Supermodels Supermodels – Gossip from the – Gossip from the

CatwalkCatwalk

John Walker Crime Trends AnalysisJohn Walker Crime Trends Analysisfor the for the OESR/JMAG Justice Modelling OESR/JMAG Justice Modelling

WorkshopWorkshopBrisbane October 2005Brisbane October 2005

Presents…Presents…

Conference Themes: The development and use of models in social and justice organisations.

• The types of models that are of interest include:– Simulation; Spatial; Temporal; Trajectory; Policy;

Economic (cost-benefit analysis), and Resource allocation.

• Models Come in All Shapes and Sizes

• Petite Models e.g.

– Court-room Capacity models, Staffing Needs models

• Size 16-26 Models e.g.

– Justice System models, Accessibility models, Funding Allocation models

• B – I – B “Supersize me” Models e.g.

– Transnational Crime, Drugs & Money Laundering models

EveryEvery Aussie knows the fundamentals Aussie knows the fundamentals of Modelling.of Modelling.

• Aussie newspapers – even the tabloids - are filled with databases and regression models, and Aussies study them carefully.

• Aussies recognise that this set of numbers represents:[a] a mediocre level of kicking accuracy, and[b] the regression equation:

Total Score = 6 times the numbers of goals, plus the number of behinds.

• “11.17.83” is a total mystery even to mathematically-minded people elsewhere. To Americans it’s the date in 1983 when Magic Johnson scored 22 assists for Cleveland against the L.A. Lakers – who cares!

• 11.17.83 ?11.17.83 ?• 11.17.83 ?11.17.83 ?• We write this as:We write this as:

TS = 6*G + 1*B + 0TS = 6*G + 1*B + 0

• Databases, Algebra and Regression Equations

• Incomprehensible statistical stuff ?

• Aussies know more than they think Aussies know more than they think

they do!they do!

Regression Analysis - Regression Analysis - natural way to look at datanatural way to look at data

• Just suppose we don’t know exactly how the total match points were Just suppose we don’t know exactly how the total match points were calculated. calculated.

• We might look at the table and think that the number of wins or the We might look at the table and think that the number of wins or the number of points for seem to be the most significant determinants of TMP. number of points for seem to be the most significant determinants of TMP.

• The charts support our first hypothesis rather than our second. The charts support our first hypothesis rather than our second. • The RThe R22 measures how closely the points are to the lines. measures how closely the points are to the lines.

Regression Relationship between Match Points and Games Won

Collingw ood

Carlton Haw thorne/ Brisbane/ Essendon

Port AdelaideFremantle/St.Kilda/

W. Bulldogs

Adelaide/Sydney /Kangaroos

Melbourne

Geelong/Richmond

W.C. EaglesR2 = 0.9896

0

5

10

15

20

25

30

35

0 1 2 3 4 5 6 7 8 9Number of Wins

Nu

mb

er

of

Ma

tch

Po

ints

Regression Relationship between Match Points and Points For

W.C. Eagles

Richmond

Melbourne

Kangaroos

W. Bulldogs

Geelong

Fremantle

St.Kilda

Sydney Adelaide

Port Adelaide

Essendon Haw thorneBrisbane

CarltonCollingw ood

R2 = 0.3219

0

5

10

15

20

25

30

35

0 200 400 600 800 1000 1200Points For

Nu

mb

er

of

Ma

tch

Po

ints

456.5

PointsForTMP Hypothesis 1: TMP = 4 * Number of Wins + 0 Hypothesis 2:

The AFL Ladder is a The AFL Ladder is a DatabaseDatabase

2-stage regression model:2-stage regression model:• F=6*G + B + 0F=6*G + B + 0• TMP = 4*W + 2*D + 0TMP = 4*W + 2*D + 0

