Essentials of EconometricsThe primary objective of the fourth edition of Essentials of Econometrics is to provide a user-friendly introduction to econometric theory and techniques. This text provides a simple and straightforward introduction to econometrics for the beginner. The book is designed to help students understand econometric techniques through extensive examples, careful explanations, and a wide variety of problem material. In each of the editions, I have tried to incorporate major developments in the field in an intuitive and informative way without resort to matrix algebra, calculus, or statistics beyond the introductory level. The fourth edition continues that tradition. |
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Page 78
... plot ( NPP ) which makes use of normal prob- ability paper , a specially ruled graph paper . On the horizontal axis , ( X - axis ) we plot values of the variable of interest ( say , OLS residuals e ; ) , and on the vertical axis ( Y ...
... plot ( NPP ) which makes use of normal prob- ability paper , a specially ruled graph paper . On the horizontal axis , ( X - axis ) we plot values of the variable of interest ( say , OLS residuals e ; ) , and on the vertical axis ( Y ...
Page 174
... plot ? b . Estimate a linear model to predict the closing stock price based on time . Does this model seem to fit ... plot . Does the plot exhibit constant variance from left to right ? c . Now estimate the following mixed model : = In Y ...
... plot ? b . Estimate a linear model to predict the closing stock price based on time . Does this model seem to fit ... plot . Does the plot exhibit constant variance from left to right ? c . Now estimate the following mixed model : = In Y ...
Page 284
... plot e against each X variable . It is possible that the patterns exhibited in Figure 9-6 can hold true of only one of the X variables . Sometimes we can resort to a shortcut . Instead of plotting e against each X variable , plot them ...
... plot e against each X variable . It is possible that the patterns exhibited in Figure 9-6 can hold true of only one of the X variables . Sometimes we can resort to a shortcut . Instead of plotting e against each X variable , plot them ...
Contents
Specifying the Mathematical Model of Labor Force Participation | 5 |
Testing the Hypothesis Derived from the Model | 11 |
PART | 19 |
Copyright | |
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Appendix assumption autocorrelation average B₁ B₂ B₂X Chapter CLFPR CLRM collinearity computed confidence interval constant correlation covariance CUNR data given dependent variable discussed dummy variable Durbin-Watson Econometrics economic elasticity Equation error term example expected value explanatory variables F value F-statistic following regression given in Eq given in Table heteroscedasticity homoscedastic hypothesis testing lagged least squares level of significance linear regression linear regression model log-linear log-linear model logit math S.A.T. score mean value measured method MINITAB multicollinearity multiple regression normal distribution Note null hypothesis observations OLS estimators P/E ratio parameters percent population Prob probability distribution problem R² value random sample random variables regression analysis regression coefficients regression results reject the null relationship residuals sample mean shows slope coefficient specification error standard errors statistically significant stochastic sum of squares textbook's transformed true two-variable type I error wage X₁ Y₁ zero