Economic Mapping Project - Washington County, Oregon · 2010-11-13 · Economic Mapping Project....

Economic Mapping Project

Project Sponsors

• Oregon Economic and Community Development Department (OECDD)

• City of Hillsboro• NAIOP• CAR/CREEC/OAR

Project Objectives

• Develop a methodology for determining the economic productivity of industrial / employment land utilizing a specific study area

• Document methodology so it can be used elsewhere

• Contribute to the current dialogue on urban and rural reserves in the Portland metro area

Methodology - Approach• Define and analyze existing employment

area as influenced by economic clustering• Determine physical constraints and net

developable acres• Identify and calculate key productivity

measures• Project findings to defined undeveloped

area

Economic Cluster Model

• Agglomeration of industries, or clusters, is currently recognized as best practice in economic development by the State of Oregon

• A network of anchor, spin-off, supplier companies and support services that generate business advantages by being located in proximity to each other

Methodology – Data Sources

• Metro – RLIS

• Oregon Employment Department – ES202

• Washington County – Assessor Data

• 2005 data set

Methodology – Data Analysis

• Productivity of land – total annual market value

• Productivity of land – total annual pay roll• Productivity of land – total annual property

tax revenue

Study Area – Vicinity Map

Physical Development Constraints

Physical Development Constraints Study Area

Study Area – Hillsboro Title 4 Land

Study Area ProfileSTUDY AREA: HILLSBORO TITLE 4 LANDS

Economic Composition: Employment PayrollManufacturing Employment: 63% 77%

Service Employment: 18% 12%Trade Employment 10% 5%Other Employment: 8% 7%

Average Payroll per Employee: 77,274$ Unconstrained Area Acreage: 3041.7 Acres

Productive Area Acreage: 1782.0 AcresAverage Employment Density: 8.91 Emp/Acre

Avg. Density per Productive Acre 15.20 Emp/Acre

Distribution of:

NAICS Description

334413 Semiconductor and Related Device Manufacturing334515 Instrument Manufacturing for Measuring and Testing Electricity and Electrical Signals561422 Telemarketing Bureaus and Other Contact Centers333295 Semiconductor Machinery Manufacturing339113 Surgical Appliance and Supplies Manufacturing335999 All Other Miscellaneous Electrical Equipment and Component Manufacturing332999 All Other Miscellaneous Fabricated Metal Product Manufacturing

Major Industries

Cluster Production Inputs• Highly skilled, specialized technology workforce• Water/manufacturing cooling capacity• Electrical power capacity• Seismically stable, low-slope land• Transportation: freeway, public transit, executive

airport• Specialized chemical and gas inputs

infrastructure• Experienced public services: large, high tech

facility planning and delivery needs

Study Area Infrastructure Costs

RecapSo far, we have identified the study area and its:

– Physical development constraints– Economic profile– Cluster characteristics– Infrastructure investments

We have also specified the following land productivity measures:– Annual market value– Annual payroll– Annual tax revenue

Productivity of Land Annual Market Value, Payroll, Property Tax Revenue

Study Area, Sub-Areas

Productivity of Land Annual Market Value, Payroll, Property Tax Revenue

Potential Urban Reserves

Economic Productivity Model

• Projected economic productivity in the new urban area is a function of the per acre value of:

– Productivity values of existing, proximate economic activity

– Productivity values of regional or aspirational economic activity

Development Profile of Reserves Area

• 25% of Reserves Area projected to be corporate headquarters

• 50% of Reserves Area projected to be high tech manufacturing

• 25% of Reserves Area projected to be professional business park

Projected Annual Economic Productivity

Conclusions

• Potential economic productivity of future employment land can be measured

• Economic productivity is a function of both existing investment and community aspirations

• Development potential of employment land is dependant on locational factors that can be identified and analyzed

Factors Influencing Economic Potential of Land

• Physical Constraint Factors– Wetlands– Floodplain– Slope

• Infrastructure Factors– Utilities– Transportation

• Adjacency Factors– Economic activity– Labor force

• State and Regional Aspiration Factors– State/Regional opportunities– Statewide Planning Goal 9: Economic Development

Next Steps

• Present the findings to get feedback and input• Apply and test methodology in other areas• Refine method for determining infrastructure

costs to support land productivity in new urban areas

• Use physical constraint, infrastructure, and economic adjacency and aspirational factors to identify potential employment lands

Appendix

Study Area Data Table

Potential Infrastructure Costs

General Location Factors• Access to major transportation routes for

distribution of product• Proximity to public utilities (e.g. sanitary sewer

and water)• Proximity to private utilities (e.g. electrical, gas,

telecommunications)• Proximity to labor force• Transportation access for labor force• Slope less that 7%• Lack of wetlands/floodplain

Characteristics of West County Clusters

• Commonly Referred to as the Silicon Forest– Led by Semiconductor and other Computer Electronics

manufacturing “Anchors” prominently including Intel.– “Anchor” firms in turn have attracted and support “Ripple Effect” or

clustered vendor, service, and customer firms including Novellus and ETEC.

– Anchors and related firms have in turn generated “Spin-Off” cluster firms by former employees or others with industry relationships including Radisys, FEI, Triquint, and Lattice Semiconductor.

– All of the above firms are highly proximate, benefit from same local high-technology labor pool, and jointly utilize mutually beneficial trade associations, business relationships and public service and infrastructure investments.

• Solar Cell Manufacturing & Biotech are poised to similarly benefit from the same cluster of labor/innovation/public investment and grow in a similar clustered manner.

Characteristics of Clusters• Agglomeration of industries, or clusters, is

currently recognized as best practice in economic development by the State of Oregon

• The Oregon Cluster Network defines:– A network of local connections to a specially

skilled local workforce and the availability of strong local suppliers in proximity to one another that generates business advantages that can not easily be imitated or competed away by low cost competitors.

Economic Productivity Model• Projected economic productivity (EP) in the new urban area is a

function of existing economic activity, per acre, (EE) and the local community’s economic aspirations, per acre, (EA), where:

• EP = ((EE x %p) + (EA x 1-%p)) x EPac

• EP = projected economic productivity• EPac = defined new urban area• EE = existing adjacent economic activity per acre • %p = policy decision on percentage of total calculated productivity to be projected to

Economic Aspiration Area• EA = economic aspirations per acre• 1-%p = policy decision on percentage of total productivity to be allocated to

aspirations • p and 1-p are policy decisions that are made by the local community that reflect the

% of each variable that they believe will contribute to the projected economic productivity (EP) within the new urban area.

Sub-Area 1 Profile

Sub-Area 2 ProfileSUBAREA 2: Corporate Campus:






Distribution of:

Sub-Area 3 Profile

Sub-Area 4 ProfileSUBAREA 4: Professional Business Park/Support Services






Distribution of:

Sub-Area 5 ProfileSUBAREA 5: Services & Regional Retail






Distribution of:

Economic Mapping Project - Washington County, Oregon · 2010-11-13 · Economic Mapping Project....

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