Non-stationary income processes are standard in quantitative life-cycle models, prompted by the observation that within-cohort income inequality increases with age. This paper generalizes Tauchen (1986) and Rouwenhorst's (1995) discretization methods to non-stationary AR(1) processes. We...

I investigate whether the popular Krusell and Smith algorithm used to solve heterogeneousagent economies with aggregate uncertainty and incomplete markets is likely to be subject to multiple self-fulfilling equilibria. In a benchmark economy, the parameters representing the equilibrium aggregate...

The computational time required to solve and estimate dynamic economic models is one of the main constraints in empirical research. The Endogenous Grid Method (EGM) proposed by Carroll (2006) is known to offer impressive speed gains over more traditional stochastic dynamic programming methods,...

This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and...

This paper introduces a new solution method for Dynamic Stochastic General Equilibrium (DSGE) models that produces non explosive paths. The proposed solution method is as fast as standard perturbation methods and can be easily implemented in existing software packages like Dynare as it is...

As suggested by recent empirical evidence, one of the causes behind the widespread rise of inequality experienced by OECD countries in the last few decades may have been the increased flexibility of labor markets. The authors explore this hypothesis through the analysis of a stock-flow...

M-PRESS-CreditRisk is a new top-down macro stress testing framework that can help supervisors gauge banks' capital adequacy related to credit risk. For the first time, it combines calibration of microprudential capital requirements and macroprudential buffers in a unified, coherent framework....

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...

In Monte Carlo simulation, Latin hypercube sampling (LHS) [McKay et al. (1979)] is a well-known variance reduction technique for vectors of independent random variables. The method presented here, Latin hypercube sampling with dependence (LHSD), extends LHS to vectors of dependent random...