Showing 1 - 10 of 398
Persistent link: https://www.econbiz.de/10003946106
This paper concentrates on the central link between productivity and knowledge capital, and shifts attention from firms and industries to regions. The objective is to measure knowledge elasticity effects within a regional Cobb-Douglas production function framework, with an emphasis on knowledge...
Persistent link: https://www.econbiz.de/10012706493
The objective of this study is to identify knowledge spillovers that spread across regions in Europe and vary in magnitude for different industries. The study uses a panel of 203 NUTS-2 regions covering the 15 pre-2004 EU-member-states to estimate the impact over the period 1998-2003, and...
Persistent link: https://www.econbiz.de/10014205704
The objective of this study is to identify knowledge spillovers that spread across regions in Europe and vary in magnitude for different industries. The study uses a panel of 203 NUTS-2 regions covering the 15 pre-2004 EU-member-states to estimate the impact over the period 1998-2003, and...
Persistent link: https://www.econbiz.de/10005572343
Persistent link: https://www.econbiz.de/10011310589
Fundamental to regional science is the subject of spatial interaction. GeoComputation - a new research paradigm that represents the convergence of the disciplines of computer science, geographic information science, mathematics and statistics - has brought many scholars back to spatial...
Persistent link: https://www.econbiz.de/10011310907
This paper presents a methodology for neural spatial interaction modelling. Particular emphasis is laid on design, estimation and performance issues in both cases, unconstrained and singly constrained spatial interaction. Families of classical neural network models, but also less classical ones...
Persistent link: https://www.econbiz.de/10011314245
Persistent link: https://www.econbiz.de/10001409908
Parameter estimation is one of the central issues in neural spatial interaction modelling. Current practice is dominated by gradient based local minimization techniques. They find local minima efficiently and work best in unimodal minimization problems, but can get trapped in multimodal...
Persistent link: https://www.econbiz.de/10013153122
This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure,...
Persistent link: https://www.econbiz.de/10014205706