Short-Run Restrictions: An Identification Device? Fabrice Collard, Patrick Fève & Julien Matheron Discussion

1. Short-Run Restrictions: An Identification Device?Fabrice Collard, Patrick Fève & Julien MatheronDiscussion Gert Peersman Ghent University

2. Situation in literature • Very interesting paper • Estimation of deep parameters of DSGE models • Strong econometric interpretation • Full characterisation of the data • Maximum likelihood methods or Bayesian methods • Weak econometric interpretation • DSGE model is calibrated as such that theoretical moments match their counterparts in the data • Fully specifying the stochastic structure of the model is not required • Often more robust than full-information estimators • E.g. minimising the difference between an impulse response function from an empirical VAR and a theoretical DSGE model

3. Situation in literature • Weak econometric interpretation • Minimum distance estimation where structural shocks in the VAR are identified with short-run zero restrictions • Rotemberg and Woodford (1998) • Christiano, Eichenbaum and Evans (2005) • Same restrictions are required in DSGE model • This paper analyses whether this approach can be used to identify the deep parameters of the DSGE model

4. But... • RW (1998) and CEE (2005) identify monetary policy shocks with short-run zero restrictions while this paper identifies a technology shock to evaluate the method • Impact of techology shock on labour (a response to be matched) is already very controversial in literature • Are the same conclusions also found when a monetary policy shock is identified with short-run restrictions? • The way short-run restrictions are implemented to identify technology shocks in the VAR using real data is problematic • Technology shock is a shock with no immediate effect on hours in a VAR containing hours and labour productivity • Implies that all other shocks do have an immediate impact on hours and labour decisions (including e.g. monetary policy shocks) • Identified shock in paper will be a combination of several shocks

5. But... • The way short-run restrictions are implemented to identify technology shocks in the VAR using real data is problematic • Technology shocks are usually identified with long-run restrictions • Authors show that impulse responses look similar anyway • Based on VAR estimated with hours in levels (Christiano, Eichenbaum and Vigfusson 2005a) while original papers are estimated with first difference specification (Gali 1999 or Francis and Ramey 2002) • Estimated impulse response functions using long-run restrictions are very uncertain: never significant different from zero (not only contemporaneous impact) • Short-run restrictions to identify technology shocks also done by Christiano, Eichenbaum and Vigfusson (2005b) • But they use simulated data obtained from a model containing the restriction with only one shock

6. Contribution of this paper • CEE (2005): monetary policy shock • Robustness check: the role of timing assumptions • Eyeball econometrics by having a look at responses when some variables are not predetermined • This paper adds some nice supplements (IRF ratio, autocorrelation function) and also a statistical procedure • Application to impact of technology shock • Information structure does matter! • Question the use of short-run zero restrictions to identify deep parameters of DSGE model!

7. Going even further • Short-run zero restrictions to identify the shocks in the VAR is already very controversial • CEE (2005): “long standing view that many macroeconomic variables do not respond immediately to policy shocks” • Start introducing these restrictions in their theoretical model • “these assumptions do not have a substantial impact on dynamic properties of the model” (magnitude, persistence, hump-shaped response) • No theoretical reason to believe in short-run zero restrictions (see also Canova and Pina, 2005) • Short-run zero restrictions have a considerable effect on the estimated impact of shocks in VARs (Peersman, 2005)

8. Going even further • Response to a monetary policy shock of 50 basis points • Response function with zero restrictions in tails of all possible responses • Also variance decompositions changes dramatically • What happens with deep parameters if these more general restrictions are implemented in the VAR?

9. Going even further • Also long-run zero restrictions can be controversial • Often questioned from an empirical point of view: Sims (1972), Faust and Leeper (1997), Erceg, Guerrieri and Gust (2005), ... • Farrant and Peersman (2006): contribution of nominal shocks to the euro/dollar exchange rate increases from 11% to 57% when qualitative restrictions are used instead of long-run zero restrictions (both obtained from the same theoretical model) • Peersman and Straub (2004): Sign of the impact of technology shocks on hours changes with qualitative restrictions

10. Going even further • Go even more general if some of qualitative restrictions are uncertain or want to be tested • Peersman and Straub (2006): use sign restrictions on the ratio of responses • Example: many models predict a rise in output and a fall in private consumption and investment after a positive government spending shock • Not useful restrictions: not robust for all models and often rejected in empirical papers • Impose a much more general restriction on the consumption-output and investment-output ratio • Data can then determine the reaction of consumption and investment

11. Going even further • Peersman and Straub (2006): use sign restrictions on the ratio of responses • Expansionary government spending shocks generate a fall in private consumption and investment • A positive shock in consumer preferences has a positive effect on investment (in contrast to New Keynesian DSGE models) • A favourable shock in investment adjustment costs has a positive impact on private consumption (in contrast to New Keynesian DSGE models) • Technology shocks cause hours to rise (in contrast to New Keynesian DSGE models)