Related Experiment Video
Updated: Jul 20, 2025
08:38
A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
Published on: November 21, 2019
7.7K
Pathways for socio-economic system transitions expressed as a Markov chain
Vanessa Jine Schweizer1,2, Alastair David Jamieson-Lane3,4, Hua Cai5,6
1Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado, United States of America.
Plos One
|July 31, 2023
Summary
This study enhances cross-impact balance (CIB) analysis by using Markov chains to explore all system evolutions. Findings suggest prioritizing economic development alongside education to avoid demographic traps in low-income countries.
Area of Science:
- Socio-economic systems analysis
- System dynamics
- Computational social science
Background:
- Cross-impact balance (CIB) analysis offers a system-theoretical perspective for complex socio-economic systems.
- Existing CIB tools are limited to single-scenario analysis and identifying system attractors.
- There is a need for methods that explore a broader range of system evolutions.
Purpose of the Study:
- To enhance CIB analysis by developing a method that models all possible system evolutions.
- To investigate system dynamics using a Markov chain approach applied to CIB.
- To analyze the demographic transition as a case study for the enhanced CIB method.
Main Methods:
- Developed a novel method to represent CIB scenarios as transitions in a Markov chain.
- Applied the enhanced CIB method to a three-variable demographic transition system (27 scenarios).
- Experimented with four different approaches for constructing CIB Markov chains.
Main Results:
- The Markov chain approach successfully replicated traditional CIB findings for the demographic transition system.
- Analysis revealed insights into system transition pathways, though some information on system attractors might be lost.
- Model results indicate low-income countries risk demographic traps without prioritized economic development and education.
Conclusions:
- The enhanced CIB method provides a more comprehensive view of system evolution by considering all potential pathways.
- Prioritizing economic development alongside educational gains is crucial for low-income countries to escape demographic traps.
- Further research is recommended to validate the methodological findings on more complex systems.
More Related Videos
Related Concept Videos
01:10Entropy Change in Reversible Processes
2.6K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.6K
01:21Path Between Thermodynamics States
3.2K
Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
3.2K
01:19Cyclic Processes And Isolated Systems
2.8K
A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state.
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state.
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
2.8K
01:24BIBO stability of continuous and discrete -time systems
437
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
437
02:31Phase Transitions
19.2K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
19.2K
01:21First Order Systems
122
First-order systems, such as RC circuits, are foundational in understanding dynamic systems due to their straightforward input-output relationship. Analyzing their responses to different input functions under zero initial conditions reveals significant insights into system behavior.
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
122