Club  P W D L F A % Total Matc

h Point

s

West Coast Eagles

9 8 0 1 919 692 133 32

Geelong 9 7 0 2 1034

774 134 28

Richmond 9 7 0 2 922 806 114 28

Melbourne 9 6 0 3 958 862 111 24

Adelaide 9 5 0 4 781 685 114 20

Sydney Swans 9 5 0 4 714 745 96 20

Kangaroos 9 5 0 4 777 873 89 20

Fremantle 9 4 0 5 856 822 104 16

St Kilda 9 4 0 5 862 838 103 16

Western Bulldogs

9 4 0 5 931 933 100 16

Port Adelaide 9 3 1 5 704 823 86 14

Hawthorn 9 3 0 6 835 819 102 12

Brisbane Lions 9 3 0 6 801 875 92 12

Essendon 9 3 0 6 757 885 86 12

Carlton 9 2 1 6 816 1038 79 10

Collingwood 9 2 0 7 757 954 79 8Game characteristics Game characteristics Game Score Game Score Match Points Match Points Ladder position Ladder position Fan Fan

SatisfactionSatisfaction

The Victoria Police Human Resource The Victoria Police Human Resource Allocation Model is a database with the Allocation Model is a database with the

same structure as the AFL laddersame structure as the AFL ladder

Variables selected on the basis of their common sense relationships with Variables selected on the basis of their common sense relationships with policing, their statistical explanatory power, their availability at the district policing, their statistical explanatory power, their availability at the district level and the frequency with which they can be updated:level and the frequency with which they can be updated:- Total population;- Total population; - Numbers of indigenous people - Numbers of indigenous people- Persons aged 20 years and below;- Persons aged 20 years and below; - Population growth rate of people below - Population growth rate of people below the age of 20the age of 20- Retail turnover - Retail turnover - Family violence reports - Family violence reports- Numbers of Liquor Licenses- Numbers of Liquor Licenses - Numbers of Black Spot intersections, - Numbers of Black Spot intersections, - Numbers of Major Events, - Numbers of Major Events, - Numbers of Stations with Police Cells, and - Numbers of Stations with Police Cells, and- Point of Presence Service considerations (how many stations needed to cover the - Point of Presence Service considerations (how many stations needed to cover the district).district).

The Victoria Police HRAM is also a The Victoria Police HRAM is also a two-stage regression modeltwo-stage regression model Stage 1 RegressionsStage 1 Regressions Stage 2 RegressionStage 2 Regression

Equation 1

Equation 2

Equation 3

Equation 4

Equation 5

Community characteristics Community characteristics Crime & Road Trauma Crime & Road Trauma Calls on Police Calls on Police Police Police Resources Resources Public Satisfaction Public Satisfaction

Forecasting in the Justice System….Forecasting in the Justice System….

1324561789

13245617891324561789

13245617891324561789

13245617891324561789

The Projections The Budget

The Scenarios

The Workshop

??????

The Environmental Scan

The Trend Analysis

Trends in Community Characteristics Trends in Community Characteristics Trends in Crime & Road Trauma Trends in Crime & Road Trauma Trends in Trends in Police Responses Police Responses

Trends in Courts Responses Trends in Courts Responses Trends in Correctional Populations Trends in Correctional Populations Strategic Strategic Planning and BudgetingPlanning and Budgeting

Accessibility Modelling for Future Accessibility Modelling for Future DemandDemand

What do we want? Prisons for criminals!

When do we want them? Now!

Where do we want them?Not Near ME! Not Near ME!

DoJ

What do we want? Emergency Services!

When do we want them? Now!

Where do we want them?Near ME! Near ME!

Location of services is important. How can Service Providers respond to these competing and conflicting demands?Trends in Settlement Patterns Trends in Settlement Patterns Trends in Regional Demands for Services Trends in Regional Demands for Services Trends in Trends in

Service Characteristics Service Characteristics Equity & Access considerations Equity & Access considerations Trends in Service Responses Trends in Service Responses Strategic Planning Strategic Planning

and Budgetingand Budgeting

Time to think B-I-B?Time to think B-I-B?

• In the micro and mid-size sections of the In the micro and mid-size sections of the scale, modelling to support “evidence-based” scale, modelling to support “evidence-based” strategic planning is now common in the strategic planning is now common in the criminal justice system in Victoriacriminal justice system in Victoria– Staff allocation models police (Peter Kewu Li)Staff allocation models police (Peter Kewu Li)– Demand Projection and Service Accessibility Demand Projection and Service Accessibility

models for prosecutions, civil and criminal courts, models for prosecutions, civil and criminal courts, prisons, community corrections, sentencing and prisons, community corrections, sentencing and forensic services (See previous JMAG conferences)forensic services (See previous JMAG conferences)

• At the B-I-B end, the U.N. has been told for At the B-I-B end, the U.N. has been told for decades that global modelling of crime and decades that global modelling of crime and justice is not possible. This myth was justice is not possible. This myth was shattered in 2005.shattered in 2005.

