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Modeling Nuclear Proliferationfor the Purpose of Warning

Presenter

Chul Min Kim

Master’s Course Student

NENS Laboratory

Dept. of Nuclear and Quantum Engineering, KAIST

12th Oct. 2014

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Modeling Nuclear Proliferation for the Purpose of Warning

Collaborators

• Man-Sung Yim, Professor of Nuclear and Quantum Engineering, KAIST

• Hyeon Seok Park, Professor of Humanities and Social Science, KAIST

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Contents

1. Introduction2. Proliferation Modeling3. Determinants of Nuclear Proliferation4. Current Research Development Status5. Future Research Objectives6. Conclusion

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• South Korea

• The only country to date to have transitioned from aid recipient to aid donor (in 2009)

• Member of IAEA• Member of NPT• The host of 2010 G20 Summit• The host of 2012 Nuclear Security Summit • Nuclear exporter • Nuclear nonproliferation is very important for the nation’s

continuing nuclear power development

• KAIST NEREC (Nonproliferation Education and Research Center)

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South Korea and Nonproliferation Studies

1. Introduction


1. Introduction

• NEREC of Korea Advanced Institute of Science and Technology (KAIST) is the sole university organization in Korea with the goal of fostering international nuclear non-proliferation conducive to peaceful use of nuclear technology.

• Main activities of NEREC are:

(1) to train and nurture non-proliferation human resources

(2) to conduct non-proliferation policy research combining technical expertise and policy insights

(3) to lead discussions on the peaceful use of nuclear technology and various aspects of nuclear non-proliferation.

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Nonproliferation Education and Research Center (NEREC)(Director: Man-Sung Yim)


• Can Nuclear proliferation risk of a country can be calculated?

• Quantitative modeling of a state’s nuclear proliferation risk

• Currently based on human judgments

• Potentially subjective to human biases

• Warning for the international community

• Past efforts have shown the possibility.

• Still the efforts have limitations.

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Modeling Nuclear Proliferation

1. Introduction


• Why do States Develop Nuclear Weapons?

• Systematic understanding of the determinants of nuclear proliferation

• Review previous models

• Related researches about proliferation history, variable selection, modeling method, and limitations

• Current research in KAIST NEREC

• Future Research Topics

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Scope of the Presentation

1. Introduction


2. Proliferation Modeling

• Meyer’s pioneering work (1984), Stoll (1996), Gartzke and Jo (2007)

• Use 10/9/7 indicators of necessary conditions for the production of nuclear weapons.

• Tried to define ‘latent nuclear capability’ countries.

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Nuclear Capability and Latency Studies

Meyer Stoll Gartzke and Jo

Target year 1982 1992 2001

# of Latent

countries34 48 45



• Some studies deal with “Nuclear Latency” issue –“how quickly a country can make nuclear weapon”.

• Wohlstetter et al. (1979), Harney et al. (2006), and G. L. Coles et al (2005)

• Analyze the nuclear infrastructure of the country.

• Sagan (2010) summarized and evaluated the related studies.

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• New latency studies at Texas A&M

• Based on pathway analysis of proliferation• Bayesian Network, agent-based modeling, etc.• Consider both capacity variables and

state’s motivation variables.

• See http://nsspi.tamu.edu/topical-subsections/research/research-areas/proliferation-risk-analysis

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• Singh and Way (2004) divided the development of the weapon into 4 levels.

• 23 exploration, 16 pursuit and 9 acquisition countries from 1945 to 2000

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Proliferation Risk Level Analysis

Level Name Description

0 No interest No proliferation attempts

1 ExplorationCountry considered nuclear weapons and conducted some

exploratory work

2 Pursuit Country started a nuclear weapons development program

3 Acquisition First explosion/assembly of nuclear weapon



• Proliferation history analyses

• In most studies, analysis method is comprised of:Multinomial logistic analysis, Weibull survival analysis, Cox survival analysis, and Rare Events logistic analysis

• G. A. Coles et al. implemented Bayesian Network Modeling

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# of Proliferation

Countries

Singh and Way

(2004)

Gartzke and Jo

(2007)Bleek (2010)

Covering Year 1945-2000 1941-2002 1929-2005

Exploration 23 21(“Program”) 30

Pursuit 16 16

Acquisition 9 9(“Possession”) 9

Proliferation Risk Level Analysis



• Uncertainties in the history data• Proliferation history modeling has large uncertainty.• When does a state ‘be a nuclear state’?

• Coefficient of the variables changes much when the history data changes.

• Proliferation history itself has large uncertainty.(Debates about Argentina’s nuclear program)

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Uncertainties in Proliferation Modeling



• Uncertainties in variable selection• Current variables were chosen from existing dataset• Similar variables exist -> correlation among the variables

• Efforts should be made to develop the effective variables based on the comprehensive review of the history.

