Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling PDF Download
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Author: Ivan Jeliazkov
Publisher: Emerald Group Publishing
ISBN: 1789732417
Category : Business & Economics
Languages : en
Pages : 331
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Book Description
In honor of Dale J. Poirier, experienced editors Ivan Jeliazkov and Justin Tobias bring together a cast of expert contributors to explore the most up-to-date research on econometrics, including subjects such as panel data models, posterior simulation, and Bayesian models.
Author: Ivan Jeliazkov
Publisher: Emerald Group Publishing
ISBN: 1789732417
Category : Business & Economics
Languages : en
Pages : 331
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Book Description
In honor of Dale J. Poirier, experienced editors Ivan Jeliazkov and Justin Tobias bring together a cast of expert contributors to explore the most up-to-date research on econometrics, including subjects such as panel data models, posterior simulation, and Bayesian models.
Author: Yoosoon Chang
Publisher: Emerald Group Publishing
ISBN: 1837532109
Category : Business & Economics
Languages : en
Pages : 360
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Book Description
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Author: Alexander Chudik
Publisher: Emerald Group Publishing
ISBN: 1802620656
Category : Business & Economics
Languages : en
Pages : 376
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Book Description
The collection of chapters in Volume 43 Part B of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
Author: Áureo de Paula
Publisher: Emerald Group Publishing
ISBN: 1838675779
Category : Business & Economics
Languages : en
Pages : 357
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Book Description
Showcasing fresh methodological and empirical research on the econometrics of networks, and comprising both theoretical, empirical and policy papers, the authors in this volume bring together a wide range of perspectives to facilitate a dialogue between academics and practitioners for better understanding this groundbreaking field.
Author: Dek Terrell
Publisher: Emerald Group Publishing
ISBN: 1789739578
Category : Business & Economics
Languages : en
Pages : 468
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Book Description
Including contributions spanning a variety of theoretical and applied topics in econometrics, this volume of Advances in Econometrics is published in honour of Cheng Hsiao.
Author: Juan J. Dolado
Publisher: Emerald Group Publishing
ISBN: 1803828315
Category : Business & Economics
Languages : en
Pages : 203
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Book Description
Both parts of Volume 44 of Advances in Econometrics pay tribute to Fabio Canova for his major contributions to economics over the last four decades.
Author: Christopher F. Parmeter
Publisher: Emerald Group Publishing
ISBN: 1837978751
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
Author: Ceron, Andrea
Publisher: Edward Elgar Publishing
ISBN: 1800374267
Category : Political Science
Languages : en
Pages : 357
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Book Description
The Elgar Encyclopedia of Technology and Politics is a landmark resource that offers a comprehensive overview of the ways in which technological development is reshaping politics. Providing an unparalleled starting point for research, it addresses all the major contemporary aspects of the field, comprising entries written by over 90 scholars from 33 different countries on 5 continents.
Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
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Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Author: Katharine G. Abraham
Publisher: University of Chicago Press
ISBN: 022680139X
Category : Business & Economics
Languages : en
Pages : 502
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Book Description
The papers in this volume analyze the deployment of Big Data to solve both existing and novel challenges in economic measurement. The existing infrastructure for the production of key economic statistics relies heavily on data collected through sample surveys and periodic censuses, together with administrative records generated in connection with tax administration. The increasing difficulty of obtaining survey and census responses threatens the viability of existing data collection approaches. The growing availability of new sources of Big Data—such as scanner data on purchases, credit card transaction records, payroll information, and prices of various goods scraped from the websites of online sellers—has changed the data landscape. These new sources of data hold the promise of allowing the statistical agencies to produce more accurate, more disaggregated, and more timely economic data to meet the needs of policymakers and other data users. This volume documents progress made toward that goal and the challenges to be overcome to realize the full potential of Big Data in the production of economic statistics. It describes the deployment of Big Data to solve both existing and novel challenges in economic measurement, and it will be of interest to statistical agency staff, academic researchers, and serious users of economic statistics.
