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Dynamic population model and an application for Leeds

Dynamic population model and an application for Leeds. B.M.Wu School of Geography University of Leeds. Outline. Introduction Approaches of modelling social systems An application for Leeds Model description Initial result analysis Model improvement Summary. Learning objectives.

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Dynamic population model and an application for Leeds

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  1. Dynamic population model and an application for Leeds B.M.Wu School of Geography University of Leeds QMSS2, Leeds, 02-09/07/09

  2. Outline • Introduction • Approaches of modelling social systems • An application for Leeds • Model description • Initial result analysis • Model improvement • Summary QMSS2, Leeds, 02-09/07/09

  3. Learning objectives • To understand: • various social modelling approaches • individual based models • dynamic MSM • how a typical dynamic MSM is structured • how a typical dynamic MSM works • importance of data for a MSM • alternative modelling approaches that may compliment MSM QMSS2, Leeds, 02-09/07/09

  4. Approaches of modelling social systems • Social Systems are “messy” • boundaries • large and • complex (Moss, 2000) QMSS2, Leeds, 02-09/07/09

  5. Approaches of modelling social systems • Individual Based Models (IBM): • MSM (Microsimulation Model) • CA (Cellular Automata) • ABM (Agent Based Model) QMSS2, Leeds, 02-09/07/09

  6. Approaches of modelling social systems • MSM + t = 1, 2, … , t = n QMSS2, Leeds, 02-09/07/09

  7. Approaches of modelling social systems MSM: Static vs Dynamic QMSS2, Leeds, 02-09/07/09

  8. Approaches of modelling social systems • Advantages of Static MSM: • quicker to run • simpler to develop and understand • lower costs: computing resources, skills and development time • often with very detailed programme simulations QMSS2, Leeds, 02-09/07/09

  9. Approaches of modelling social systems • Advantages of Dynamic MSM: • more details • better representation of population ageing, especially in long term, as it accounts interim changes in economic and demographic trends • generally accepted more realistic representation of micro population unit changes QMSS2, Leeds, 02-09/07/09

  10. Approaches of modelling social systems MSM: Spatial and non-Spatial “One can not be at two places at the same time.” (Hägerstrand, 1967) “Means are to be employed somewhere.” (De Man, 1998) People have to live in a local area and they are affected by local environment. QMSS2, Leeds, 02-09/07/09

  11. CA source: http://www.bitstorm.org/gameoflife/ QMSS2, Leeds, 02-09/07/09

  12. ABM QMSS2, Leeds, 02-09/07/09

  13. An application of Leeds: modelling objectives • Modelling objectives: • To develop a complete representation of the Leeds population at a fine spatial scale • To produce rich, detailed and robust forecasts of the future population of Leeds • To investigate scenarios which relate demographics to service provision QMSS2, Leeds, 02-09/07/09

  14. Modelling Description • Dynamic representation of key demographic events /transactions in a geographically identified population • Macrosimulation and microsimulation models (MSM) are alternative ways of realising the processes (van Imhoff and Post, 1998) • We use a spatial MSM of the population and its dynamics, but the structure parallels the macro multi-state cohort-component (MSCC) projection model • An MSM depends on good data on the important transitions experienced by individuals • We experimented with an Agent Based Model(ABM) for a sub-population, students, where empirical data on migration has often proved problematic QMSS2, Leeds, 02-09/07/09

  15. What does that mean? • Scale • Leeds population:760,000 • Each individual has about 60 individual variables + 20 household variables + area variables • Various probabilities/rates eg: localised single year of age based mortality probabilities • Movement, interaction and behaviour • Distinctive behaviours from various population groups in different demographic processes • Interdependency of household and individual variables in different demographic processes QMSS2, Leeds, 02-09/07/09

  16. Demographic processes in the MSM • 6 modularised processes : • simple processes • complex processes • individuals and households QMSS2, Leeds, 02-09/07/09

  17. Initial Results: Leeds population change QMSS2, Leeds, 02-09/07/09

  18. Initial Results: small area variation QMSS2, Leeds, 02-09/07/09

  19. Characteristics of student migrants • Students are highly mobile during their studies in the universities • Mostly only move around the area close to the universities where they study, NOT in the suburban areas • Most of them will leave the city once they finish their study, NOT growing old in the suburban areas • Due to the replenishment of the student population each year, the population of the small areas where university student stay tends to remain younger than other areas QMSS2, Leeds, 02-09/07/09

  20. ABM • An alternative approach that models individuals as agents through their interactions with each other and the environment that they live in. • It is very flexible to introduce heterogeneous agents with distinctive behaviours through their built-in rules • It is useful in modelling features of the population where knowledge and data is lacking (Billari et al. , 2002). QMSS2, Leeds, 02-09/07/09

  21. ABM experiments: Student Migrants • We recognise the following groups: • First year undergraduates • Other undergraduates • Master students • Doctoral students • We apply the following general rules: • Each group is allowed set years to stay in the area • Students prefer to stay with their fellow students • Students stay close to their university of study, subject to housing availability • They don’t “do” marriage and fertility QMSS2, Leeds, 02-09/07/09

  22. Comparison of Results: Pure MSM Observed Predicted QMSS2, Leeds, 02-09/07/09

  23. Comparison of Results: MSM with ABM Observed Predicted QMSS2, Leeds, 02-09/07/09

  24. Summary We have discussed the difficulty in modelling the social systems and various modelling approaches. IBM provide detailed info at individual level and MSM is an important social modelling approach, especially in assisting public policy development and planning. Dynamic MSM provides a more realistic reflection of the studied system than static MSM. Typical dynamic MSM structure and functions. MSM depends on quality data and may be strengthened by complementary techniques such as ABM where there is a knowledge gap. QMSS2, Leeds, 02-09/07/09

  25. Thank you!B.Wu@Leeds.ac.uk QMSS2, Leeds, 02-09/07/09

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