Valuing the Global Illicit Drug Markets Valuing the Global Illicit Drug Markets – 1980-2004– 1980-2004

• Numerous attempts to quantify Illicit Drugs markets in the Numerous attempts to quantify Illicit Drugs markets in the past, past,

• The Financial Action Task Force (FATF) estimated in the The Financial Action Task Force (FATF) estimated in the late 1980s, sales of cocaine, heroin and cannabis late 1980s, sales of cocaine, heroin and cannabis approximated $124 billion per year in the US and Europe, approximated $124 billion per year in the US and Europe, equivalent today to some $200 billionequivalent today to some $200 billion

– OECDOECD, FATF Working Group on Statistical and Methods, Narcotics Money Laundering - Assessment of , FATF Working Group on Statistical and Methods, Narcotics Money Laundering - Assessment of Scale of the Problem, 1989,Scale of the Problem, 1989, Financial Action Task Force on Money Laundering, report, 1990. Financial Action Task Force on Money Laundering, report, 1990.

• Based on 1995 drug production estimates, UNDCP arrived at Based on 1995 drug production estimates, UNDCP arrived at a global estimate of $85 billion to $1000 billion [1]. Given a global estimate of $85 billion to $1000 billion [1]. Given this broad range and the uncertain validity of assumptions this broad range and the uncertain validity of assumptions made, UNDCPs’ 1997 World Drug Report, spoke of a likely made, UNDCPs’ 1997 World Drug Report, spoke of a likely turnover of around $400 billion [2]. Questioned by some turnover of around $400 billion [2]. Questioned by some experts as possibly too high. However, no alternative experts as possibly too high. However, no alternative calculations were provided. calculations were provided.

– [1] [1] UNDCP, UNDCP, Economic and Social Consequences of Drug Abuse and Illicit Trafficking, (Technical Series Economic and Social Consequences of Drug Abuse and Illicit Trafficking, (Technical Series 1997)1997). .

– [2] UNDCP, [2] UNDCP, World Drug Report,World Drug Report, (Oxford University Press 1997). (Oxford University Press 1997).

• In the late 1990s, the Financial Action Task Force experts In the late 1990s, the Financial Action Task Force experts could not agree on the most appropriate methodological could not agree on the most appropriate methodological approach - top-down or bottom-up. Recommendations made approach - top-down or bottom-up. Recommendations made to countries to improve data collection systems and to to countries to improve data collection systems and to undertake drug market estimates at the national level. undertake drug market estimates at the national level.

– OECD Financial Action Task Force, OECD Financial Action Task Force, Report of the FATF Ad Hoc Group on Estimating the Magnitude of Report of the FATF Ad Hoc Group on Estimating the Magnitude of Money Laundering on Assessing Alternative Methodologies for Estimating Revenues from Illicit DrugsMoney Laundering on Assessing Alternative Methodologies for Estimating Revenues from Illicit Drugs (2000).(2000).

Valuing the Global Illicit Drug Markets - Valuing the Global Illicit Drug Markets - 20052005

• Information on the value of the drug sector and Information on the value of the drug sector and consequently the analysis of various aspects of the consequently the analysis of various aspects of the implication of money laundering was a gap in the implication of money laundering was a gap in the otherwise comprehensive coverage of the World Drug otherwise comprehensive coverage of the World Drug Report. Report.

• One of the reasons for this is that the measurement of One of the reasons for this is that the measurement of such activities is difficult and prone to criticism. It is, such activities is difficult and prone to criticism. It is, however, a vital element of the global drug control however, a vital element of the global drug control equation. equation.

