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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) 
Damásio, B. & Mendonça, S. (2019). Modelling insurgent-incumbent dynamics: vector autoregressions, multivariate Markov chains, and the nature of technological competition. Applied Economics Letters. 26 (10), 843-849
Exportar Referência (IEEE) 
B. Damásio and S. M. Mendonça,  "Modelling insurgent-incumbent dynamics: vector autoregressions, multivariate Markov chains, and the nature of technological competition", in Applied Economics Letters, vol. 26, no. 10, pp. 843-849, 2019
Exportar BibTeX 
@article{damásio2019_1732210950063,
	author = "Damásio, B. and Mendonça, S.",
	title = "Modelling insurgent-incumbent dynamics: vector autoregressions, multivariate Markov chains, and the nature of technological competition",
	journal = "Applied Economics Letters",
	year = "2019",
	volume = "26",
	number = "10",
	doi = "10.1080/13504851.2018.1502863",
	pages = "843-849",
	url = "https://www.tandfonline.com/doi/full/10.1080/13504851.2018.1502863"
}
Exportar RIS 
TY  - JOUR
TI  - Modelling insurgent-incumbent dynamics: vector autoregressions, multivariate Markov chains, and the nature of technological competition
T2  - Applied Economics Letters
VL  - 26
IS  - 10
AU  - Damásio, B.
AU  - Mendonça, S.
PY  - 2019
SP  - 843-849
SN  - 1350-4851
DO  - 10.1080/13504851.2018.1502863
UR  - https://www.tandfonline.com/doi/full/10.1080/13504851.2018.1502863
AB  - The struggle between sail and steam is a long-standing theme in economic history. But this technological competition story has only been partly tackled, since most studies have appreciated the rivalry between the two alternative modes of commercial sea carriage in the late 19th century while the early period has remained relatively under-analysed. This paper models the early dynamics between the two capital goods using a vector autoregression approach (VAR) and a Multivariate Markov Chain approach (MMC). We find evidence that the relationship was non-linear, with a strong indication of complementarities and cross-technology learning effects.
ER  -