Introduction to EconometricsAn introduction to econometrics. Among the topics covered are simple regression, multiple regression, autocorrelation, multicollinearity, dummy variables, truncated variables and simultaneous equation models. |
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Page 27
... analysis is one of the most commonly used tools in econometric work . We will , therefore , start our discussion with an outline of regression analysis . The subsequent chapters will deal with some modifications and extensions of this ...
... analysis is one of the most commonly used tools in econometric work . We will , therefore , start our discussion with an outline of regression analysis . The subsequent chapters will deal with some modifications and extensions of this ...
Page 50
... ANALYSIS OF VARIANCE FOR THE SIMPLE REGRESSION MODEL Yet another item that is often presented in connection with the simple linear regression model is the analysis of variance . This is the breakdown of the total sum of squares TSS into ...
... ANALYSIS OF VARIANCE FOR THE SIMPLE REGRESSION MODEL Yet another item that is often presented in connection with the simple linear regression model is the analysis of variance . This is the breakdown of the total sum of squares TSS into ...
Page 55
... analysis of residuals . A more detailed discussion of analysis of residuals is given in Chapter 12. Actually , what we are doing is a diagnostic checking of our patient ( regression equation ) to see whether anything is wrong . An ...
... analysis of residuals . A more detailed discussion of analysis of residuals is given in Chapter 12. Actually , what we are doing is a diagnostic checking of our patient ( regression equation ) to see whether anything is wrong . An ...
Contents
REVIEW OF SOME BASIC RESULTS | 8 |
SIMPLE REGRESSION | 27 |
4 | 83 |
Copyright | |
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Common terms and phrases
2SLS adaptive expectations analysis assumptions autocorrelation autoregressive B₁ B₁x₁ B₂ Chapter compute confidence interval consider consistent estimates constant term D₁ degrees of freedom demand function denote dependent variable dummy variables Econometrica Econometrics economic endogenous variables error term estimator of ẞ exogenous explanatory variables F-test H₁ Hence heteroskedasticity Illustrative Example instrumental variable K₁ least squares estimators least squares residuals linear probability model logit model measure multicollinearity multiple regression n₂ normal distribution observations obtained OLS estimation omitted variables P₁ parameters plim prediction error probit problem procedure proxy rational expectations recursive residuals regression coefficient regression equation regression model regressors relationship residual sum sample serial correlation significance level ẞ₁ ẞ₂ ẞx standard errors studentized residuals suggested sum of squares supply function t-ratios Table test statistic u₁ uncorrelated v₁ values X₁ y₁ y₂ z₁ zero σ²