• Blank data problem in specific years and countries

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• Uncertainties in modeling methods• How many countries should we analyze? • All countries in the world or some capable countries?

• Limitations of the event history modeling• Small number of proliferation cases• Repeated nuclear weapons program (e.g. India)

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• Numerous attempts have been made to find the determinants of nuclear proliferation.

• Several categories

• Capability of the country (industrial, technological, economic)• Nuclear cooperation between countries or including

international institutions• “Motivation” variables – domestic politics, international

security, international norms, etc.• The mechanism is still not well understood.

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Why do States Build Nuclear Weapons?

3. Determinants of Nuclear Proliferation


• Binary indicators in capability studies(10 variables in Meyer, 9 variables in Stoll, 7 variables in Gartzke and Jo)

• Did not consider the material accessibility

• Economic and nuclear technology variables in proliferation risk studies

• GDP, GDP2, GDP per capita, industry capability indicator• Li and Yim (2010) used nuclear technology variables as

independent variable

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Capability (“Supply-side”) Variables



• Researches deal with technological assistance from outside of the country

• Kroenig (2009a) – sensitive nuclear assistance• Fuhrmann (2009) – peaceful nuclear technology cooperation• Brown and Kaplow (2014) – IAEA’s fuel cycle-related

technical cooperation (TC) programs

• Further researches should deal with various technological assistance cases

• Effectiveness of illicit trafficking of nuclear materials on the nuclear weapons programs is still not known

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Capability (“Supply-side”) Variables



• Why do states try to build nuclear weapons?• Most proliferation risk modeling studies have variable set based

on motivation variables.

• We categorize the variables into domestic politics and international politics.

Researcher Categorization

Singh and Way External and domestic determinants

Gartzke and Jo“Willingness” – international security,

domestic politics, norms, and status

BleekSecurity Motivations, institutional constraints,

status motivations, and domestic politics

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Motivation (“Demand-side”) Variables



• Domestic politics – regime type, leader analysis, etc.

• Current Polity IV – easy to understand and implement• Problem in the analysis – democracy increases risk?

• Importance of leader’s characteristics• Hymans (2006) Rublee (2008), O’Reilly (2012)• Way and Weeks (2014) argue

personalistic dictatorships are more likely to pursue nuclear weapons, based on quantitative research.

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• International relations – rivalry states, dispute data, security guarantee, etc.

• Previous researches focus on the • Existence of rivalry states• Rivalry state’s nuclear proliferation status• Dispute data in MID (Militarized Interstate Disputes)• The affinity of nations using UN General Assembly voting data• Existence of nuclear security guarantees

• However, no common findings of the determinants among the researches.

• Future researches should be linked with domestic politics.

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• Researches consider the determinants either from the capability side or motivation side.

• Decision affects the capability, and capability affects the decision – however, we do not have enough knowledge.

• Three main issues

• Role of international norms• Relationship between civilian nuclear power industry

and nuclear proliferation• Impact of nuclear weapons deployment

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Relationship Between Capability and Motivation


Modeling Nuclear Proliferation for the Purpose of Warning4. Current Research Development Status

• Based on Li and Yim’s work (2010) and taking into account Sagan’s argument, several variables were added.

• Expanded the previous dataset and collected various data set by characterization of the history .

• Enhanced result of the modeling capability is observed.

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Modeling Effort in KAIST NEREC

Total 117 cases Multinomial Weibull Cox

ScoreModel

improved

Model did

not improve

Model

improved

Model did

not improve

Model

improved

Model did

not improve

“Exploration” 6 1 5 0 4 4

“Pursuit” 9 1 10 1 7 4

“Acquire” 8 0 1 1 12 0

Total 23 2 16 2 23 8


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Pursuit case of Country A


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Explore case of Country B

Modeling Nuclear Proliferation for the Purpose of Warning5. Future Research Objectives

• Real time analysis & prediction issue

• Can the necessary variable set and data be constructed and updated annually?

• Can time-dependent analysis be made?• Can the proliferation behavior of a state be predicted?• Network analysis should be developed.

• Determinants of nuclear renunciation

• Why would a country renounce nuclear weapons?• How can a country be persuaded to renounce nuclear

weapons program? • Muller and Schmidt (2010) claims the key role of the NPT.

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New Quantitative Models


6. Conclusion

• Quantitative modeling of nuclear proliferation risk of a country can be useful in decision making process.

• Fundamental limitations of the quantitative study still exist.

• Exploring relationship between capability and motivation will enhance the modeling capability of the model.

• Additional knowledge on the real time analysis, prediction and determinants of nuclear renunciation will expand the view of nuclear proliferation modeling

• Cooperation between qualitative and quantitative researchers will enhance the effectiveness of the model

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Conclusion


Thank You.

Any Questions will be Welcomed.

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