New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks
This paper addresses the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restricted VARs are well documented, the recent attempt to overcome...
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2019
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| Online Access: | http://documents.worldbank.org/curated/en/133781571930814658/New-Approaches-to-the-Identification-of-Low-Frequency-Drivers-An-Application-to-Technology-Shocks http://hdl.handle.net/10986/32656 |
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okr-10986-326562022-09-19T12:17:19Z New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks Dieppe, Alistair Neville, Francis Kindberg-Hanlon, Gene TECHNOLOGY SHOCK PRODUCTIVITY STRUCTURAL VECTOR AUTOREGRESSION ECONOMIC SHOCKS BUSINESS CYCLE This paper addresses the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restricted VARs are well documented, the recent attempt to overcome said issues using the Max-Share approach of Francis et al. (2014) and Barsky and Sims (2011) has its own shortcomings, primarily that they are vulnerable to bias from confounding non-technology shocks. A modification to the Max-Share approach and two further spectral methods are proposed to improve empirical identification. Performance directly hinges on whether these confounding shocks are of high or low frequency. Applied to US and emerging market data, spectral identifications are most robust across specifications, and non-technology shocks appear to be biasing traditional methods of identifying technology shocks. These findings also extend to the SVAR identification of dominant business-cycle shocks, which are shown will be a variance-weighted combination of shocks rather than a single structural driver. 2019-11-21T16:40:38Z 2019-11-21T16:40:38Z 2019-10 Working Paper http://documents.worldbank.org/curated/en/133781571930814658/New-Approaches-to-the-Identification-of-Low-Frequency-Drivers-An-Application-to-Technology-Shocks http://hdl.handle.net/10986/32656 English Policy Research Working Paper;No. 9047 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
TECHNOLOGY SHOCK PRODUCTIVITY STRUCTURAL VECTOR AUTOREGRESSION ECONOMIC SHOCKS BUSINESS CYCLE |
| spellingShingle |
TECHNOLOGY SHOCK PRODUCTIVITY STRUCTURAL VECTOR AUTOREGRESSION ECONOMIC SHOCKS BUSINESS CYCLE Dieppe, Alistair Neville, Francis Kindberg-Hanlon, Gene New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| relation |
Policy Research Working Paper;No. 9047 |
| description |
This paper addresses the identification
of low-frequency macroeconomic shocks, such as technology,
in Structural Vector Autoregressions. Whilst identification
issues with long-run restricted VARs are well documented,
the recent attempt to overcome said issues using the
Max-Share approach of Francis et al. (2014) and Barsky and
Sims (2011) has its own shortcomings, primarily that they
are vulnerable to bias from confounding non-technology
shocks. A modification to the Max-Share approach and two
further spectral methods are proposed to improve empirical
identification. Performance directly hinges on whether these
confounding shocks are of high or low frequency. Applied to
US and emerging market data, spectral identifications are
most robust across specifications, and non-technology shocks
appear to be biasing traditional methods of identifying
technology shocks. These findings also extend to the SVAR
identification of dominant business-cycle shocks, which are
shown will be a variance-weighted combination of shocks
rather than a single structural driver. |
| format |
Working Paper |
| author |
Dieppe, Alistair Neville, Francis Kindberg-Hanlon, Gene |
| author_facet |
Dieppe, Alistair Neville, Francis Kindberg-Hanlon, Gene |
| author_sort |
Dieppe, Alistair |
| title |
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| title_short |
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| title_full |
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| title_fullStr |
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| title_full_unstemmed |
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks |
| title_sort |
new approaches to the identification of low-frequency drivers : an application to technology shocks |
| publisher |
World Bank, Washington, DC |
| publishDate |
2019 |
| url |
http://documents.worldbank.org/curated/en/133781571930814658/New-Approaches-to-the-Identification-of-Low-Frequency-Drivers-An-Application-to-Technology-Shocks http://hdl.handle.net/10986/32656 |
| _version_ |
1764477006285635584 |