Titlebook: Statistical Inference in Random Coefficient Regression Models; P. A. V. B. Swamy Book 1971 Springer-Verlag Berlin · Heidelberg 1971 Invest

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https://doi.org/10.1007/978-3-642-80653-7Investment; calculus; efficiency; management; sets; statistical inference; time series

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Statistical Inference in Random Coefficient Regression Models978-3-642-80653-7Series ISSN 0075-8442 Series E-ISSN 2196-9957

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Statistical Inference in Random Coefficient Regression Models Using Panel Data, panel data. We specify a regression equation with coefficients random across units but coming from the same multivariate distribution. We develop an estimation procedure which produces at least asymptotically efficient estimators of the parameters of the model.

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Introduction,cient regression (RCR) models which treat both intercept and slope coefficients as random variables and will develop appropriate statistical inference procedures. Following Zellner (1966), we discuss the implications of RCR models for the aggregation problem. Further, we discuss the problems of iden

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Aggregate Consumption Function with Coefficients Random across Countries,d the limitations of these studies it is always desirable to subject the same body of data to different types of analyses based on different sets of assumptions. Zellner and Sankar (1967) analyzed Houthakker’s data from the standpoint of errors-in-variables model in an effort to. determine whether t

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Book 1971eity of behavior among individuals. These complications have been discussed in this monograph. Limitations of economic data, particularly their non-experimental nature, do not permit us to know a priori the correct specification of a model. I have considered several different sets of assumptionR abo

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Statistical Inference in Random Coefficient Regression Models

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0075-8442 eir non-experimental nature, do not permit us to know a priori the correct specification of a model. I have considered several different sets of assumptionR abo978-3-540-05603-4978-3-642-80653-7Series ISSN 0075-8442 Series E-ISSN 2196-9957