In writing this new edition we have had two major objectives. The first is to provide a comprehensive and accessible account of available econometric methods. The second is to illustrate these methods with applications to some real data sets, which are given on the data diskette that accompanies the book; thus, the reader can replicate the applications in the text, experiment with some of the problems suggested at the chapter ends, and carry out further analyses of her own choosing.
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The TwoVariable Linear Model
Chapter 3 Extensions of the TwoVariable Linear Model
Elements of Matrix Algebra
30 other sections not shown
2SLS alternative applied assumed assumption asymptotic autocorrelation Chap column vector computed condition constant covariance defined in Eq degrees of freedom denote dependent variable derived determinant deviations diagonal disturbance term dummy variables Durbin-Watson statistic Econometrica Econometrics economic eigenvalues elements endogenous variables example expected explanatory variables expressed F statistic follows function given gives heteroscedasticity homoscedasticity indicates inference procedures intercept inverse lagged least-squares likelihood likelihood function linear combination linearly independent mean multipliers nonsingular normal distribution null hypothesis nullspace obtained OLS estimator OLS regression orthogonal parameters percent polynomial positive definite problem procedure quadratic form random recursive residuals relation residual sum restrictions result sample data sample observations sampling variance scalar significance slope specification stochastic structural equation sum of squares Suppose symmetric Table test statistic transformed unbiased estimator unknown values variance matrix variance-covariance matrix yield zero