Get Applied Econometrics: A Modern Approach Using Eviews and PDF

By Dimitrios Asteriou

ISBN-10: 0230506402

ISBN-13: 9780230506404

This new econometrics textual content bargains in particular with using econometric software program. The textual content takes the reader from a number of the kinds of econometric info (time sequence, pass sectional and panel), via their formatting in digital media (eg ASCII) to their move to and use in regular software program packages--Excel, Microfit and Eviews. so much economics levels now require scholars to take advantage of correct software program to check econometric types and this article illustrates basically how this can be to be performed.

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Additional info for Applied Econometrics: A Modern Approach Using Eviews and Microfit Revised Edition

Example text

Reducing the frequency from monthly to quarterly figures). The choice of method for calculating the reduced frequency depends partly on whether we have a sto~;k variable or a flow variable. g. g. annual gross domestic product, GOP, in , 1998 is the sum of quarterly GOP in each of the four qua&ters of 1998). g. from quarterly to monthly) involves extrapolation and should be used with great caution. The resultant series will appear quite smooth and is a 'manufactured' series which would normally be used for ease of comparison with a series of similar frequency.

Ill \l lJ conduct general the (0· Step 1 Set the null and alternative hypothesis. It can be either Ho: f3 = 0; Ha: f3 ,;. 0 (two-tailed test), or if there is prior knowledge about the sign of the estimated coefficient (let's assume positive), H 0 : f3 = 0; Ha: f3 > 0 (one-tail test). l 11 Calculate the t-statistic by t = ((3- {3)/Sfi, where here because f3 u'nder null is equal to zero it becomes (3;sjJ (note that this is the t-statistic that• is automatically provided by EViews and Microfit in their starldard regression outputs).

8 = f3 + Cov(X,u)fn Var(X)/n [.! 56) *We add and subtract Y. " ~, L ,. , 37 Simple Regression [. Using the law of large numbers·, we know that Cov(X, u)jn converges to its expectation which is Cov(Xt, Ut). Similarly, Var(X)jn converges to Var(Xt). e. if X 1 and Ut are uncorrelated). Thus pis a consistent estimator of the true population .. · parameter {J. J I We showed before that the regression equation obtained from the OLS method fits a scatter diagram quite closely. However, we need to know how close it is to the scattered observed values to be able to judge whether a particular line describes the relationship among Yt and Xt better than ari alternative line.

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Applied Econometrics: A Modern Approach Using Eviews and Microfit Revised Edition by Dimitrios Asteriou


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