One important goal of this study is to develop a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first...

In this paper we specify a linear Cliff and Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate a multi-step...

The inefficiency of health care provision presents a major health policy concern in Germany. In order to address the issue of efficiency comprehensively - i.e. at the level of the entire system of health care provision rather than individual service providers - empirical analyses are often based...

We propose two simple diagnostic tests for spatial error autocorrelation and spatial lag dependence. The idea is to reformulate the testing problem such that the test statistics are asymptotically equivalent to the familiar LM test statistics. Speci cally, our version of the test is based on a...

In this paper, we make multi-step forecasts of the annual growth rates of the real GRP for each of the 31 Chinese provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence between the GRP growth rates. In addition, the...

In analyzing the disparities of the regional developments in the volume of employment in Germany, in the recent empirical literature so called shift-share-regression-models are frequently applied. However, these models usually neglect spatial interdependencies, even though such interdependencies...