Titlebook: Handbook of Regional Science; Manfred M. Fischer,Peter Nijkamp Reference work 20141st edition Springer-Verlag Berlin Heidelberg 2014 Locat

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Zoltan Acs,Mark Sanderslinear relationship to contaminated observed data. Such ?tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and pub

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William Cochrane,Jacques Pootationship to contaminated observed data. Such ?tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and published in

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Philip S. Morrisonlinear relationship to contaminated observed data. Such ?tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and pub

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Julie Le Gallo,Bernard Fingletonationship to contaminated observed data. Such ?tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and published in

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Labor Market Theory and Modelsels used to study differences in earnings across labor markets as well as the effects of boom and bust cycles are also discussed. An empirical technique is presented for decomposing employment change within a community into four key labor market concepts: commuting, unemployment, labor force participation, and migration.

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