Search Results for "introduction-to-statistics-and-econometrics"

Introduction to Statistics and Econometrics

Introduction to Statistics and Econometrics

  • Author: Takeshi Amemiya
  • Publisher: Harvard University Press
  • ISBN: 9780674462250
  • Category: Business & Economics
  • Page: 368
  • View: 804
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This outstanding text by a foremost econometrician combines instruction in probability and statistics with econometrics in a rigorous but relatively nontechnical manner. Unlike many statistics texts, it discusses regression analysis in depth. And unlike many econometrics texts, it offers a thorough treatment of statistics. Although its only mathematical requirement is multivariate calculus, it challenges the student to think deeply about basic concepts. The coverage of probability and statistics includes best prediction and best linear prediction, the joint distribution of a continuous and discrete random variable, large sample theory, and the properties of the maximum likelihood estimator. Exercises at the end of each chapter reinforce the many illustrative examples and diagrams. Believing that students should acquire the habit of questioning conventional statistical techniques, Takeshi Amemiya discusses the problem of choosing estimators and compares various criteria for ranking them. He also evaluates classical hypothesis testing critically, giving the realistic case of testing a composite null against a composite alternative. He frequently adopts a Bayesian approach because it provides a useful pedagogical framework for discussing many fundamental issues in statistical inference. Turning to regression, Amemiya presents the classical bivariate model in the conventional summation notation. He follows with a brief introduction to matrix analysis and multiple regression in matrix notation. Finally, he describes various generalizations of the classical regression model and certain other statistical models extensively used in econometrics and other applications in social science.

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
  • ISBN: 9780521542241
  • Category: Business & Economics
  • Page: 323
  • View: 7472
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This book is intended for use in a rigorous introductory PhD level course in econometrics.

Introduction to Statistical Time Series

Introduction to Statistical Time Series

  • Author: Wayne A. Fuller,J.K. Watson,Wayne Arthur Fuller
  • Publisher: John Wiley & Sons
  • ISBN: 9780471552390
  • Category: Mathematics
  • Page: 698
  • View: 9486
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The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: Moving average and autoregressive processes Introduction to Fourier analysis Spectral theory and filtering Large sample theory Estimation of the mean and autocorrelations Estimation of the spectrum Parameter estimation Regression, trend, and seasonality Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.

Introduction to the Theory and Practice of Econometrics

Introduction to the Theory and Practice of Econometrics

  • Author: George G. Judge
  • Publisher: John Wiley & Sons
  • ISBN: N.A
  • Category: Business & Economics
  • Page: 839
  • View: 1492
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Foundations: statistical model specification, estimation, and inferencce; The general linear statistical model; The generalized linear statistical model; Simultaneous linear statistical models; Some procedures for handling an unknown covariance matrix; Pooling of data and varying parameter models; Unobservable and qualitative variables; Nonsample information, biased estimation and choosing the dimension and form of the design matrix; The nonlinear statistical model; Time series and distributed lag models.

Introduction to Bayesian Econometrics

Introduction to Bayesian Econometrics

  • Author: Edward Greenberg
  • Publisher: Cambridge University Press
  • ISBN: 1107015316
  • Category: Business & Economics
  • Page: 249
  • View: 362
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This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.

Ökonometrie für Dummies

Ökonometrie für Dummies

  • Author: Roberto Pedace
  • Publisher: John Wiley & Sons
  • ISBN: 3527801529
  • Category: Business & Economics
  • Page: 388
  • View: 1752
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Theorien verstehen und Techniken anwenden Was haben die Gehälter von Spitzensportlern und der Mindestlohn gemeinsam? Richtig, man kann sie mit Ökonometrie erforschen. Im Buch steht, wie es geht. Und nicht nur dafür, sondern für viele weitere Gebiete lohnt es sich, der zunächst etwas trocken und sperrig anmutenden Materie eine Chance zu geben. Lernen Sie von den Autoren, wie Sie spannende Fragen formulieren, passende Variablen festlegen, treffsichere Modelle entwerfen und Ihre Aussagen auf Herz und Nieren prüfen. Werden Sie sicher im Umgang mit Hypothesentests, Regressionsmodellen, Logit- & Probit-Modellen und allen weiteren gängigen Methoden der Ökonometrie. So begleitet Ökonometrie für Dummies Sie Schritt für Schritt und mit vielen Beispielen samt R Output durch dieses spannende Thema.

An Introduction to Bayesian Inference in Econometrics

An Introduction to Bayesian Inference in Econometrics

  • Author: Arnold Zellner
  • Publisher: Wiley-Interscience
  • ISBN: 9780471169376
  • Category: Mathematics
  • Page: 448
  • View: 369
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This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics. This historical volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The coverage ranges from the fundamental concepts and operations of Bayesian inference to analysis of applications in specific econometric problems and the testing of hypotheses and models.

