As the COVID-19 pandemic has progressed in the US,“hotspots” have been shifting
geographically over time to suburban and rural counties showing a high prevalence of the …

Planning the use of non-renewable energy resources is a crucial issue for social and
environmental development, both at global and local scales. Although fossil fuel depletion is …

Spatial auto-regressive (SAR) models are widely used in geosciences for data analysis;
their main feature is the presence of weight (W) matrices, which define the neighboring …

This paper proposes estimating higher-order spatial autoregressions with spatial
autoregressive errors and heteroskedastic error innovations without searching for …

Solar photovoltaic (PV) has established itself as a fairly promising, fast-growing renewable
energy source. The main determinants of solar PV deployment are thought to be physical …

This paper proposes estimating linear dynamic panels by explicitly exploiting the
endogeneity of lagged dependent variables and expressing the crossmoments between the …

This paper proposes estimating parameters in higher-order spatial autoregressive models,
where the error term also follows a spatial autoregression and its innovations are …

This paper proposes a new estimation procedure for the first-order spatial autoregressive
(SAR) model, where the disturbance term also follows a first-order autoregression and its …

As the COVID-19 pandemic progressed in the USA,'hotspots' shifted geographically over
time to suburban and rural counties showing a high prevalence of the disease. We analyse …

This paper proposes two models that incorporate both heterogeneity and multiple sources of
spatial correlation for dynamic panels. One uses convex combinations of them to form a …