This book provides an account of the Cambridge Multisectoral Dynamic Model, based on a highly disaggregated macroeconometric model. The first part covers the econometric theory and methodology, the organization of the data, the structure of the model, estimation and computer programming. The second part examines the modeling of different aspects of the system in detail and describes the relationships used, the parameter estimates and the results obtained. The model has been developed by the Cambridge Growth Project and is unique among models of the UK economy in its level of disaggregation.
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Based on a highly disaggregated macroeconometric model developed by the CGP, this model is unique among models of the U.K. economy in its level of disaggregation.
'The book does an excellent job of surveying its chosen topics ... such a comprehensive treatment as this book provides has previously been lacking. Thus the book fills an important gap in the literature. It will no doubt be widely read and used. It should be useful both to individuals interested in these topics at a theoretical level and those interested in applications. In the latter regard, an excellent feature of the book is that it contains a lot of empirical examples.' Journal of the American Statistical Association
' ... a significant contribution to the literature on limited dependent and qualitative variables. It should serve as a major reference for researchers doing empirical work with these models. It should also be useful to graduate students as well as econometric theorists.' American Journal of Agriculture Economics
'To summarise, the book contains a very useful and clearly written account of many of the aspects of the limited dependent and qualitative variable models with an extensive use of empirical examples. The econometric issues raised by the models are neatly produced without taxing the reader too greatly. There will undoubtedly be other books appearing in the near future in the same area ... he has produced a book which, by virtue of its extensive coverage, will be very hard to beat.' The Economic Journal
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Condition: New. An econometric 1998 analysis of single and simultaneous-equation models where the jointly dependent variables can be continuous, categorical, or truncated. Editor(s): Barker, Terry; Peterson, William. Series: Cambridge Studies in Applied Econometrics. Num Pages: 532 pages, 128 tables. BIC Classification: KCC. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 33. Weight in Grams: 725. . 1988. hardcover. . . . . Seller Inventory # V9780521330046
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Hardcover. Condition: new. Hardcover. This book presents the econometric analysis of single-equation and simultaneous-equation models in which the jointly dependent variables can be continuous, categorical, or truncated. Despite the traditional emphasis on continuous variables in econometrics, many of the economic variables encountered in practice are categorical (those for which a suitable category can be found but where no actual measurement exists) or truncated (those that can be observed only in certain range). Such variables are involved, for example, in models of occupational choice, choice of tenture in housing, and choice of type of schooling. Models with regulated prices and rationing and models for program evaluation also represent areas of application for the techniques presented by the author. Econometric analysis of single and simultaneous-equation models where the jointly dependent variables can be continuous, categorical, or truncated. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521330046
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This 1998 book presents the econometric analysis of single and simultaneous-equation models in which the jointly dependent variables can be continuous, categorical, or truncated. Despite the traditional emphasis on continuous variables in econometrics, many. Seller Inventory # 446932142
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