We consider a spatial econometric model containing a spatial lag in the dependent variable and the disturbance term with an unknown form of heteroskedasticity in innovations. We first prove that the maximum likelihood (ML) estimator for spatial autoregressive models is generally inconsistent...

In this study, we propose simple test statistics for identifying the source of spatial dependence in spatial autoregressive models with endogenous weights matrices. Elements of the weights matrices are modelled in such a way that endogenity arises when the unobserved factors that affect elements...

We analyze the role of food insurance on the housing markets of coastal cities. To do so we have assembled a parcel-level dataset including the universe of residential sales for three coastal urban areas in the United States – Miami-Dade county (2008-2015), New York city (2003-2016), and...

In this study, we propose a spatial stochastic volatility model in which the latent log-volatility terms follow a spatial autoregressive process. Though there is no spatial correlation in the outcome equation (the mean equation), the spatial autoregressive process defined for the log-volatility...

Are coastal cities adjusting to rising sea levels? This paper argues that large-scale events have the potential to ignite the process. We examine the effects of hurricane Sandy on the New York City housing market. We assemble a large plot-level dataset with rich geographic data on housing sales...