Parameter spaces for stationary DGPs in spatial econometric modelling

Unlike the time series literature the spatial econometric literature has not really dealt with the issue of the parameter space. This paper shows that current parameter space concepts for spatial econometric DGPs are inadequate. It proves that the parameter space proposed by Kelejian and Prucha 2008 can result in nonstationary DGPs, while the parameter space proposed by Lee and Liu 2010 can be too restrictive in applied cases. Furthermore it is discussed that the practice of row standardizing lacks a mathematical foundation. Due to these problems concerning the current parameter space consepts, this paper provides a new de…nition for the spatial econometric parameter space. It is able to show which assumptions are necessary to give row standardizing the needed mathematical foundation. Finally two additional applications for the new parameter space de…nition concerning models with group interaction and panels with fixed cross section sample size are provided. Both applications result in parameter spaces that are substantially larger than the ones the literature would so far considered to be stationary.

Enumeration of generalized polyominoes

As a generalization of polyominoes we consider edge-to-edge connected nonoverlapping unions of regular $k$-gons. For $n\le 4$ we determine formulas for the number $a_k(n)$ of generalized polyominoes consisting of $n$ regular $k$-gons. Additionally we give a table of the numbers $a_k(n)$ for small $k$ and $n$ obtained by computer enumeration. We finish with some open problems for $k$-polyominoes.Comment: 10 pages, 6 figures, 3 table

Agent Teams and Evolutionary Computation: Optimizing Semi- Parametric Spatial Autoregressive Models

Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be used to address this issue. Therefore an advanced semi- parametric modelling approach for spatial autoregressive models is introduced. Advanced semi-parametric modelling requires determining the best configuration of independent variable vectors, number of spline-knots and their positions. To solve this combinatorial optimization problem an asynchronous multi-agent system based on genetic-algorithms is utilized. Three teams of agents work each on a subset of the problem and cooperate through sharing their most optimal solutions. Through this system more complex relationships between the dependent and independent variables can be derived. These could be better suited for the possibly non-linear real-world problems faced by applied spatial econometricians.

A spatial panel data version of the knowledge capital model

This paper attempts to analyze the impact of knowledge and knowledge spillovers on regional total factor productivity (TFP) in Europe. Regional patent stocks are used as a proxy for knowledge, and TFP is measured in terms of a superlative index. We follow Fischer et. al (2008) by using a spatial-spillover model and a data set covering 203 regions for six time periods. In order to estimate the impact of knowledge stocks we use a spatial autoregressive model with random effects, which allows for three kinds of spatial dependence: Spatial correlation in the innovations, the exogenous and the endogenous variables. The results suggest that there is a significant positive impact of knowledge on regional TFP levels, and that knowledge spills over to neighboring regions. These spillovers decay exponentially with distance at a rate of 8%. Using Monte Carlo simulations we calculate the distribution of direct and indirect effects. The average elasticity of a region's TFP with respect to its own knowledge stock is 0.2 and highly significant. The average effect of all other regions' TFP is about 50% higher, which confirms that the cross-country externalities are important in the measuring of the impact.

RANGE NESTING: A FAST METHOD TO EVALUATE QUANTIFIED QUERIES

Database queries explicitly containing existential and universal quantification become increasingly important in a number of areas such as integrity checking, interaction of databases, and statistical databases. Using a concept of range nesting in relational calculus expressions, the paper describes evaluation algorithms and transformation methods for an important class of quantified relational calculus queries called perfect expressions. This class includes well-known classes of "easy" queries such as tree queries (with free and existentially quantified variables only), and complacent (disconnected) queries.Information Systems Working Papers Serie

Augmented reality supported work instructions for onsite facility maintenance

During the operation and maintenance phase of buildings operators need to perform on site maintenance activities to prevent functional failures of technical equipment. As this phase is the longest and most expensive one respective improvements can significantly reduce the overall lifecycle budget. Based on their previous work, in this paper the authors present an Augmented Reality (AR) based concept and implementation to support mobile and onsite maintenance activities by (1) preparing and generating AR work order instructions based on Product Lifecycle Management (PLM) information, (2) using these to aid the actual onsite maintenance job using hybrid 3D tracking, and (3) creating enhanced and context-related maintenance service reports to be fed back to the PLM system. Preliminary results reveal the potential of the proposed solution, but also leave room for future improvements

Of cells and cities: a comparative Econometric and Cellular Automata approach to Urban Growth Modeling

This paper presents a comparative assessment of two distinct urban growth modeling approaches. The first urban model uses a traditional Cellular Automata methodology, based on Markov transition chains to prospect probabilities of future urban change. Drawing forth from non-linear cell dynamics, a multi-criteria evaluation of known variables prospects the weights of variables related to urban planning (road net- works, slope and proximity to urban areas). The latter model, frames a novel approach to urban growth modeling using a linear Logit model (LLM) which can account for region specific variables and path depen- dency of urban growth. Hence, the drivers and constraints for both models are used similarly and the same study area is assessed. Both models are projected in the segment of Faro-Olh ̃ao for 2006 and a comparative assessment to ground truth is held. The calculation of Cohenââ¬â¢s Kappa for both projections in 2006 allows for an assessmentof both models. This instrumental approach illuminates the differ- ences between the traditional model and the new type of urban growth model which is used. Both models behave quite differently: While the Markov Cellular Automata model brings an over classification of ur- ban growth, the LLM responds in the underestimation of urban sprawl for the same period. Both excelled with a Kappa calculation of over 89%, and showed to have fairly good estimations for the study area. One may conclude that the Markov CA Model permits a riper un- derstanding of urban growth, but fails to analyze urban sprawl. The LLM model shares interesting results within the possibility of identi- fying urban sprawl patterns, and is therefore an interesting solution for some locations. Another advantage of the LLM is directly linked to the possibility of establishing probability for urban growth. Thus, while the traditional methodology shared better results, LLM can be also an interesting estimate for urban patterns from an econometric perspective. Hence further research is needed in exploring the utility of spatial econometric approaches to urban growth.

Modulation of the Work Function by the Atomic Structure of Strong Organic Electron Acceptors on H-Si(111)

Advances in hybrid organic/inorganic architectures for optoelectronics can be achieved by understanding how the atomic and electronic degrees of freedom cooperate or compete to yield the desired functional properties. Here we show how work-function changes are modulated by the structure of the organic components in model hybrid systems. We consider two cyano-quinodimethane derivatives (F4-TCNQ and F6-TCNNQ), which are strong electron-acceptor molecules, adsorbed on H-Si(111). From systematic structure searches employing range-separated hybrid HSE06 functional including many body van der Waals contributions, we predict that despite their similar composition, these molecules adsorb with significantly different densely-packed geometries in the first layer, due to strong intermolecular interaction. F6-TCNNQ shows a much stronger intralayer interaction (primarily due to van der Waals contributions) than F4-TCNQ in multilayered structures. The densely-packed geometries induce a large interface-charge rearrangement that result in a work-function increase of 1.11 and 1.76 eV for F4-TCNQ and F6-TCNNQ, respectively. Nuclear fluctuations at room temperature produce a wide distribution of work-function values, well modeled by a normal distribution with {\sigma}=0.17 eV. We corroborate our findings with experimental evidence of pronounced island formation for F6-TCNNQ on H-Si(111) and with the agreement of trends between predicted and measured work-function changes