Theory of econometrics: an introductory exposition of econometric methods. / A. Koutsoyiannis

By: Koutsoyiannis, AMaterial type: TextTextPublisher: New York: Palgrave Macmillan, 1977Edition: 2nd edDescription: xvii, 681 p.: illISBN: 9780333778227; 0333778227Subject(s): EconometricsLOC classification: HB139.K88
Contents:
Contents: 1. Correlation theory: the simple linear regression model: Definition, scope and division of econometrics -- Methodology of econometric research -- Correlation theory -- The Simple linear regression model: the ordinary Least Squares Method(OLS) -- Statistical tests of significance of the estimates -- Properties of the least squares estimates -- Multiple regression and other extensions of the simple linear regression model -- Regression and analysis of variance -- 2. Econometric problems: second-order tests of the assumptions of the linear regression model: The Assumptions of randomness, zero mean, constant variance and normality of the disturbance variable -- Autocorrelation -- Multicollinearity -- Errors in variables, time as a variable, dummy variables, grouped data -- Lagged variables and distributed-lag models -- 3. Models of simultaneous relationships: Simultaneous-equation models -- Identification -- Simultaneous-equation methods -- Mixed estimation methods: the method of principal components -- Maximum likelihood methods -- Three-stage least squares -- Testing the forecasting power of an estimated model -- Choice of econometric technique. Monte Carlo studies --
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Includes index.

Contents: 1. Correlation theory: the simple linear regression model: Definition, scope and division of econometrics -- Methodology of econometric research -- Correlation theory -- The Simple linear regression model: the ordinary Least Squares Method(OLS) -- Statistical tests of significance of the estimates -- Properties of the least squares estimates -- Multiple regression and other extensions of the simple linear regression model -- Regression and analysis of variance -- 2. Econometric problems: second-order tests of the assumptions of the linear regression model: The Assumptions of randomness, zero mean, constant variance and normality of the disturbance variable -- Autocorrelation -- Multicollinearity -- Errors in variables, time as a variable, dummy variables, grouped data -- Lagged variables and distributed-lag models -- 3. Models of simultaneous relationships: Simultaneous-equation models -- Identification -- Simultaneous-equation methods -- Mixed estimation methods: the method of principal components -- Maximum likelihood methods -- Three-stage least squares -- Testing the forecasting power of an estimated model -- Choice of econometric technique. Monte Carlo studies --

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