Data analysis using circular causality in networks

Complex systems in causal relationships are known to be circular rather than linear; this means that a particular result is not produced by a single cause, but rather that both positive and negative feedback processes are involved. However, although interpreting systemic interrelationships requires a language formed by circles, this has only been developed at the diagram level, and not from an axiomatic point of view. The first difficulty encountered when analysing any complex system is that usually the only data available relate to the various variables, so the first objective was to transform these data into cause-and-effect relationships. Once this initial step was taken, our discrete chaos theory could be applied by finding the causal circles that will form part of the system attractor and allow their behavior to be interpreted. As an application of the technique presented, we analyzed the system associated with the transcription factors of inflammatory diseases.

A Sociocybernetics Data Analysis Using Causality in Tourism Networks

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Does the Common Agricultural Policy Reduce Farm Labour Migration? Panel data analysis across EU regions. Factor Markets Working Paper No. 28, July 2012

This paper deals with the determinants of labour out-migration from agriculture across 149 EU regions over the 1990–2008 period. The central aim is to shed light on the role played by payments from the common agricultural policy (CAP) on this important adjustment process. Using static and dynamic panel data estimators, we show that standard neoclassical drivers, like relative income and the relative labour share, represent significant determinants of the intersectoral migration of agricultural labour. Overall, CAP payments contributed significantly to job creation in agriculture, although the magnitude of the economic effect was rather moderate. We also find that pillar I subsidies exerted an effect approximately two times greater than that of pillar II payments.

National Center for Statistics and Analysis collected technical studies. Volume I: accident data analysis of vehicle crashworthiness - ten papers.

Mode of access: Internet.

Prototype tidal data analysis for Mississippi Sound and adjacent areas /

This is a photocopy reproduction.

State inspection program evaluation and data analysis: data base E SPSS frequencies tabulations for brake components and explanatory variables. Volume III. Final report.

National Highway Traffic Safety Administration, Office of Vehicle Safety Research, Washington, D.C.

An analysis of mopeds as a potential safety problem in the United States. Volume II: data analysis and usage and accident projections. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Light truck characteristics, historical data base. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Lake data analysis and nutrient budget modeling /

Mode of access: Internet.

Improving pavements with Long-Term Pavement Performance : products for today and tomorrow : winning papers from the 2001-2002 International Contest on Long-Term Pavement Performance Data Analysis /

"HRDI-13/11-05(1M)E"--P. [4] of cover.

Budget baselines, historical data, and alternatives for the future.

"January 1993."

Data analysis of tractor-trailer drivers to access drivers' perception of heavy duty truck ride quality. Final report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Research, Washington, D.C.

Automobile characteristics historical data base. Final report.

Transportation Systems Center, Cambridge, Mass.

Zero base review of FMCSRs. Volume II: data analysis. Final report.

Federal Highway Administration, Washington, D.C.

Accident data analysis of side-impact, fixed-object collisions. Final report.

Federal Highway Administration, Washington, D.C.