Incorporating Conjunctural Analysis in Structural Models
This volume celebrates the work of Michael Woodford and his many contributions to economics.
One of Mike's most influential papers is the 1997 paper (co-authored with Julio Rotemberg) “An optimization-based econometric framework for the evaluation of monetary policy.” This paper constituted the first attempt at estimation of a small scale dynamic stochastic general equilibrium model (DSGE) in which prices are set by monopolistically competitive firms, and prices cannot be instantaneously and costlessly adjusted. Since the work of Rotemberg and Woodford, these models have become more complex and increasingly large [see Christiano, Eichenbaum and Evans (2005), Smets and Wouters (2003), and, more recently, Christoffel, Coenen and Warne (2008) and Adolfson, Laséen, Lindé and Svensson (2008)]. By explicitly taking into account forwardlooking behavior on the part of the agents, DSGEs provide a useful framework to analyze the effects of alternative policies. These models are now routinely used in many central banks, including the European Central Bank, and knowledge has been built up on their reliability, their forecasting performance and on what are the reasonable values for calibrated parameters and the setting of the priors.
KeywordsMonetary Policy Total Factor Productivity Euro Area Capacity Utilization Total Factor Productivity Growth
Unable to display preview. Download preview PDF.
- Aastveit, K. A., and T. G. Trovik. 2008. “Nowcasting Norwegian GDP: The role of asset prices in a small open economy.” Norges Bank Working Paper 2007/09.Google Scholar
- Adolfson, M., S. Laséen, J. Lindé, and L. E. O. Svensson. 2008. “Opti mal Monetary Policy in an Operational Medium-Sized DSGE Model.” National Bureau of Economic Research Working Paper 14092.Google Scholar
- Anderson, B. D. O., and J. B. Moore. 1979. Optimal Filtering. Prentice-Hall.Google Scholar
- Anderson, E., L. P. Hansen, E. R. McGrattan, and T. J. Sargent. 1996. “Mechanics of Forming and Estimating Dynamic Linear Economies.” In Handbook of Computational Economics, Volume 1, ed. D. A. K. Hans, M. Amman, and J. Rust, 171–252. North-Holland.Google Scholar
- Angelini, E., G. Camba-Méndez, D. Giannone, G. Rünstler, and L. Reichlin. 2008. “Short-term forecasts of euro area GDP growth.” ECB mimeo.Google Scholar
- Banbura, M., D. Giannone, and L. Reichlin. 2008. “Large Bayesian VARs.” European Central Bank Working Paper Series 966.Google Scholar
- Boivin, J., and M. Giannoni. 2006. “DSGE Models in a Data-Rich Environment.” National Bureau of Economic Research Working Paper 12772.Google Scholar
- Christoffel, K., G. Coenen, and A. Warne. 2008. “The new area-wide model of the euro area — a micro—founded open-economy model for forecasting and policy analysis.” European Central Bank Working Paper Series 944.Google Scholar
- Giannone, D., F. Monti, and L. Reichlin. 2008. “Short-term Analysis with Structural Models.” London Business School Mimeo.Google Scholar
- Matheson, T. 2007. “An analysis of the informational content of New Zealand data releases: The importance of business opinion surveys.” Reserve Bank of New Zealand Discussion Paper Series DP2007/13, revised.Google Scholar
- Rotemberg, J., and M. Woodford. 1997. “An optimization-based econometric framework for the evaluation of monetary policy.” In NBER macroeconomics annual 1997, ed. B. S. Bernanke and J. J. Rotemberg, 297–346.Google Scholar