A mother formula for econometric estimation, the issue of parent linear models of best-fit solutions and its dual problem

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

Abstract

The body of econometric estimation theory in linear models must necessarily hinge, as a frame of reference, on Rao s unified theories of linear estimation and least squares. The mathematical counterpart of the basic statistical setups turns out to be quadratic optimization problems, whose solutions yield the optimal estimators. These solutions rest on the inversion of the fundamental bordered matrix of the first-order conditions for optimality. A recently devised partitioned inversion rule leads to a mother formula for estimators within a linear framework. In addition, this paper casts further light on the link between the best fit approach to estimation and model specifications. Indeed, by taking least squares as a bridge-head and best unbiasedness as a benchmark, quite a deep insight into parameter inference is gained, whose applicative spin-offs are brought to light by a wide-ranging reappraisal of statistic and econometric estimators.
Lingua originaleEnglish
pagine (da-a)113-134
Numero di pagine22
RivistaSTATISTICA & APPLICAZIONI
VolumeVII
Stato di pubblicazionePubblicato - 2009

Keywords

  • Best unbiasedness
  • Econometric models
  • Inversion rules
  • Least squares
  • Orthogonal complements

Fingerprint Entra nei temi di ricerca di 'A mother formula for econometric estimation, the issue of parent linear models of best-fit solutions and its dual problem'. Insieme formano una fingerprint unica.

Cita questo