Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

**Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression.** / Lanne, Markku; Luoto, Jani.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Lanne, M & Luoto, J 2020, 'Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression', *Oxford Bulletin of Economics and Statistics*, vol. 82, no. 2, pp. 425-452. https://doi.org/10.1111/obes.12338

Lanne, M., & Luoto, J. (2020). Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression. *Oxford Bulletin of Economics and Statistics*, *82*(2), 425-452. https://doi.org/10.1111/obes.12338

Lanne M, Luoto J. 2020. Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression. Oxford Bulletin of Economics and Statistics. 82(2):425-452. https://doi.org/10.1111/obes.12338

Lanne, Markku and Jani Luoto. "Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression". *Oxford Bulletin of Economics and Statistics*. 2020, 82(2). 425-452. https://doi.org/10.1111/obes.12338

Lanne M, Luoto J. Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression. Oxford Bulletin of Economics and Statistics. 2020 Apr;82(2):425-452. doi: 10.1111/obes.12338

Lanne, Markku ; Luoto, Jani. / **Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression**. In: Oxford Bulletin of Economics and Statistics. 2020 ; Vol. 82, No. 2. pp. 425-452.

@article{30c688e087dc46babcd77241f1d98aca,

title = "Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression",

abstract = "Theories often make predictions about the signs of the effects of economic shocks on observable variables, thus implying inequality constraints on the parameters of a structural vector autoregression (SVAR). We introduce a new Bayesian procedure to evaluate the probabilities of such constraints, and, hence, to validate the theoretically implied economic shocks. We first estimate a SVAR, where the shocks are identified by statistical properties of the data, and subsequently label these statistically identified shocks by the Bayes factors calculated from their probabilities of satisfying given inequality constraints. In contrast to the related sign restriction approach that also makes use of theoretically implied inequality constraints, no restrictions are imposed. Hence, it is possible that only a subset or none of the theoretically implied shocks can be labelled. In the latter case, we conclude that the data do not lend support to the theory implying the signs of the effects in question. We illustrate the method by empirical applications to the crude oil market, and U.S. monetary policy.",

keywords = "DISENTANGLING DEMAND, OIL MARKET, SIGN RESTRICTIONS, SUPPLY SHOCKS",

author = "Markku Lanne and Jani Luoto",

year = "2020",

month = apr,

doi = "10.1111/obes.12338",

language = "English",

volume = "82",

pages = "425--452",

journal = "Oxford Bulletin of Economics and Statistics",

issn = "0305-9049",

publisher = "Wiley-Blackwell Publishing Ltd.",

number = "2",

}

TY - JOUR

T1 - Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression

AU - Lanne, Markku

AU - Luoto, Jani

PY - 2020/4

Y1 - 2020/4

N2 - Theories often make predictions about the signs of the effects of economic shocks on observable variables, thus implying inequality constraints on the parameters of a structural vector autoregression (SVAR). We introduce a new Bayesian procedure to evaluate the probabilities of such constraints, and, hence, to validate the theoretically implied economic shocks. We first estimate a SVAR, where the shocks are identified by statistical properties of the data, and subsequently label these statistically identified shocks by the Bayes factors calculated from their probabilities of satisfying given inequality constraints. In contrast to the related sign restriction approach that also makes use of theoretically implied inequality constraints, no restrictions are imposed. Hence, it is possible that only a subset or none of the theoretically implied shocks can be labelled. In the latter case, we conclude that the data do not lend support to the theory implying the signs of the effects in question. We illustrate the method by empirical applications to the crude oil market, and U.S. monetary policy.

AB - Theories often make predictions about the signs of the effects of economic shocks on observable variables, thus implying inequality constraints on the parameters of a structural vector autoregression (SVAR). We introduce a new Bayesian procedure to evaluate the probabilities of such constraints, and, hence, to validate the theoretically implied economic shocks. We first estimate a SVAR, where the shocks are identified by statistical properties of the data, and subsequently label these statistically identified shocks by the Bayes factors calculated from their probabilities of satisfying given inequality constraints. In contrast to the related sign restriction approach that also makes use of theoretically implied inequality constraints, no restrictions are imposed. Hence, it is possible that only a subset or none of the theoretically implied shocks can be labelled. In the latter case, we conclude that the data do not lend support to the theory implying the signs of the effects in question. We illustrate the method by empirical applications to the crude oil market, and U.S. monetary policy.

KW - DISENTANGLING DEMAND

KW - OIL MARKET

KW - SIGN RESTRICTIONS

KW - SUPPLY SHOCKS

UR - http://www.scopus.com/inward/record.url?scp=85070780699&partnerID=8YFLogxK

U2 - 10.1111/obes.12338

DO - 10.1111/obes.12338

M3 - Journal article

AN - SCOPUS:85070780699

VL - 82

SP - 425

EP - 452

JO - Oxford Bulletin of Economics and Statistics

JF - Oxford Bulletin of Economics and Statistics

SN - 0305-9049

IS - 2

ER -