This volume focuses on econometric models that confront estimation and inference issues occurring when sample data exhibit spatial or spatiotemporal dependence. This can arise when decisions or transactions of economic agents are related to the behaviour of nearby agents. Dependence of one...

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

County-level estimates of employment, unemployment, and the unemployment rate are not produced directly from a sample survey; rather, they are developed through models that use information on the labor force from a number of statistical programs such as the CPS (Current Population Survey), CES...

Advances in Econometrics is a research annual whose editorial policy is to publish original research articles that contain enough details so that economists and econometricians who are not experts in the topics will find them accessible and useful in their research. Volume 37 exemplifies this...

Front Cover -- Spatial Econometrics: Qualitative and Limited Dependent Variables -- Copyright Page -- Contents -- List of Contributors -- Part I: Introduction -- Progress in Spatial Modeling of Discrete and Continuous Dependent Variables -- Part II: Discrete Dependent Variables - Maximum...

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

<title>Abstract</title> Spatial filtering in various forms has become a popular way to address spatial dependence in statistical models (Griffith, 2003; Tiefelsdorf & Griffith, 2007). However, spatial filtering faces computational challenges for large <italic>n</italic> as the current method requires order of n-super-3 operations....