Introduction to the Mathematical and Statistical Foundations of Econometrics, Herman J. Bierens
Автор: Angrist, J.d. Pischke, Jorn-steffen Название: Mostly harmless econometrics ISBN: 0691120358 ISBN-13(EAN): 9780691120355 Издательство: Wiley Рейтинг: Цена: 7128 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Shows how the basic tools of applied econometrics allow the data to speak. This book covers regression-discontinuity designs and quantile regression - as well as how to get standard errors right. It is suitable for various areas in contemporary social science.
Автор: Dougherty Christopher Название: Introduction to Econometrics, 5 ed. ISBN: 0199676828 ISBN-13(EAN): 9780199676828 Издательство: Oxford Academ Рейтинг: Цена: 11403 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Combining the rigour of econometric theory with an accessible style, Dougherty`s step by step explanations and relevant practical exercises ensure students develop an intuitive understanding of econometrics, and gain hands-on experience of the tools used in economic and financial forecasting.
Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems.
Автор: Philip Hans Franses Название: A Concise Introduction to Econometrics ISBN: 0521520908 ISBN-13(EAN): 9780521520904 Издательство: Cambridge Academ Рейтинг: Цена: 6334 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Assuming only basic familiarity with matrix algebra and calculus this 2002 book is an ideal introduction for students of econometrics. Focusing on a limited number of the most widely used methods, the book reviews the basics of econometrics and ends with seven case studies drawn from recent empirical work.
Автор: Moss Название: Mathematical Statistics for Applied Econometrics ISBN: 1466594098 ISBN-13(EAN): 9781466594098 Издательство: Taylor&Francis Рейтинг: Цена: 15246 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An Introductory Econometrics Text
Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques.
Uses Computer Systems to Simplify Computation
The text explores the unifying themes involved in quantifying sample information to make inferences. After developing the necessary probability theory, it presents the concepts of estimation, such as convergence, point estimators, confidence intervals, and hypothesis tests. The text then shifts from a general development of mathematical statistics to focus on applications particularly popular in economics. It delves into matrix analysis, linear models, and nonlinear econometric techniques.
Students Understand the Reasons for the Results
Avoiding a cookbook approach to econometrics, this textbook develops students' theoretical understanding of statistical tools and econometric applications. It provides them with the foundation for further econometric studies.
Автор: Brooks Название: Introductory Econometrics for Finance ISBN: 1107661455 ISBN-13(EAN): 9781107661455 Издательство: Cambridge Academ Рейтинг: Цена: 7918 р. Наличие на складе: Нет в наличии.
Описание: This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.
Автор: Baum Название: An Introduction to Modern Econometrics Using Stata ISBN: 1597180130 ISBN-13(EAN): 9781597180139 Издательство: Taylor&Francis Рейтинг: Цена: 12631 р. Наличие на складе: Невозможна поставка.
Описание:
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata.
As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming. Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.
Автор: Dougherty, Christopher Название: Introduction to Econometrics ISBN: 0199567085 ISBN-13(EAN): 9780199567089 Издательство: Oxford Academ Рейтинг: Цена: 7285 р. Наличие на складе: Нет в наличии.
Описание: Introduction to Econometrics provides students with clear and simple mathematics notation and step-by step explanations of mathematical proofs to give them a thorough understanding of the subject. Extensive exercises throughout to encourage students to apply the techniques and gain confidence with, this new edition has been thoroughly revised in line with market feedback. Retaining its student-friendly approach, Introduction to Econometrics has a comprehensive revision guide to all the essential statistical concepts needed to study econometrics, more Monte Carlo simulations than before and new summaries and non-technical introductions to more advanced topics at the end of chapters.
Автор: Verbeek M Название: A Guide to Modern Econometrics ISBN: 1119951674 ISBN-13(EAN): 9781119951674 Издательство: Wiley Рейтинг: Цена: 7918 р. Наличие на складе: Нет в наличии.
Описание: This highly successful text serves as a guide to alternative techniques in econometrics with an emphasis on the practical application of these approaches. The 4th Edition features: Coverage of a wide range of topics, including time series analysis, cointegration, limited dependent variables, panel data analysis and the generalized method of moments. Intuitive presentation and discussion, with a focus on implementation and practical relevance. A large number of empirical illustrations taken from a wide variety of fields, including international economics, finance, labour economics and macroeconomics. Increased focus on robust inference and small sample properties. End-of-chapter exercises, both theoretical and empirical, reviewing key concepts. Updated and expanded coverage, on various topics such as missing data, outliers, forecast evaluation, the estimation of treatment effects and panel unit root tests. Supplementary material, including PowerPoint slides for lecturers, data sets of the empirical illustrations and exercises, and solutions to selected exercises in each chapter, available at www.wileyeurope.com/college/verbeek
Название: Introduction to Spatial Econometrics ISBN: 142006424X ISBN-13(EAN): 9781420064247 Издательство: Taylor&Francis Рейтинг: Цена: 15972 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. This title explores a range of alternative topics, including maximum likelihood and Bayesian estimation and applied modeling situations involving different circumstances.
Автор: Greenberg Название: Introduction to Bayesian Econometrics ISBN: 1107015316 ISBN-13(EAN): 9781107015319 Издательство: Cambridge Academ Рейтинг: Цена: 7760 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook is an introduction to econometrics from the Bayesian viewpoint. New material includes a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The R programming language is also emphasized.
Автор: Greenberg Название: Introduction to Bayesian Econometrics ISBN: 110743677X ISBN-13(EAN): 9781107436770 Издательство: Cambridge Academ Рейтинг: Цена: 5701 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook is an introduction to econometrics from the Bayesian viewpoint. New material includes a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The R programming language is also emphasized.
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