This paper presents a method to improve existing spatial dependence-robust inference procedures for spatial data. Our method involves augmenting a regression specification with functions of locations that reduce spatial correlation in regression scores and serves as a pre-whitener, followed by...

We explore the application of integrated nested Laplace approximations for the Bayesian estimation of stochastic volatility models characterized by long memory. The logarithmic variance persistence in these models is represented by a Fractional Gaussian Noise process, which we approximate as a...

Small area poverty estimates are important for social and economic policy, however the required data are often unavailable. This paper presents a Small Area Estimation (SAE) technique called Conditional Monte Carlo (CMC). CMC provides robust estimates of small area poverty rates, subject to...