A Stochastic Model for Population and Well-Being Dynamics

Abstract

This article presents a stochastic dynamic model to study the demographic evolution per sexes and the corresponding well-being of a general human population. The main model variables are population per sexes and well-being. The considered well-being variable is the Gender-Related Development Index (GDI), a United Nations index. The model's objectives are to improve future well-being and to reach a stable population in a country. The application case consists of adapting, validating, and using the model for Spain in the 2000-2006 period. Some instance strategies have been tested in different scenarios for the 2006-2015 period to meet these objectives by calculating the reliability of the results. The optimal strategy is ''government invests more in education and maintains the present health investment tendency.''

Simulating Demography and Human Development Dynamics

“…Thus, the alternative considered to describe cycles is a cosine pattern. This pattern has also been used in a similar context by Sanz et al (2014) for some input variables depending on time. Thus, a line tendency (an increasing or decreasing trend) plus a cosine pattern (cycle) has been considered in the present study.…”

“…The authors propose a deterministic human population model (no genders and ages are considered), in which birth and death rates depend on the former HDI. A second precedent is presented by Sanz et al (2014). They consider the gender-structured human population stochastic dynamics related with the GDI.…”

“…The double formulation is applied to the validation process (Spain in the 2003-2008 period and Belgium in the 2001-2008 period), providing a high model reliability in order to simulate the future (Caselles 1992a;Sanz et al 2014).…”

An application of fuzzy cognitive maps to improve well‐being, sustainability and the globalization process

“…In order to obtain early useful partial results, the degree of detail of the model would be the minimum to serve the proposed objectives; disaggregation and validation would be made step by step. For instance, it seems natural to begin with an aggregated demographic model related with a well‐being index (the Human Development Index of the UN) (Caselles et al ., ); next, it could proceed to disaggregate population per ages in this model (Micó et al ., ); next to disaggregate population per ages and sexes (Micó et al ., ); previous models are deterministic and, next, it may proceed to make them stochastic and try to use them to find adequate strategies to stabilize population (Sanz et al ., ); next, it may proceed to incorporate more economic variables and to try to find good strategies to reduce unemployment; and so on. Participation and free disposition . Given the complexity of the model and the modelling process, and given the general consequences of intervention strategies, it seems convenient to state its openness to participation and its free disposition.…”

Including an environmental quality index in a demographic model

“…Caselles et al (2008) and Sanz et al (2011) proposed two deterministic human population-dynamics models using these three indices; the second model is more complex and has been validated for Belgium for the 1997-2008 period. Sanz et al (2014a) presented a stochastic human populationdynamics model per gender, in which fertility and death rates depended on the GDI. The model has been validated for Spain for the 2000-2006 period and has been applied to select government investments for the 2006-2015 period.…”