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...

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...

This publication's aim is to celebrate the 100th issue of Statistics in Transition new series and the 30th anniversary of the launch of the journal. The book features several 'special issues' of Statistics in Transition new series focusing on specific topics of current research interest released...

We introduce a new methodology to detect and measure economic activity using geospatial data and apply it to steel production, a major industrial pollution source worldwide. Combining plant output data with geospatial data, such as ambient air pollutants, nighttime lights, and temperature, we...