Economic Analysis for DHS:Microeconomic/Macroeconomic Modeling, Simulation, and Analysis

Briefing to The White HouseWashington, D.C.May 10, 2006

Mark A. Ehlen, Ph.D.Computational Economics GroupNational Systems Modeling & AnalysisSandia National LaboratoriesAlbuquerque, NMmaehlen@sandia.gov

Real DHS problems drive NISAC economic analyses

Natural disastersHurricanes: Isabel, Dennis, Ivan, Frances,

Katrina, Rita, Wilma, Pre-Hurricane SeasonAnalysis (ongoing)

Earthquake: Seattle (2005)Bio: Impacts of pandemic influenza (Table Top

Exercise), smallpox (2006), BSE (2003)

Infrastructure disruptionsImpacts of Pacific Northwest port shutdown

(2003)Impacts of rail disruptions on chemical industry

(2003)Impacts of U.S. airspace disruptions (2005

Senior Officials Exercise)Impacts of pandemic influenza on critical

infrastructure performance (ongoing)Impacts of Soo Lock disruption on regional

economies (2006)

Value chainsChemical industry (2003 chlorine, 2004 TIH)Goodyear global supply chain (ongoing)Impacts of regional disruptions on food industry

(ongoing)Impacts of AI on medical/food industries

(forthcoming)

Financial and other marketsImpacts of infrastructure disruptions on payment

system functions (ongoing)Impacts of terrorism on commodity futures

markets (ongoing)Effects of rolling brownouts on California electric

power markets (ongoing)

Public policyAsset prioritization (2006)State grants process (2005)

DHS requests are for macroeconomic and microeconomic impacts

MacroeconomicDomestic

GDP, employment, incomePrice levels (CPI, producer prices)By industrial sector, state

InternationalGNP, changes in growth ratesChanges in current account (trade

flows) and capital account (financialflows), exchange rates

MicroeconomicClasses of firms impacted most

By industry, firm size, corporatestructure, economic preparedness

Chemical, food, medical industrieschanges to production, inventories,

shipments, profitability

Regional/national agent-based microeconomic (N-ABLE)

These requests drive NISAC analytics and tool development

2003 2004 2004 2005 2006

Regional/national econometricmacroeconomic (REMI)

Internationaleconometric macro

National system-dynamicsmacroeconomic (CIPDSS)

Economic insightInfrastructure insight

NISAC and CIPDSS infrastructure analysis

Benefit-costanalysis

year

domain

2007

NISAC macroeconomic tools

REAcctInput-output and CGE-based methodology forestimating first-order direct/indirect impacts of man-made/natural disasters

Generally for short-run, temporary business disruptions

REMI50-state + WDC, 70-industry econometric IO model

CGE, Keynesian, historically observedoutput/employment/price conditions.Most heavily documented, peer-reviewed macroeconomicmodel availab le

DHS applications:Hurricane Katrina, Rita, MANPAD, pandemic influenza,state grants process

World Economy ModelREMI, G-Cubed, GEM, or Yale MCU econometricmodel.

~80% of world GNP, 10-industryDHS applications:

Pandemic influenza

Problem-driven tool development: REAcct

PurposeTo automate the process of (1) identifying economic firmsdirectly impacted by disruptions, (2) estimating direct andindirect impacts, and (3) conducting sensitivity analysis of theseestimates to changes in disruption assumptions.

Data sourcesCounty Business Patterns, GDP-by-Industry Data, NationalIncome and Product Accounts, RIMS II multipliers, research.

MethodologyA combination of input-output and supply chain effects models;future extensions will include techniques that capture on-siteand in-transit inventory effects, regional purchase coefficients,and infrastructure disruption effects captured by other NISACinfrastructure and economic models.

ApplicationsNISAC FAIT tool - programmatically applying REAcct to thenetwork analysis of infrastructure disruption cascades, so as torank-order critical assets.

NISAC MAP tool - as part of asset prioritization for DHS, MAPteam is considering REAcct for rapid, first-order estimates ofasset economic value.

