A Guide to Econometrics (6th Edition) by Peter Kennedy PDF

By Peter Kennedy

ISBN-10: 1405182571

ISBN-13: 9781405182577

6th variation and the final variation there'll ever be, because the writer handed away.


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Additional info for A Guide to Econometrics (6th Edition)

Example text

The more prominent of these are EVIEWS, GAUSS, LIMDEP, PC­ GIVE, RATS, SAS, SHAZAM, SPSS, STATA, and TSP. 4 Highest R2 OX. The Journal of Applied Econometrics and the Journal of Economic Surveys both publish • R2 is called the coefficient of determination. It is software reviews regularly. All these packages are the square of the correlation coefficient between very comprehensive, encompassing most of the y and its OLS estimate y. econometric techniques discussed in textbooks. • The total variation of the dependent variable y For applications that they do not cover, in most about its mean, L ( y - Y) 2 , is called SST (the cases, specialized programs exist.

Goldfeld and Quandt ( 1 972, p. 277) report an example in which a sample size of 30 is sufficiently large and an example in which a sample of 200 is required. They also note that large sample sizes are needed if interest focuses on estimation of estimator vari­ ances rather than on estimation of coefficients. " In practice most people use the two terms synonymously, as is done in this book, but technically the latter refers to the limit of the expected value, which is usually, but not always, the same as the plim.

The MLE is the particular pair of values µMLE and (a2)MLE that creates the greatest probability of having obtained the sample in question; that is, no other pair of values would be preferred to this maximum likelihood pair, in the sense that pair B is preferred to pair A. The means by which the econometrician finds this MLE is discussed in the technical notes to this section. In addition to its intuitive appeal, the maximum likelihood estimator has several desirable asymptotic properties. It is asymptotically unbiased, it is consistent, it is asymptotically efficient, it is distributed asymptotically normally, and its asymptotic variance can be found via a standard formula (the Cramer-Rao lower bound - see the technical notes to this section).

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A Guide to Econometrics (6th Edition) by Peter Kennedy

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