Principles of Econometrics
Mathematical tools: matrix algebra; Statistical tools: inference and distribution theory; Least squares and the standerd linear model; Partial and miltiple correlation; The statistical analysis of sisturbances; Generalized least squares and linear constraints; The combination of several linear relations; Asymptotic distribution theory.
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2SLS analysis apply approximation Assumption asymptotic autocorrelation BLUS residuals canonical correlation characteristic vectors coefficient estimator coefficient vector computed condition consider consists constant term constraints converges in probability correlation coefficient corresponding covariance matrix defined demand equation dependent variable derived diagonal elements expectation explanatory variables function given Hence implies independent inverse Kronecker product lagged left-hand likelihood function limiting distribution linear unbiased linearly logarithm LS coefficient LS estimator LS residuals mean vector moment-generating function multicollinearity nonsingular normally distributed Note null hypothesis observation matrix obtain orthogonal parameter vector point estimates positive semidefinite positive semidefinite matrix premultiply Problem procedure prove quadratic form random variables ratio regression result right-hand side roots rows sample scalar covariance matrix Section specification standard errors standard linear model sum of squares Suppose symmetric textile example Theorem tion tlie tn2t tne true unbiased estimator zero mean