Printed from https://ideas.repec.org
IDEAS/RePEc search
IDEAS search now includes synonyms. If you feel that some synonyms are missing, you are welcome to suggest them for inclusion
- Sevgi Coskun (2020): Technology Shocks and Non-stationary Hours in Emerging Countries and DSVAR
Motivated by this fact, we first estimate a structural vector autoregression (SVAR) model with a specification of hours in difference (DSVAR) and then set up a DSGE model by incorporating permanent labour supply (LS) shocks that can generate a unit root in hours worked, while preserving the property of a balanced growth path. ... For inference purposes, we compare empirical impulse responses based on the EMEs data to impulse responses from DSVARs run on the simulated data from the model. The results show that a DSGE model with permanent LS shocks that can generate a unit root in hours worked is required to properly evaluate the DSVAR in EMEs as this model is able to replicate indirectly impulse responses obtained from a DSVAR on the actual data.
RePEc:sae:mareco:v:14:y:2020:i:2:p:129-163 Save to MyIDEAS - Martial Dupaigne & Patrick Feve & Julien Matheron (2007): Technology Shocks, Non-stationary Hours and DSVAR
Structural Vector Autoregressions with a differenced specification of hours (DSVAR) suggest that productivity shocks identified using long--run restrictions lead to a persistent and significant decline in hours worked. ... We find that, once augmented with a moderate amount of real frictions, the model can mimic well impulse responses obtained form a DSVAR on actual data. Using this model as a data generating process, we show that our estimation method is less subject to bias than a method that would directly compare theoretical responses with responses from the DSVAR.
RePEc:red:issued:05-128 Save to MyIDEAS - Dupaigne, Martial & Feve, Patrick & Matheron, Julien (2007): Some analytics on bias in DSVARs
No abstract is available for this item.
RePEc:eee:ecolet:v:97:y:2007:i:1:p:32-38 Save to MyIDEAS - Mark Bognanni (2018): A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification
This paper develops a new class of structural vector autoregressions (SVARs) with time-varying parameters, which I call a drifting SVAR (DSVAR). The DSVAR is the first structural time-varying parameter model to allow for internally consistent probabilistic inference under exact?... I prove that the DSVAR implies a reduced-form representation, from which structural inference can proceed similarly to the widely used two-step approach for SVARs: beginning with estimation of a reduced form and then choosing among observationally equivalent candidate structural parameters via the imposition of identifying restrictions.
RePEc:fip:fedcwp:1811 Save to MyIDEAS - V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan (2004): A Critique of Structural VARs Using Real Business Cycle Theory
The main substantive finding of the recent structural vector autoregression literature with a differenced specification of hours (DSVAR) is that technology shocks lead to a fall in hours. ... We evaluate the DSVAR approach by asking, is the specification derived from this approach misspecified when the data are generated by the very model the literature is trying to discard?
RePEc:cla:levrem:122247000000000518 Save to MyIDEAS - V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan (2005): A critique of structural VARs using real business cycle theory
The main substantive finding of the recent structural vector autoregression literature with a differenced specification of hours (DSVAR) is that technology shocks lead to a fall in hours. ... We evaluate the DSVAR approach by asking, is the specification derived from this approach misspecified when the data are generated by the very model the literature is trying to discard?
RePEc:fip:fedmwp:631 Save to MyIDEAS