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On The Road Again:Wyoming Commuting Patterns

Doug Leonard, Senior EconomistWyoming Department of Employment, Research &

Planningdleona1@state.wy.us

(307) 473-3811

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Research & Planning:

OUR ORGANIZATION:R&P is a separate, exclusively statistical entity.

WHAT WE DO:R&P collects, analyzes, and publishes timely and accurate labor market information (LMI)

meeting established statistical standards.

OUR CUSTOMERS:LMI makes the labor market more efficient by

providing the public and the public’s representatives with the basis for

informed decision making.

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Project History

Commuting pattern research began as a feasibility study of a Park-n-Ride facility in Teton County (2001)

Commuting Data for Campbell County--Susan Bigelow, Executive Director Campbell County Economic Development Corporation (CCEDC) 9/24/03

Some prior research results located at http://doe.state.wy.us/lmi/commute.htm

Latest revision of methodology applied to current study (2006) Latitude and longitude assigned to residence location based

on driver’s license physical address PO address lat./lon. used for PO boxes Calculate distances where Lat./Lon. assigned

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Commuting Pattern Development

Two items must be determined: Residence Location Work Location

In some instances, work location is estimated Where possible out of state data are used to

model interstate worker flows

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Data Sources

Unemployment Insurance Wage Records Liable employers report all SSNs and wages

each quarter Employer Master File

Contains aggregate information regarding UI liable businesses employment and wages

WYDOT Driver’s License File Contains driver names, SSNs and physical

addresses

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Linking Residence to Work

Link established each quarter for each job a worker holds = 1 Transaction

Worker Residence Location

Employer CLocation

Employer BLocation

Employer ALocation

T T

T

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Commuting Terms

Intercounty Commuting Reside in one county, work in another county (e.g.,

commute from Douglas to Casper) Intracounty Commuting

Reside and work in the same county (e.g., commute from Glenrock to Douglas)

Base County The county being studied (e.g., Campbell)

Outflow Workers who leave the base county for work in another

county (e.g., people residing in Campbell and commuting to Johnson)

Inflow Workers who arrive in the base county from another

county for work (e.g., people residing in Crook who commute to Campbell for work)

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Why Study Worker Commuting Patterns?

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Commuting Study and Context Analysis

Focus on one net outflow county (Converse) and two net inflow counties (Campbell & Natrona) Historical Trends

Gross and net flow rates Rates by sex Rates by age group

Implications The “Demographic Sledgehammer”

Rapidly aging population Effects on consumer spending and commuting

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Commuting Study Results1

Gross and net flows by county Flows by age group Flows by sex Wage differentials Imported labor

1Results available in tabular form on the web; shown here in graphical form for illustrative purposes.

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Figure: Campbell County Commuting Flows, 2000Q4-2005Q4

-6,000

-4,000

-2,000

0

2,000

4,000

6,000

8,000

10,000

12,000

2000

Q4

2001

Q1

2001

Q2

2001

Q3

2001

Q4

2002

Q1

2002

Q2

2002

Q3

2002

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2003

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2003

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2004

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2004

Q2

2004

Q3

2004

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2005

Q1

2005

Q2

2005

Q3

2005

Q4

Date

Com

muti

ng F

low

Outflow

Inflow

Net Flow

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Population and school

enrollments can LAG

employment increases when

large commuting

inflows occur.

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Figure: Natrona County Commuting Flows, 2000Q4-2005Q4

-8,000

-6,000

-4,000

-2,000

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2000

Q4

2001

Q1

2001

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2001

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2001

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2002

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2002

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2004

Q2

2004

Q3

2004

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2005

Q1

2005

Q2

2005

Q3

2005

Q4

Date

Com

muti

ng F

low

Outflow

Inflow

Net Flow

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Figure: Converse County Commuting Flows, 2000Q4-2005Q4

-3,000

-2,500

-2,000

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

2000

Q4

2001

Q1

2001

Q2

2001

Q3

2001

Q4

2002

Q1

2002

Q2

2002

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2002

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2003

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2004

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2005

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2005

Q3

2005

Q4

Date

Com

muti

ng

Flo

w Outflow

Inflow

Net Flow

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Population and school

enrollments can LEAD

employment increases when

large commuting

outflows occur.

