12
HIGHLIGHTS The statistics about older workers in Kansas in 2004 show this group’s propor- tion of the state’s labor force has increased. Changes in the size and com- position of age groups may affect govern- ment program and policy choices and the options available to businesses. National projections indicate that the population 65 and older will increase from about 1 in 8 people to 1 in 5 people by 2030, so that older workers will likely compose an increasingly larger proportion of each state’s workforce. 1 Whether, and in what industries, the large wave of workers born during the Baby Boom of 1946 to 1964 are currently working may influence their labor force behavior beyond tradi- tional retirement ages. That is important information for firms planning for the eventual loss of experienced workers and the payout of pensions. In 2004, the Baby Boom cohort was aged 40 to 58. This report uses data from the Local Employment Dynamics (LED) program to show the geographic distribution and the economic dynamics among private sector workers 55 and older (also including some statistics on those aged 45 to 54). It includes comparisons among the coun- ties (and county equivalents) and between metropolitan and nonmetropoli- tan areas of Kansas. 2 U.S. Department of Commerce Economics and Statistics Administration U.S. CENSUS BUREAU Issued December 2008 LED-OW04-KS The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 By Cynthia Taeuber and Matthew R. Graham Sponsored by the National Institute on Aging National Institutes of Health U.S. Department of Health and Human Services Local Employment Dynamics U S C E N S U S B U R E A U Helping You Make Informed Decisions 1 U.S. Census Bureau, 2004. “U.S. Interim Projections by Age, Sex, Race, and Hispanic Origin,” <http://www.census.gov/ipc/www/usinterimproj /natprojtab02a.xls>. 2 The metropolitan and nonmetropolitan county classifications are based on Census 2000. For definitions of specific metropolitan statistical areas, see <http://www.census.gov/population/www /estimates/metroarea.html>. What’s in This Report? HIGHLIGHTS THE LOCAL EMPLOYMENT DYNAMICS PROGRAM SOURCES AND ACCURACY OF THE ESTIMATES CHARACTERISTICS AND EMPLOYMENT DYNAMICS OF OLDER WORKERS Table 1— Percentage of Workers by Age in Metropolitan Statistical Areas and Nonmetropolitan Area Workplaces in Kansas: 2004 Figure 1— Kansas Workforce by Age Group: 1993 to 2004 Figure 2— Percentage of Workers 45 to 54 Years Old by County of Workplace in Kansas: 2004 Figure 3— Percentage of Workers 55 to 64 Years Old by County of Workplace in Kansas: 2004 Figure 4— Percentage of Workers 65 and Older by County of Workplace in Kansas: 2004 Figure 5— Percentage Change in Number of Workers 55 and Older by County of Workplace in Kansas: 2001 to 2004 ADDITIONAL RESOURCES

The Geographic Distribution and Characteristics of … · position of age groups may affect govern- ... with 6.4 percent. • In nonmetropolitan area work-places in Kansas, ... lowest

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HIGHLIGHTS

The statistics about older workers inKansas in 2004 show this group’s propor-tion of the state’s labor force hasincreased. Changes in the size and com-position of age groups may affect govern-ment program and policy choices and theoptions available to businesses. Nationalprojections indicate that the population65 and older will increase from about 1 in8 people to 1 in 5 people by 2030, sothat older workers will likely compose anincreasingly larger proportion of eachstate’s workforce.1 Whether, and in whatindustries, the large wave of workersborn during the Baby Boom of 1946 to1964 are currently working may influencetheir labor force behavior beyond tradi-tional retirement ages. That is importantinformation for firms planning for theeventual loss of experienced workers andthe payout of pensions. In 2004, the BabyBoom cohort was aged 40 to 58.

