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Author: Duo Qin
Publisher: Taylor & Francis
ISBN: 1003819389
Category : Business & Economics
Languages : en
Pages : 129
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Book Description
Haavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.
Author: Duo Qin
Publisher: Taylor & Francis
ISBN: 1003819389
Category : Business & Economics
Languages : en
Pages : 129
Get Book
Book Description
Haavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.
Author: Duo Qin
Publisher: Taylor & Francis
ISBN: 1003819362
Category : Business & Economics
Languages : en
Pages : 113
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Book Description
Haavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.
Author: Qin Duo
Publisher: Clarendon Press
ISBN: 0191521353
Category : Business & Economics
Languages : en
Pages : 226
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Book Description
Duo Qin has provided a scholarly study of a crucial period in the history of econometrics. She traces the formation of econometric theory during the period 1930-1960, and focuses on the formalization of mathematical and scientific processes to analyse economic problems. This book deals with the advances made in the practice of econometrics as a discipline, in terms of the basic issues is econometric modelling: the probability of foundations, estimations, identification, testing, and model construction and specification. Duo Qin argues that, while the probability revolution in econometrics in the early 1940s laid the basis for the systematization of econometric theory, it was actually an incomplete revolution, and its incompleteness underlay various problems and failures that occurred in applying the newly eastablished theory to modelling practice. Model construction and hypothesis testing remained problematic because the basic problem of induction in econometrics was not properly formalized and solved. The book thus links early econometric history with many issues of interest to contemporary developments in econometrics.
Author: George G. Judge
Publisher: John Wiley & Sons
ISBN: 047189530X
Category : Business & Economics
Languages : en
Pages : 1062
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Book Description
This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
Author: Badi H. Baltagi
Publisher: John Wiley & Sons
ISBN: 047099830X
Category : Business & Economics
Languages : en
Pages : 736
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Book Description
A Companion to Theoretical Econometrics provides a comprehensive reference to the basics of econometrics. This companion focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners. The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts. Focuses on the foundations of econometrics. Integrates real-world topics encountered by professionals and practitioners. Draws on up-to-date research in areas not covered by standard econometrics texts. Organized to provide clear, accessible information and point to further readings.
Author: William A. Barnett
Publisher: Cambridge University Press
ISBN: 9780521424318
Category : Business & Economics
Languages : en
Pages : 512
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Book Description
Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.
Author: Bernt P. Stigum
Publisher: Princeton University Press
ISBN: 9780691113005
Category : Business & Economics
Languages : en
Pages : 804
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Book Description
This work shows that an econometrician with the proper understanding of economic theory and the right kind of questions can gain knowledge about characteristic features of the social world. It addresses varied topics in both classical and Bayesian econometrics.
Author: Christopher A. Sims
Publisher: Cambridge University Press
ISBN: 9780521566094
Category : Business & Economics
Languages : en
Pages : 434
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Book Description
This 1994 two-volume set of articles reflects the state of research in theoretical and applied econometrics. The topics covered include time series methods, semiparametric methods, seasonality, financial economics, model solution techniques, economic development and labour economics.
Author: A. C. Darnell
Publisher: Edward Elgar Publishing
ISBN:
Category : Business & Economics
Languages : en
Pages : 200
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Book Description
Econometric issues have provoked a lively and sometimes adversarial debate in the economics profession. The excitement and intellectual vitality of that debate is captured here for the reader in a lucid overview of econometric approaches, describing their advantages and limitations. This ambitious book focuses on the underlying methodological issues rather than concentrating upon econometric techniques. The limits of econometric investigations are identified through a critical appraisal of three different approaches associated with the work of Professors Hendry, Leamer and Sims. After explaining why the early optimism in econometrics was misplaced, it argues that rejection is not an appropriate response. It offers a rich spectrum of approaches to a problem of central importance in the development of modern economics. The book will appeal not only to all econometricians whatever their persuasion but also to all those with an interest in the methodology of economics.
Author:
Publisher: Elsevier
ISBN: 0444643125
Category : Mathematics
Languages : en
Pages : 330
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Book Description
Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art