• Project Outputs: Project Outputs: – An estimate of the value of the retail and wholesale An estimate of the value of the retail and wholesale

markets for heroin/opium, coca/cocaine, cannabis, and markets for heroin/opium, coca/cocaine, cannabis, and Amphetamine-Type Substances, Amphetamine-Type Substances,

– a report documenting these results and methodologies a report documenting these results and methodologies used to derive them, used to derive them,

– a data base, complete documentation of the data base, a data base, complete documentation of the data base, – an evaluation of the feasibility of applying these methods an evaluation of the feasibility of applying these methods

to other illicit markets. to other illicit markets. John Walker Crime Trends Analysis for theJohn Walker Crime Trends Analysis for theUnited Nations Office on Drugs and Crime World Drug Report 2005United Nations Office on Drugs and Crime World Drug Report 2005

Obvious Truths and Heresies…Obvious Truths and Heresies…

• Illicit drugs constitute a trans-national industry, just like the motor Illicit drugs constitute a trans-national industry, just like the motor

industry. industry.

• Both industries market a wide range of products, at a wide range of Both industries market a wide range of products, at a wide range of

prices. prices.

• In both industries, production of key components is concentrated in a few In both industries, production of key components is concentrated in a few

countries, but final products are distributed to many (all?).countries, but final products are distributed to many (all?).

• Both industries are subject to heavy burdens of taxes, regulation and Both industries are subject to heavy burdens of taxes, regulation and

stock shrinkage.stock shrinkage.

• Both industries’ products are addictive and can be dangerous – users Both industries’ products are addictive and can be dangerous – users

build their whole lives around their use, and sometimes shorten them.build their whole lives around their use, and sometimes shorten them.

• To an engineer, a botanist or a chemist, these industries are very To an engineer, a botanist or a chemist, these industries are very

different.different.• To an economist, they are To an economist, they are identicalidentical..

– They have production costs that vary from place to place.They have production costs that vary from place to place.– They produce a range of products that compete for customers, They produce a range of products that compete for customers,

horizontally (e.g. different products) and vertically (different horizontally (e.g. different products) and vertically (different suppliers).suppliers).

– There is price competition and there are substitution effects.There is price competition and there are substitution effects.– They have distribution networks that are subject to a variety of They have distribution networks that are subject to a variety of

economic pressures.economic pressures.– They have marketing strategies that emphasise factors such as They have marketing strategies that emphasise factors such as

customer loyalty (addiction?) and “trendiness.”customer loyalty (addiction?) and “trendiness.”– They are sometimes indifferent to the poor safety features inherent in They are sometimes indifferent to the poor safety features inherent in

their products, which creates the need for regulation.their products, which creates the need for regulation.

Asia  Australasia 

Africa  Europe  S. America  N. America 

Producers 

Asia 

Australasia 

Africa 

Europe 

S. America 

N. America 

Total Produced 

Consumers 

Total Consumed 

Drug Type 3

Asia  Australasia 

Africa  Europe  S. America  N. America 

Producers 

Asia 

Australasia 

Africa 

Europe 

S. America 

N. America 

Total Produced 

Consumers 

Total Consumed 

Drug Type 2

The Structure of the IndustryThe Structure of the Industry

• Many different drug types – new “models” always being Many different drug types – new “models” always being marketedmarketed

• Many different producer countries – different productsMany different producer countries – different products• Many different consumer countries – different Many different consumer countries – different

preferencespreferences• Fits the Multinational Input-Output model frameworkFits the Multinational Input-Output model framework

Asia  Australasia 

Africa  Europe  S. America  N. America 

Producers 

Asia 

Australasia 

Africa 

Europe 

S. America 

N. America 

Total Produced 

Consumers 

Total Consumed 

Drug Type 1

Top-down or Bottom-up Top-down or Bottom-up approach?approach?

• Top-down (start with the row and column totals):Top-down (start with the row and column totals):– Look for global or regional aggregates of Look for global or regional aggregates of

production, consumptionproduction, consumption– Look for global average pricesLook for global average prices– Multiply and sum across drug typesMultiply and sum across drug types

• Bottom-up (start by trying to fill the rows and columns Bottom-up (start by trying to fill the rows and columns of the matrix):of the matrix):– Look for country-level aggregates of production, Look for country-level aggregates of production,

consumptionconsumption– Look for country-level average pricesLook for country-level average prices– Multiply and sum across drug types and countriesMultiply and sum across drug types and countries

• Problems with both:Problems with both:– Few credible findings on global aggregate dataFew credible findings on global aggregate data– Many gaps in country-level dataMany gaps in country-level data

