Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

In this paper we compare the in-sample fit and out-of-sample forecasting performance of no-arbitrage quadratic and essentially affine term structure models, as well as the dynamic Nelson-Siegel model. In total eleven model variants are evaluated, comprising five quadratic, four affine and two...

Capital-labor substitution and total factor productivity (TFP) estimates are essential features of growth and income distribution models. In the context of a Monte Carlo exercise embodying balanced and near balanced growth, we demonstrate that the estimation of the substitution elasticity can be...

The paper presents an analysis of the trade-offs of participants of different type between payment delay and liquidity requirement on the basis of synthetically generated data. The generation of the synthetic transaction data set for a simple RTGS system is described and calibrated using real...

This note is concerned with two recent agent-based models of speculative dynamics from the literature, one by Gaunersdorfer and Hommes and the other by He and Li. At short as well as long lags, both of them display an autocorrelation structure in absolute and squared returns that comes...

This paper provides high-dimensional and flexible importance sampling procedures for the likelihood evaluation of dynamic latent variable models involving finite or infinite mixtures leading to possibly heavy tailed and/or multi-modal target densities. Our approach is based upon the efficient...

We build a dynamic factor model with time-varying parameters and stochastic volatility and use it to decompose the variance of a large set of financial and macroeconomic variables for 22 OECD countries spanning from 1960 onwards into contributions from country-specific uncertainty,...

We determine optimal monetary policy under commitment in a forwardlooking New Keynesian model when nominal interest rates are bounded below by zero. The lower bound represents an occasionally binding constraint that causes the model and optimal policy to be nonlinear. A calibration to the U.S....

We determine optimal discretionary monetary policy in a New-Keynesian model when nominal interest rates are bounded below by zero. Nominal interest rates should be lowered faster in response to adverse shocks than in the case without bound. Such ‘preemptive easing’ is optimal because...

We show how to use a simple perturbation method to solve non-linear rational expectation models. Drawing from the applied mathematics literature we propose a method consisting of series expansions of the non-linear system around a known solution. The variables are represented in terms of their...