Direct economic impacts

Number of small businesses

NISAC microeconomic tools

NISAC Agent-Based Laboratory forEconomics (N-ABLE™)

Large-scale, enterprise-firm modeling of supplychains, regional economies, entire nation.Enterprise-level connections to criticalinfrastructures.

Identifies sectors, classes of firms(small/medium/large), regions of the country mostvulnerable to infrastructure disruptions.

Overall model is designed for simulations running106 firms on Thunderbird, Sandia’s parallelcomputing cluster (currently 5th fastest in theworld).

Benefit-cost analysisModels investment decision process ofgovernment authorities.

Compares cost effectiveness of newtechnologies/strategies against “do-nothing”(baseline) strategy.

N-ABLE enterprise model

An N-ABLE value chain

Problem-driven tool development: N-ABLE™

PurposeTo analyze the impacts of disruptions on regional value chains, specifically: (1) identify the networks offirms impacted directly and indirectly, (2) estimate the intra-firm impacts (e.g., production, inventories)and inter-firm impacts (e.g., sales and shipment levels), and (3) estimate how the collective network canadapt to a disruption and any related policy instruments.

Data sourcesE.g., County Business Patterns, GDP-by-Industry Data, National Income and Product Accounts, privatedate sources (e.g., Chlorine Institute, Goodyear Tire & Rubber Company, Probe Economics).

Methodology(1) Use data-driven, agent-basedenterprise model to create synthetic firmsthat resemble operational and marketcharacteristics of actual firms;(2) model value chains as market-basedand non-market-based (e.g., socialinteractions) networks;(3) analyze networks using network theorymetrics (connectedness, betweenness) toestimate brittleness/robustness of valuechain;(4) estimate impacts to GDP, employment,income, inventories, shipments, production,over days to months.

Network representation of chlorine supply chain (5000 firms)

NISAC is collaborating with Goodyear Tire & Rubber Company toadvance its economic analysis capabilities

PurposeAnalyze the economic impacts of

infrastructure disruptions on privatecompanies:

1. create an agent-based economic networkrepresentation of firms’ purchasing,shipping, production, distribution, and end-use sale;

2. perform validation of model againstexisting GY distribution optimizationtechniques;

3. model impacts of various infrastructuredisruptions (electric power, transportation)on production, shipping, inventories, costs;

4. assist in new GY disaster planning groupformed to mitigate losses due toinfrastructure-based supply chaindisruptions.

Network representation of Goodyear supply chain

Validating analysis of distribution centers

An example of how economic analysis fits in NISAC: Katrina

Storm data, infrastructure data, economic data

Electricpower

Telecomm-unications

Transportation/commodities

Petroleum/natural gas

Chemical/HAZMAT

Physicaldamage

Economic disruptionis superset of all population,

physical damage, andinfrastructure disruptions

Local direct andindirect impacts

(REAcct)

Regional andnational macroimpacts (REMI)

Financialmarketsanalysis

Regional and nationalvalue chain analysis

(N-ABLE - experimental)

Smallbusinessanalysis

Collectedand rationalizedeconomic results

2 pre-reports,10 post-reports,1 post-post report

Populationeffects

Relocationimpact

analysis

Current path: strengthening our capabilities

“Since Hurricane Katrina, NISAC hassignificantly improved their capabilityto provide reports detailing thecascading impact of major disasterson the Nation’s infrastructure but itdoes not include a robustassessment of the economicimpacts.”

Advancing tools to meet DHS needNeed to tune existing models (e.g., REAcct) to moreclasses of disruptions

Need to productionize microeconomic simulation,analysis, and reporting tasks

Need more tools that can estimate impacts of short-term(days to weeks to months) disruptions

Accessing critical dataNeed access to more restricted-use infrastructure,commodity flow, and economic data

Increasing strategic collaborationsPublic: DOT, BEA, BLS, Treasury, FAA, DOS, USDAPrivate: Firms and associations across industriesAcademic: have worked with MIT, Cornell, WSU