We developed…We developed…

C o n ce p tua l E xce l L in ka g es

H e ro in /O p iumS u b -m o d e l

C o ca /C o ca ineS u b -m o d e l

C a n na b isS u b -m o d e l

A T SS u b -m o d e l

L inkm o d e l

• A set of interconnected Excel spreadsheetsA set of interconnected Excel spreadsheets• One sub-model for each drug typeOne sub-model for each drug type• A Link Model to incorporate theories of drug A Link Model to incorporate theories of drug

substitutability and price elasticities, and to substitutability and price elasticities, and to bring together all the submodels into an bring together all the submodels into an overall model of illicit drugs.overall model of illicit drugs.

• This gives maximum flexibility for future modeling, including:This gives maximum flexibility for future modeling, including:• Ability to add new drug typesAbility to add new drug types• Ability to model different drug types with different process Ability to model different drug types with different process

modelsmodels

A Model like this…A Model like this…

• Is stable and will not become outdated by new Is stable and will not become outdated by new

theoriestheories

• Allows easy and flexible data entryAllows easy and flexible data entry

• Facilitates clear statement of assumptionsFacilitates clear statement of assumptions

• Allows for new drug types (sub-models)Allows for new drug types (sub-models)

• Highlights inconsistencies in input dataHighlights inconsistencies in input data

• Permits extraction of results at any stage of Permits extraction of results at any stage of

production and consumption processesproduction and consumption processes

• Permits aggregation of results to any regional Permits aggregation of results to any regional

structure or across groupings of drug typesstructure or across groupings of drug types

• Allows easy sensitivity analysisAllows easy sensitivity analysis

• Supports forecasting techniquesSupports forecasting techniques

Production and Transfer to Production and Transfer to Markets:Markets:

[1] “Total available for Wholesale” = “Total Production” – “Seizures/losses in [1] “Total available for Wholesale” = “Total Production” – “Seizures/losses in the source country”,the source country”,

andand[2] “Producer Income” = “Total available for Sale” * average “Farm gate price”[2] “Producer Income” = “Total available for Sale” * average “Farm gate price”

In “ Demand-constrained” regions, total consumption is estimated by In “ Demand-constrained” regions, total consumption is estimated by multiplying the estimated numbers of users in the region by the estimated multiplying the estimated numbers of users in the region by the estimated annual consumption per user. This will be generally the case in producer annual consumption per user. This will be generally the case in producer and transit countries and regions, where supply is plentiful relative to and transit countries and regions, where supply is plentiful relative to demand. demand.

[3] “Estimated Actual Consumption” = "Estimated User Population" * "Average [3] “Estimated Actual Consumption” = "Estimated User Population" * "Average Consumption per user ",Consumption per user ",

andand[4] “Total Transferred to Markets” = "Estimated Actual Consumption" + "Total [4] “Total Transferred to Markets” = "Estimated Actual Consumption" + "Total

Seized/Lost at Destination“Seized/Lost at Destination“

In "Supply-constrained" regions, Total Transferred to Markets is estimated In "Supply-constrained" regions, Total Transferred to Markets is estimated from the data on the Total Seized/Lost in Transit, using the research from the data on the Total Seized/Lost in Transit, using the research finding that seizure rates are reasonable indicators of relative finding that seizure rates are reasonable indicators of relative consumption around the world, and are consistent over time. consumption around the world, and are consistent over time.

[5] “Total Transferred to Markets” = "Total Seized/Lost in Transit " / ["Global [5] “Total Transferred to Markets” = "Total Seized/Lost in Transit " / ["Global Seizure rate” * “Regional adjustment"]Seizure rate” * “Regional adjustment"]

In the first step in model calibration, the value for the global seizure rate In the first step in model calibration, the value for the global seizure rate is chosen so that the truism “supply=demand” is achieved:is chosen so that the truism “supply=demand” is achieved:

  [6] ∑“Total Transferred to Markets” [from producers] = ∑“Total available for [6] ∑“Total Transferred to Markets” [from producers] = ∑“Total available for Sale”[in consumer regions]Sale”[in consumer regions]

The Wholesale and Retail The Wholesale and Retail Markets:Markets:

