When demography met social simulation: A tale of two modelling approaches

JASSS

Volumn 16, Issue 4, 2013, Pages

  Silverman, Eric ^a   Bijak, Jakub ^a   Hilton, Jason ^a   Cao, Viet Dung ^a   Noble, Jason ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Complexity science; Demography; Health care; Scenario generation

Indexed keywords

EID: 84887012843     PISSN: 14607425     EISSN: None     Source Type: Journal    
DOI: 10.18564/jasss.2327     Document Type: Article

References (60)

1. APARICIO-DIAZ, B., Fent, T., Prskawetz, A. & Bernardi, L. (2011). Transition to Parenthood: The Role of Social Interaction and Endogenous Networks. Demography, 48(2): 559-579. [doi:10.1007/s13524-011-0023-6].
2. AXELROD, R. (1984). The Evolution of Cooperation, New York: Basic Books.
3. AXTELL, R.L., Epstein, J.M., Dean, J.S., Gumerman, G.J., Swedlund, A.C., Harberger, J., Chakravarty, S., Hammond, R., Parker, J. & Parker, M. (2002). Population Growth and Collapse in a Multi-Agent Model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences, Colloquium 99(3): 7275-7279.
4. BENENSON, I., Omer, I. & Hatna, E. (2003). Agent-Based Modeling of Householders' Migration Behaviour and Its Consequences. In: Billari, F. and Prskawetz, A. (eds.), Agent-Based Computational Demography: Using Simulation to Improve Our Understanding of Demographic Behaviour. Heidelberg: Physica Verlag. (pp. 97-115). [doi:10.1007/978-3-7908-2715-6_6].
5. BERNARDI, L. (2003). Channels of social influence on reproduction, Population Research and Policy Review, 22(5-6): 527-555.
6. BERNARDI, L., Keim, S., & von der Lippe, H. (2007). Social Influences on Fertility: A Comparative Mixed Methods Study in Eastern and Western Germany. Journal of Mixed Methods Research, 1: 23-47. [doi:10.1177/2345678906292238].
7. BERRINGTON, A., & Diamond, I. (2000). Marriage or cohabitation_: a competing risks formation analysis of first-partnership among the 1958 British birth cohort. Journal of the Royal Statistical Society, Series A, 163(2): 127-151. [doi:10.1111/1467-985X.00162].
8. BIJAK, J. (2010). Forecasting International Migration in Europe: A Bayesian View. Springer Series on Demographic Methods and Population Analysis, vol. 24. Dordrecht: Springer.
9. BIJAK, J., Hilton, J., Silverman, E. & Cao, V. D. (2013). Reforging the Wedding Ring: Exploring a Semi-Artificial Model of Population for the United Kingdom with Gaussian process emulators. Demographic Research, 29(27): 729-766. http://www.demographic-research.org/volumes/vol29/27/29-27.pdf [doi:10.4054/DemRes.2013.29.27].
10. BILLARI, F., Aparicio Diaz, B., Fent, T. & Prskawetz A. (2007). The "Wedding-Ring". An agent-based marriage model based on social interaction. Demographic Research, 17(3): 59-82. http://www.demographic-research.org/Volumes/Vol17/3/17-3.pdf [doi:10.4054/DemRes.2007.17.3].
11. BILLARI, F., Fent T., Prskawetz A. & Scheffran J. (eds.) (2006). Agent-Based Computational Modelling: Applications in Demography, Social, Economic and Environmental Sciences. [doi:10.1007/3-7908-1721-X] Heidelberg: Physica Verlag.
12. BILLARI, F. & Prskawetz, A. (eds.) (2003), Agent-Based Computational Demography: Using Simulation to Improve Our Understanding of Demographic Behaviour. Heidelberg: Physica Verlag. [doi:10.1007/978-3-7908-2715-6].
13. BILLARI, F.C. (2006). Bridging the gap between micro-demography and macro-demography. In: Caselli, G., Vallin J., and Wunsch, G. (eds.)Demography: analysis and synthesis, Vol 4. New York: Academic Press/Elsevier (pp. 695-707).
14. BÜHLER, Ch. and Fratczak, E. (2007). Learning from others and receiving support: the impact of personal networks on fertility intentions in Poland. European Societies, 9(3): 359-382. [doi:10.1080/14616690701314101].
15. BURCH, T. (2003a). Demography in a new key: A theory of population theory. Demographic Research, 9(11): 263-284. http://www.demographic-research.org/Volumes/Vol9/11 [doi:10.4054/DemRes.2003.9.11].
16. BURCH, T.K. (2003b). Data, Models, Theory and Reality: The Structure of Demographic Knowledge. In: Billari, F. and Prskawetz, A. (eds.), Demographic Research. (pp. 19-40).
17. CEDERMAN, L.-E. (1997). Emergent Actors in World Politics: How States and Nations Develop and Dissolve. Princeton, NJ: Princeton University Press.
