System Dynamics Implementation of a Model of Population and Resource Dynamics with Adaptation

 System Dynamics Implementation of a Model of Population and Resource Dynamics with Adaptation

Abstract

This is a dynamic population model that entails population birth and birth rates. It shows the simulation results of how a constant birth rate in a given economy improves sustainability as measured by indicators such as natural resources stock and per capita income. Still, it is possible when combined with other technological progress. Sensitive scrutiny also shows a probable impediment with an application of exogenous consumer preference, which is assumable in standard economics.

Keywords: Endogenous innovation on input substitutability, population-resource dynamics, Out-of-equilibrium (adaptation), system dynamics, sustainability.

Introduction

This report uses insight maker to simulate the development of a population economic archetypal that is inflexibly grounded on economic theories and the results and justification of the model using a dynamic system method (Anderies, 2013). System proactive approach shows feedback discerning, loop supremacy, and also enchanting an endogenous point of view; furthermore, system design modeling uses methods for drawing a model, that includes; flow diagram, causal loop diagrams, and stock diagrams to envision this system(Brander & Scott, 2014).

Methods

The model shows the population and birth rates. Input available at each period is confined by the current magnitudes of the population (Daly & Joshua, 2010). This simulation shows how the birth rates affect the community; hence when there are more birth rates, the people will increase.

Considering the description of the specifications of the model, each time period representatives make a consumption and production decision with the given size of them;

• population (l)
• birth (s)
• birth rates(k)

This optimization yields the:

• the transition paths how the system changes over time

System design facilitates the analysis of a mixed population by making it simple (Anderies, 2013). It uses two steps( construct a system model whose specification of the feedback loops are founded on an economic concept, and  the model disclose the transitional tracks of the variable by means of adoption)

The figure above shows the population rate and births of a particular economy.

The increase in population is a result of increased food production (Basener & Ross, 2015). hence when there is an increase in birth rates, it means the loop will be positive while the decrease in the population shows negative feedback (Bullard, 2016).

The arrow shows the direction of the casualty; for instance, the rise of the population is a result of an increase in birth rates and a decrease in other factors affecting depopulation.

The above picture shows how time is also a factor affecting the growth of population

Unemployment is also another significant problem in evolving economies. Still, ensuing the typical handling in growth literature, for effortlessness aspects that thwart the SD model from attaining full employment is outside the scope and are excepted from the reports the arithmetical standards implemented for the base model (Basener & Ross, 2015). Exogenous variables for the reference line model are attuned to produce a performance in such a way that the birth rates and the population are, to some extent, stabilized over time, as seen in the picture above.

Conclusion

These demonstrate the benefit of using simulation modeling in ecological economies; hence it is helpful in forecasting and planning a countries budget. It focuses on the examination of the time dynamics, equilibrium conditions, and feedback structures. One should run an extensive assortment of the tests to try the models and upsurge the understanding ultimately. This project aims to determine the paybacks of using the dynamics system process to analyze the population. The benefits include the emphasis on the study of the feedback constructions, reliability in using simulation rather than analytical solutions experiments on the population collapse and for trajectories. This is helpful for the evaluation of long-term goals. Investigations concerning the sensitivity constraints in the population model,  designate the latent for both population downfall and for routes that are more firm and does not lead to collapse.

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References

Anderies, J. M. (2013). Economic development, demographics, and renewable resources: a dynamical systems approach. Environment and Development Economics, 8, 219-246.

Basener, B. & Ross, D. S. (2015). Booming and crashing populations and Easter Island. SIAM, Journal on Applied Mathematics, 65(2), 684-701.

Brander, J. A., & Scott, T. M. (2014). The simple economics of Easter Island: a Ricardo–Malthus model of renewable resource use. American Economic Review, 88 (1), 119–138.

Bullard, J. B. (2016). The learnability criterion and monetary policy. Federal Reserve Bank of St. Louis Review, 203-217.

Daly, H.E. & Joshua, F. (2010). Ecological Economics: Principles and Applications (2nd Ed.). Washington: Island Press.