This report uses data from the LocalEmployment Dynamics (LED) program toshow the geographic distribution and theeconomic dynamics among private sectorworkers 55 and older (also includingsome statistics on those aged 45 to 54).It includes comparisons among the coun-ties (and county equivalents) andbetween metropolitan and nonmetropoli-tan areas of Kansas.2

U.S.Department of CommerceEconomics and Statistics Administration

U.S. CENSUS BUREAU

Issued December 2008

LED-OW04-KS

The Geographic Distribution andCharacteristics of Older Workers in Kansas: 2004

By Cynthia Taeuberand Matthew R. Graham

Sponsored by the National Institute on AgingNational Institutes of HealthU.S. Department of Health and Human Services

Local Employment Dynamics

U S C E N S U S B U R E A UHelping You Make Informed Decisions

1 U.S. Census Bureau, 2004. “U.S. InterimProjections by Age, Sex, Race, and Hispanic Origin,”<http://www.census.gov/ipc/www/usinterimproj/natprojtab02a.xls>.

2 The metropolitan and nonmetropolitan countyclassifications are based on Census 2000.

For definitions of specific metropolitan statisticalareas, see <http://www.census.gov/population/www/estimates/metroarea.html>.

What’s in This Report?

HIGHLIGHTS

THE LOCAL EMPLOYMENTDYNAMICS PROGRAM

SOURCES AND ACCURACY OFTHE ESTIMATES

CHARACTERISTICS ANDEMPLOYMENT DYNAMICS OFOLDER WORKERS

Table 1— Percentage of Workers byAge in MetropolitanStatistical Areas andNonmetropolitan AreaWorkplaces in Kansas: 2004

Figure 1— Kansas Workforce by AgeGroup: 1993 to 2004

Figure 2— Percentage of Workers 45 to54 Years Old by County ofWorkplace in Kansas: 2004

Figure 3— Percentage of Workers 55 to64 Years Old by County ofWorkplace in Kansas: 2004

Figure 4— Percentage of Workers 65and Older by County ofWorkplace in Kansas: 2004

Figure 5— Percentage Change inNumber of Workers 55 andOlder by County ofWorkplace in Kansas: 2001to 2004

ADDITIONAL RESOURCES

2 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

Industries are classified accordingto the North American IndustryClassification System (NAICS).Because the Quarterly WorkforceIndicators (QWI) are updated every3 months, the numbers in thisreport may differ from the mostrecent ones on the current LED Website, <http://lehd.did.census.gov>.

This report defines “older workers”as those 55 and older. Informationis displayed for all workers by agegroups to facilitate comparisonsamong workers and provide infor-mation about the potential charac-teristics of future older workers.The characteristics and geographicdistribution throughout Kansas ofthree groups of older workers areshown: those who may be receiv-ing pension income but who areworking (65 and older) and twopre-retirement groups of workers(those aged 45 to 54 and aged 55to 64), who may start collectingpensions and social security overthe next two decades.

With the LED information, stateplanners can monitor changes inthe workforce and emergingtrends. Detailed statistics aboutworkers by age in counties andmetropolitan and nonmetropolitanareas of Kansas are available onthe U.S. Census Bureau’s Web site,<http://www.census.gov>.

Following are highlights from thedetailed statistics.

Age Composition of theWorkforce

• Of the 105 counties in Kansas,20.0 percent or more of thetotal workforce in 18 countieswas 55 and older.

• Statewide, 14.4 percent of work-ers were 55 and older. The fivecounties with the highest per-centage of workers 55 and olderwere:3

Percentage County of workforce

Jewell . . . . . . . . . . . . . . . 25.6

Republic . . . . . . . . . . . . . 24.2

Decatur . . . . . . . . . . . . . . 23.5

Washington . . . . . . . . . . . 22.6

Smith . . . . . . . . . . . . . . . 22.2

• Statewide, 3.5 percent of work-ers were 65 and older. The fivecounties with the highest per-centage of workers 65 and olderwere:4

Percentage County of workforce

Washington . . . . . . . . . . . 9.5

Clay . . . . . . . . . . . . . . . . 7.8

Anderson . . . . . . . . . . . . 7.3

Osage . . . . . . . . . . . . . . . 7.1

Marion . . . . . . . . . . . . . . 7.0

• Of the 105 counties in Kansas,99 counties experienced anincrease from 2001 to 2004 inthe percentage of the countyworkforce that was 55 andolder. The largest increase wasin Decatur County.

