Abstract
Evaluation is a critical step in the analysis of social policies which, itself, can influence public thinking (Unrau, 1993; Manski and Garfinkel, 1992). Policy-relevant spatial modelling is an expanding area of research, which has a lot of potential for the evaluation of the socio-economic and spatial effects of major national social policy programmes. However, traditional modelling approaches to social policy analysis usually focus on the impact on the socio-economic structure of the population and they have tended to ignore the geographical dimensions of social policies. In particular, the focus has usually been on the redistributive effects of government policies (such as budget changes and social security benefit policies etc.) between households, but there has generally been a paucity of studies that investigate the spatial impacts of these policies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alvanides, S. (2000), Zone Design Methods for Application in Human Geography. Unpublished PhD thesis, School of Geography, University of Leeds.
Armstrong, H. (1993), `The local income and employment impact of Lancaster University.’ Urban Studies, 30, 1653–1668.
Armstrong, H. and J. Taylor (1993), Regional Economics and Policy ( 2nd edition ). Harvester Wheatsheaf, Brighton.
Atkinson, A.B. (1996), `Seeking to explain the distribution of income.’ In J. Hills (ed.), New Inequalities: The Changing Distribution of Income and Wealth in the United Kingdom. Cambridge University Press, Cambridge, pp. 19–48.
Ballas, D. and G.P. Clarke (2000a), `GIS and microsimulation for local labour market analysis.’ Computers, Environment and Urban Systems, 24, 305–330.
Ballas, D. and G.P. Clarke (2000b), A Spatial Microsimulation Approach to the Analysis of Local Multiplier Effects. Paper presented at the 31st Regional Science Association British and Irish Section Conference, University of Bath.
Ballas, D. and G.P. Clarke (2001a), `Modelling the local impacts of national social policies: a spatial microsimulation approach.’ Environment and Planning C: Government and Policy, 19, 587–606.
Ballas, D. and G.P. Clarke (2001b), `The local implications of major job transformations in the city: a spatial microsimulation approach.’ Geographical Analysis, 33, 291–311.
Ballas, D., G.P. Clarke and L. Turton (1999), Exploring Microsimulation Methodologies for the Estimation of Household Attributes. Paper presented at the 4th International Conference on GeoComputation, Fredericksburg, Virginia, USA.
Bennett, R. (1980), The Geography of Public Finance. Methuen, London.
Birkin, M. and M. Clarke (1988), `SYNTHESIS — a synthetic spatial information system for urban and regional analysis: methods and examples.’ Environment and Planning A, 20, 1645–1671.
Birkin, M. and M. Clarke (1989), `The generation of individual and household incomes at the small area level.’ Regional Studies, 23, 535–548.
Birkin, M. and G.P. Clarke (1995), `Using microsimulation methods to synthesize census data.’ In S. Openshaw (ed.), Census Users’ Handbook. Geoinformation International, London, pp. 363–387.
Clarke, G.P. (1996), `Microsimulation: an introduction.’ In G.P. Clarke (ed.), Microsimulation for Urban and Regional Policy Analysis. Pion, London, pp. 1–9.
Curtis, S. (1989), The Geography of Public Welfare Provision. Routledge, London.
Dorling, D. and J. Tomaney (1995), `Poverty in the old industrial regions: a comparative view.’ In C. Philo (ed.), Off the Map: The Social Geography of Poverty in the UK. Child Poverty Action Group, London, pp. 103–132.
Dowsland, K. (1993), `Simulated annealing.’ In C. Reeves (ed.), Modern Heuristic Techniques for Combinatorial Problems. Blackwell, Oxford.
Edwards, J. (1995), `Social Policy and the City: A Review of Recent Policy Developments and Literature.’ Urban Studies, 32, 695–712.
Falkingham, J. and C. Lessof (1992), `Playing God: or LIFEMOD — the construction of a dynamic microsimulation model.’ In R. Hancock and H. Sutherland H (eds.), Microsimulation Models for Public Policy Analysis: New Frontiers. Suntory-Toyota International Centre for Economics and Related Disciplines, LSE, London.
George, C., D. Allirajah and M. Barnes (1999), Welfare Benefits Handbook 1999/2000, Vol. 1. CPAG, London.
George, C., D. Allirajah and M. Barnes (1999), Welfare Benefits Handbook 1999/2000, Vol. 2. CPAG, London.
Goodwin, M. (1995), `Poverty in the city: “you can raise your voice, but who is listening?”’ In C. Philo (ed.), Off the Map: The Social Geography of Poverty in the UK. Child Poverty Action Group, London, pp. 65–82.
Green, A.E. (1996), `Aspects of the changing geography of poverty and wealth.’ In J. Hills (ed.), New Inequalities: The Changing Distribution of Income and Wealth in the United Kingdom. Cambridge University Press, Cambridge, pp. 265–291.
Green, A.E. (1998), `The geography of earnings and incomes in the 1990s.’ Environment and Planning C: Government and Policy, 16, 633–648.
Hamnett, C. (1997), `A stroke of the Chancellor’s pen: the social and regional impact of the Conservative’s 1988 higher rate tax cuts.’ Environment and Planning A, 29, 129–147.
Hancock, R. and H. Sutherland (eds.) (1992), Microsimulation Models for Public Policy Analysis: New Frontiers. Suntory-Toyota International Centre for Economics and Related Disciplines, LSE, London.
Higgs, G. (1994), `GIS in local government: analysis of the spatial implications of the council tax.’ Local Government Policy Making, 21, 33–37.
Hill, M. and G. Bramley (1986), Analysing Social Policy. Blackwell, Oxford.
Hills, J. (1996), `Introduction: after the turning point.’ In J. Hills (ed.), New Inequalities: The Changing Distribution of Income and Wealth in the United Kingdom. Cambridge University Press, Cambridge, pp. 1–16.
