Identification through heteroskedasticity in a likelihood-based approach: some theoretical results
AbstractIn this paper we show how the analysis of identification of simultaneous systems of equations with different volatility regimes can be addressed in a conventional likelihood-based setup, generalizing previous works in different directions. We discuss general conditions for identification and one of the results shows that an adequate number of different levels of heteroskedasticity is sufficient to identify the parameters of the structural form without the inclusion of any kind of restriction. A Full Information Maximum Likelihood (FIML) algorithm is discussed.
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Bibliographic InfoPaper provided by Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano in its series Departmental Working Papers with number 2010-38.
Date of creation: 29 Nov 2010
Date of revision:
Simultaneous equations model; heteroskedasticity; identification; FIML;
Find related papers by JEL classification:
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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