• Of the total workforce employedin metropolitan statistical areas,about 13.8 percent was 55 andolder; in nonmetropolitan areaworkplaces, the proportion was15.7 percent.

Industry Sectors With theHighest Proportions of OlderWorkers in 20045

• Statewide, among industry sec-tors that employed 100 or moreworkers 55 and older, RealEstate and Rental and Leasing(NAICS 53) had the highest pro-portion of workers in this agegroup. This sector had the high-est percentage of workers 55and older in 1 county.

• Statewide, no individual indus-try sectors employed more than20.0 percent of workers whowere 55 and older.

• In metropolitan statistical areasof the state, the industry sectorthat employed the largest per-centage of workers 55 and olderwas Mining (NAICS 21), with19.4 percent; the industry sec-tor with the highest proportionof workers 65 and older wasReal Estate and Rental andLeasing (NAICS 53), with 6.4percent.

• In nonmetropolitan area work-places in Kansas, the industrysector that employed the largestpercentage of workers 55 andolder was Educational Services(NAICS 61), with 22.8 percent.Real Estate and Rental andLeasing (NAICS 53) was theindustry sector with the highestproportion of workers 65 andolder, with 8.8 percent.

3 Counties with low employment (fewerthan 100 employees) in the 55-and-older agegroup are not included in this list.

4 Counties with low employment (fewerthan 100 employees) in the 65-and-older agegroup are not included in this list.

5 Sectors are groups of industries. For more information, see <http://www.census.gov/epcd/www/naicsect.htm>.

U.S. Census Bureau The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 3

Industry Sectors Most Likelyto Employ Older Workers in 2004

• Of the workers in the state 55and older, 18.0 percent wereemployed in Manufacturing(NAICS 31–33), the highest pro-portion for that age group ofany industry sector in the state.This industry was ranked num-ber one in 22 of 105 counties.

• Of the workers 55 and older inthe state’s metropolitan statisti-cal areas, 17.8 percent wereemployed in Manufacturing(NAICS 31–33), the highest pro-portion for that age groupstatewide among industrialsectors.

• Of the workers 55 and older inthe state’s nonmetropolitan areaworkplaces, 19.2 percent wereemployed in Health Care andSocial Assistance (NAICS 62), thehighest proportion for that agegroup statewide among indus-trial sectors.

Quarterly Job Gains andLosses in 2004

• On average, for workers 55 to64 years old, 5,526 jobs werecreated quarterly and 6,858jobs were lost quarterly. Forworkers 65 and older, the num-bers were 2,418 and 3,405,respectively.

• The county with the largest shareof job gains for workers 55 to 64years old was Johnson County,with 25.2 percent. The largestshare of job losses for suchworkers was also in JohnsonCounty, with 24.8 percent.

• The county with the largest shareof job gains for workers 65 andolder was Johnson County, with22.5 percent. The largest shareof job losses for such workerswas also in Johnson County, with22.7 percent.

• The industry sector with thelargest gain in jobs for workers55 to 64 years old was RetailTrade (NAICS 44–45), with anaverage of 780 jobs gained perquarter at the state level. Themost jobs lost by that agegroup were also in Retail Trade(NAICS 44–45), with an averageof 915 jobs lost per quarter atthe state level.

• The industry sector with thelargest gain in jobs for workers65 and older was Retail Trade(NAICS 44–45), with 358 jobsgained per quarter at the statelevel. The most jobs lost by thatage group were also in RetailTrade (NAICS 44–45), with 547jobs lost per quarter at the state level.

Average Earnings of OlderWorkers in 2004

• Statewide, on average, workers55 and older earned $3,149 amonth.

• Of industry sectors employingat least 100 workers 55 andolder, the highest paying wasInformation (NAICS 51). Workersin that sector earned, on aver-age, $5,072 per month. Thelowest paying was Arts,Entertainment, and Recreation(NAICS 71). Workers in this sec-tor earned, on average, $1,374per month. The following tableshows statewide average

monthly earnings in 2004 forfull-quarter, private-sector wageand salary workers 55 and olderby NAICS sector.

