In the presence of heteroskedasticity, conventional test statistics based on the ordinary least square estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of...

The conventional model of immigrant earnings does not account for the correlation of outcomes across immigrant ethnic networks. We apply a spatial autoregressive network approach to account for the spill-over effects of migrant ethnic group economic resources and labour market outcomes. We...

In the spatial econometrics literature, spatial error dependence is characterized by spatial autoregressive processes, which relate every observation in the cross-section to any other with distance-decaying intensity: i.e., dependence obeys Tobler's First Law of Geography ('everything is related...

The present paper examines the effect of entrepreneurship capital and spatial productivity spillovers on Greek regional labour productivity during Greek financial crisis. A spatial autoregressive (SAR) dynamic panel data model using the robust Blundell and Bond GMM estimator suggests that...

This paper suggests an improved GMM estimator for the autoregressive parameter of a spatial autoregressive error model by taking into account that unobservable regression disturbances are different from observable regression residuals. Although this difference decreases in large samples, it is...

We introduce a new estimation framework which extends the Generalized Method of Moments (GMM) to settings where a subset of the parameters vary over time with unknown dynamics. To filter out the dynamic path of the time-varying parameter, we approximate the dynamics by an autoregressive process...

In social interaction models, the identification of the network effect is based on either group size variation, structure of the network or the relative position in the network measured by the Bonacich centrality measure. These identification strategies imply the use of many instruments or...