| 书目名称 | Multicollinearity in linear economic models | | 编辑 | D. Neeleman | | 视频video | | | 丛书名称 | Tilburg Studies in Economics | | 图书封面 |  | | 描述 | It was R. Frisch, who in his publications ‘Correlation and Scatter Analysis in Statistical Variables‘ (1929) and ‘Statistical Confluence Analysis by means of Complete Regression Systems‘ (1934) first pointed out the complications that arise if one applies regression analysis to variables among which several independent linear relations exist. Should these relationships be exact, then there exist two closely related solutions for this problem, viz. 1. The estimation of ‘stable‘ linear combinations of coefficients, the so-called estimable functions. 2. The dropping of the wen-known condition of unbiasedness of the estimators. This leads to minimum variance minimum bias estimators. This last solution is generalised in this book for the case of a model consisting of several equations. In econometrics however, the relations among variables are nearly always approximately linear so that one cannot apply one of the solutions mentioned above, because in that case the matrices used in these methods are, although ill-conditioned, always of full rank. Approximating these matrices by good-conditioned ones of the desired rank, it is possible to apply these estimation methods. In order to get an | | 出版日期 | Book 1973 | | 关键词 | econometrics; regression; regression analysis; simulation | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-011-7486-2 | | isbn_softcover | 978-94-011-7488-6 | | isbn_ebook | 978-94-011-7486-2 | | copyright | Springer Science+Business Media Dordrecht 1973 |
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发表于 2025-3-21 16:35:42