18. COURGEAU, D. (2007). Multilevel Synthesis: From the Group to the Individual. Springer Series on Demographic Methods and Population Analysis, vol. 18. Dordrecht: Springer.
19. COURGEAU, D. (2012). Probability and Social Science. Methodological Relationships between the two Approaches. Methodos Series, vol. 10. Dordrecht: Springer. [doi:10.1007/978-94-007-2879-0].
20. DIEKMANN, A. (1989). Diffusion and survival models for the process of entry into marriage. Journal of Mathematical Sociology, 14(1): 31-44.[doi:10.1080/0022250X.1989.9990042].
21. EPSTEIN, J. M. (2008). Why model? Journal of Artificial Societies and Social Simulation, 11(4),12 http://jasss.soc.surrey.ac.uk/11/4/12.html.
22. EUROSTAT (2011). Eurostat Statistics Database; Domain Population and Social Conditions. Retrieved from http://epp.eurostat.ec.europa.eu on 27/10/11.
23. FRANCK, R. (ed.) (2002). The explanatory power of models. Bridging the gap between empirical and theoretical research in the social sciences. Dordrecht: Kluwer Academic Publishers. [doi:10.1007/978-1-4020-4676-6].
24. GEARD, N., McCaw, J. M., Dorin, A., Korb, K. B. & McVernon, J. (2013) Synthetic Population Dynamics: A Model of Household Demography. Journal of Artificial Societies and Social Simulation, 16(1): 8, http://jasss.soc.surrey.ac.uk/16/1/8.html.
25. GILBERT, N. & Troitzsch, K.G. (2005). Simulation for the Social Scientist. 2nd ed. Maidenhead: Open University Press.
26. GODFREY-SMITH, P. (2006). The strategy of model-based science. Biology and Philosophy, 21(5): 725-740. [doi:10.1007/s10539-006-9054-6].
27. GRIM, P., Thomas, S.B., Fisher, S., Reade, C., Singer, D.J., Garza, M.A., Frye, C.S. & Chatman, J. (2012). Polarization and Belief Dynamics in the Black and White Communities: An Agent-Based Network Model from the Data. In: Artificial Life XIII: Proceedings of the Thirteenth International Conference, MIT Press: Cambridge, MA, USA (pp. 186-193). Retrieved from http://mitpress.mit.edu/books/artificial-life-13 on 14/10/13.
28. HAJNAL, J. (1955). The prospects for population forecasts. Journal of the American Statistical Association, 50(270): 309-322.[doi:10.1080/01621459.1955.10501267].
29. HEILAND, F. (2003). The Collapse of the Berlin Wall: Simulating State-Level East to West German Migration Patterns. In: Billari, F. and Prskawetz, A. (eds.), Journal of the American Statistical Association. (pp. 73-96).
30. HERNES, G. (1972). The Process of Entry into First Marriage. American Sociological Review, 37(2): 173-182. [doi:10.2307/2094025].
31. HILLS, T. & Todd, P. (2008). Population Heterogeneity and Individual Differences in an Assortative Agent-Based Marriage and Divorce Model (MADAM) Using Search with Relaxing Expectations. Journal of Artificial Societies and Social Simulation, 11(4),5 http://jasss.soc.surrey.ac.uk/11/4/5.html.
32. HUMAN Mortality Database. (2011). Human Mortality Database. Retrieved from http://www.mortality.org/cgi-bin/hmd on 26/07/11.
33. KENNEDY, M. (2004). Description of the Gaussian process model used in GEM-SA. Software manual. Retrieved fromhttp://ctcd.group.shef.ac.uk/gem.html on 23/05/12.
34. KENNEDY, M., O'Hagan, T. (2001). Bayesian Calibration of Computer Models. Journal of the Royal Statistical Society, Series B, 63(3): 425-464.[doi:10.1111/1467-9868.00294].
35. KEYFITZ, N. (1971). Models. Demography, 8(4): 571-580. [doi:10.2307/2060692].
36. KEYFITZ, N. (1981). The limits of population forecasting. Population and Development Review, 7(4): 579-593. [doi:10.2307/1972799].
37. KNIVETON, D., Smith, Ch. & Wood, S. (2011). Agent-based model simulations of future changes in migration flows for Burkina Faso. Global Environmental Change, 21 (Suppl. 1): S34-S40. [doi:10.1016/j.gloenvcha.2011.09.006].
38. LEE, R. D. & Carter, L. R. (1992). Modeling and Forecasting U.S. Mortality. Journal of the American Statistical Association, 87(419): 659-671.
39. LELIÈVRE, É., Bonvalet C. & Bry X. (1998). Event History Analysis of Groups. Findings of an On-Going Research Project. Population-English edition, 10: 11-38.
40. MURPHY, M. (2003). Bringing Behavior Back into Micro-Simulation: Feedback Mechanisms in Demographic Models. In: F. Billari and A. Prskawetz (eds.), Population-English edition. (pp. 159-174).
