S. An and F. Schorfheide, Bayesian Analysis of DSGE Models, Econometric Reviews, vol.31, issue.2-4, pp.113-172, 2007.
DOI : 10.2307/1912526

O. J. Blanchard and D. Quah, The dynamic e¤ects of aggregate demand and supply disturbances, American Economic Review, vol.79, pp.655-73, 1989.

F. Canova and L. Sala, Back to square one: Identification issues in DSGE models, Journal of Monetary Economics, vol.56, issue.4, pp.431-449, 2009.
DOI : 10.1016/j.jmoneco.2009.03.014

Y. Chang, T. Doh, and F. Schorfheide, Non-stationary Hours in a DSGE Model, Journal of Money, Credit and Banking, vol.28, issue.1, pp.1357-1373, 2007.
DOI : 10.1162/154247603770383415

V. V. Chari, P. J. Kehoe, and E. R. Mcgrattan, Are structural VARs with long-run restrictions useful in developing business cycle theory?, Journal of Monetary Economics, vol.55, issue.8, pp.1337-52, 2008.
DOI : 10.1016/j.jmoneco.2008.09.010

L. J. Christiano and M. Eichenbaum, Current real business cycle theories and aggregate labor market ?uctuations, American Economic Review, vol.82, pp.430-450, 1992.
DOI : 10.4324/9780203070710.ch10

L. J. Christiano, M. Eichenbaum, and R. Vigfusson, What happens after a technology shock, 2004.

L. J. Christiano, M. Eichenbaum, and R. Vigfusson, Alternative Procedures for Estimating Vector Autoregressions Identified with Long-Run Restrictions, Journal of the European Economic Association, vol.4, issue.2-3, pp.475-483, 2006.
DOI : 10.1162/jeea.2006.4.2-3.475

T. Cogley and J. Nason, Output Dynamics in Real-Business-Cycle Models, American Economic Review, vol.84, pp.492-511, 1995.
DOI : 10.4324/9780203070710.ch30

T. F. Cooley and M. Dwyer, Business cycle analysis without much theory A look at structural VARs, Journal of Econometrics, vol.83, issue.1-2, pp.57-88, 1998.
DOI : 10.1016/S0304-4076(97)00065-1

D. A. Dickey and W. A. Fuller, Distribution of the estimators for autoregressive time series with unit root, Journal of the American Statistical Association, vol.74, pp.427-481, 1979.

D. A. Dickey and W. A. Fuller, Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root, Econometrica, vol.49, issue.4, pp.1057-1072, 1981.
DOI : 10.2307/1912517

M. Dupaigne, P. Fève, and J. Matheron, Some analytics on bias in DSVARs, Economics Letters, vol.97, issue.1, pp.32-38, 2007.
DOI : 10.1016/j.econlet.2007.02.010

G. Elliott, T. J. Rothenberg, and J. H. Stock, Efficient Tests for an Autoregressive Unit Root, Econometrica, vol.64, issue.4, pp.813-836, 1996.
DOI : 10.2307/2171846

C. J. Erceg, L. Guerrieri, and C. Gust, Can Long-Run Restrictions Identify Technology Shocks?, Journal of the European Economic Association, vol.3, issue.6, pp.1237-1278, 2005.
DOI : 10.1162/154247605775012860
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.462.2971

J. Faust and E. S. Leeper, When Do Long-Run Identifying Restrictions Give Reliable Results?, Journal of Business & Economic Statistics, vol.15, issue.3, pp.345-53, 1997.
DOI : 10.1080/07350015.1997.10524712

P. Fève and A. Guay, The Response of Hours to a Technology Shock: A Two-Step Structural VAR Approach, Journal of Money, Credit and Banking, vol.97, issue.5, pp.987-1013, 2009.
DOI : 10.1111/j.1538-4616.2009.00241.x

N. Francis and V. A. Ramey, Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited, Journal of Monetary Economics, vol.52, issue.8, pp.1379-99, 2005.
DOI : 10.1016/j.jmoneco.2004.08.009

J. Galí, Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?, American Economic Review, vol.89, issue.1, pp.249-71, 1999.
DOI : 10.1257/aer.89.1.249

J. Galí and P. Rabanal, Technology shocks and aggregate ?uctuations: How well does the real business cycle model ?t postwar U.S. data? Working Paper No 10636, 2004.

