Work in ProgressNA-242 Globalization Study

Network Analysis Concepts for Technology Diffusion Through Trade

Tom Wood - PNNL

DOE-NA-242 Multilateral Team Meeting

Globalization Project

P h ase 1Tota l trad e

P h ase2S en s it ive Trad e

Trad e F lows Task In d u s try O u tlook Task O th er P R A P p rod cu c ts

G lob a liza tion P ro jec t

The Issues

• Which countries represent high risks for secondary transfers (transshipment, re-export, reverse engineering, etc.) of sensitive technology?

• How is this dependent on [1] country of origin, [2] ultimate destination, [3] nature of technology?

• What is globalization doing to the technology transfer network?

• What sort of control regime can effectively address this problem?

Premise

• Network models best represent the relevant features of diffusion of nuclear and other sensitive technology– Large number of actors

– Immense number of transactions

– Well-defined but mutable “structure” in network

– Barriers, partitions, and clusters

– Scalable – applicable to entities at individual, firm, industry, and country scales

– Can represent transmission of hardware, specs, information, etc.

Latent Distance MeasuresBackground and Relevance

• Concept of “latent” (unobservable but estimable) distances and spaces is emerging in social network analysis literature (Hoff, Raferty, and Handcock 2001)

• Published approaches (that I have seen) assume a “normed” space – i.e. with a metric measure of distance.

• Extension of this concept to non-metric spaces captures the essence of our technology diffusion problem.

• We are using this as a descriptive (not an inferential) framework for now.

Network Identification for Trade Flows Problem – iteration 1

Select DataFit or Select

Relational Model

Screen for Relevance

Code to HTS or other system

Sensitive Technology Lists

Set Constraints

Critical Examination

Transactions

UN-OCED

DOTS

transaction

Sectoral

Calculate Distances

Solve Shortest Path Problem

Structure and

Parse Network

Figure 1. Scheme for Preliminary Calculations

Gravity Models and Economic Distances

Gravity Models are the standard for predicting bi-lateral trade flows.The general form is:

Tij = [ (Ai * Aj ) ]/ dij

or dij = [ (Ai * Aj)/Tij]

1/

 

Where A is some measure of activity (“economic mass”) and d is distance. The term gravity model is from the analogy to Newton’s formula for gravitational force.

Typically, these models are fit to minimize error in an estimate of Tij.

We take T and A as given to calculate dij.

In this context, dij represents more than physical distance – ie “effective” or “implicit” or “latent” economic distance.

Internal Average SCL Economic Distance - Gravity Model

1000

11000

21000

31000

41000

51000

61000

71000

81000

91000

Russia

n Fed

erat

ion

Tajikis

tan

Turkm

enist

an

Uzbek

istan

Kazak

hsta

n

Ukrai

ne

Belar

us

Syrian

Ara

b Rep

ublic

Azerb

aijan

Isra

el

China

, P.R

.

Geo

rgia

Sudan

Pakist

an

Mol

dova

Kyrgy

z Rep

ublic

Armen

iaIn

dia

China

, Hon

g Kon

g

Iran,

Islam

ic Rep.

Alger

ia

Figure 4. Internal SCL Economic Distances

Avg Economic Distance - NSG to SCL Countries - Gravity Model

1000

11000

21000

31000

41000

51000

61000

71000

81000

91000

Figure 5. NSG to SCL Distances – Sorted by NSG

Figure 6. Direct vs. Indirect Distances

Indirect ED <= Direct ED

Direct ED < Indirect ED

Histogram – Number of Intermediate Countries in Shortest Paths from NSG to SCL case 138.b14

“Joining Tree” for World Economy – Based on ED relationships

Shortest Paths for Four Selected NSG to SCL Pairs

Sensitivity of Shortest Paths to Model Parameters

Shortest Path AnalysisSome Preliminary Observations

• In all cases, the set of intermediate countries on the shortest path set is compact, and moderately to highly skewed. Typically, a dozen countries account for about 70% of the total instances.

• In most cases, the set of intermediate countries is highly disjoint from both the NSG and the SCL.

• In many cases, scale effects appear to give implausible shortest paths. Very small countries with a high degree of economic dependence (e.g. islands) have very short distances both among themselves and to more developed counties (particularly their former colonial masters).

GEOGRAPHIC AND ECONOMIC DISTANCE ELASTICITIES BY SECTOR

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

-1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0

Geographic Distance Regression Coefficient

Ec

on

om

ic D

ista

nc

e R

eg

res

sio

n C

oe

ffic

ien

t

Dairy

Pharmaceuticals

precision, optical inst.

Scientific & Medical Equip.

Chemicals, petrol refining

Industrial chems

Radio, TV

Aircraft

Non-ferrousMetals

Paper

Automotive

Plastics

Tubes, Pipes

Cement

Shipbuilding

Soaps, detergents

Wire

Tires

Agriculturalmachines

MeatYarns

Lime, Clay products

Stone Products

Knitting

Iron & Steel Foundries

Tobacco

Sector Namexxx

Sector Geographic/Economic Distance Coefficients

Next Steps

• Build the data set for the “Sensitive Technology sector” based on LANL coding of lists to HTS.

– Which lists do we wish to use? (all, all nuclear, etc.)– Parse country list to exclude very small and or backward countries –

• Unless of special interest – let me know

• Characterize the R&D intensity and concentration of this sector – (Pick the economic model on which to base the distance measures)

• Calculate measures, solve and analyze shortest paths • MLT workshop to explore policy implications

• .

Some Possible Policy Ideas

• “Special Status” for selected countries posing high risk for re-transfer

– Unilaterally

– Multilaterally

• “Export Substitution” – A policy of identification and incentivized transfer of technology which has a high substitutability in legitimate uses and low substitutability in weapons uses.

Selected Literature

Morstein, Jennifer Hunt and Wayne D. Perry. 2000. Commercial Nuclear Trading Networks as Indicators of Nuclear Weapons Intentions. The Nonproliferation Review/Fall-Winter 2000, Monterey, California.  Conley, Timothy G. and Ethan Ligon. Economic Distance and Cross-Country Spillovers. Unpublished Monograph, University of Chicago Department of Economics. 2001.  Van Houtum, Henk. Borders, Distances, and Spaces – A typology of borders in terms of distances. Proceedings of European Regional Science Association. Dublin 1999.  Boisso, dale and Michael Ferrantino. 1997 Economic Distance, Cultural Distance, and Openness in International Trade: Empirical Puzzles. Journal of Economic Integration.  Sen, Ashish and Tony Smith. 2002. Gravity models of Spatial Interaction Behavior. Springer-Verlag. Berlin. [LCN 95035034]  Haynes, Kingsly E. Gravity and Spatial Interaction Models. Sage Publications. 1984.[LCCN 84050799]

Handcock, M.S. 2002. Degeneracy and Inference for Social Network Models. Working paper, Center for Statistics and the Social Sciences. University of Washington [csss.washington.edu] Priebe, Volker. 2001. Average Case Complexity of Shortest Path Problems. Dissertation. University of Saarlandes