41. NOBLE, J., Silverman, E., Bijak, J., Rossiter, S., Evandrou, M., Bullock, S., Vlachantoni, A. & Falkingham, J. (2012). Linked lives: the utility of an agent-based approach to modelling partnership and household formation in the context of social care. In Laroque, C., Himmelspach, J., Pasupathy, R., Rose, O. & Uhrmacher, J.M. (Eds.), Proceedings of the 2012 Winter Simulation Conference. IEEE. http://ieeexplore.ieee.org.
42. OAKLEY, J. & O'Hagan, A. (2002). Bayesian inference for the uncertainty distribution of computer model outputs. Biometrika, 89(4), 769-784.[doi:10.1093/biomet/89.4.769].
43. OAKLEY, J. & O'Hagan, A. (2004). Probabilistic sensitivity analysis of complex models: a Bayesian approach. Journal of the Royal Statistical Society, Series B, 66(3), 751-769. [doi:10.1111/j.1467-9868.2004.05304.x].
44. O'HAGAN, A. (2006). Bayesian analysis of computer code outputs: A tutorial. Reliability Engineering and System Safety, 91(10-11): 1290-1300.[doi:10.1016/j.ress.2005.11.025].
45. ONS (1998). Birth Statistics. Series FM1 (27), London: Office for National Statistics.
46. ONS (2011). Characteristics of Mother 1, England and Wales. London: Office for National Statistics. Retrieved fromhttp://www.ons.gov.uk/ons/rel/vsob1/characteristics-of-Mother-1--england-and-wales/2011/index.htmlon 21/03/2013.
47. SCHELLING, T. (1978). Micromotives and Macrobehavior. Norton, New York, USA.
48. SILVERMAN, E., Bijak, J. & Noble, J. (2011) Feeding the Beast: Can Computational Demographic Models Free Us from the Tyranny of Data? In: Lenaerts, T., Giacobini, M., Bersini, H., Bourgine, P., Dorigo, M. and Doursat, R. (eds.) Advances in Artificial Life, ECAL 2011, MIT Press, Cambridge MA, USA (pp. 747-754).
49. SILVERMAN, E., Bijak, J., Noble, J., Cao, V. & Hilton, J. (2012) Semi-Artificial Models of Population: Connecting Demography with Agent-Based Modelling. Paper for the 4th World Congress on Social Simulation, Taipei, Taiwan, 4-7 September 2012.
50. SILVERMAN, E. & Bullock, S. (2004). Empiricism in Artificial Life. In Artificial Life IX: Proceedings of the Ninth International Conference, MIT Press: Cambridge, MA, USA (pp. 534-539).
51. SILVERMAN, E. & Bryden, J. (2007). From artificial societies to new social science theory. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I. and Coutinho, A. (eds.) Advances in Artificial Life, 9th European Conference, ECAL 2007 Proceedings. Berlin-Heidelberg: Springer (pp. 645-654).
52. TODD, P.M., Billari, F.C. & Simão, J. (2005). Aggregate age-at-marriage patterns from individual mate-search heuristics. Demography, 42(3): 559-574.
53. VERBRUGGE, L.M., & Jette, A.M. (1994). The disablement process. Social Science and Medicine, 38(1): 1-14. [doi:10.1016/0277-9536(94)90294-1].
54. VLACHANTONI, A., Shaw, R., Willis, R., Evandrou, M., & Luff, J. F. R. (2011). Measuring unmet need for social care amongst older people. Population Trends 145: 60-76. [doi:10.1057/pt.2011.17].
55. WILLEKENS, F. (1990). Demographic forecasting; state-of-the-art and research needs. In: Hazeu, C.A. and Frinking, G.A.B. (eds.), Emerging issues in demographic research. Amsterdam: Elsevier (pp. 9-66).
56. WILLEKENS, F. (2005). Biographic forecasting: bridging the micro-macro gap in population forecasting. New Zealand Population Review, 31(1): 77-124.
57. WILLEKENS, F. (2012) Migration: A perspective from complexity science. Paper for the Migration workshop of the Complexity Science for the Real World (CSRW) network, Chilworth, UK, 16 February 2012.
58. WRIGHT, G. & Goodwin, P. (2009). Decision making and planning under low levels of predictability: Enhancing the scenario method. International Journal of Forecasting, 25(4): 813-825. [doi:10.1016/j.ijforecast.2009.05.019].
59. YABIKU, S. T. (2006). Neighbors and neighborhoods: effects on marriage timing. Population Research and Policy Review, 25(4): 305-327.[doi:10.1007/s11113-006-9006-5].
60. ZINN, S., Gampe, J., Himmelspach, J. & Uhrmacher, A. M. (2009). MIC-CORE: a tool for microsimulation. In: Rossetti, M.D., Hill, R.R., Johansson, B., Dunkin, A. and Ingalls, R.G. (eds.) Proceedings of the 2009 Winter Simulation Conference. IEEE (pp. 992-1002). http://ieeexplore.ieee.org.