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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Martins, L. F. & Gabriel, V. J. (2009). New Keynesian Phillips Curves and potential identification failures: a Generalized Empirical Likelihood analysis. Journal of Macroeconomics. 31 (4), 561-571
Exportar Referência (IEEE) 
L. F. Martins and V. J. Gabriel,  "New Keynesian Phillips Curves and potential identification failures: a Generalized Empirical Likelihood analysis", in Journal of Macroeconomics, vol. 31, no. 4, pp. 561-571, 2009
Exportar BibTeX 
@article{martins2009_1713931003508,
	author = "Martins, L. F. and Gabriel, V. J.",
	title = "New Keynesian Phillips Curves and potential identification failures: a Generalized Empirical Likelihood analysis",
	journal = "Journal of Macroeconomics",
	year = "2009",
	volume = "31",
	number = "4",
	doi = "10.1016/j.jmacro.2009.01.003",
	pages = "561-571",
	url = "http://www.sciencedirect.com/science/article/pii/S016407040900007X?via%3Dihub"
}
Exportar RIS 
TY  - JOUR
TI  - New Keynesian Phillips Curves and potential identification failures: a Generalized Empirical Likelihood analysis
T2  - Journal of Macroeconomics
VL  - 31
IS  - 4
AU  - Martins, L. F.
AU  - Gabriel, V. J.
PY  - 2009
SP  - 561-571
SN  - 0164-0704
DO  - 10.1016/j.jmacro.2009.01.003
UR  - http://www.sciencedirect.com/science/article/pii/S016407040900007X?via%3Dihub
AB  - In this paper, we examine parameter identification in the hybrid specification of the New Keynesian Phillips Curve proposed by Gali and Gertler [Gali, J., Gertler, M., 1999. Inflation dynamics: a structural econometric analysis. Journal of Monetary Economics 44, 195-222]. We employ recently developed moment conditions inference procedures, which provide a more efficient and reliable econometric framework for the analysis of the NKPC. In particular, we address the issue of parameter identification, obtaining robust confidence sets for the model's parameters. Our results cast serious doubts on the empirical validity of the NKPC.
ER  -