Earnings Industry [dollars]

Information . . . . . . . . . . . . . . 5,072

Management of companies

and enterprises . . . . . . . . . . 4,935

Utilities . . . . . . . . . . . . . . . . . 4,867

Professional, scientific,

and technical services . . . . 4,152

Manufacturing . . . . . . . . . . . 4,117

Finance and insurance . . . . . 4,035

Wholesale trade . . . . . . . . . . 3,823

Mining . . . . . . . . . . . . . . . . . 3,616

Construction . . . . . . . . . . . . . 3,428

Educational services . . . . . . . 2,892

Health care and

social assistance . . . . . . . . . 2,878

Transportation and

warehousing . . . . . . . . . . . . 2,747

Administrative and support

and waste management

and remediation services . . 2,498

Agriculture, forestry, fishing,

and hunting . . . . . . . . . . . . 2,397

Real estate and rental

and leasing . . . . . . . . . . . . . 2,369

Other services (except

public administration) . . . . 1,898

Retail trade . . . . . . . . . . . . . . 1,892

Accommodation and

food services . . . . . . . . . . . 1,402

Arts, entertainment,

and recreation . . . . . . . . . . 1,374

4 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

Older Workers in MetropolitanStatistical Areas and inNonmetropolitan AreaWorkplaces in 2004

• In metropolitan statistical areas,the five industry sectors withthe largest percentage of work-ers 55 and older were:

Percentage Industry of workers

Mining . . . . . . . . . . . . . . . 19.4

Real estate and rental

and leasing . . . . . . . . . . 18.1

Utilities . . . . . . . . . . . . . . 17.8

Agriculture, forestry,

fishing, and hunting . . . 17.7

Management of companies

and enterprises . . . . . . . 17.6

• In nonmetropolitan area work-places, the five industry sectorswith the largest percentage ofworkers 55 and older were:

Percentage Industry of workers

Educational services . . . . 22.8

Finance and insurance . . . 21.3

Real estate and rental

and leasing . . . . . . . . . . 20.8

Utilities . . . . . . . . . . . . . . 19.5

Other services (except

public administration) . . 19.0

• In metropolitan statistical areas,of industry sectors employing atleast 100 workers 55 and older,the highest paying for workers55 and older was Information(NAICS 51), which paid, on aver-age, $5,803 a month. The low-est paying was Arts,Entertainment, and Recreation(NAICS 71), which paid, on aver-age, $1,455 a month.

• In nonmetropolitan area work-places, of industry sectorsemploying at least 100 workers55 and older, the highest payingfor workers 55 and older wasUtilities (NAICS 22), which paid,on average, $4,869 a month.The lowest paying wasAccommodation and FoodServices (NAICS 72), which paid,on average, $1,019 a month.

THE LOCAL EMPLOYMENTDYNAMICS PROGRAM

The LED program is a partnershipbetween the Census Bureau and theparticipating states. LED producesQWI for each partner state, as wellas each partner state’s metropolitanareas, combined nonmetropolitanareas, counties, and WorkforceInvestment Board areas. Quarterlyand annual averages are available at<http://lehd.did.census.gov>.6

Overview

The QWI are measures of economiccharacteristics and change selectedjointly by the Census Bureau andits partner states. Each componentof the QWI provides a critical meas-ure of an area’s economy and canbe used as a tool to better under-stand changes in the core perform-ance of local economies.

Listed in this report are figures anddata tables that show selected QWIstatistics on older workers.Comprehensive summary data thatcover geographic areas and includeage and gender composition byindustry, total employment, net jobflows, job gains and job losses, sep-arations, new hires, skill level (quar-ters of employment), and averagemonthly earnings are available at<http://lehd.did.census.gov>.

Nine months after a quarter ends,the Census Bureau and its partnersupdate the workforce indicators forthat quarter. This provides currentand historical information aboutthe characteristics of America’sworkers and a tool to monitor eco-nomic change.7 The statistics arecomparable across time, making itpossible to identify emergingworkforce trends and turningpoints and to compare geographicareas and demographic groupsworking in specific industries.Industries are classified accordingto the NAICS.

