They are not well-behaved. The main problem is that one cannot control the radius of convergence when using perturbation techniques. Just outside the radius of convergence, higher-order approximations can easily behave extremely badly, and even within the radius of convergence one can expect...

Users of regular higher-order perturbation approximations can face two problems: policy functions with odd oscillations and simulated data that explode. We propose a perturbation-based approximation that (i) does not have odd shapes, (ii) generates stable time paths, and (iii) avoids the...

Using a country-industry panel dataset (EUKLEMS) we uncover a robust empirical regularity, namely that high-risk innovative sectors are relatively smaller in countries with strict employment protection legislation (EPL). To understand the mechanism, we develop a two-sector matching model where...

Using a country-industry panel dataset (EUKLEMS) we uncover a robust empirical regularity, namely that high-risk innovative sectors are relatively smaller in countries with strict employment protection legislation (EPL). To understand the mechanism, we develop a two-sector matching model where...

We show empirically that high-risk innovative sectors are relatively small in countries with strict employment protection legislation (EPL). To understand the mechanism, we develop a two-sector matching model where firms endogenously choose between safe and risky technology. Simulations with our...

We construct a new-Keynesian DSGE model tailored to the Netherlands and interpret it as a multivariate unobserved components model. We identify three major stochastic trends in the data — trends in general - purpose technology, investment-specific technology, and labor supply — and model...