We present several fast algorithms for computing the distribution of a sum of spatially dependent, discrete random variables to aggregate catastrophe risk. The algorithms are based on direct and hierarchical copula trees. Computing speed comes from the fact that loss aggregation at branching...

Modern systems of official statistics require the estimation and publication of business statistics for disaggregated domains, for example, industry domains and geographical regions. Outlier robust methods have proven to be useful for small area estimation. Recently proposed outlier robust...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

Rainfall is a truly exogeneous variable and hence popular as an instrument for many outcomes. But by its very nature, rainfall in nearby areas tends to be correlated. I show theoretically that if there are also spatial trends in outcomes of interest, this may create spurious correlation. In...

A large literature exploits geographic variation in the concentration of immigrants to identify their impact on a variety of outcomes. To address the endogeneity of immigrants' location choices, the most commonly-used instrument interacts national inflows by country of origin with immigrants'...

Necessary and sufficient conditions for the equality of ordinary least squares and generalized least squares estimators in the linear regression model with firstorder spatial error processes are given.

Bounds for the efficiency of ordinary least squares relative to generalized least squares estimator in the linear regression model with first order spatial error process are given.

Conditions for the consistency of the estimator s2 of the variance of the disturbance a2u under first-order spatial error processes are given.

A model is considered in which optimal search intensity is a result of a trade off between short run losses due to higher search costs (more interviews, commuting...) and long-run gains due to a higher chance of finding a job. We show that this optimal search intensity is higher in areas...

This study estimates the impact of the non-aesthetic view and odor caused by Preemraff, a refinery on the Swedish west coast, on house values in the surrounding area. To carry out the analysis a spatial hedonic house price model was applied to transaction data for the period 1994 - 1996,...