C. Gust and R. Vigfusson, The power of long-run structural VARs, International Finance Discussion Papers 978, 2009.

N. Haldrup and M. Jansson, Improving Size and Power in the Unit Root Testing, Palgrave Handbook of Econometrics: Econometric Theory, 2006.
DOI : 10.2139/ssrn.1147594

G. D. Hansen, Indivisible labor and the business cycle, Journal of Monetary Economics, vol.16, issue.3, pp.309-327, 1985.
DOI : 10.1016/0304-3932(85)90039-X

G. D. Hansen, Technological progress and aggregate ?uctuations, Journal of Political Economy, vol.16, pp.1005-1023, 1997.

C. Kascha and K. Mertens, Business cycle analysis and VARMA models, Journal of Economic Dynamics and Control, vol.33, issue.2, pp.267-282, 2009.
DOI : 10.1016/j.jedc.2008.05.006
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.619.2390

R. King, C. Plosser, J. Stock, and M. Watson, Stochastic trends and economic ?uctuations, American Economic Review, vol.81, pp.819-940, 1991.
DOI : 10.3386/w2229
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.406.6117

D. Kwiatkowski, P. Phillips, P. Schmidt, and Y. Shin, Testing the null hypothesis of stationarity against the alternative of a unit root, Journal of Econometrics, vol.54, issue.1-3, pp.159-178, 1992.
DOI : 10.1016/0304-4076(92)90104-Y

F. Kydland and E. Prescott, Time to Build and Aggregate Fluctuations, Econometrica, vol.50, issue.6, pp.1345-70, 1982.
DOI : 10.2307/1913386

J. Linde, Estimating New-Keynesian Phillips curves: A full information maximum likelihood approach, Journal of Monetary Economics, vol.52, issue.6, pp.1135-1149, 2005.
DOI : 10.1016/j.jmoneco.2005.08.007

P. Liu and K. Theodoridis, DSGE model restrictions for structural VAR identi?cation, 2010.

J. Mackinnon, Critical values for cointegration tests Long-run Economic Relationships, Readings in Cointegration, pp.267-276, 1991.

C. R. Nelson and C. I. Plosser, Trends and random walks in macroeconmic time series, Journal of Monetary Economics, vol.10, issue.2, pp.139-162, 1982.
DOI : 10.1016/0304-3932(82)90012-5

S. Ng and P. Perron, Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag, Journal of the American Statistical Association, vol.90, issue.429, pp.268-281, 1995.
DOI : 10.1214/aos/1176344897

S. Ng and P. Perron, LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power, Econometrica, vol.69, issue.6, pp.1519-1554, 2001.
DOI : 10.1111/1468-0262.00256

P. Perron and S. Ng, Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties, The Review of Economic Studies, vol.63, issue.3, pp.435-465, 1996.
DOI : 10.2307/2297890

P. C. Phillips and P. Perron, Testing for a unit root in time series regression, Biometrika, vol.75, issue.2, pp.347-353, 1988.
DOI : 10.1093/biomet/75.2.335

E. C. Prescott, Theory ahead of business-cycle measurement, Carnegie-Rochester Conference Series on Public Policy, vol.25, pp.11-44, 1986.
DOI : 10.1016/0167-2231(86)90035-7

F. Ravenna, Vector autoregressions and reduced form representations of DSGE models, Journal of Monetary Economics, vol.54, issue.7, pp.2048-2064, 2007.
DOI : 10.1016/j.jmoneco.2006.09.002

D. V. Vougas, GLS detrending and unit root testing, Economics Letters, vol.97, issue.3, pp.222-229, 2007.
DOI : 10.1016/j.econlet.2007.03.016

K. T. Whelan, Technology shocks and hours worked: Checking for robust conclusions, Journal of Macroeconomics, vol.31, issue.2, pp.231-239, 2009.
DOI : 10.1016/j.jmacro.2008.06.003