[7] “Total Available for Consumption” = “Total Intended for Consumption” – “Total Seized/Lost [7] “Total Available for Consumption” = “Total Intended for Consumption” – “Total Seized/Lost at Destination”,at Destination”,

andand [8] “Gross Wholesaler Income” = “Total Available for Consumption” * “Wholesale price at [8] “Gross Wholesaler Income” = “Total Available for Consumption” * “Wholesale price at Destination”Destination”  Retailers of illicit drugs, like any other retail business, face “leakage and shrinkage” Retailers of illicit drugs, like any other retail business, face “leakage and shrinkage” problems. Leakage and shrinkage is a euphemism for stock losses from thefts and problems. Leakage and shrinkage is a euphemism for stock losses from thefts and deterioration. Leakage and shrinkage are only a significant issue in supply deterioration. Leakage and shrinkage are only a significant issue in supply constrained regions; in demand constrained regions, by definition, supply matches constrained regions; in demand constrained regions, by definition, supply matches demand. For each supply constrained region, therefore:demand. For each supply constrained region, therefore:  [9] “Estimated Actual Consumption” = "Total Available for Consumption” – “Leakage and [9] “Estimated Actual Consumption” = "Total Available for Consumption” – “Leakage and shrinkage”, shrinkage”,   while if the region is defined as “demand constrained”:while if the region is defined as “demand constrained”:

  [10] “Estimated Actual Consumption” = “Estimated User Population” * “Average Consumption [10] “Estimated Actual Consumption” = “Estimated User Population” * “Average Consumption per user”,per user”,

If the calculated usage rates are inconsistent with other findings, it is likely that If the calculated usage rates are inconsistent with other findings, it is likely that there are related to assumptions regarding seizure rates, and these should be there are related to assumptions regarding seizure rates, and these should be reconsidered. Then, in all regions:reconsidered. Then, in all regions:  [11] “Implied Consumption per user” = “Estimated Actual Consumption” / “Estimated User [11] “Implied Consumption per user” = “Estimated Actual Consumption” / “Estimated User Population”.Population”.  Once, the user is satisfied that the model is providing credible estimates of Once, the user is satisfied that the model is providing credible estimates of consumption per user in all regions, gross retailer income can now also be consumption per user in all regions, gross retailer income can now also be calculated:calculated:  [12] “Gross Retailer Income” = “Estimated Actual Consumption” * “Average Unit Retail Price”[12] “Gross Retailer Income” = “Estimated Actual Consumption” * “Average Unit Retail Price”

UNODC Illicit Drugs UNODC Illicit Drugs model………model………

Table 1. Production and Distribution from Source Countries to Destination Countries

Consumer Regions

Producer Regions

Total Production in

Source Country

(Kg Heroin Equiv)

Total Seized/Lost in Source Country

(Kg Heroin Equiv)

Total Available for Sale

(Kg Heroin Equiv)

Transferred to Markets

(Kg Heroin Equiv)

Total Seized/ lost in Transit

(Kg Heroin Equiv)

East Africa 0 0 0 2,293 47 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0North Africa 714 0 714 3,410 35 0 714 0 0 0 0 0 0 0 0 0 0 0 0 0 0 714Southern Africa 0 0 0 1,099 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0West and Central Africa 0 0 0 9,954 51 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Caribbean 0 0 0 364 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Central America 0 0 0 783 180 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0North America 8,400 209 8,191 28,735 6,621 0 0 0 0 0 0 8,191 0 0 0 0 0 0 0 0 0 8,191South America 5,268 440 4,829 3,255 399 0 0 0 0 0 0 1,574 3,255 0 0 0 0 0 0 0 0 4,829C. Asia & Transcaucasus 770 0 770 12,076 2,748 0 0 0 0 0 0 0 0 770 0 0 0 0 0 0 0 770East and South-East Asia 94,050 582 93,468 59,928 6,885 240 267 119 1,076 39 85 2,050 0 1,222 59,928 0 6,663 9,483 10,508 1,028 762 93,468Nr & M.East /SW Asia 365,150 9,551 355,599 78,352 27,723 2,053 2,429 980 8,878 325 698 16,920 0 10,084 0 78,352 55,003 78,283 86,740 9,180 5,673 355,599South Asia 0 0 0 61,666 252 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Eastern Europe 2,147 0 2,147 89,913 923 0 0 0 0 0 0 0 0 0 0 0 0 2,147 0 0 0 2,147Western & Central Europe 0 0 0 97,248 3,994 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0South East Europe 0 0 0 10,208 4,713 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Oceania 0 0 0 6,436 198 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0All Countries 476,500 10,781 465,719 465,719 54,856 2,293 3,410 1,099 9,954 364 783 28,735 3,255 12,076 59,928 78,352 61,666 89,913 97,248 10,208 6,436 465,719

