Econometric Methods with Applications in Business and Economics [NOOK Book]

Overview

Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics.

Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple...
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Econometric Methods with Applications in Business and Economics

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Overview

Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics.

Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration
data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations).

Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management.

Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics.

Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions.

Derivations and theory exercises are clearly marked for students in advanced courses.

This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
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Product Details

  • ISBN-13: 9780191608407
  • Publisher: OUP Oxford
  • Publication date: 3/25/2004
  • Sold by: Barnes & Noble
  • Format: eBook
  • File size: 59 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Christiaan Heij is Associate Professor at the Econometric Institute of the Erasmus University in Rotterdam and specialises in econometrics and statistics. Paul de Boer is Assistant Professor at the Econometric Institute of the Erasmus University in Rotterdam and specialises in econometrics and statistics. Philip Hans Franses is Professor of Applied Econometrics and Professor of Marketing Research, both at the Erasmus University Rotterdam. He has published in leading international journals on applied econometrics, time series analysis, empirical finance, and marketing research. He is the (co-)author of various books published by Oxford University Press and Cambridge University Press.
Teun Kloek is Professor Emeritus of Econometrics at Erasmus University Rotterdam. He has published in leading international journals on econometric theory, applied econometrics and quantitative economics. Herman K. van Dijk is Professor of Econometrics and director of the Econometric Institute of the Erasmus University in Rotterdam. His fields of research are Bayesian Inference and Decision Analysis in Econometrics, Computational Economics, Stochastic Trends and Cycles in Time Series Econometrics and Income Distributions.

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Table of Contents

Detailed Contents
List of Exhibits
Abbreviations
Guide to the Book
Introduction 1
1 Review of Statistics 11
2 Simple Regression 75
3 Multiple Regression 117
4 Non-Linear Methods 187
5 Diagnostic Tests and Model Adjustments 273
6 Qualitative and Limited Dependent Variables 437
7 Time Series and Dynamic Models 531
App. A: Matrix Methods 723
App. B: Data Sets 747
Index 773
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