Econometric Models and Economic ForecastsThis updated edition of the text has been restructured into four parts: multiple regression model; single-equation regression models; revised exposition and a small macroeconomic model; and a revised treatment of time-series analysis. |
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Page 76
... ( dependent variable ) and the level of aggregate wages and salaries in the economy ( independent variable ) . One would expect a higher level of wages and salaries to lead to an increase in auto sales . The following is a summary of the ...
... ( dependent variable ) and the level of aggregate wages and salaries in the economy ( independent variable ) . One would expect a higher level of wages and salaries to lead to an increase in auto sales . The following is a summary of the ...
Page 99
... dependent variable . Both standardized coefficients and partial correlation coefficients are con- nected with the variance of Y , the dependent variable . However , the rescaling associated with the normalized regression makes it ...
... dependent variable . Both standardized coefficients and partial correlation coefficients are con- nected with the variance of Y , the dependent variable . However , the rescaling associated with the normalized regression makes it ...
Page 325
... dependent variable is censored : information is missing for the dependent variable , but the corresponding in- formation for the independent variables is present . ( If both kinds of data are missing , we describe the dependent variable ...
... dependent variable is censored : information is missing for the dependent variable , but the corresponding in- formation for the independent variables is present . ( If both kinds of data are missing , we describe the dependent variable ...
Contents
Introduction to the Regression Model | 1 |
1 The Use of Summation Operators | 13 |
A Review | 19 |
Copyright | |
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Econometric Models and Economic Forecasts Robert S. Pindyck,Daniel L. Rubinfeld No preview available - 1998 |
Common terms and phrases
2SLS a₂ actual ARIMA model associated assume assumption autocorrelation function autoregressive B₁ B₂ C₁ calculate Chapter coefficients confidence intervals consider consistent estimator consumption covariance degrees of freedom demand dependent variable dynamic econometric endogenous variables equal error term error variance example exogenous explanatory variables F distribution FIGURE follows forecast error heteroscedasticity income independent intercept interest rate least-squares estimation linear regression matrix mean measure moving average nonlinear nonstationary normally distributed null hypothesis observations obtain ordinary least squares P₁ parameter estimates percent level period predict procedure random variable random walk reduced form regression equation regression model reject the null residuals sample autocorrelation function serial correlation significant single-equation slope specification standard deviation standard error stationary statistic stochastic sum of squares time-series model uncorrelated w₁ X₁ Y₁ ŶT+1 zero ΣΧ