N Africa

S America

E & SE Asia

C Asia &

Transcaucasus

C America

N America

E Africa

S Africa

W & C Africa

E Europe

W & C Europe

SE Europe

Oceania

Caribbean

Near & Middle

East /SW Asia

S Asia

All Countries

Table 2. Supply and Demand in Destination Countries

RegionsE Africa

N Africa

S Africa

W & C Africa

Caribbean

C America

N America

S America

C Asia &

Transcaucasus

E & SE Asia

Near & Middle

East /SW Asia

S Asia

E Europe

W & C Europe

SE Europe

Oceania

All Countries

0 714 0 0 0 0 8400 5268 770 94050 365150 0 2147 0 0 0 4765000 0 0 0 0 0 209 440 0 582 9551 0 0 0 0 0 107810 714 0 0 0 0 8191 4829 770 93468 355599 0 2147 0 0 0 4657190 0 0 0 0 0 0 0 0 1339 2830 0 0 0 0 0 2520

0 2 0 0 0 0 21 12 2 125 1006 0 5 0 0 0 1173

2293 3410 1099 9954 364 783 28735 3255 12076 59928 78352 61666 89913 97248 10208 6436 46571947 35 7 51 80 180 6621 399 2748 6885 27723 252 923 3994 4713 198 54856

2246 3375 1092 9903 285 603 22113 2856 9328 53042 50629 61413 88990 93254 5496 6237 41086328 42 28 15 38 73 98 25 21 38 7 71 36 73 26 140 5063 142 30 153 11 44 2175 71 194 2022 379 4355 3198 6779 145 874 20635

84 108 85 524 21 24 1301 286 370 2105 2009 3102 2406 1450 180 99 14154.32021 3038 983 8913 285 603 22113 2856 9328 53042 50629 61413 80091 83929 5496 5614 39035324.2 28.0 11.5 17.0 13.5 25.2 17.0 10.0 25.2 25.2 25.2 19.8 33.3 57.9 30.6 56.5 27.6

40 124 81 57 41 83 402 101 51 108 12 123 133 302 183 561 16682 377 80 508 12 50 8886 288 480 5725 596 7567 10681 25340 1006 3148 64825

0 2 0 0 0 0 21 12 2 125 1006 0 5 0 0 0 1173- 30 - - - - 620 71 12 1,942 157 - 76 - - - 2908

38 84 18 153 7 44 1311 0 60 0 0 4355 2175 5729 37 803 1481319 236 49 355 1 6 6711 217 286 3703 217 3212 7483 18560 861 2274 4419157 351 68 508 8 50 8663 300 360 5770 1381 7566 9739 24290 898 3076 63085

International Wholesalers' Income less Purchase CostsNet Retailer Profit (US$mill)

Gross Value of Regional Trade

Retailer Income (US$mill)

Regional Net Values:Source Country Producers' Income

Source Country Wholesalers' Income less Purchase Costs

Estimated User Population (Thousands)Estimated Actual Consumption per year (Kg Heroin Equiv)

Implied Consumption per user (gms Heroin Equiv)Average Retail Price US$ /gm

Wholesale price at Destination US$ /gmWholesaler Income (US$mill)

Demand:

Producer Income (US$mill)

Supply:Total Intended for Consumption (Kg Heroin Equiv)

Total Production in Source Country (Kg Heroin Equiv)Total Seized/Lost in Source Country (Kg Heroin Equiv)

Total Available for Sale (Kg Heroin Equiv)Farmgate Price at Origin (US$/Kg Heroin Equiv)

Total Seized/Lost at Destination (Kg Heroin Equiv)Total Available for Consumption (Kg Heroin Equiv)

Production:

Meaningful policy information Meaningful policy information (at last!)(at last!)

