Among the simulation-based methods, indirect estimation techniques like Indirect Inference (INDINF) and Efficient Method of Moments (EMM) provide a simple solution to many computational problems associated with intractable Likelihood functions. Optimisation of the objective function can be critical in presence of not continuous response variables like, for instance, binary choice or discrete choice models, limited dependent variables, switching regime models. In particular, gradient-based optimisation algorithms can face difficulties when the not continuous response involves discontinuities in the objective function. A simple computational tool is suggested to "empirically" solve the problem. The case study is EMM applied to the autoregressive model with exponential marginal distribution (EAR). The proposed solution is also compared with the performance of the Conditional Least Squares estimation, suitable for this autoregressive model, by a set of Monte Carlo experiments. © 2005 Elsevier B.V. All rights reserved.

Discontinuities in indirect estimation: An application to EAR models

DI IORIO, FRANCESCA;
2006

Abstract

Among the simulation-based methods, indirect estimation techniques like Indirect Inference (INDINF) and Efficient Method of Moments (EMM) provide a simple solution to many computational problems associated with intractable Likelihood functions. Optimisation of the objective function can be critical in presence of not continuous response variables like, for instance, binary choice or discrete choice models, limited dependent variables, switching regime models. In particular, gradient-based optimisation algorithms can face difficulties when the not continuous response involves discontinuities in the objective function. A simple computational tool is suggested to "empirically" solve the problem. The case study is EMM applied to the autoregressive model with exponential marginal distribution (EAR). The proposed solution is also compared with the performance of the Conditional Least Squares estimation, suitable for this autoregressive model, by a set of Monte Carlo experiments. © 2005 Elsevier B.V. All rights reserved.
File in questo prodotto:
File Dimensione Formato  
CDSA_diiorio_calzolari.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Accesso privato/ristretto
Dimensione 165.37 kB
Formato Adobe PDF
165.37 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/103731
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact