School of Geography
FACULTY OF ENVIRONMENT
Mark Birkin
Professor of Spatial Analysis and Policy
University of Leeds

• What is Spatial Microsimulation ?
• Why is it interesting to the audience at a workshop on Crime, Policing and Society ?

• Introduced to economics in the 1950s by Guy
Orcutt
– Motivated by a desire to understand the distributional consequences of financial policies
(tax, benefits etc)
– Represent individual households or population members rather than array-based aggregates
– Apply rules e.g. person(s) under 18 then allocate child benefit
• Idea enthusiastically adopted by geographers
– also concerned with (spatial) distributions

HB claim no.
Claimant's
NI no.
Claimant
DOB
100284068 JB187699D
102577377 SJ420608A
102535368 JS441324A
100643900 JR946647D
25/01/1905
09/04/1962
07/08/1990
07/06/1980
100076017 ZS062575C 30/08/1938
100243466 YB731969D 27/02/1944
102140780 NW093710C 16/06/1970
102447058 JN815575D 05/07/1981
Tenancy
Type Postcode
1 LS10 4HH
1 LS10 4LW
3 LS16 5AF
3 LS25 2EU
1 LS9 7UD
1 WF10 2HS
1 LS12 4RD
1 LS16 7BD
Passporte d /
Standard
Indicator no. of child dependen ts
2
4
4
4
4
4
1
3
0
0
0
0
1
1
0
2 no. of nonstatus of dependen ts
HB claim at extract
0
0
0
0
1
0
0
0
HB Claim
Entitlement
Start Date
1 07/04/2003
1 14/04/2008
1 07/05/2007
1 21/12/2009
1 12/01/2009
1 07/04/2003
1 27/09/2004
1 27/07/2009
Weekly
Housing
Benefit
Entitleme nt £
5379
5696
9801
11483
3236
4467
5775
5550
Frequenc y of
Payment of HB
Council
Tax Band
1 A
2 A
3 B
3 B
1 A
1 A
1 A
3 A
10011922X JC971278C 22/09/1975
10220693X NS672732B 04/02/1970
102731632 WE225453C 21/10/1958
100060213 YT659048A 24/08/1956
102796419 YP859509C 23/05/1951
100680082 NW410270C 06/11/1970
100100742 JC988101B
ZB813715C
26/09/1975
19/07/1932
102426343 JE274869B 22/07/1976
100143265 NE686652C 27/11/1964
102446188 PX782018C
100506583 JC459247D
04/03/1976
24/02/1917
100711368 JN455169B 21/02/1985
102832964 YB270876A 15/09/1943
102803592 ZP628017A
YT870915C
08/07/1935
17/08/1948
100286603 LT593491C
100109750 JT573102C
08/04/1924
24/02/1982
100721697 JR817278C 18/02/1987
10296873X ES202175A 03/07/1923
102283904 WL028070C 17/01/1960
1 LS7 1DP
1 LS9 0JA
1 LS7 2HH
1 LS5 3PB
9 LS9 6AL
3 LS29 6AA
1 LS7 1HL
7 LS9 6ES
1 LS11 8LD
4 LS17 6WB
1 LS9 6RY
1 LS19 6JA
3 LS15 8BN
3 LS11 7EN
1 LS19 6EB
7 LS22 5LP
1 LS26 9DA
1 LS15 0BP
4 LS8 5NR
4 LS25 1JB
1 LS11 5UP
3
2
4
4
3
4
1
3
1
5
1
2
4
2
4
2
4
1
1
4
5
0
0
0
2
2
0
0
2
2
0
2
0
1
0
0
0
0
2
1
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1 07/04/2003
1 13/09/2010
1 27/10/2008
1 07/04/2003
1 15/06/2009
1 04/10/2004
1 27/07/2009
0
1 02/11/2009
1 27/07/2009
1 07/08/2006
1 07/04/2003
1 31/03/2009
1 20/04/2009
1 16/02/2009
0
1
1
1
1
1
07/04/2003
17/11/2008
27/10/2008
09/11/2009
30/06/2008
5221
5801
5612
4081
10356
14103
4808
0
6039
11473
5922
5723
8833
10356
4033
0
5964
5437
6656
7987
5105
1 A
3 B
1 A
1 B
3 E
3 B
1 A
F
1 B
A
3 A
3 A
1 A
1 A
A
1 A
1 A
3 A
3 C
1 A
A
6039
11473
5922
5723
11885
10356
5322
0
5221
5801
5612
5716
10356
14192
4808
0
6114
5437
6656
10488
5105
Weekly
Eligible
Rent
Amount £
5379
5696
11308
12692
5250
5914
5775
5550

 Easy to generate
 Easy to aggregate
 Easy to link
 Easy to manipulate
 Easy to scale
 Easy to implement
 Easy to project

Kavroudakis D, Ballas D, Birkin M (2012) Using spatial microsimulation to model social and spatial inequalities in educational attainment, Applied Spatial Analysis and Policy, in press.