The Geographic The Geographic DimensionDimension

Using Transportation Maths to Using Transportation Maths to Analyse Transnational Crime Analyse Transnational Crime

and Illicit Drugsand Illicit Drugs

John WalkerJohn Walker

March 2005March 2005

Towards a “Trafficking Harm Towards a “Trafficking Harm Index”Index”

• Harm is caused by Illicit Drugs/firearms/people Harm is caused by Illicit Drugs/firearms/people trafficking, etc etc)trafficking, etc etc)– In the country of origin/production:In the country of origin/production:

• Diversion of economic activity into crimeDiversion of economic activity into crime• Corruption/violence to protect illegal activitiesCorruption/violence to protect illegal activities• Easy availability of trafficked good/services in Easy availability of trafficked good/services in

domestic marketdomestic market– In the country of destination/consumption:In the country of destination/consumption:

• Diversion of economic activity into crime; Diversion of economic activity into crime; excess profits to criminalsexcess profits to criminals

• Corruption/violence to protect illegal activitiesCorruption/violence to protect illegal activities• Health/poverty impacts of trafficked Health/poverty impacts of trafficked

good/servicesgood/services• This harm can generally be measured fairly directly This harm can generally be measured fairly directly

as economic costs in the origin and destination as economic costs in the origin and destination countriescountries

Towards a “Trafficking Harm Towards a “Trafficking Harm Index”Index”

• Harm is ALSO caused by Illicit Harm is ALSO caused by Illicit Drugs/firearms/people trafficking, etc etc)Drugs/firearms/people trafficking, etc etc)

– In the countries through which the trafficked In the countries through which the trafficked goods/services transit:goods/services transit:

• Mainly corruption/violence to ensure passage Mainly corruption/violence to ensure passage of illegal goods/servicesof illegal goods/services

• To measure this harm, we need to:To measure this harm, we need to:

– Identify the transit routes taken by the Identify the transit routes taken by the traffickerstraffickers

– Allocate harm according to some logic – eg Allocate harm according to some logic – eg proportionate to the fraction of the trafficked proportionate to the fraction of the trafficked goods/services that use each country in transit.goods/services that use each country in transit.

Towards a “Trafficking Harm Towards a “Trafficking Harm Index”Index”• A general model that can “predict” trafficking route options A general model that can “predict” trafficking route options

would need to consider that:would need to consider that:– Transnational trafficking (by definition) crosses Transnational trafficking (by definition) crosses

international borders by land, sea or airinternational borders by land, sea or air– Land or sea transport routes permit bulky goods; air Land or sea transport routes permit bulky goods; air

transport generally doesn’ttransport generally doesn’t– Some countries’ borders are more “porous” than othersSome countries’ borders are more “porous” than others

– Land routes can only connect pairs of “contiguous” Land routes can only connect pairs of “contiguous” countriescountries

– Sea routes can only connect sea portsSea routes can only connect sea ports

Contiguous countries

Shipping links

Country CCountry B

Country A

Towards a “Trafficking Harm Towards a “Trafficking Harm Index”Index”

Some “beautiful” maths starts with a simple “link/no link” matrix• This particular matrix is very special, because if you multiply it by itself, it gives the number of routes between pairs of countries VIA A THIRD country. All routes can be identified by the list of countries they pass through. • The possible routes between A and D are - A(E)D and A(B)D• The possible routes between G and F are - G(C)F, G(ED)F and G(CBD)F …and so on.• If we know that a quantity of drugs, firearms or laundered money travels from G to F, it can take these routes.• Harm is scattered along its trail.

Destination →

Origin ↓

Country A

Country B

Country C

Country D

Country E

Country F

Country G

Country A * 1 0 0 1 0 0

Country B 1 * 1 1 0 0 0

Country C 0 1 * 0 0 1 1

Country D 0 1 0 * 1 1 0

Country E 1 0 0 1 * 0 1

Country F 0 0 1 1 0 * 0

Country G 0 0 1 0 1 0 *

Country ECountry D

Country G

Country F

Towards a “Towards a “Trafficking Trafficking Harm Harm Index”Index”