The QWI come from a mixture ofdata sources, the base of which is acensus of jobs. The LED databaseincludes all jobs a worker holds andallows multiple definitions of“employment” in order to respondto a wide variety of questions aboutthe workforce (see “Sources andAccuracy of the Estimates” in thefollowing section). The definition of“employment” in this report, unlessstated otherwise, is “beginning ofquarter” employment—that is, thetotal number of workers who wereemployed by the same employer inthe reference quarter and theprevious quarter.

QWI for partner states anddetailed information aboutthe LED program are availablewithout cost at<http://lehd.did.census.gov>.

6 For more complete information on QWI,see Abowd, John M., Bryce E. Stephens, LarsVilhuber, Fredrik Andersson, Kevin L.McKinney, Marc Roemer, and SimonWoodcock, 2005. The LEHD InfrastructureFiles and the Creation of the QuarterlyWorkforce Indicators. LEHD Technical Paper,TP-2006-01. U.S. Census Bureau, Washington,DC. Available at <http://lehd.did.census.gov/led/library/techpapers/tp-2006-01.pdf>.

7 Because the QWI are updated quarterly,the numbers in this report may differ fromthe most recent ones, which are shown onthe current LED Web site. For the latest list of partner states, see <http://lehd.did.census.gov/led/led/statepartners.html>.Additional states are in the process of joining.

U.S. Census Bureau The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 5

As job-based statistics, the QWI arenot directly comparable with statis-tics from worker-based surveyssuch as the decennial and eco-nomic censuses, the AmericanCommunity Survey, or the CurrentPopulation Survey.8 Neither are theQWI exactly comparable with datafrom establishment surveys, suchas those from the U.S. Bureau ofLabor Statistics’ Quarterly Censusof Employment and Wages (QCEW)program, which capture employ-ment data at establishments on the12th of the month.

Throughout this report, “earnings”refer only to the earnings of work-ers who were employed for a fullquarter—that is, those who wereemployed by the same employer inthe reference, previous, and subse-quent quarters. This earningsmeasure reflects the earnings of“attached” employees, generallyworkers who worked for the sameemployer for the whole quarter.The measures of earnings from theQWI are not directly comparablewith measures of earnings fromthe Bureau of Labor Statistics.

SOURCES AND ACCURACYOF THE ESTIMATES

Because the QWI are job-based sta-tistics, not the worker-based statis-tics familiar to many researchers,the LED database allows multipledefinitions of “employment” andcan respond to a wide variety ofquestions about the workforce.9

Sources

Enhanced unemployment insurance(UI) wage records and the QCEWare the basic data sources for theQWI. These are administrative dataprovided to the Census Bureau bypartner states. The QWI’s coverage,timing of data collection, and con-cept definitions differ from thosein worker-based surveys, such asthe decennial and economic cen-suses, the American CommunitySurvey, and the Current PopulationSurvey. Also, QWI data are notexactly comparable with Bureau ofLabor Statistics information, due totiming differences.

Administrative data from thesesources almost certainly containnonsampling errors. The extent ofthe nonsampling errors isunknown. Sources of nonsamplingerrors include errors made in datacollection, such as recording andcoding errors, errors made in pro-cessing the data, errors made inestimating values for missing data,and errors from failing to representall units within a target population(undercoverage).

The LED program undertakes aprocess of continuous monitoringto attempt to control the nonsam-pling errors in the integrated datathat underlie the LED database. Inparticular, identifiers on both theUI wage records and the QCEWrecords are subjected to longitudi-nal editing every quarter. A set ofquality assurance tests is appliedto the integrated data. These testsdetect problems known to causenonsampling errors—primarily,tests for missing records of varioustypes (based on estimates of thenumber of expected records fromalternative sources), tests forincomplete wage or earnings infor-mation, and tests for changes inthe structure of identifiers or enti-ties. Problems detected by these

quality assurance tests are investi-gated and corrected before dataintegration and production of theQWI are allowed to continue.10

Industries are based upon theNAICS.

