Skewness and Time-Varying Second Moments in a Nonlinear Production Network: Theory and Evidence

10.3386/w29499 ◽

2021 ◽

Author(s):

Ian Dew-Becker ◽

Alireza Tahbaz-Salehi ◽

Andrea Vedolin

Keyword(s):

Network Theory ◽

Time Varying ◽

Production Network ◽

Second Moments

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From the Difference of Structures to the Structure of the Difference

Complexity ◽

10.1155/2018/4326097 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Massimiliano Zanin ◽

Ernestina Menasalvas ◽

Xiaoqian Sun ◽

Sebastian Wandelt

Keyword(s):

Complex System ◽

Network Theory ◽

General Framework ◽

Random Noise ◽

Time Varying ◽

Evolving Systems ◽

Multiple Networks ◽

Stochastic Fluctuations ◽

Multidimensional Complex ◽

The Difference

When dealing with evolving or multidimensional complex systems, network theory provides us with elegant ways of describing their constituting components, through, respectively, time-varying and multilayer complex networks. Nevertheless, the analysis of how these components are related is still an open problem. We here propose a general framework for analysing the evolution of a (complex) system, by describing the structure created by the difference between multiple networks by means of the Information Content metric. Differently from other approaches, which focus on assessing the magnitude of the change, the proposed one allows understanding if the observed changes are due to random noise or to structural (targeted) modifications; in other words, it allows describing the nature of the force driving the changes and discriminating between stochastic fluctuations and intentional modifications. We validate the framework by means of sets of synthetic networks, as well as networks representing real technological, social, and biological evolving systems. We further propose a way of reconstructing network correlograms, which allow converting the system’s evolution to the frequency domain.

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Glokalisierung und Feminisierung: Zur strukturellen Krise von Lohnarbeit im europäischen Raum

Geographica Helvetica ◽

10.5194/gh-76-261-2021 ◽

2021 ◽

Vol 76 (2) ◽

pp. 261-273

Author(s):

Stefanie Hürtgen

Keyword(s):

Economic Integration ◽

Network Theory ◽

Feminist Geography ◽

Production Network ◽

Spatial Form ◽

Social Fragmentation ◽

Labour Process ◽

Production Regime ◽

The One ◽

European Production

Abstract. The article discusses the glocalized socio-spatial form of European production as socially crisis-ridden. Combining literature from transnational production network theory, critical political economy, labour process theory and feminist geography the article shows that a European production regime has developed which is based on the transnationalization of economic and competitive parameters on the one hand and multiscalar social fragmentation of labour processes on the other. Its very logic is, hence, functional economic integration based on labour's socio-spatial disintegration. The regime pushes for what we can call the feminization of work because it systematically cuts the former, patriarchal and uneven connection between waged work and socio-political integration. As feminist debates show, progressive perspectives have to be transnational and multiscalar and they have to include fundamental questions about the concept and status of work in society.

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Time Varying Behavior of Share Returns in Australia: 1988–2004

Review of Pacific Basin Financial Markets and Policies ◽

10.1142/s0219091516500041 ◽

2016 ◽

Vol 19 (01) ◽

pp. 1650004

Author(s):

Yew-Choe Lum ◽

Sardar M. N. Islam

Keyword(s):

Stock Returns ◽

Future Research ◽

Practical Reasons ◽

Time Varying ◽

Asymmetric Effect ◽

Conditional Capm ◽

Conditional Mean ◽

Second Moments ◽

Statistical Sense ◽

Capm Model

The model in this paper is similar to Brailsford and Faff (1997), using a conditional CAPM model with the GARCH-M framework, but with a significant additional dummy term (in the conditional mean of the share return) that will help explain the models better in both economic and statistical sense. The relatively simpler asymmetric model in this paper is compatible to other more complex asymmetric models and hence should be easier to model and explain for practical purposes. The model in this paper is also a more effective model, in both economical and statistical terms, as compared to some other models in the GARCH family as it captures the asymmetric effect in the modeling process in both the conditional first and second moments. The findings in this paper have contributed in re-evaluating the nature and process of time varying behavior of time series of stock returns and will provide researchers and practitioners additional options and incentives to explore for future research. We have also provided statistical and practical reasons to support these findings.

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