Growing evidence suggests that many social and economic networks are scale free in that their degree distribution has a power-law tail. A common explanation for this phenomenon is a random network formation process with preferential attachment. For a general version of such a process, we develop...

Growing evidence suggests that many social and economic networks are scale free in that their degree distribution P(d) is approximately proportional to d^{-γ}. The most widespread explanation for this phenomenon is a random network formation process with preferential attachment. For a general...

We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...

We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...

Estimation of agent-based models is currently an intense area of research. Recent contributions have to a large extent resorted to simulation-based methods mostly using some form of simulated method of moments estimation (SMM). There is, however, an entire branch of statistical methods that...

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning a MCMC sampling...

We point out that the simple slice sampler generates chains that are correlation-free when the target distribution is centrally symmetric. This property explains several results in the literature about the relative performance of the simple and product slice samplers. We exploit it to improve...

This study focuses on the role of heterogeneity in network peer effects by accounting for network-specific factors and different driving mechanisms of peer behavior. We propose a novel Multivariate Instrumental Variable (MVIV) estimator which is consistent for a large number of networks keeping...