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Author: Karim Chalak
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Karim Chalak
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Karim Chalak
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We examine how structural systems can yield observed variables instrumental in identifying and estimating causal effects. We provide an exhaustive characterization of potentially identifying conditional exogeneity relationships and demonstrate how structural relations determine exogeneity and exclusion restrictions that yield moment conditions supporting identification. This provides a comprehensive framework for constructing instruments and covariates. We introduce notions of conditioning and conditional extended instrumental variables (XIVs). These permit identification but need not be traditional instruments, as they may be endogenous. We distinguish between observed XIVs and proxies for unobserved XIVs. A main message is the importance of sufficiently specifying causal relations governing the unobservables. (Les auteurs examinent comment des systmes structurels peuvent engendrer des variables observes instrumentales dans l'identification et l'estimation d'effets de causalit. On fournit une caractrisation exhaustive des relations d'exognit conditionnelle potentiellement porteuses d'identification, et on dmontre comment des relations structurelles dterminent les restrictions d'exognit et d'exclusion qui engendrent les conditions de moment qui supportent l'identification. Cela fournit un cadre comprhensif pour construire instruments et covariables. On introduit des notions de variables instrumentales tendues conditionnantes et conditionnelles (XIVs). Celles-ci permettent l'identification, mais n'ont pas tre des instruments traditionnels, parce qu'elles peuvent tre endognes. On distingue entre les XIVs observes et les variables concomitantes avec les XIVs non-observes. Un message central est l'importance de suffisamment spcifier les relations causales qui gouvernent les non-observables.).
Author: Karim Marwan Chalak
Publisher:
ISBN: 9781109974256
Category :
Languages : en
Pages : 203
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Book Description
This dissertation studies the definition, identification, and estimation of causal effects within the settable system framework of White and Chalak.
Author: Jennifer Castle
Publisher: OUP Oxford
ISBN: 0191553255
Category : Business & Economics
Languages : en
Pages : 464
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Book Description
David F. Hendry is a seminal figure in modern econometrics. He has pioneered the LSE approach to econometrics, and his influence is wide ranging. This book is a collection of papers dedicated to him and his work. Many internationally renowned econometricians who have collaborated with Hendry or have been influenced by his research have contributed to this volume, which provides a reflection on the recent advances in econometrics and considers the future progress for the methodology of econometrics. Central themes of the book include dynamic modelling and the properties of time series data, model selection and model evaluation, forecasting, policy analysis, exogeneity and causality, and encompassing. The book strikes a balance between econometric theory and empirical work, and demonstrates the influence that Hendry's research has had on the direction of modern econometrics. Contributors include: Karim Abadir, Anindya Banerjee, Gunnar Bårdsen, Andreas Beyer, Mike Clements, James Davidson, Juan Dolado, Jurgen Doornik, Robert Engle, Neil Ericsson, Jesus Gonzalo, Clive Granger, David Hendry, Kevin Hoover, Søren Johansen, Katarina Juselius, Steven Kamin, Pauline Kennedy, Maozu Lu, Massimiliano Marcellino, Laura Mayoral, Grayham Mizon, Bent Nielsen, Ragnor Nymoen, Jim Stock, Pravin Trivedi, Paolo Paruolo, Mark Watson, Hal White, and David Zimmer.
Author: Bernard Fichet
Publisher: Springer Science & Business Media
ISBN: 3642133126
Category : Mathematics
Languages : en
Pages : 460
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Book Description
The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.
Author: Xiaohong Chen
Publisher: Springer Science & Business Media
ISBN: 1461416531
Category : Business & Economics
Languages : en
Pages : 582
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Book Description
This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.
Author: Richard J. Murnane
Publisher: Oxford University Press
ISBN: 0199890153
Category : Psychology
Languages : en
Pages : 414
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Book Description
Educational policy-makers around the world constantly make decisions about how to use scarce resources to improve the education of children. Unfortunately, their decisions are rarely informed by evidence on the consequences of these initiatives in other settings. Nor are decisions typically accompanied by well-formulated plans to evaluate their causal impacts. As a result, knowledge about what works in different situations has been very slow to accumulate. Over the last several decades, advances in research methodology, administrative record keeping, and statistical software have dramatically increased the potential for researchers to conduct compelling evaluations of the causal impacts of educational interventions, and the number of well-designed studies is growing. Written in clear, concise prose, Methods Matter: Improving Causal Inference in Educational and Social Science Research offers essential guidance for those who evaluate educational policies. Using numerous examples of high-quality studies that have evaluated the causal impacts of important educational interventions, the authors go beyond the simple presentation of new analytical methods to discuss the controversies surrounding each study, and provide heuristic explanations that are also broadly accessible. Murnane and Willett offer strong methodological insights on causal inference, while also examining the consequences of a wide variety of educational policies implemented in the U.S. and abroad. Representing a unique contribution to the literature surrounding educational research, this landmark text will be invaluable for students and researchers in education and public policy, as well as those interested in social science.
Author: Roger John Bowden
Publisher: Cambridge University Press
ISBN: 9780521385824
Category : Business & Economics
Languages : en
Pages : 240
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Book Description
This book will be useful for advanced undergraduates and graduates, and be a source of reference for researchers in econometrics and statistics.
Author: Carlo Berzuini
Publisher: John Wiley & Sons
ISBN: 1119941733
Category : Mathematics
Languages : en
Pages : 387
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Book Description
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book: Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addresses examples from medicine, biology, economics and political science to aid the reader's understanding. Is authored by leading experts in their field. Is written in an accessible style. Postgraduates, professional statisticians and researchers in academia and industry will benefit from this book.
Author: American Psychopathological Association. Meeting
Publisher: Oxford University Press
ISBN: 0199754640
Category : Medical
Languages : en
Pages : 377
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Book Description
This volume contains contributions from leading scholars of causal thinking in epidemiology and psychopathology research. Based on presentations at the ground-breaking 2008 meeting of the American Psychopathological Association, the authors explore the meaning of causal statements that are made from statistical and experimental evidence; then, they suggest novel approaches to analyze these statements and thus make them more informative and medically rigorous.