Introduction to Spatial Econometrics

Introduction to Spatial Econometrics

  • Author: James LeSage,Robert Kelley Pace
  • Publisher: CRC Press
  • ISBN: 9781420064254
  • Category: Mathematics
  • Page: 340
  • View: 9729
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Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances. Leaders in this field, the authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models, especially ones that include spatial lags of the dependent variable. The authors also examine the relationship between spatiotemporal processes and long-run equilibrium states that are characterized by simultaneous spatial dependence. MATLAB® toolboxes useful for spatial econometric estimation are available on the authors’ websites. This work covers spatial econometric modeling as well as numerous applied illustrations of the methods. It encompasses many recent advances in spatial econometric models—including some previously unpublished results.

Statistical Foundations of Econometric Modelling

Statistical Foundations of Econometric Modelling

  • Author: Aris Spanos
  • Publisher: Cambridge University Press
  • ISBN: 9780521269124
  • Category: Business & Economics
  • Page: 695
  • View: 7513
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This book provides an introduction to econometrics through a thorough grounding in probability theory and statistical inference. The emphasis is on the concepts and ideas underlying probability theory and statistical inference, and on motivating the learning of them both at a formal and an intuitive level. By basing its approach on the underlying theory, it is able to cover fully the econometric theory required up to the intermediate level; its emphasis on mastering the concepts makes it an ideal introduction to the advanced texts and the econometric literature.

Introduction to Statistics

Introduction to Statistics

Using Interactive MM*Stat Elements

  • Author: Wolfgang Karl Härdle,Sigbert Klinke,Bernd Rönz
  • Publisher: Springer
  • ISBN: 3319177044
  • Category: Business & Economics
  • Page: 516
  • View: 4047
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This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students’ knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and the practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc.

Einführung in die Statistik der Finanzmärkte

Einführung in die Statistik der Finanzmärkte

  • Author: Jürgen Franke,Wolfgang Karl Härdle,Christian Matthias Hafner
  • Publisher: Springer-Verlag
  • ISBN: 3642170498
  • Category: Business & Economics
  • Page: 428
  • View: 1147
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Introduction to Econometrics

Introduction to Econometrics

  • Author: Christopher Dougherty
  • Publisher: Oxford University Press
  • ISBN: 0199567085
  • Category: Business & Economics
  • Page: 573
  • View: 2043
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Taking a modern approach to the subject, this text provides students with a solid grounding in econometrics, using non-technical language wherever possible.

An Introduction to Modern Econometrics Using Stata

An Introduction to Modern Econometrics Using Stata

  • Author: Christopher F. Baum
  • Publisher: Stata Press
  • ISBN: 1597180130
  • Category: Business & Economics
  • Page: 341
  • View: 3493
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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.

Introduction to Statistical Methods for Financial Models

Introduction to Statistical Methods for Financial Models

  • Author: Thomas A Severini
  • Publisher: CRC Press
  • ISBN: 1351981900
  • Category: Business & Economics
  • Page: 370
  • View: 1185
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This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.

Handbook of Applied Economic Statistics

Handbook of Applied Economic Statistics

  • Author: Aman Ullah
  • Publisher: CRC Press
  • ISBN: 9780824701291
  • Category: Mathematics
  • Page: 640
  • View: 1258
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This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.

Introduction to Statistics and Data Analysis

Introduction to Statistics and Data Analysis

With Exercises, Solutions and Applications in R

  • Author: Christian Heumann,Michael Schomaker,Shalabh
  • Publisher: Springer
  • ISBN: 3319461621
  • Category: Mathematics
  • Page: 456
  • View: 9409
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This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

Contemporary Bayesian Econometrics and Statistics

Contemporary Bayesian Econometrics and Statistics

  • Author: John Geweke
  • Publisher: John Wiley & Sons
  • ISBN: 0471744727
  • Category: Mathematics
  • Page: 300
  • View: 5691
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Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding ofBayesian analysis that is grounded in the theory of inference andoptimal decision making. Contemporary Bayesian Econometrics andStatistics provides readers with state-of-the-art simulationmethods and models that are used to solve complex real-worldproblems. Armed with a strong foundation in both theory andpractical problem-solving tools, readers discover how to optimizedecision making when faced with problems that involve limited orimperfect data. The book begins by examining the theoretical and mathematicalfoundations of Bayesian statistics to help readers understand howand why it is used in problem solving. The author then describeshow modern simulation methods make Bayesian approaches practicalusing widely available mathematical applications software. Inaddition, the author details how models can be applied to specificproblems, 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 decadeof classroom experience, and readers will find the author'sapproach very engaging and accessible. There are nearly 200examples and exercises to help readers see how effective use ofBayesian statistics enables them to make optimal decisions. MATLAB?and R computer programs are integrated throughout the book. Anaccompanying Web site provides readers with computer code for manyexamples and datasets. This publication is tailored for research professionals who useeconometrics and similar statistical methods in their work. Withits emphasis on practical problem solving and extensive use ofexamples and exercises, this is also an excellent textbook forgraduate-level students in a broad range of fields, includingeconomics, statistics, the social sciences, business, and publicpolicy.