How individual decisions shape religious groups over time

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Modeling religious change with agent-based models Societies are comprised of diverse individuals, each one characterized by their own goals, relationships, and personality. Modeling Religious Change uses cutting-edge agent-based models to incorporate and track individual characteristics, allowing us to measure the impact of complex factors on personal (non)religious identity and general religious change. Society-wide religious change results from …

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Understanding changing populations with the cohort-component method

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When governments set out to design long-term projects and plans, they need to know how many people those future projects must accommodate. Many turn to demographic projections to provide data on future population sizes and make-up. The cohort-component method (CCM) is commonly used by the government and academia to create these demographic projections. In a CCM projection, the target …

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Adapting Cohort-Component Methods to a Microsimulation: A case study

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Ivan Puga-Gonzalez, Rachel J. Bacon, David Voas, F. LeRon Shults, George Hodulik, Wesley J. Wildman Abstract Social scientists generally take United Nations (UN) population projections as the baseline when considering the potential impact of any changes that could affect fertility, mortality or migration, and the UN typically does projections using the cohort-component method (CCM). The CCM technique is computationally simple …

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Can we measure (and predict) religious change?

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We can’t predict the future, but we want to get closer Written by Jessie Saeli, edited by Nicole R. Smith and Rachel J. Bacon The year is 2050. Although millions of Europeans and North Americans have abandoned Christianity and become nonreligious, the share of nonreligious people worldwide has decreased in comparison to increases in Christian, Muslim, and Hindu populations. …

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Religious Exiting and Social Networks: Computer Simulations of Religious/Secular Pluralism

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Research Article Authors: Ryan Cragun, Kevin McCaffree, Ivan Puga-Gonzalez, Wesley Wildman, F. LeRon Shults Abstract Statistical models attempting to predict who will disaffiliate from religions have typically accounted for less than 15% of the variation in religious affiliations, suggesting that we have only a partial understanding of this vital social process. Using agent-based simulations in …

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