Coverage

This report covers civilian noninsti-tutionalized workers in the privatesector only. While this report doesnot include federal governmentworkers, the complete QWI data-base does include most state andlocal government employees. TheQWI database covers about 98 per-cent of nonagricultural, privatewage, salaried employment. Theremaining 2 percent of the nona-gricultural, private wage, salariedworkers are railroad workers andworkers for some nonprofit organi-zations. Self-employed workersand independent contractors arenot in the covered universe.11

Definitions

The LED database includes all jobsheld:

• In a quarter, regardless of thelength of time the job is held.

• At the beginning of a quarter—the measure used in this report(workers employed by the sameemployer in the reference quar-ter and the previous quarter).

• At the end of a quarter.

• For a full quarter (total numberof workers who were employedby the same employer in the ref-erence, previous, and subse-quent quarters). This measure is

10 Technical documentation is available at<http://lehd.did.census.gov>.

11 See David W. Stevens. Employment ThatIs Not Covered by State Unemployment.LEHD Technical Paper, TP-2002-16. U.S. Census Bureau, Washington, DC.Available at <http://lehd.did.census.gov/led/library/techpapers/tp-2002-16.pdf>.

8 Information about the decennial censusis available at <http://www.census.gov/main/www/cen2000.html>. American CommunitySurvey information is available at<http://www.census.gov/acs/www>.Information about economic censuses isavailable at <http://www.census.gov/econ/census02/>.

9 For the QWI, a “job” is defined as anemployer-employee pair among administra-tive datasets.

6 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

used in this report for averageearnings because it reflects theearnings of employees in morestable jobs.

The measure that is closest to theQCEW definition of employment isthe second one, jobs held at thebeginning of a quarter. This secondmeasure has the additional advan-tage of capturing trends similar tothose shown by worker-based sur-veys, such as the decennial census.

Annual figures are simple averageswith each quarter weightedequally. There is no differentialweighting of averages for seasonalindustries, for example.

Earnings are measured differentlyamong the various datasets.According to the BLS Handbook ofMethods (1997), UI wage recordsmeasure “gross wages and salaries,bonuses, stock options, tips, andother gratuities, and the value ofmeals and lodging, where sup-plied.” They do not includeamounts paid for Old-Age,Survivors, and Disability Insurance(OASDI), health insurance, workers’compensation, unemploymentinsurance, private pensions, andwelfare funds. The LED databasedoes not include the number ofhours or weeks an employee

worked. Thus, low average earn-ings in a given year or quarter inan industry sector may reflect rela-tively low hourly wages, or manypart-time jobs, or both, as oftenoccurs in the retail trade sector.

Some large companies have multi-ple work sites but may report alltheir workers at the company’smain address. This creates a prob-lem for the correct geographic dis-tribution of the workers. LED usesan imputation process to allocateworkers to geographic areas inorder to maintain appropriate dis-tributions within the QWI dataset.

Confidentiality of informationabout individuals and firms is protected.

The Census Bureau and the statepartners are committed to protect-ing the confidentiality of the dataused to create the LED estimates.One technical approach used toconceal individual informationinvolves combining cell suppressionmethodology and statistical noise,thereby controlling key measures tocounty employment levels asreported by the Bureau of LaborStatistics. In other words, theCensus Bureau uses statistical tech-niques in which the actual statisticsare not shown if the numbers in a

cell are small. In addition, the statis-tics that are shown are “fuzzy,”meaning close to the actual infor-mation but not exact.

Only Census Bureau employeesand individuals who have SpecialSworn Status are permitted towork with the input data. Everyonewho has access to data protectedby Title 13 of the U.S. Code musthave an official security clearancebased on a background check,including fingerprinting.12

Additionally, these individuals aresubject to a fine of up to$250,000, up to 5 years in prison,or both, if confidential informationis disclosed. The Census Bureauand the state data custodiansreview all products before releaseto avoid disclosure of confidentialinformation.

More detailed information aboutthe confidentiality protection sys-tem is available under the“Confidentiality” menu at<http://lehd.did.census.gov>.

12 The Census Bureau’s Data Protectionand Privacy Policy, including information on Title 13, is available at <http://www.census.gov/privacy>.

