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.

Modeling the growth effects of regional knowledge production: The GMR-Europe model and its applications for EU Framework Program policy impact simulations

This paper introduces the Geographic Macro and Regional (GMR) model for NUTS-2 regions of the Euro zone. This model consists of three blocks: the TFP, the SCGE and the MACRO blocks. The model is built for impact analysis of policies targeting intangible assets in the forms of R&D, human capital and social capital. The analysis can be done both at the regional and the EU macroeconomic levels. Policy simulations on the growth impacts of the 6th European Framework Program illustrate the capabilities of the complex model system.

The economic impact of the Budapest Airport on the local economy

Airports have an unquestionably dominant role in the transport of the 21st century; air transport is the heart of the modern, globalised economy. Beyond this primary function, the international literature also emphasises the considerable economic and economy development effects of airports. The significant airports of the world not only facilitate the local economy but fundamentally determine that. The aim of the analysis is not only the study of the economic impact of the Budapest Ferihegy International Airport, but also examining the economic impact of the complex system of the companies operating at the airport and complementing each other. First of all, we discuss the methods and concepts to be applied in the analysis of the economic impact of the Budapest Airport. Although the methods and the terminology is fairly uniform in the course of the general review studies, the actual pieces of research can mean something different by the same concepts or they may examine the same thing with different concepts.

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.

Quantifying rate dependence of hysteretic systems

Hysteresis nonlinearities are formally defined as deterministic, rate-independent operators for a great variety of systems. Rate independence frequently occurs in problems in which the time scales of interest are much longer than the intrinsic time scales of the system. In this paper we propose a measure of rate dependence and numerically evaluate the corresponding metric for two rate-dependent systems, namely, a linearly viscous damper and a class of shape memory materials exhibiting thermomechanical behavior [1]. The rate-independent extended Bouc-Wen model of hysteresis [2] is used to validate the robustness of our rate-independence criterion. On the other hand, the shown rate dependence in shape memory materials working in nonisothermal conditions is associated with the ensuing thermomechanical coupling

Inter-hemispheric integration of tactile-motor responses across body parts

In simple detection tasks, reaction times are faster when stimuli are presented to the visual field or side of the body ipsilateral to the body part used to respond. This advantage, the crossed-uncrossed difference (CUD), is thought to reflect inter-hemispheric interactions needed for sensorimotor information to be integrated between the two cerebral hemispheres. However, it is unknown whether the tactile CUD is invariant when different body parts are stimulated. The most likely structure mediating such processing is thought to be the corpus callosum (CC). Neurophysiological studies have shown that there are denser callosal connections between regions that represent proximal parts of the body near the body midline and more sparse connections for regions representing distal extremities. Therefore, if the information transfer between the two hemispheres is affected by the density of callosal connections, stimuli presented on more distal regions of the body should produce a greater CUD compared to stimuli presented on more proximal regions. This is because interhemispheric transfer of information from regions with sparse callosal connections will be less efficient, and hence slower. Here, we investigated whether the CUD is modulated as a function of the different body parts stimulated by presenting tactile stimuli unpredictably on body parts at different distances from the body midline (i.e., Middle Finger, Forearm, or Forehead of each side of the body). Participants detected the stimulus and responded as fast as possible using either their left or right foot. Results showed that the magnitude of the CUD was larger on the finger (~2.6 ms) and forearm (~1.8 ms) than on the forehead (~-0.9 ms). This result suggests that the interhemispheric transfer of tactile stimuli varies as a function of the strength of callosal connections of the body parts

Collective behavior of interacting self-propelled particles

Abstract We discuss biologically inspired, inherently non-equilibrium models of self-propelled particles, in which the particles interact with their neighbors by choosing at each time step the local average direction of motion. We summarize some of the results of large-scale simulations and theoretical approaches about the e ects of noise and dimensionality on the scaling behavior of such systems

Tax Rate Cuts and Tax Compliance

The paper shows how tax rate cuts can increase revenues by improving tax compliance. The intuition is that tax evasion has externalities: tax evaders protect each other, because they tie down limited enforcement capacity. Thus, relatively small tax rate cuts, which decrease incentives to evade taxes, can lead to increased revenues through spillovers - creating Laffer effects. Interestingly, tax rate cuts here imply increasing effective taxes. The model is consistent with what happened in Russia, and may provide basis for further thinking about tax rate cuts in other countries.Tax revenues;Taxes;tax authority, tax evasion, tax compliance, tax rate cuts, tax evaders, tax rates, tax reform, tax enforcement, tax cuts, tax authorities, tax changes, flat tax, tax avoidance, tax collection, tax base, personal income tax, tax policy, tax rate changes, tax experiment, behavior of taxpayers, tax audits, tax audit, personal income tax rate, effective tax rates, higher income, tax increases, taxable income, tax burden, flat taxes, tax reforms, public finance, tax payments, international tax, tax countries, government spending, budget constraint, increase in tax revenues, tax revenue, fixed government expenditure, marginal tax rates, taxation, income effect, government expenditure, federal tax, internal revenue, income shifting, high tax rates, taxpayer compliance