By Badi H. Baltagi

ISBN-10: 047099830X

ISBN-13: 9780470998304

ISBN-10: 063121254X

ISBN-13: 9780631212546

ISBN-10: 140510676X

ISBN-13: 9781405106764

ISBN-10: 1405142073

ISBN-13: 9781405142076

A spouse to Theoretical Econometrics presents a finished connection with the fundamentals of econometrics. This spouse makes a speciality of the principles of the sector and whilst integrates renowned themes frequently encountered by way of practitioners. The chapters are written via foreign specialists and supply updated learn in components now not often coated via typical econometric texts. makes a speciality of the rules of econometrics. Integrates real-world themes encountered by means of execs and practitioners. attracts on updated examine in parts now not lined through regular econometrics texts. equipped to supply transparent, obtainable details and aspect to additional readings.

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**Additional resources for A Companion to Theoretical Econometrics (Blackwell Companions to Contemporary Economics)**

**Example text**

23), or statistics asymptotically equivalent to it. 26) which works because the denominator tends to a probability limit of 1 as n → ∞. This statistic is, of course, in F rather than χ2 form. Another frequently used test statistic is available if Q is actually the vector of restricted estimates, that is, the estimator that minimizes the criterion function when the restriction that θ2 = 0 is imposed. 25) is a valid test statistic. 24) is zero, by property (1). 25). 23). 26) and the nR2 statistic are still valid test statistics, because they are both ratios.

G. MACKINNON C H A P T E R O N E Artificial Regressions Russell Davidson and James G. MacKinnon 1 INTRODUCTION All popular nonlinear estimation methods, including nonlinear least squares (NLS), maximum likelihood (ML), and the generalized method of moments (GMM), yield estimators which are asymptotically linear. Provided the sample size is large enough, the behavior of these nonlinear estimators in the neighborhood of the true parameter values closely resembles the behavior of the ordinary least squares (OLS) estimator.

26) which works because the denominator tends to a probability limit of 1 as n → ∞. This statistic is, of course, in F rather than χ2 form. Another frequently used test statistic is available if Q is actually the vector of restricted estimates, that is, the estimator that minimizes the criterion function when the restriction that θ2 = 0 is imposed. 25) is a valid test statistic. 24) is zero, by property (1). 25). 23). 26) and the nR2 statistic are still valid test statistics, because they are both ratios.

### A Companion to Theoretical Econometrics (Blackwell Companions to Contemporary Economics) by Badi H. Baltagi

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