U.S. Census Bureau The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 7

CHARACTERISTICS AND EMPLOYMENT DYNAMICS OF OLDER WORKERS

Table 1.Percentage of Workers by Age in Metropolitan Statistical Areas and NonmetropolitanArea Workplaces in Kansas: 2004

sraey99ot55sraey99ot56sraey46ot55sraey45ot54ecalpkrowfoaerA

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.6 10.9 3.5 14.4Kansas City, MO-KS (KS part) . . . . . . . . . . . . . . . . . . . . . . . . . . 21.1 10.3 3.1 13.4Lawrence, KS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.4 8.4 2.8 11.3St. Joseph, MO-KS (KS part) . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.4 12.0 6.0 17.9Topeka, KS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.1 11.2 3.7 14.9Wichita, KS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.1 11.2 3.3 14.5

All metropolitan areas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.7 10.6 3.2 13.8All nonmetropolitan area workplaces. . . . . . . . . . . . . . . . . . . . . 21.4 11.5 4.2 15.7

Note: Discrepancies may occur due to rounding.

Source: U.S. Census Bureau and the state of Kansas, Local Employment Dynamics program, 2006. See <http://lehd.did.census.gov>.

Beginning-of-quarteremployment

Total number of workersemployed by the sameemployer in the referencequarter and the previousquarter.

Figure 1.Kansas Workforce by Age Group: 1993 to 2004

Note: Universe is all jobs identified by the LED program.

Source: U.S. Census Bureau and the state of Kansas, Local Employment Dynamics program, 2006. See <http://lehd.did.census.gov>.

Percent of beginning-of-quarter employment

65+

14–44

45–54

55–64

20001998199619941993

0

10

20

30

40

50

60

70

80

90

100

4321432143214321432143214321432143214321432143Q2

2002 2004

8 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

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ING

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RBO

NED

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RY

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RTH

FRAN

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-EN

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ORT

H

WYA

ND

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Spat

ial D

ata

Sourc

e: U

.S. C

ensu

s Bu

reau

, C

ensu

s 2

00

0.

Stat

isti

cal D

ata

Sourc

e: L

ongit

udin

al E

mplo

yer-

House

hold

Dyn

amic

s Pr

ogra

m,

U.S

. C

ensu

s Bu

reau

, 2

00

6.

Perc

enta

ge

of

Work

ers

45

to 5

4 b

y C

ounty

Note

: A

ll boundar

ies

and n

ames

ar

e as

of

Januar

y 1

, 2

00

0.

STAT

EC

OU

NT

Y

24

.1 t

o 3

0.8

22

.5 t

o 2

4.0

20

.6 t

o 2

2.4

15

.6 t

o 2

0.5

02

55

07

51

00

Kilo

met

ers

02

55

07

51

00

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s

Key

val

ues

may

not

refl

ect

pre

cise

cat

egory

bre

aks

due

to r

oundin

g.

Figure

2.

Perc

en

tage o

f W

ork

ers

45

to 5

4 Y

ears

Old

by C

ou

nty

of

Work

pla

ce i

n K

an

sas: 2

00

4

U.S. Census Bureau The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 9

NEB

RA

SKA

OK

LAH

OM

A

MIS

SOU

RI

CO

LOR

AD

O

REN

O

NES

S

FORD

BUTL

ER

GO

VE

FIN

NEY

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S

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E

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BARB

ER

LOG

AN

CLA

RKSU

MN

ER

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DE

LAN

E

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LIN

N

ROO

KS

CLA

YTH

OM

AS

RAW

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S

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ASE

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Y

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RIO

N

PRAT

T

PHIL

LIPS

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ELL

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MA

N

BART

ON

KIO

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RD

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OTT

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Spat

ial D

ata

Sourc

e: U

.S. C

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s Bu

reau

, C

ensu

s 2

00

0.

Stat

isti

cal D

ata

Sourc

e: L

ongit

udin

al E

mplo

yer-

House

hold

Dyn

amic

s Pr

ogra

m,

U.S

. C

ensu

s Bu

reau

, 2

00

6.

