Principal researcher

Michal Kejak

Members of the working group

Jaromír Baxa, Roman Horváth, Michal Kejak, Sergey Slobodyan, Tomáš Havránek, Aleš Maršál, Roman Šustek, Ctirad Slavík

The research objectives

Recently, Dynamic Stochastic General Equilibrium (DSGE) models became a standard analytical tool particularly useful to studying monetary and fiscal policy. In this part of the project we will extend the standard DSGE models in several directions.

Estimation of DSGE Models with Bounded Rationality.

Rational expectations is a standard approach to modelling agents’ expectations. It is important to check the consequences of relaxing this assumption. One of approaches to bounded rationality in the recent literature is adaptive learning, cf. Evans and Honkapohja (2001). The only estimated DSGE models with adaptive learning that moved beyond the small New Keynesian models are Slobodyan and Wouters (2007, 2009). The proposed project would continue a program of estimating the DSGE models under adaptive learning, extending it in several ways.

Estimation of DSGE Models with Asset Markets and Incomplete Information.

The outstanding DSGE literature so far has focused predominantly on complete information rational expectation frameworks. Notable contributions include e.g. Campbell and Cochrane (1999). Although the Bayesian literature has been predominant mostly in empirical work, quite recent and increasingly more computationally intensive studies e. g. Chen and Pakoš (2007) and Hansen and Sargent (2009), seem to validate the apriori neglected role of Bayesian learning in DSGE modelling of the hidden state of the macroeconomy, and the related transitional dynamics in asset prices induced therein.

DSGE Models with Financial Markets.

Recent financial crisis has challenged many traditional macroeconomic models and highlighted the role of interactions between macroeconomic developments and financial sector stability. Recent work in this area includes e.g. Cúrdia and Woodford (2010). We will extend DSGE macroeconomic models in a way to explicitly account for complex interactions with financial sector as well as with fiscal policy.

Optimal Taxation in DSGE Models with Heterogeneous Agents and Incomplete Markets.

The current prevailing methodology used in the theory of optimal taxation with heterogenous agents is based on the seminal Mirrlees (1971), which has been further extended by Kocherlakota (2005), who study optimal social planner policies with asymmetric information. Our approach is very different as we propose to solve for the optimal tax schedule within the standard neoclassical, general equilibrium, full information and full commitment economy with heterogeneous agents and incomplete markets where agents are exposed to idiosyncratic shocks and non-borrowing constraints, see Aiyagari (1995) and Boháček and Kejak (2005) for its basic explanation. The closest paper to ours is Conesa and Krueger (2006) who compute the optimal progressivity of the income tax code in an overlapping generations economy. We will develop models of several different economies with different tax structures searching for the optimal tax schedules in them.


  • Aiyagari, R. S. (1995). Optimal Capital Income Taxation with Incomplete Markets, Borrowing Constraints, and Constant Discounting. Journal of Political Economy 103, 1158–1175.
  • Boháček, R. and Kejak, M. (2005). On the Optimal Tax Schedule. CERGE-EI Working Paper Series 272.
  • Conesa, J. C. and Krueger, D. (2006). On the Optimal Progressivity of the Income Tax Code. Journal of Monetary Economics 53, 1425–1450.
  • Campbell, J. Y. and Cochrane, J. H. (1999). By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior. Journal of Political Economy 107, 205–251.
  • Chen, H. and Pakoš, M. (2008). Asset Pricing with Uncertainty About the Long Run. Manuscript, Sloan School of Management, M.I.T.
  • Cúrdia, V. and Woodford, M. (2010). Credit Spreads and Monetary Policy. Journal of Money, Credit and Banking 42, 3–35.
  • Evans, G. W. and Honkapohja, S. (2001). Learning and Expectations in Macroeconomics. Princeton University Press, Princeton, New Jersey.
  • Hansen, L. P. and Sargent, T. (2010). Fragile Beliefs and the Price of Uncertainty. Quantitative Economics 1, 129–162.
  • Kocherlakota, N. R. (2005). Zero Expected Wealth Taxes: A Mirrlees Approach to Dynamic Optimal Taxation. Econometrica 73 (5), 1587–1621.
  • Mirrlees, J. (1971). An Exploration in the Theory of Optimum Income Taxation. Review of Economic Studies 38, 175–208.
  • Slobodyan, S. and Wouters, R. (2009). Learning in an Estimated DSGE Model. CERGE-EI Working Paper Series 396.
  • JEL Classification. C11, D31, D58, D84, E30, E52, E62, H21.