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Introduction to the Mathematical and Statistical Foundations of Econometrics

Introduction to the Mathematical and Statistical Foundations of Econometrics
Author: Herman J. Bierens
Publisher: Cambridge University Press
Total Pages: 356
Release: 2004-12-20
Genre: Business & Economics
ISBN: 9780521542241

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This book is intended for use in a rigorous introductory PhD level course in econometrics.


Intermediate Statistics and Econometrics

Intermediate Statistics and Econometrics
Author: Dale J. Poirier
Publisher: MIT Press
Total Pages: 744
Release: 1995
Genre: Business & Economics
ISBN: 9780262161497

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The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.


Statistical Foundations of Data Science

Statistical Foundations of Data Science
Author: Jianqing Fan
Publisher: CRC Press
Total Pages: 752
Release: 2020-09-21
Genre: Mathematics
ISBN: 1466510854

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Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.


Statistical Foundations of Econometric Modelling

Statistical Foundations of Econometric Modelling
Author: Aris Spanos
Publisher: Cambridge University Press
Total Pages: 722
Release: 1986-10-30
Genre: Business & Economics
ISBN: 9780521269124

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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.


Econometrics

Econometrics
Author: P. J. Dhrymes
Publisher: Springer Science & Business Media
Total Pages: 605
Release: 2012-12-06
Genre: Business & Economics
ISBN: 1461393833

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The Foundations of Econometric Analysis

The Foundations of Econometric Analysis
Author: David F. Hendry
Publisher: Cambridge University Press
Total Pages: 582
Release: 1997-02-20
Genre: Business & Economics
ISBN: 9780521588706

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Collection of classic papers by pioneer econometricians


An Introduction to Econometric Theory

An Introduction to Econometric Theory
Author: James Davidson
Publisher: John Wiley & Sons
Total Pages: 256
Release: 2018-07-18
Genre: Business & Economics
ISBN: 1119484928

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A guide to economics, statistics and finance that explores the mathematical foundations underling econometric methods An Introduction to Econometric Theory offers a text to help in the mastery of the mathematics that underlie econometric methods and includes a detailed study of matrix algebra and distribution theory. Designed to be an accessible resource, the text explains in clear language why things are being done, and how previous material informs a current argument. The style is deliberately informal with numbered theorems and lemmas avoided. However, very few technical results are quoted without some form of explanation, demonstration or proof. The author — a noted expert in the field — covers a wealth of topics including: simple regression, basic matrix algebra, the general linear model, distribution theory, the normal distribution, properties of least squares, unbiasedness and efficiency, eigenvalues, statistical inference in regression, t and F tests, the partitioned regression, specification analysis, random regressor theory, introduction to asymptotics and maximum likelihood. Each of the chapters is supplied with a collection of exercises, some of which are straightforward and others more challenging. This important text: Presents a guide for teaching econometric methods to undergraduate and graduate students of economics, statistics or finance Offers proven classroom-tested material Contains sets of exercises that accompany each chapter Includes a companion website that hosts additional materials, solution manual and lecture slides Written for undergraduates and graduate students of economics, statistics or finance, An Introduction to Econometric Theory is an essential beginner’s guide to the underpinnings of econometrics.


Probability Theory and Statistical Inference

Probability Theory and Statistical Inference
Author: Aris Spanos
Publisher: Cambridge University Press
Total Pages: 787
Release: 2019-09-19
Genre: Business & Economics
ISBN: 1107185149

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This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.


Introductory Econometrics for Finance

Introductory Econometrics for Finance
Author: Chris Brooks
Publisher: Cambridge University Press
Total Pages: 752
Release: 2008-05-22
Genre: Business & Economics
ISBN: 1139472305

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This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.