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September 26, 2017

SMOOTHIES: A Toolbox for the Exact Nonlinear and Non-Gaussian Kalman Smoother

In this paper, I present a new toolbox that implements the exact nonlinear and non-Gaussian Kalman smoother for a wide class of discrete-time state space models, including models with implicit functions and equality constraints.

September 26, 2017

Exact Nonlinear and Non-Gaussian Kalman Smoother for State Space Models with Implicit Functions and Equality Constraints

In this paper, I present a novel implementation of the exact nonlinear and non-Gaussian Kalman smoother that can also deal with implicit functions in the measurement and/or state equations as well as equality constraints.

September 9, 2016

The Impact of Uncertainty Shocks: Continental Europe versus the Anglo-Saxon World

For economic forecasting it is important to know how the real economy responds to major events such as the fall of the Soviet Union, the Greek debt crisis, the recent terrorism attacks in Europe, and the Brexit.

November 2, 2015

An estimated DSGE model for the Netherlands with unemployment

The Lucas critique is an important problem for economic policy analysis.

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February 24, 2015

Technical background document for BVAR models used at CPB

At CPB, we have developed two Bayesian vector autoregressive (VAR) models, one for the Dutch economy and one for the world trade.

No title
August 20, 2014

Onzekerheidsvarianten bij verdere escalatie Oekraïne-conflict

Een inschatting door het CPB van de macro-economische gevolgen van een verdere politieke en militaire escalatie van de situatie in Oekraïne.

No title
March 25, 2014

Time variation in the dynamic effects of unanticipated changes in tax policy

Using a structural vector autoregression with time-varying parameters, I analyze to what extent the dynamic effects of unanticipated changes in tax policy have changed structurally over the post World War II period in the United States.

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March 25, 2014

Reduced-rank time-varying vector autoregressions

The standard time-varying VAR workhorse suffers from overparameterization, which is a serious problem as it limits the number of variables and lags that can be incorporated in the model.

No title