IDEAS home Printed from https://ideas.repec.org/p/unu/wpaper/rp2004-26.html
   My bibliography  Save this paper

Assessing Poverty and Inequality at a Detailed Regional Level: New Advances in Spatial Microsimulation

Author

Listed:
  • Ann Harding
  • Rachel Lloyd
  • Anthea Bill
  • Anthony King

Abstract

During the past three years NATSEM has developed pathbreaking spatial microsimulation techniques, involving the creation of synthetic data about the socioeconomic characteristics of households at a detailed regional level. The data are potentially available at any level of geographic aggregation, down to the level of the Census Collection District (about 200 households).

Suggested Citation

  • Ann Harding & Rachel Lloyd & Anthea Bill & Anthony King, 2004. "Assessing Poverty and Inequality at a Detailed Regional Level: New Advances in Spatial Microsimulation," WIDER Working Paper Series RP2004-26, World Institute for Development Economic Research (UNU-WIDER).
    • Handle: RePEc:unu:wpaper:rp2004-26
    as

    Download full text from publisher

    File URL: https://www.wider.unu.edu/sites/default/files/rp2004-026.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. P Williamson & M Birkin & P H Rees, 1998. "The Estimation of Population Microdata by Using Data from Small Area Statistics and Samples of Anonymised Records," Environment and Planning A, , vol. 30(5), pages 785-816, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karyn Morrissey & Cathal O'Donoghue, 2011. "The Spatial Distribution of Labour Force Participation and Market Earnings at the Sub-National Level in Ireland," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 3(1), pages 80-101, July.
    2. Jill Wright & Ma. Rebecca Valenzuela & Duangkamon Chotikapanich, 2011. "Measuring Poverty and Inequality from Highly Aggregated Small Area Data: The Changing Fortunes of Latrobe Valley Households," Monash Econometrics and Business Statistics Working Papers 4/12, Monash University, Department of Econometrics and Business Statistics.
    3. Azizur Rahman & Ann Harding & Robert Tanton & Shuangzhe Liu, 2010. "Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 3-22.
    4. S.F. Chin & Ann Harding & Anthea Bill, 2007. "Regional Dimensions: Preparation of 1998-99 HES for reweighting to small-area benchmarks," NATSEM Working Paper Series 34, University of Canberra, National Centre for Social and Economic Modelling.
    5. BARTHELEMY Johan & CORNELIS Eric, 2012. "Synthetic populations: review of the different approaches," LISER Working Paper Series 2012-18, Luxembourg Institute of Socio-Economic Research (LISER).
    6. Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Loughrey, Jason & O’Donoghue, Cathal & Meredith, David & Murphy, Ger & Shanahan, Ultan & Miller, Corina, 2018. "The Local Impact of Cattle Farming," 166th Seminar, August 30-31, 2018, Galway, West of Ireland 276231, European Association of Agricultural Economists.
    2. Lovelace, Robin & Ballas, Dimitris & Watson, Matt, 2014. "A spatial microsimulation approach for the analysis of commuter patterns: from individual to regional levels," Journal of Transport Geography, Elsevier, vol. 34(C), pages 282-296.
    3. Robert Tanton & Paul Williamson & Ann Harding, 2014. "Comparing Two Methods of Reweighting a Survey File to Small Area Data," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 76-99.
    4. Ma, Lu & Srinivasan, Sivaramakrishnan, 2016. "An empirical assessment of factors affecting the accuracy of target-year synthetic populations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 247-264.
    5. O'Donoghue, Cathal & Grealis, Eoin & Farrell, Niall, 2015. "Modelling the Spatial Distributional Agricultural Incomes," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212654, European Association of Agricultural Economists.
    6. Hanley, Nicholas & Hynes, Stephen & O'Donoghue, Cathal, 2008. "A combinatorial optimisation approach to non-market environmental benefit aggregation," Stirling Economics Discussion Papers 2008-08, University of Stirling, Division of Economics.
    7. Robert Tanton, 2014. "A Review of Spatial Microsimulation Methods," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 4-25.
    8. Itismita Mohanty & Robert Tanton & Yogi Vidyattama & Marcia Keegan & Robert Cummins, 2013. "‘Small area estimates of Subjective Wellbeing: Spatial Microsimulation on the Australian Unity Wellbeing Index Survey’," NATSEM Working Paper Series 13/23, University of Canberra, National Centre for Social and Economic Modelling.
    9. Farooq, Bilal & Bierlaire, Michel & Hurtubia, Ricardo & Flötteröd, Gunnar, 2013. "Simulation based population synthesis," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 243-263.
    10. Sun, Lijun & Erath, Alexander & Cai, Ming, 2018. "A hierarchical mixture modeling framework for population synthesis," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 199-212.
    11. Ann Harding & Robert Tanton, 2014. "Policy and people at the small-area level: using micro-simulation to create synthetic spatial data," Chapters, in: Robert Stimson (ed.), Handbook of Research Methods and Applications in Spatially Integrated Social Science, chapter 25, pages 560-586, Edward Elgar Publishing.
    12. M. Esteban Muñoz H. & Irene Peters, 2014. "Constructing an Urban Microsimulation Model to Assess the Influence of Demographics on Heat Consumption," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 127-157.
    13. Stephen Hynes & Nick Hanley & Cathal O’Donoghue, 2010. "A Combinatorial Optimization Approach to Nonmarket Environmental Benefit Aggregation via Simulated Populations," Land Economics, University of Wisconsin Press, vol. 86(2), pages 345-362.
    14. Saadi, Ismaïl & Mustafa, Ahmed & Teller, Jacques & Farooq, Bilal & Cools, Mario, 2016. "Hidden Markov Model-based population synthesis," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 1-21.
    15. Malcolm Campbell & Dimitris Ballas, 2013. "A spatial microsimulation approach to economic policy analysis in Scotland," Regional Science Policy & Practice, Wiley Blackwell, vol. 5(3), pages 263-288, August.
    16. Lopes, Mafalda Mendes & Moura, Filipe & Martinez, Luis M., 2014. "A rule-based approach for determining the plausible universe of electric vehicle buyers in the Lisbon Metropolitan Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 22-36.
    17. O'Donoghue, Cathal & Grealis, Eoin & Loughrey, Jason & Donnellan, Trevor & Hanrahan, Kevin & Hennessy, Thia, 2015. "The Spatial Distributional Effect of Common Agricultural Policy Reform," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212656, European Association of Agricultural Economists.
    18. D. H. Judson, 2007. "Information integration for constructing social statistics: history, theory and ideas towards a research programme," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 483-501, March.
    19. Kate A Timmins & Kimberley L Edwards, 2016. "Validation of Spatial Microsimulation Models: a Proposal to Adopt the Bland-Altman Method," International Journal of Microsimulation, International Microsimulation Association, vol. 9(2), pages 106-122.
    20. David Pritchard & Eric Miller, 2012. "Advances in population synthesis: fitting many attributes per agent and fitting to household and person margins simultaneously," Transportation, Springer, vol. 39(3), pages 685-704, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:unu:wpaper:rp2004-26. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Siméon Rapin (email available below). General contact details of provider: https://edirc.repec.org/data/widerfi.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.