Duo Qin has produced a study of a crucial period in the history of econometrics. She analyses the development of the theory and methodology between 1930 and 1960, arguing in particular that the "probability revolution" of the 1940s was incomplete, and resulted in later problems.
Reformation of Econometrics is a sequel to The Formation of Econometrics: A Historical Perspective (1993, OUP) which traces the formation of econometric theory during the period 1930-1960. This book provides an account of the advances in the field of econometrics since the 1970s. Based on original research, it focuses on the reformists' movement and schools of thought and practices that attempted a paradigm shift in econometrics in the 1970s and 1980s. It describes the formation and consolidation of the Cowles Commission (CC) paradigm and traces and analyses the three major methodological attempts to resolve problems involved in model choice and specification of the CC paradigm. These attempts have reoriented the focus of econometric research from internal questions (how to optimally estimate a priori given structural parameters) to external questions (how to choose, design, and specify models). It also examines various modelling issues and problems through two case studies - modelling the Phillips curve and business cycles. The third part of the book delves into the development of three key aspects of model specification in detail - structural parameters, error terms, and model selection and design procedures. The final chapter uses citation analyses to study the impact of the CC paradigm over the span of three and half decades (1970-2005). The citation statistics show that the impact has remained extensive and relatively strong in spite of certain weakening signs. It implies that the reformative attempts have fallen short of causing a paradigm shift.
five years later he caught her sneaking home with her child if you don't agree i'll destroy her the sharp words of the woman rushed into his heart but he was unable to do anything as he was favored by the heavens and could only clench his fist huo yunzheng i really hate you if there is an afterlife i will not let you down gu yi you must have done it on purpose
This book presents the spatial and temporal dynamics of land use and land cover in the central Tibetan Plateau during the last two decades, based on various types of satellite data, long-term field investigation and GIS techniques. Further, it demonstrates how remote sensing can be used to map and characterize land use, land cover and their dynamic processes in mountainous regions, and to monitor and model relevant biophysical parameters. The Tibetan Plateau, the highest and largest plateau on the Earth and well known as “the roof of the world,” is a huge mountainous area on the Eurasian continent and covers millions of square kilometers, with an average elevation of over 4000 m. After providing an overview of the background and an introduction to land use and land cover change, the book analyzes the current land use status, dynamic changes and spatial distribution patterns of different land-use types in the study area, using various types of remotely sensed data, digital elevation models and GIS spatial analysis methods to do so. In turn, it discusses the main driving forces, based on the main physical environment variables and socioeconomic data, and provides a future scenario analysis of land use change using a Markov chain model. Given its scope, it provides a valuable reference guide for researchers, scientists and graduate students working on environmental change in mountainous regions around the globe, and for practitioners working at government and non-government agencies.
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.
Duo Qin has produced a study of a crucial period in the history of econometrics. She analyses the development of the theory and methodology between 1930 and 1960, arguing in particular that the "probability revolution" of the 1940s was incomplete, and resulted in later problems.
Written from the Haavelmo-Cowles Commission econometric perspective, this book provides an account of the advances in the field of econometrics since the 1970s.
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