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Introduction To The Mathematical And Statistical Foundations Of Econometrics


Introduction To The Mathematical And Statistical Foundations Of Econometrics
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Introduction To The Mathematical And Statistical Foundations Of Econometrics


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.



Introduction To The Mathematical And Statistical Foundations Of Econometrics


Introduction To The Mathematical And Statistical Foundations Of Econometrics
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Author : Herman J. Bierens
language : en
Publisher:
Release Date : 2003

Introduction To The Mathematical And Statistical Foundations Of Econometrics written by Herman J. Bierens and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Econometria categories.




Statistical Foundations Of Econometric Modelling


Statistical Foundations Of Econometric Modelling
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Author : Aris Spanos
language : en
Publisher: Cambridge University Press
Release Date : 1986-10-30

Statistical Foundations Of Econometric Modelling written by Aris Spanos 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 1986-10-30 with Business & Economics categories.


A thorough foundation in probability theory and statistical inference provides an introduction to the underlying theory of econometrics that motivates the student at a intuitive as well as a formal level.



The Oxford Handbook Of Applied Nonparametric And Semiparametric Econometrics And Statistics


The Oxford Handbook Of Applied Nonparametric And Semiparametric Econometrics And Statistics
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Author : Jeffrey Racine
language : en
Publisher: Oxford University Press
Release Date : 2014-04

The Oxford Handbook Of Applied Nonparametric And Semiparametric Econometrics And Statistics written by Jeffrey 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 2014-04 with Business & Economics categories.


This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.



Applied Time Series Econometrics


Applied Time Series Econometrics
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Author : Geda, Alemayehu
language : en
Publisher: University of Nairobi Press
Release Date : 2015-03-16

Applied Time Series Econometrics written by Geda, Alemayehu and has been published by University of Nairobi Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Business & Economics categories.


This book attempts to demystify time series econometrics so as to equip macroeconomic researchers focusing on Africa with solid but accessible foundation in applied time series techniques that can deal with challenges of developing economic models using African data.



Econometric Modeling And Inference


Econometric Modeling And Inference
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Author : Jean-Pierre Florens
language : en
Publisher: Cambridge University Press
Release Date : 2007-07-02

Econometric Modeling And Inference written by Jean-Pierre Florens 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 2007-07-02 with Business & Economics categories.


Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.



Econometric Modelling With Time Series


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.



Statistical Theory And Inference


Statistical Theory And Inference
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Author : David J. Olive
language : en
Publisher: Springer
Release Date : 2014-05-07

Statistical Theory And Inference written by David J. Olive and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-07 with Mathematics categories.


This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.



Almost All About Unit Roots


Almost All About Unit Roots
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Author : In Choi
language : en
Publisher: Cambridge University Press
Release Date : 2015-05-12

Almost All About Unit Roots written by In Choi 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 2015-05-12 with Business & Economics categories.


Many economic theories depend on the presence or absence of a unit root for their validity, making familiarity with unit roots extremely important to econometric and statistical theory. This book introduces the literature on unit roots in a comprehensive manner to empirical and theoretical researchers in economics and other areas.



Time Series And Panel Data Econometrics


Time Series And Panel Data Econometrics
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Author : M. Hashem Pesaran
language : en
Publisher: Oxford University Press
Release Date : 2015-10-01

Time Series And Panel Data Econometrics written by M. Hashem Pesaran 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 2015-10-01 with Business & Economics categories.


This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.