HM Treasury (2000), Prudent for a Purpose: Working for a Stronger and Fairer Britain. Available from http://www.hm-treasury.gov.uk/budget2000/index.html, accessed May 2000.
Joseph Rowntree Foundation (1995) Inquiry into Income and Wealth, Vol. 1. Joseph Rowntree Foundation, York.
Kirkpatrick, S., C.D. Gelatt Jr. and M.P. Vecchi (1983), `Optimization by simulated annealing.’ Science, 220, 671–680.
Krupp, H. (1986), `Potential and limitations of microsimulation models.’ In G. H.Orcutt, J. Mertz and H. Quinke (eds.), Microanalytic Simulation Models to Support Social and Financial Policy. North-Holland, Amsterdam, pp. 31–41.
Longley, P., P. Higgs and D. Martin (1996), `The rates revisited? a geographical reassignment of property valuations and local tax burdens under the council tax.’ Environment and Planning C: Government and Policy, 14, 101–120.
Manski, C.F. and I. Garfinkel (1992), Evaluating Welfare and Training Programs. Harvard University Press, Cambridge, MA.
Marsh, C. (1993), `Privacy, confidentiality and anonymity in the 1991 Census.’ In A. Dale and C. Marsh (eds.), The 1991 Census User’s Guide. HMSO, London.
Martin, R. (1995), `Income and poverty inequalities across regional Britain: the North-South divide lingers on.’ In C. Philo (ed.), Off the Map: The Social Geography of Poverty in the UK. Child Poverty Action Group. London, pp. 23–44.
Mertz, J. (1991), `Microsimulation — a survey of principles developments and applications.’ International Journal of Forecasting, 7, 77–104.
McCormick, J. and C. Philo (1995), `Where is poverty? The hidden geography of poverty in the United Kingdom.’ In C. Philo (ed.), Off the Map: The Social Geography of Poverty in the UK. Child Poverty Action Group, London, pp. 1–22.
McKendrick, J. (1995), `Poverty in the UK: the Celtic divide.’ In C. Philo (ed.), Off the Map: the Social Geography of Poverty in the UK. Child Poverty Action Group, London, pp. 45–64.
Metropolis, N., A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller and E. Teller (1953), `Equation of state calculations by fast computing machines.’ Journal of Chemical Physics, 21, 1087–1092.
Middleton, E. (1995), Samples of anonymized Records. In S Openshaw (ed.), Census users’ handbook. Geoinformation International, London, 337–362.
Musgrave, R.A. and Musgrave, P.B. (1984), Public finance in theory and practice. McGraw Hill, New York
Noble, M. and G. Smith (1996), `Two nations? Changing patterns of income and wealth in two contrasting areas.’ In J. Hills (ed.), New Inequalities: The Changing Distribution o f Income and Wealth in the United Kingdom. Cambridge University Press, Cambridge, pp. 292–318.
Norman, P. (1999), Putting Iterative Proportional Fitting (IPF) on the Researcher’s Desk. Working Paper 99/03, School of Geography, University of Leeds, Leeds.
Office for National Statistics (ONS) (1997), New Earnings Survey 1997. The Stationery Office, London.
Openshaw, S. and L. Rao (1995), `Algorithms for reengineering 1991 Census geography.’ Environment and Planning A, 27, 425–446.
Orcutt, G.H., Mertz, J. and Quinke H. (eds.) (1986), Microanalytic Simulation Models to Support Social and Financial Policy. North-Holland, Amsterdam.
Pham, D.T. and D. Karaboga (2000), Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks. Springer, London.
Philo, C. (ed.) (1995), Off the Map: The Social Geography of Poverty in the UK. Child Poverty Action Group, London.
Pinch, S. (1997), Worlds of Welfare: Understanding the Changing Geographies of Social Welfare Provision. Routledge, London.
The Guardian (2000a), The Difference in Your Pocket. 22 March, 2000.
The Guardian (2000b), Budget: The Main Points. 22 March, 2000.
The Guardian (2000c), Common Sense for Pensioners, William Hague’s Full Speech to the LSE. 24 May, 2000.
The Guardian (2000d), Hague’s Pension Plans `Rob Peter to pay Paul’. 24 May, 2000.
Unrau, Y.A. (1993) Expanding the role of program evaluation in social welfare policy analysis. Evaluation Review, 17, 653–662.
Van Laarhoven, P.J.M. and E.H.L. Aarts (1987), Simulated Annealing: Theory and Applications. Kluwer Academic Publishers, Dordrecht.
Williamson, P. (1992), Community Care Policies for the Elderly: A Microsimulation Spproach. Unpublished Ph.D. Thesis, School of Geography, University of Leeds, Leeds.
Williamson, P., M. Birkin and P. Rees (1998), `The estimation of population microdata by using data from small area statistics and samples of anonymised records.’ Environment and Planning A, 30, 785–816.
Williamson, P. and D. Voas (2000), Income imputation for small areas: interim progress report. Paper presented at the conference Census of Population: 2000 and Beyond, Manchester.
Wong, D.W.S (1992), `The reliability of using the iterative proportional fitting procedure.’ Professional Geographer, 44, 340–348.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Ballas, D., Clarke, G.P., Turton, I. (2003). A Spatial Microsimulation Model for Social Policy Evaluation. In: Boots, B., Okabe, A., Thomas, R. (eds) Modelling Geographical Systems. The GeoJournal Library, vol 70. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2296-4_8
Download citation
DOI: https://doi.org/10.1007/978-94-017-2296-4_8
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6104-1
Online ISBN: 978-94-017-2296-4
eBook Packages: Springer Book Archive