Skip to main content

Parameterisation of Individual Working Dynamics

  • Chapter
  • First Online:
Empirical Agent-Based Modelling - Challenges and Solutions

Abstract

How do European rural areas evolve? While for decades the countryside in many regions of Europe was synonymous with inevitable decline, nowadays, some areas experience a rebirth, even in areas where until recently development was not considered possible. Our modelling effort aims at better understanding these heterogeneities. To deal with this objective, the modelling and the parameterisation should be strongly constraint by available data. This chapter focusses on the modelling of the individual working dynamics describing how we can design the entering on the labour marking, the job search decision and process and every other process related to work from available data. We argue about the utility of large existing databases to design complex integrated individual dynamics.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This work has been funded under the PRIMA (Prototypical policy impacts on multifunctional activities in rural municipalities) collaborative project, EU 7th Framework Programme (ENV 2007-1), contract no. 212345.

  2. 2.

    Eurostat defines the NUTS (Nomenclature of Territorial Units for Statistics) classification as a hierarchical system for dividing up the EU territory: NUTS 1 for the major socio-economic regions; NUTS 2 for the basic regions for the application of regional policies; NUTS 3 as small regions for specific diagnoses; LAU (Local Administrative Units 1 and 2) has been added more recently to allow local level statistics.

  3. 3.

    Consists of municipalities or equivalent units.

  4. 4.

    A nuclear family corresponds to the parents and the children; that is a reductive definition of the family corresponding on the most common way to define the family in Europe nowadays.

  5. 5.

    A complex household is a household which is not a single, a couple with or without children.

  6. 6.

    made available by the Maurice Halbwachs Center of the Quételet Network (http://www.reseau-quetelet.cnrs.fr/spip) for 1990. For 1999 and 2006, they are directly accessible through internet via the website of INSEE http://www.recensement-1999.insee.fr/ and http://www.insee.fr/fr/publics/default.asp?page=communication/recensement/particuliers/diffusion_resultats.htm).

  7. 7.

    http://www.reseau-quetelet.cnrs.fr/spip/.

References

  • Aubert F, Dissart JC, Lépicier D (2009) Facteurs de localisation de l’emploi résidentiel en France, XLVIème Colloque de l’Association de Science Régionale de Langue Française (ASRDLF), 6–8 juillet, Clermont-Ferrand, France, 27

    Google Scholar 

  • Ballas D, Clarke GP, Wiemers E (2005) Building a dynamic spatial microsimulation model for Ireland. Popul Space Place 11:157–172

    Google Scholar 

  • Ballas D, Clarke GP, Wiemers E (2006) Spatial microsimulation for rural policy analysis in Ireland: the implications of CAP reforms for the national spatial strategy. J Rur Stud 22:367–378

    Article  Google Scholar 

  • Ballas D et al (2007) Using SimBritain to model the geographical impact of national government policies. Geogr Anal 39:44–77

    Google Scholar 

  • Baqueiro Espinosa O et al (2011) Two adaptations of a micro-simulation model to study the impacts of policies at the municipality level. In PRIMA European project (ed) Working paper (p 62). Newcastle University, Cemagref

    Google Scholar 

  • Berger T, Schreinemachers P (2006) Creating agents and landscapes for multiagent systems from random sample. Ecol Soc 11(2):19

    Google Scholar 

  • Birkin M, Clarke M (2011) Spatial microsimulation models: a review and a glimpse into the future. In J Stillwell and M Clarke (eds) Population dynamics and projection methods (Understanding population trends and processes Vol 4, pp 193–208). Springer, Netherlands

    Google Scholar 

  • Birkin M, Wu B (2012) A review of microsimulation and hybrid agent-based approaches. In AJ Heppenstall et al (eds) Agent-based models of geographical systems (pp 51–68). Springer: Netherlands

