Download e-book for kindle: A Companion to Theoretical Econometrics by Badi H. Baltagi

By Badi H. Baltagi

ISBN-10: 063121254X

ISBN-13: 9780631212546

A spouse to Theoretical Econometrics offers a finished connection with the fundamentals of econometrics. This significant other makes a speciality of the principles of the sector and whilst integrates renowned themes usually encountered through practitioners. The chapters are written by means of overseas specialists and supply updated examine in components now not frequently coated by means of general econometric texts.

  • Focuses at the foundations of econometrics.
  • Integrates real-world subject matters encountered by way of execs and practitioners.
  • Draws on up to date examine in parts now not coated through commonplace econometrics texts.
  • Organized to supply transparent, available info and aspect to extra readings.

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Additional resources for A Companion to Theoretical Econometrics

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Simple LM tests of mis-specification for ordered logit models. Economics Letters 52, 137–41. Orme, C. (1995). On the use of artificial regressions in certain microeconometric models. Econometric Theory 11, 290–305. A. T. P. Flannery (1992). , Cambridge: Cambridge University Press. Thomas, J. (1993). On testing the logistic assumption in binary dependent variable models. Empirical Economics 18, 381–92. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity.

MacKinnon (1993). Estimation and Inference in Econometrics. New York: Oxford University Press. G. MacKinnon (1999). Bootstrap testing in nonlinear models. International Economic Review 40, 487–508. , and T. Stengos (1994). Semiparametric specification testing of non-nested econometric models. Review of Economic Studies 61, 291–303. F. (1984). Wald, Likelihood Ratio and Lagrange Multiplier Tests in Econometrics. In Zvi Griliches and Michael D. ). Handbook of Econometrics, Vol. II, Amsterdam: North-Holland.

Since X(β) plays the role of R(θ), we see that 1 n R‫(ׅ‬θ)R(θ) = 1 n X‫(ׅ‬β)X(β). 14) is evaluated at any root-n consistent estimator T, it must tend to the same probability limit as n−1X ‫ׅ‬0 X0. 15) n →∞ where σ 20 is the true variance of the error terms; see, for example, Davidson and MacKinnon (1993, ch. 5). Thus the GNR would satisfy condition (2) except that there is a factor of σ 20 missing. However, this factor is automatically supplied by the regression package. 16) where L2 = SSR/(n − k) is the estimate of σ 2 from the artificial regression.

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A Companion to Theoretical Econometrics by Badi H. Baltagi


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