Identification of Technology Shocks in Structural Vars

Economic Journal

Volumn 120, Issue 549, 2010, Pages 1284-1318

  Fève, Patrick ^a,b   Guay, Alain ^a,b  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b UNIVERSITÉ DU QUÉBEC À MONTRÉAL   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BUSINESS CYCLE; COMPUTER SIMULATION; EXPERIMENTAL STUDY; IDENTIFICATION METHOD; INTEREST RATE; MACROECONOMICS; NUMERICAL MODEL; STRUCTURAL ADJUSTMENT; TECHNOLOGY ADOPTION; THEORETICAL STUDY; VECTOR AUTOREGRESSION;

EID: 78649394918     PISSN: 00130133     EISSN: 14680297     Source Type: Journal    
DOI: 10.1111/j.1468-0297.2009.02328.x     Document Type: Article

References (35)

1. Andrews, D.W.K. and Mohanan, J.C. (1992). 'An improved heteroskedasticidy and autocorrelation consistent covariance matrix estimator', Econometrica, vol. 60, pp. 953-66.
2. Basu, S., Fernald, J. and Kimball, M. (2006). 'Are technology improvements contractionary?', American Economic Review, vol. 96(5), pp. 1418-48.
3. Blanchard, O.J. and Quah, D. (1989). 'The dynamic effects of aggregate demand and supply disturbances', American Economic Review, vol. 79(4), pp. 655-73.
4. Burnside, C. and Eichenbaum, M. (1996). 'Factor-hoarding and the propagation of business-cycle shocks', American Economic Review, vol. 86(5), pp. 1154-74.
5. Chang, P. and Sakata, S. (2007). 'Estimation of impulse response functions using long autoregression', Econometrics Journal, vol. 10, pp. 453-69.
6. Chang, Y., Doh, T. and Schorfheide, F. (2007). 'Non-stationary hours in a DSGE model', Journal of Money Credit and Banking, vol. 39(6), pp. 1357-73.
7. Chari, V., Kehoe, P. and Mc Grattan, E. (2007a). 'Business cycle accounting', Econometrica, vol. 75(3), pp. 781-836.
8. Chari, V., Kehoe, P. and Mc Grattan, E. (2007b). 'A critique of structural VARs using real business cycle theory', Federal Reserve Bank of Minneapolis, Research Department Staff Report No. 364, revised May 2007.
9. Christiano, L., Eichenbaum, M. and Vigfusson, R. (2004). 'What happens after a technology shock', NBER Working Paper No. 9819, revised version 2004.
10. Christiano, L., Eichenbaum, M. and Vigfusson, R. (2006). 'Assessing structural VARs'. in (D. Acemoglu, K. Rogoff and M. Woodford, eds), NBER Macroeconomics Annual, pp. 1-72, Cambridge MA: The MIT Press.
11. Cochrane, J. (1994). 'Permanent and transitory components of GDP and stock returns', Quarterly Journal of Economics, vol. 109(1), pp. 241-66.
12. Cogley, T., Primiceri, G. and Sargent, T. (2008). 'Inflation-gap persistence in the US', unpublished manuscript, Department of Economics, NYU.
13. Cooley, T. and Dwyer, M. (1998). 'Business cycle analysis without much theory: a look at structural VARs', Journal of Econometrics, vol. 83(1-2), pp. 57-88.
14. Erceg, C., Guerrieri, L. and Gust, C. (2005). 'Can long-run restrictions identify technology shocks', Journal of European Economic Association, vol. 3, pp. 1237-78.
15. Faust, J. and Leeper, E.M. (1997). 'When do long-run identifying restrictions give reliable results?', Journal of Business & Economic Statistics, vol. 15(3), pp. 345-53.
16. Francis, N. and Ramey, V. (2005). 'Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited', Journal of Monetary Economics, vol. 52, pp. 1379-99.
17. Francis, N. and Ramey, V. (2008). 'Measures of per capita hours and their implications for the rechnology-hours debate'. mimeo UCSD.
18. Francis, N., Owyang, M. and Roush, J. (2005). 'A flexible finite-horizon identification of technology shocks'. Board of Governors of the Federal Reserve System, International Finance Discussion Paper No. 832, April.
19. Galí, J. (1999). 'Technology, employment and the business cycle: do technology shocks explain aggregate fluctuations?', American Economic Review, vol. 89(1), pp. 249-71.
20. Galí, J. (2005). 'Trends in hours, balanced growth and the role of technology in the business cycle', Federal Reserve Bank of Saint Louis Review, vol. 87(4), pp. 459-86.
21. Galí, J. and Rabanal, P. (2004). 'Technology shocks and aggregate fluctuations: how well does the RBC model fit postwar U.S. data?', in (M. Gertler and K. Rogoff, eds), NBER Macroeconomics Annual, pp. 225-88, Cambridge MA: The MIT Press.
22. Gospodinov, N. (2006). 'Inference in nearly nonstationary SVAR models with long-run identifying restriction'. mimeo Concordia University, forthcoming Journal of Business Economics and Statistics.
23. Hall, R. (1997). 'Macroeconomic fluctuations and the allocation of time', Journal of Labor Economics, vol. 15(1), pp. 223-50.
24. Ireland, P. (2003). 'Endogenous money or sticky prices?', Journal of Monetary Economics, vol. 50(8), pp. 1623-48
25. Jordà, Ò. (2005). 'Estimation and inference of impulse responses by local projections', American Economic Review, vol. 95(1), pp. 161-82.
26. Juselius, K. (2006) The Cointegrated VAR Model, Advanced Texts in Econometrics, Oxford: Oxford University Press.
27. King, R., Plosser, C., Stock, J. and Watson, M. (1991). 'Stochastic trends and economic fluctuations', American Economic Review, vol. 81(4), pp. 819-40.
28. Lewis, R. and Reinsel, G.C. (1985). 'Prediction of multivariate time series by autoregressive model fitting', Journal of Multivariate Analysis, vol. 15(1), pp. 393-411.
29. Patton, A., Politis, D.N. and White, H. (2009). 'Correction to: automatic block-length selection for the dependent bootstrap', Econometric Reviews, vol. 28(4), pp. 372-5.
30. Pesavento, E. and Rossi, B. (2005). 'Do technology shocks drive hours up or down', Macroeconomic Dynamics, vol. 9(4), pp. 478-88.
31. Politis, D.N. and White, H. (2004). 'Automatic block-length selection for the dependent bootstrap', Econometric Reviews, vol. 23(1), pp. 53-70.
32. Prescott, E.C. (1986). 'Theory ahead of business cycle measurement'. Quarterly Review Federal Reserve Bank of Minneapolis, Fall issue, pp. 9-22.
33. Ravenna, F. (2007). 'Vector autoregressions and reduced form representations of DSGE models', Journal of Monetary Economics, vol. 57(7), pp. 2048-64.
34. Stock, J. and Watson, M. (2005). 'Why has U.S. inflation become harder to forecast?', Journal of Money, Banking and Credit, vol. 39(1), pp. 3-34.
35. Vigfusson, R. (2004). 'The delayed response to a technology shock. A flexible price explanation'. Board of Governors of the Federal Reserve System, International Finance Discussion Paper No. 810, July.