Identification, estimation and testing of conditionally heteroskedastic factor models

Sentana, Enrique; Fiorentini, Gabriele

doi:10.1016/s0304-4076(01)00051-3

Cited by 234 publications

(161 citation statements)

References 21 publications

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“…To simplify the discussion, we abstract from other controls and concentrate mainly on the simultaneous equations 1 See Fisher (1976). 2 Other theoretical derivations can be found in Sentana (1992) and Sentana and Fiorentini (2001). 3 Applications where the heteroskedasticity is modeled as a GARCH process are Caporale et al (2002a), Rigobon (2002a) and Rigobon and Sack (2003a).…”

Section: Endogeneitymentioning

confidence: 99%

Once again, is openness good for growth?

Lee¹,

Ricci

Rigobón³

2004

Journal of Development Economics

122

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Rodriguez and Rodrik (2000) argue that the relation between openness and growth is still an open question. One of the main problems in the assessment of the effect is the endogeneity of the relation. In order to address this issue, this paper applies the identification through heteroskedasticity methodology to estimate the effect of openness on growth while properly controlling for the effect of growth on openness. The results suggest that openness would have a positive effect on growth, although small. This result stands, despite the equally robust effect from growth to openness. D

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Section: Endogeneitymentioning

confidence: 99%

Once again, is openness good for growth?

Lee¹,

Ricci

Rigobón³

2004

Journal of Development Economics

122

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show abstract

“…However, it is necessary to note the generality of this proposition since it has been obtained without assuming any particular parametrization for the dynamic conditional heteroskedasticity, and hence relies only on the conditional orthogonality of the factors, the time-variation of their variances and the constancy of the matrix X s t (for more details on the identification problem, the reader is referred to Sentana andFiorentini 2001 andCarnero et al 2004).…”

Section: The Factor Analysed Hidden Markov Modelmentioning

confidence: 99%

Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models

Saidane

Lavergne

2009

Comput Econ

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“…The idea behind the approach is to impose restrictions on higher moments in order to achieve identification. Several recent examples of variants of this approach are Dagenais and Dagenais (1997); Lewbel (1997); Cragg (1997); Sentana and Fiorentini (2001), and Rigobon (2002Rigobon ( , 2003. The concept was recently generalized by Lewbel (unpublished manuscript, Boston College), who provides Monte Carlo evidence that restrictions on higher moments may yield nontrivial identification.…”

Section: Internal Instruments Approachmentioning

confidence: 99%