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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.
Providing an introduction to mathematical analysis as it applies to economic theory and econometrics, this book bridges the gap that has separated the teaching of basic mathematics for economics and the increasingly advanced mathematics demanded in economics research today. Dean Corbae, Maxwell B. Stinchcombe, and Juraj Zeman equip students with the knowledge of real and functional analysis and measure theory they need to read and do research in economic and econometric theory. Unlike other mathematics textbooks for economics, An Introduction to Mathematical Analysis for Economic Theory and Econometrics takes a unified approach to understanding basic and advanced spaces through the application of the Metric Completion Theorem. This is the concept by which, for example, the real numbers complete the rational numbers and measure spaces complete fields of measurable sets. Another of the book's unique features is its concentration on the mathematical foundations of econometrics. To illustrate difficult concepts, the authors use simple examples drawn from economic theory and econometrics. Accessible and rigorous, the book is self-contained, providing proofs of theorems and assuming only an undergraduate background in calculus and linear algebra. Begins with mathematical analysis and economic examples accessible to advanced undergraduates in order to build intuition for more complex analysis used by graduate students and researchers Takes a unified approach to understanding basic and advanced spaces of numbers through application of the Metric Completion Theorem Focuses on examples from econometrics to explain topics in measure theory
Taking a modern approach to the subject, this text provides students with a solid grounding in econometrics, using non-technical language wherever possible.
Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.-Publisher's description.
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians. In addition, because economic data are generated in a variety of different contexts (time series, cross sections, time series--cross sections), we pay particular attention to the similarities and differences in the techniques appropriate to each of these contexts.
Introduce your students to how empirical researchers actually think about and apply econometric methods with the practical, professional approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Unlike traditional texts, this book's unique presentation demonstrates how econometrics can be used to empirically study and answer questions across a variety of disciplines. A reflection of how econometric instruction has evolved, INTRODUCTORY ECONOMETRICS is organized around the type of data being analyzed with a systematic approach, where assumptions are introduced only as they are needed to obtain a certain result. This approach simplifies the exposition and makes the text's material easier for students to comprehend. Packed with timely, relevant applications the text emphasizes examples that have implications for policy or provide evidence for or against economic theories. More than 100 intriguing data sets are now available in six formats for your teaching flexibility. A wealth of new and revised instructor resources, written by the author, is provided at no cost to the instructor. The Instructor's Manual with Solutions contains answers to all problems and exercises, teaching tips on how to present the material in each chapter and also sources for each of the data files, with many suggestions on how to use them on problem sets, exams, and term papers. For the first time ever, a new Test Bank has been created to aid instructors as they teach the course. PowerPoint slides and Scientific Word slides are also new to this edition. The updated Data Set Handbook is also available to help instructors present the latest emerging developments in the field. Give your students a full understanding of how econometrics is genuinely useful for answering questions in business, policy evaluation, and forecasting environments with INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
This textbook makes learning the basic principles of econometrics easy for all undergraduate and graduate students of economics. It takes the readers step-by-step from introduction to understanding, first introducing the basic statistical tools like concepts of probability, statistical distributions, and hypothesis tests, and then going on to explain the two variable linear regression models along with certain additional tools like use of dummy variables, various data transformations amongst others. The most innovative feature of this textbook is that it familiarizes students with the role of R, which is a flexible and popular programming language. With its help, the student will be able to implement a linear regression model and deal with the associated problems with substantial confidence.
Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.
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.