Next Article in Journal
Correction: Li, Q.; Liang, S.Y. Incipient Fault Diagnosis of Rolling Bearings Based on Impulse-Step Impact Dictionary and Re-Weighted Minimizing Nonconvex Penalty Lq Regular Technique. Entropy 2017, 19, 421
Next Article in Special Issue
Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation
Previous Article in Journal
A Study on Non-Linear DPL Model for Describing Heat Transfer in Skin Tissue during Hyperthermia Treatment
Previous Article in Special Issue
Magnetisation Processes in Geometrically Frustrated Spin Networks with Self-Assembled Cliques
 
 
Article

On the Structure of the World Economy: An Absorbing Markov Chain Approach

1
Faculty of Economics-Prilep, “St. Kliment Ohridski” University, 7000 Bitola, Macedonia
2
Macedonian Academy of Sciences and Arts, 1000 Skopje, Macedonia
3
Faculty of Economics, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
4
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(4), 482; https://doi.org/10.3390/e22040482
Received: 10 March 2020 / Revised: 13 April 2020 / Accepted: 21 April 2020 / Published: 23 April 2020
(This article belongs to the Special Issue Dynamic Processes on Complex Networks)
The expansion of global production networks has raised many important questions about the interdependence among countries and how future changes in the world economy are likely to affect the countries’ positioning in global value chains. We are approaching the structure and lengths of value chains from a completely different perspective than has been available so far. By assigning a random endogenous variable to a network linkage representing the number of intermediate sales/purchases before absorption (final use or value added), the discrete-time absorbing Markov chains proposed here shed new light on the world input/output networks. The variance of this variable can help assess the risk when shaping the chain length and optimize the level of production. Contrary to what might be expected simply on the basis of comparative advantage, the results reveal that both the input and output chains exhibit the same quasi-stationary product distribution. Put differently, the expected proportion of time spent in a state before absorption is invariant to changes of the network type. Finally, the several global metrics proposed here, including the probability distribution of global value added/final output, provide guidance for policy makers when estimating the resilience of world trading system and forecasting the macroeconomic developments. View Full-Text
Keywords: world economy; global production networks; discrete-time absorbing Markov chain; quasi-stationary product distribution; global metrics world economy; global production networks; discrete-time absorbing Markov chain; quasi-stationary product distribution; global metrics
Show Figures

Figure 1

MDPI and ACS Style

Kostoska, O.; Stojkoski, V.; Kocarev, L. On the Structure of the World Economy: An Absorbing Markov Chain Approach. Entropy 2020, 22, 482. https://doi.org/10.3390/e22040482

AMA Style

Kostoska O, Stojkoski V, Kocarev L. On the Structure of the World Economy: An Absorbing Markov Chain Approach. Entropy. 2020; 22(4):482. https://doi.org/10.3390/e22040482

Chicago/Turabian Style

Kostoska, Olivera, Viktor Stojkoski, and Ljupco Kocarev. 2020. "On the Structure of the World Economy: An Absorbing Markov Chain Approach" Entropy 22, no. 4: 482. https://doi.org/10.3390/e22040482

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop