlo and nonparametric statistical methods for models, simulations, analyses, and interpretations of statistical and econometric data. The author explores applications of Monte Carlo methods in Bayesian estimation, state space modeling, and bias correction of ordinary least squares in autoregressive models. The book offers straightforward explanations of mathematical concepts, hundreds of figures and tables, and a range of empirical examples. A CD-ROM packaged with the book contains all of the source codes used in the text.
Foundations Of Modern Econometrics A Unified Approach
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Author : Yongmiao Hong
language : en
Publisher: World Scientific
Release Date : 2020-07-13
Foundations Of Modern Econometrics A Unified Approach written by Yongmiao Hong and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-13 with Business & Economics categories.
Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.
Econometric Modelling With Time Series
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Author : Vance Martin
language : en
Publisher: Cambridge University Press
Release Date : 2013
Econometric Modelling With Time Series written by Vance Martin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
"Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.
Introduction To The Mathematical And Statistical Foundations Of Econometrics
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Author : Herman J. Bierens
language : en
Publisher: Cambridge University Press
Release Date : 2004-12-20
Introduction To The Mathematical And Statistical Foundations Of Econometrics written by Herman J. Bierens and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-20 with Business & Economics categories.
This book is intended for use in a rigorous introductory PhD level course in econometrics.
Contemporary Bayesian Econometrics And Statistics
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Author : John Geweke
language : en
Publisher: John Wiley & Sons
Release Date : 2005-10-03
Contemporary Bayesian Econometrics And Statistics written by John Geweke and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-03 with Mathematics categories.
Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making. Contemporary Bayesian Econometrics and Statistics provides readers with state-of-the-art simulation methods and models that are used to solve complex real-world problems. Armed with a strong foundation in both theory and practical problem-solving tools, readers discover how to optimize decision making when faced with problems that involve limited or imperfect data. The book begins by examining the theoretical and mathematical foundations of Bayesian statistics to help readers understand how and why it is used in problem solving. The author then describes how modern simulation methods make Bayesian approaches practical using widely available mathematical applications software. In addition, the author details how models can be applied to specific problems, including: * Linear models and policy choices * Modeling with latent variables and missing data * Time series models and prediction * Comparison and evaluation of models The publication has been developed and fine- tuned through a decade of classroom experience, and readers will find the author's approach very engaging and accessible. There are nearly 200 examples and exercises to help readers see how effective use of Bayesian statistics enables them to make optimal decisions. MATLAB? and R computer programs are integrated throughout the book. An accompanying Web site provides readers with computer code for many examples and datasets. This publication is tailored for research professionals who use econometrics and similar statistical methods in their work. With its emphasis on practical problem solving and extensive use of examples and exercises, this is also an excellent textbook for graduate-level students in a broad range of fields, including economics, statistics, the social sciences, business, and public policy.
Applied Time Series Econometrics
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Author : Helmut Lütkepohl
language : en
Publisher: Cambridge University Press
Release Date : 2004-08-02
Applied Time Series Econometrics written by Helmut Lütkepohl and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-02 with Business & Economics categories.
Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
Econometrics In Theory And Practice
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Author : Panchanan Das
language : en
Publisher: Springer Nature
Release Date : 2019-09-05
Econometrics In Theory And Practice written by Panchanan Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-05 with Business & Economics categories.
This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.