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Commuting Study Results

Gross and net flows by county Flows by age group Flows by sex Wage differentials Imported labor

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Figure: Converse County Commuting Ouflows by Age Group

-700

-600

-500

-400

-300

-200

-100

0

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Outfl

ow

16 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 All Other

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Figure: Natrona County Commuting Inflows by Age Group

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Inflow

16 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 All Other

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Figure: Campbell County Commuting Inflows by Age Group

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Inflow

Com

muti

ng

16 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 All Other

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Commuting Study Results

Gross and net flows by county Flows by age group Flows by sex Wage differentials Imported labor

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Figure: Natrona County Commuting Inflows by Sex

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Inflow

Females Males Undetermined

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Figure: Campbell County Inflow Commuting by Sex

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Inflow

Com

mu

tin

g

Females Males Undetermined

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Figure: Converse County Commuting Outflows by Sex

-1,800

-1,600

-1,400

-1,200

-1,000

-800

-600

-400

-200

0

2000Q4 2001Q4 2002Q4 2003Q4 2004Q4 2005Q4

Date

Outfl

ow

Females Males Undetermined

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Commuting Study Results

Gross and net flows by county Flows by age group Flows by sex Wage differentials Imported labor

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Figure: Average Wages for Campbell County Commuters, 2000Q1-2005Q4

$5,000

$5,500

$6,000

$6,500

$7,000

$7,500

$8,000

$8,500

$9,000

$9,500

$10,000

$10,500

2000

Q1

2000

Q2

2000

Q3

2000

Q4

2001

Q1

2001

Q2

2001

Q3

2001

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2002

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2002

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Date

Avera

ge W

ages

Inflow from Other Counties Outflow to Other Counties Within County Commuters

“Bonus” for living and working in Campbell County

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Figure: Average Wages for Converse County Commuters, 2000Q1-2005Q4

$4,000

$4,500

$5,000

$5,500

$6,000

$6,500

$7,000

$7,500

$8,000

$8,500

$9,000

2000

Q1

2000

Q2

2000

Q3

2000

Q4

2001

Q1

2001

Q2

2001

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2001

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2002

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2005

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2005

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Date

Avera

ge W

ages

Inflow from Other Counties Outflow to Other Counties Within County Commuters

“Penalty” for working in Converse County

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Commuting Study Results

Gross and net flows by county Flows by age group Flows by sex Wage differentials Imported labor

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Imported LaborFigure: Top State of Origin Inflows to Wyoming for Workers without Wyoming Driver Licenses

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

2001

Q1

2001

Q2

2001

Q3

2001

Q4

2002

Q1

2002

Q2

2002

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2002

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Q4

Date

Inflow

WY

CA

CO

TX

UT

ID

MT

Undetermined

MI

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Other Factors: The “Demographic Sledgehammer” Aging population Consumption patterns

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Figure: Projected Population Growth for Wyoming, 2000-2030

49,92853,294

39,798 37,557 38,554 37,902

45,520

57,693

63,414

72,658

88,842

109,655

128,605

138,586

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

2000 2005 2010 2015 2020 2025 2030

Year

Po

pu

lati

on

18-24 65+

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Number of 1992 Worker Cohort Age 16-34 Still Working in Wyoming

112,318

94,658

84,247

76,87571,583

68,065

0

20,000

40,000

60,000

80,000

100,000

120,000

1992 1993 1994 1995 1996 1997

7.9%

Loss of 44,253 workers in five years

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Number of 2000 Worker Cohort Age 16-34 Still Working in Wyoming

116,229

96,162

85,57278,899

74,71971,102

0

20,000

40,000

60,000

80,000

100,000

120,000

2000 2001 2002 2003 2004 2005

7.6%

Loss of 45,127 workers in five years

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Average annual away from home food consumption is 23.8% less for 55 - 64 year olds than for those 45 - 54 years of age

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Research Extensions

Model likelihood of relocation Lag between commuting and changes in

school enrollments Lag between commuting and changes in

population Assist law enforcement in officer placements Connect commuting data to highway accident

and Worker’s Compensation data

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Conclusion

Inadequate Monitoring Leads to misdiagnosis of issues Move beyond headlines to quantitative understanding

Rapidly increasing commuting flows Increased road deterioration Increased motor vehicle accidents Increased demands for first responder services

Aging population Need to “convert” out of state commuters and

temporary workers to residents to maintain tax base If older workers are not replaced, aggregate

consumption will decline Social welfare programs strained