By Badi H. Baltagi
A significant other to Theoretical Econometrics offers a finished connection with the fundamentals of econometrics. This better half makes a speciality of the principles of the sphere and even as integrates renowned themes usually encountered through practitioners. The chapters are written via overseas specialists and supply up to date examine in components no longer frequently lined through usual econometric texts.
- Focuses at the foundations of econometrics.
- Integrates real-world subject matters encountered by means of execs and practitioners.
- Draws on updated study in parts now not coated by means of average econometrics texts.
- Organized to supply transparent, available details and aspect to extra readings.
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Extra info for A Companion to Theoretical Econometrics
1′) is due to the arbitrary choice that the estimator is defined by minimizing Q(θ) rather than maximizing it. Condition (2) has been written in a particularly simple form, and some nonstandard artificial regressions do not actually satisfy it. However, as we will see, this does not prevent them from having essentially the same properties as artificial regressions that do satisfy it. Condition (3), which is perhaps the most interesting of the three conditions, will be referred to as the one-step property.
17), for a full discussion of GMM estimation. Now consider the artificial regression f(θ) = PW J(θ)b + residuals. 32). 34) that condition (2) is also satisfied. 35). 35) can be used in exactly the same way as the GNR. Either the regressand and regressors can be divided by a suitable consistent estimate of σ, or else all test statistics can be computed as ratios, in F or nR2 form, as appropriate. 35) is provided by the class of regression models, linear or nonlinear, estimated with instrumental variables (IV).
Several extensions of this literature are discussed including (i) higher order cointegrated systems; (ii) fractionally cointegrated systems; (iii) nearly cointegrated systems; (iv) nonlinear error correction models; and (v) structural breaks in cointegrated systems. Modelling seasonality has progressed from the traditional view that seasonal patterns are a nuisance which need to be removed to the current view, see Ghysels (1994), that they are an informative feature of economic time series that should be modeled explicitly.