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Authors: Arbia, Giuseppe (2014) - This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.
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Authors: Nguyen Ngoc Thach (2021) - This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on financial econometrics. There is a major need for such techniques, since the traditional way of designing mathematical models - based on researchers' insights - can no longer keep pace with the ever-increasing data flow.
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Authors: Vogelvang, Ben (2005) - The author combines econometric theory with practice by demonstrating its use with the software package EViews through extensive use of screen shots. The emphasis is on understanding how to select the right method of analysis for a given situation, and how to actually apply the theoretical methodology correctly.
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Authors: John Guerard (2017) - This book provides a rigorous introduction to the principles of econometrics and gives students and practitioners the tools they need to effectively and accurately analyze real data. Thoroughly updated to address the developments in the field that have occurred since the original publication of this classic text, the second edition has been expanded to include two chapters on time series analysis and one on nonparametric methods
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Authors: - (2019) - This book uniquely demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions in business, policy evaluation, and forecasting.
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Authors: Wooldridge, Jeffrey (2019) - The author has organized the book's presentation around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 data sets in different formats.
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Authors: - (2015) - 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.
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Authors: Magnus, Jan R (1999) - Matrix Differential Calculus With Applications in Statistics and Econometrics Revised Edition Jan R. Magnus, CentER, Tilburg University, The Netherlands and Heinz Neudecker, Cesaro, Schagen, The Netherlands " .deals rigorously with many of the problems that have bedevilled the subject up to the present time." -- Stephen Pollock, Econometric Theory "I continued to be pleasantly surprised by the variety and usefulness of its contents " -- Isabella Verdinelli, Journal of the American Statistical Association Continuing the success of their first edition, Magnus and Neudecker present an exhaustive and self--contained revised text on matrix theory and matrix differential calculus
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Authors: Hill, R. Carter (2011) - Designed to arm finance professionals with an understanding of why econometrics is necessary, this book also provides them with a working knowledge of basic econometric tools. The fourth edition has been thoroughly updated to reflect the current state of economic and financial markets. New discussions are presented on Kennel Density Fitting and the analysis of treatment effects. A new summary of probability and statistics has been added. In addition, numerous new end-of-chapter questions and problems have been integrated throughout the chapters. This will help finance professionals apply basic econometric tools to modeling, estimation, inference, and forecasting through real world pro...
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Authors: Kreinovich, Vladik (2021) - Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Processing uncertainty is essential, considering that computers - which help us understand real-life processes and make better decisions based on that understanding - get their information from measurements or from expert estimates, neither of which is ever 100% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques
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Authors: Independently published (2020) - Introduces the popular, powerful and free programming language and software package R Focus : implementation of standard tools and methods used in econometrics Compatible with "Introductory Econometrics" by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation Companion website with full text, all code for download and other goodies Praise : "A very nice resource for those wanting to use R in their introductory econometrics courses." ( Jeffrey M. Wooldridge ) Using R for Introductory Econometrics is a fabulous modern resource
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Authors: - (2016) - Introduces the popular, powerful and free programming language and software package R Focus : implementation of standard tools and methods used in econometrics Compatible with "Introductory Econometrics" by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation Companion website with full text, all code for download and other goodies Praise : "A very nice resource for those wanting to use R in their introductory econometrics courses." ( Jeffrey M. Wooldridge ) Using R for Introductory Econometrics is a fabulous modern resource
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