Tomintz M., Clarke G.P., Rigby J. (2008) The geography of smoking in Leeds: estimating individual smoking rates and the implications for the location for stop smoking services, Area 40(3), 341-353

Spatial microsimulation for rural policy analysis in Ireland: The implications of CAP reforms for the national spatial strategy D. Ballas, G.P. Clarke, E. Wiemers, Journal of Rural Studies 22 (2006) 367–378

Survey
Carry On 7%
Change Route 9%
Change Mode 7%
Change
Destination
23%
54% Unaffected
Scenario 1 Scenario 2
33 wards in central ring with £5 charge
9%
33 wards in central ring with £10 charge
2%
6%
7%
23%
4%
12%
27%
55% 55%
Scenario 3 Scenario 4
69 wards in extended ring with £5 charge
69 wards in extended ring with £5 charge
10%
5%
12%
24%
2%
2%
22%
30%
49% 44%
Birkin M, Malleson N, Hudson-Smith A, Gray S, Milton R (2011) Calibration of a Spatial Interaction
Model with Volunteered Geographical Information, International Journal of Geographical Information
Science, forthcoming.

population statistics
Households
Unemployed (as a % of economically active)
LLTI (%)
Elderly (over 64 years as a % of all individuals)
Economically active (%)
Health problems: Anxiety, depression (%)
“Loneliness” (% with no one to talk to in times of need)
Single person households
Cars/Households ratio
1991 2001 2011 2021
41,855 47,202 51,074 54,796
4.6%
9.5%
2.7%
8.3%
1.8%
5.8%
1.5%
3.9%
34.5% 41.9%
46.2% 49.3%
5.7% 4.8%
6.6% 7.2%
34.4% 42.3%
0.73 0.88
41.3%
55.1%
3.7%
8.8%
43.4%
1.02
45.9%
58.4%
3.8%
11.5%
41.8%
1.03
Ballas, D., Clarke G.P., Dorling D. Rossiter D. (2007) Using SimBritain to model the geographical impact of national government policies, Geographical Analysis, 39(1), 44-77

X Lack of standards
X Lack of software
X Data is messy and heterogeneous
? Strong applications, weak theory
? Challenging ethics
X Tend to be mechanistic

• Need some insights from agent-based modelling to bolster the MSM
– Conceptual and behavioural detail
– Evidence driven and policy rich
• Wu B, Birkin M, Rees P (2008) A spatial microsimulation model with student agents, Computers Environment and Urban Systems, 32, 440-453.
• Jordan, R., Birkin, M., Evans, A. (2011): ‘Agent-based Simulation Modelling of Housing Choice and Urban Regeneration Policy’. In: Bosse, T., Geller, A. and Jonker, C. (eds.), Multi-Agent-Based Simulation XI. Springer, Berlin,
152-166. Malleson and Birkin (2012)
• Malleson N., Birkin M. (2012) Analysis of crime patterns through the integration of an agent-based model and a population microsimulation,
Computers, Environment and Urban Systems, http://dx.doi.org/10.1016/j.compenvurbsys.2012.04.003

MSM-IBM for Crime
Policy Analysis
Explore relationship between house type and residential burglary
• Are certain house types more at risk?
• And do community demographics have an effect?
Burglary rates by Housing Type by OAC Super Group
Neighbourhood cohesion?
?
Low guardianship?
Affluence within disadvantage?

In recent years, criminologists have become interested in understanding crime variations at progressively finer spatial scales, right down to individual streets or even houses. To model at these fine spatial scales , and to better account for the dynamics of the crime system , agent-based models of crime are emerging. Generally, these have been more successful in representing the behaviour of criminals than their victims . In this paper it is suggested that individual representations of criminal behaviour can be enhanced by combining them with models of the criminal environment which are specified at a similar scale. In the case of burglary this means the identification of individual households as targets. We will show how this can be achieved using the complementary technique of microsimulation . The work is significant because it allows agent-based models of crime to be refined geographically (to allow, for example, individual households with varying wealth or occupancy measures) and leads to the identification of the characteristics of individual victims.

• Microsimulation is a proven technique in applied economics and spatial analysis
• Many established applications in housing, health, education, transport...
• Extension to crime is natural and obvious
• Strength of the techniques include applied scale and policy relevance
• Tendency towards rigidity – a more flexible combination of individual based approaches may be the way forward here