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 40
... percent level of significance ) in favor of the alternative - rather vague - hypothesis that the mean is not 0. Note that the null hypothesis has been rejected because it is unlikely that we would have obtained a sample mean of 3 if the ...
... percent level of significance ) in favor of the alternative - rather vague - hypothesis that the mean is not 0. Note that the null hypothesis has been rejected because it is unlikely that we would have obtained a sample mean of 3 if the ...
Page 45
... percent level of significance . Because we have just barely rejected the null , it might be interesting to ask about ... percent of the women would pass , as would 45 percent of the men , a differential of 10 percentage points . With a ...
... percent level of significance . Because we have just barely rejected the null , it might be interesting to ask about ... percent of the women would pass , as would 45 percent of the men , a differential of 10 percentage points . With a ...
Page 69
... level of significance as long as the critical value of the t distribution is correctly chosen . Confidence intervals ... percent level ) . In this case 7 percent of the t distribution lies outside an interval of t , standard devia- tions ...
... level of significance as long as the critical value of the t distribution is correctly chosen . Confidence intervals ... percent level ) . In this case 7 percent of the t distribution lies outside an interval of t , standard devia- tions ...
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