    Google Scholar 

  • Blanc M, Schmitt B (2007) Orientation économique et croissance locale de l’emploi dans les bassins de vie des bourgs et petites villes. Economie et Statistique 402:57–74

    Article  Google Scholar 

  • Bousquet F, Le Page C (2004) Multi-agent simulations and ecosystem management: a review. Ecol Model 176:313–332

    Article  Google Scholar 

  • Bozon M, Héran F (1987) La découverte du conjoint: I. evolution et morphologie des scènes de rencontre. Population 42(6):943–985

    Article  Google Scholar 

  • Bozon M, Héran F (1988) La découverte du conjoint: II. Les scènes de rencontre dans l’espace social. Population 43(1):121–150

    Article  Google Scholar 

  • Brown DG, Robinson DT (2006) effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecol Soc 11(1):46

    Google Scholar 

  • Brown DG, Aspinal R, Bennett DA (2006) Landscape models and explanation in landscape ecology—a space for generative landscape science. Prof Geo 58(4):369–382

    Article  Google Scholar 

  • Champetier Y (2000) The (re)population of rural areas. Leader Magazine 23(Springer Special Issue)

    Google Scholar 

  • Coulombel N (2010) Residential Choice and Household Behavior: State of the Art, (Working Paper 2.2a: Ecole Normale Supérieure de Cachan), 69.

    Google Scholar 

  • Davezies L (2009) L’économie locale “résidentielle”. Géographie économie société 11(1):47–53

    Article  Google Scholar 

  • Deffuant G. et al (2001), Rapport final du projet FAIR 3 2092 IMAGES: Modélisation de la diffusion de l’adoption de mesures agri-environnementales par les agriculteurs (1997–2001).

    Google Scholar 

  • Deffuant G et al (2002) How can extremism prevail? A study based on the relative agreement interaction model. JASSS 5(4):4

    Google Scholar 

  • Deffuant G, Huet S, Amblard F (2005) An individual-based model of innovation diffusion mixing social value and individual payoff dynamics. Am J Soc 110(4):1041–1069

    Google Scholar 

  • Deffuant G, Skerrat S, Huet S (2008) An agent based model of agri-environmental measure diffusion: what for? In A Lopez Paredes, C Hernandez Iglesias (eds) Agent based modelling in natural resource management (pp 55–73). INSISOC, Valladolid

    Google Scholar 

  • Dubuc S (2004) Dynamisme rural: l’effet des petites villes. L’Espace Géographique 1:69–85

    Google Scholar 

  • Felemou M (2011) Analyse de données de flux de navetteurs. Extractions de modèles (p 31 Rapport de stage de 1ère année de Master Statistiques et Traitement de Données). Cemagref, Aubière

    Google Scholar 

  • Fernandez LE et al (2005) Characterizing location preferences in an exurban population: implications for agent-based modeling. Plan Des 32(6):21

    Google Scholar 

  • Fontaine C, Rounsevell M (2009) An agent-based approach to model future residential pressure on a regional landscape. Landscape Ecol 24(9):1237–54

    Article  Google Scholar 

  • Gargiulo F et al (2010) An iterative approach for generating statistically realistic populations of households. PLoS One 5(1):9

    Article  Google Scholar 

  • Gargiulo F et al (2011) Commuting network model: going to the bulk. JASSS 15(2):6

    Google Scholar 

  • Gilbert N, Troitzsch KG (2005) Simulation for the social scientist. Open University Press, Maidenhead

    Google Scholar 

  • Givord P (2003) Une nouvelle enquête Emploi. Economie et Statistiques 362:59–66

    Google Scholar 

  • Goux D (2003) Une histoire de l’enquête Emploi. Economie et Statistiques 362:41–57

    Article  Google Scholar 

  • Grimm V et al (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198:115–126

    Google Scholar 

  • Grimm V et al (2010) The ODD protocol: a review and first update. Ecol Model 221:2760–2768

