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GMM estimation of non-Gaussian structural vector autoregression

Lanne, Markku; Luoto, Jani - In: Journal of business & economic statistics : JBES ; a … 39 (2021) 1, pp. 69-81

Persistent link: https://www.econbiz.de/10012424500

GMM estimation of non-Gaussian structural vector autoregression

Lanne, Markku; Luoto, Jani - 2018

Persistent link: https://www.econbiz.de/10011800283

Noncausal Bayesian vector autoregression

Lanne, Markku; Luoto, Jani - In: Journal of applied econometrics 31 (2016) 7, pp. 1392-1406

Persistent link: https://www.econbiz.de/10011687545

A new time-varying parameter autoregressive model for U.S. inflation expectations

Lanne, Markku; Luoto, Jani - In: Journal of money, credit and banking : JMCB 49 (2017) 5, pp. 969-995

Persistent link: https://www.econbiz.de/10011946516

Data-driven inference on sign restrictions in Bayesian structural vector autoregression

Lanne, Markku; Luoto, Jani - 2016

Persistent link: https://www.econbiz.de/10011421768

Statistical identification of economic shocks by signs in structural vector autoregression

Lanne, Markku; Luoto, Jani - In: Essays in honour of Fabio Canova, (pp. 165-175). 2022

Persistent link: https://www.econbiz.de/10013445154

Statistically identified structural VAR model with potentially skewed and fat-tailed errors

Anttonen, Jetro; Lanne, Markku; Luoto, Jani - In: Journal of applied econometrics 39 (2024) 3, pp. 422-437

Persistent link: https://www.econbiz.de/10014517491

Noncausal Bayesian vector autoregression

Lanne, Markku; Luoto, Jani - 2014

Persistent link: https://www.econbiz.de/10010256309

Identifying structural vector autoregression via leptokurtic economic shocks

Lanne, Markku; Liu, Keyan; Luoto, Jani - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 4, pp. 1341-1351

Persistent link: https://www.econbiz.de/10014448648

Identifying Structural Vector Autoregression via Large Economic Shocks

Lanne, Markku; Liu, Keyan; Luoto, Jani - 2021

We revisit the generalized method of moments (GMM) estimation of the non-Gaussian structural vector autoregressive (SVAR) model. It is shown that in the n-dimensional SVAR model, global and local identification of the contemporaneous impact matrix is achieved with as few as n^2+n(n-1)/2 suitably...

Persistent link: https://www.econbiz.de/10013214740