We show how to speed up Sequential Monte Carlo (SMC) for Bayesian inference in large data problems by data subsampling. SMC sequentially updates a cloud of particles through a sequence of distributions, beginning with a distribution that is easy to sample from such as the prior and ending with...

Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with proposed parameter draws obtained by iterating on a discretized version of the Hamiltonian dynamics. The iterations make HMC computationally costly, especially in problems with large datasets,...

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important...

Time series subject to parameter shifts of random magnitude and timing are commonly modeled with a change-point approach using Chib's (1998) algorithm to draw the break dates. We outline some advantages of an alternative approach in which breaks come through mixture distributions in state...

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation....

This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models such as Generalized Autoregressive Conditional...

Stock returns are considered as a convolution of two random processes that are the return innovation and the volatility innovation. The correlation of these two processes tends to be negative which is the so-called leverage effect. In this study, we propose a dynamic leverage stochastic...

We propose a theoretical framework for analyzing the problems associated to unilateral immigration policy in receiving countries and for evaluating the grounds for reform of international institutions governing immigration. We build a model with multiple destination countries and show that...

This paper studies the relationship between export policy and food prices. We show that, when individuals are loss averse, food exporters may use trade policy to shield the domestic economy from large price shocks. This creates a complementarity between the price of food in international markets...

We study immigration policy in a small receiving economy under self-selection of migrants. We show that a non-discriminatory immigration policy choice affects and is affected by the migratory decisions of skilled and unskilled foreign workers. From this interaction multiple equilibria may arise,...