    Article  Google Scholar 

  • Holme E et al (2004) The SVERIGE spatial microsimulation model: content, validation and example applications (p 55). Spatial Modelling Centre, Sweden

    Google Scholar 

  • Huet S et al (2011) Micro-simulation model of municipality network in the Auvergne case study. In PRIMA (ed) Working paper (p 63). IRSTEA, Aubière

    Google Scholar 

  • INSEE division Redistribution et Politiques Sociales (1999) Le modèle de simulation dynamique DESTINIE. Série des documents de travail de la Direction des Etudes et Synthèses Economiques 124:1–49

    Google Scholar 

  • Johansson M, Rauhut D (2007) The spatial effects of demographic trends and migration. E. P. 1.1.4., European Observation Network for Territorial Development and Cohesion (ESPON):65

    Google Scholar 

  • Lenormand M, Huet S et al (2012a) Deriving the number of jobs in proximity services from the number of inhabitants in French rural municipalities. PLoS One 7(7):13

    Google Scholar 

  • Lenormand M, Huet S et al (2012b) A universal model of commuting networks. PLoS One 7(10)

    Google Scholar 

  • Moeckel R et al (2003) Microsimulation of land use. Int J Urb Sci 71(1):14–31

    Google Scholar 

  • Morand E et al (2010) Demographic modelling: the state of the art (FP7–244557 Project SustainCity, p 39). INED: Paris

    Google Scholar 

  • Müller K, Axhausen KW (2011) Population synthesis for microsimulation: State of the art, 90th Annual Meeting of the Transportation Research Board (Washington D.C.)

    Google Scholar 

  • Orcutt GH (1957) A new type of socio economic system. Rev Econ Statist 58:773–97

    Google Scholar 

  • Parker Dawn C et al (2003) Multi-agent systems for the simulation of land-use and land-cover change: a review. Ann Assoc Am Geogr 93(2):314–37

    Article  Google Scholar 

  • Perrier-Cornet Ph (2001) La dynamique des espaces ruraux dans la société française: un cadre d’analyse. Territoires 2020, 3 (Etudes et prospectives—Data), 61–74

    Google Scholar 

  • Polhill JG et al (2008) Using the ODD protocol for describing three agent-based social simulation models of land-use change. JASSS 11 (2.3):30

    Google Scholar 

  • Rindfuss R et al (2004) Developing a science of land change: Challenges and methodological issues. PNAS 101(39):13976–81

    Article  Google Scholar 

  • Soumagne J (2003) Les services en milieu rural, enjeu d’aménagement territorial. Revista da Faculdade de Letras—Geografia I série, XIX.

    Google Scholar 

  • Turci L et al (2010) Provisional demographic outline (FP7–244557 Project SustainCity, p 24). INED, Paris

    Google Scholar 

  • Ullman E, Dacey M (1960) The minimum requirement approach to the urban economic base. Pap Proc Reg Sci Ass 6(192):175–194

    Google Scholar 

  • Verburg PH et al (2002) Modelling the spatial dynamics of regional land use: the clue-s model. Environ Manage 30(3):391–405

    Article  Google Scholar 

  • Verburg PH et al (2004) Land use modelling: current practice and research priorities. GeoJournal 61:309–324

    Article  Google Scholar 

  • Verburg PH et al (2006) Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agri Eco Environ 114:39–56

    Article  Google Scholar 

Download references

Acknowledgements

This work has been funded under the PRIMA (Prototypical policy impacts on multifunctional activities in rural municipalities) collaborative project, EU 7th Framework Programme (ENV 2007-1), contract no. 212345.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Huet .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Huet, S., Lenormand, M., Deffuant, G., Gargiulo, F. (2014). Parameterisation of Individual Working Dynamics. In: Smajgl, A., Barreteau, O. (eds) Empirical Agent-Based Modelling - Challenges and Solutions. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6134-0_8

Download citation

Publish with us

Policies and ethics