Perc

enta

ge

of

Work

ers

55

to 6

4 b

y C

ounty

Note

: A

ll boundar

ies

and n

ames

ar

e as

of

Januar

y 1

, 2

00

0.

STAT

EC

OU

NT

Y

13

.7 t

o 1

7.8

12

.4 t

o 1

3.6

11

.4 t

o 1

2.3

8.4

to 1

1.3

02

55

07

51

00

Kilo

met

ers

02

55

07

51

00

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s

Key

val

ues

may

not

refl

ect

pre

cise

cat

egory

bre

aks

due

to r

oundin

g.

Figure

3.

Perc

en

tage o

f W

ork

ers

55

to 6

4 Y

ears

Old

by C

ou

nty

of

Work

pla

ce i

n K

an

sas: 2

00

4

10 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

NEB

RA

SKA

OK

LAH

OM

A

MIS

SOU

RI

CO

LOR

AD

O

REN

O

NES

S

FORD

BUTL

ER

GO

VE

FIN

NEY

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S

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ER

LOG

AN

CLA

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ER

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DE

LAN

E

CO

WLE

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N

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KS

CLA

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OM

AS

RAW

LIN

S

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ASE

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Y

MA

RIO

N

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T

PHIL

LIPS

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MA

N

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ON

KIO

WA

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GE

SCO

TT

SALI

NE

HA

RPER

CLO

UD

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HA

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NO

RTO

N

WA

LLA

CE

SED

GW

ICK

CH

EYEN

NE

MIA

MI

OSB

ORN

E

DEC

ATU

R

PAW

NEE

HA

MILTO

N

GRE

ELEY

MO

RRIS

KIN

GM

AN

SHER

IDA

N

GRE

EN-

WO

OD

CO

FFEY

STEV

ENS

MA

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ALL

WIC

HIT

A

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AH

A

LIN

CO

LNO

TTAW

A

GRA

NT

ALL

EN

MO

RTO

N

REPU

BLIC

SEW

ARD

LABE

TTE

BRO

WN

DIC

KIN

-SO

N

STA

FFO

RD

WIL

SON

MIT

CH

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KSO

N

MC

PHER

-SO

N

HO

DG

EMA

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STA

NTO

NN

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L

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MA

NC

HE

WABA

UN

SEE

WA

SH-

ING

TON

BOU

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NED

WA

RDS

GEA

RY

ELLS

WO

RTH

FRAN

KLIN

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NEE

CH

ERO

KEE

JEFF

ER-

SON

POTT

A-

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OM

IE

AN

DER

-SO

N

CRA

WFO

RD

JOH

NSO

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LAS

WO

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CH

AU

T-A

UQ

UA

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NT-

GO

MER

YATCH

ISO

N

DO

NI-

PHA

N LEAV

-EN

W-

ORT

H

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OTT

E

Spat

ial D

ata

Sourc

e: U

.S. C

ensu

s Bu

reau

, C

ensu

s 2

00

0.

Stat

isti

cal D

ata

Sourc

e: L

ongit

udin

al E

mplo

yer-

House

hold

Dyn

amic

s Pr

ogra

m,

U.S

. C

ensu

s Bu

reau

, 2

00

6.

Perc

enta

ge

of

Work

ers

65

to 9

9 b

y C

ounty

Note

: A

ll boundar

ies

and n

ames

ar

e as

of

Januar

y 1

, 2

00

0.

STAT

EC

OU

NT

Y

6.2

to 9

.8

5.1

to 6

.1

4.0

to 5

.0

2.7

to 3

.9

02

55

07

51

00

Kilo

met

ers

02

55

07

51

00

Mile

s

Key

val

ues

may

not

refl

ect

pre

cise

cat

egory

bre

aks

due

to r

oundin

g.

Figure

4.

Perc

en

tage o

f W

ork

ers

65

an

d O

lder

by C

ou

nty

of

Work

pla

ce i

n K

an

sas: 2

00

4

U.S. Census Bureau The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 11

NEB

RA

SKA

OK

LAH

OM

A

MIS

SOU

RI

CO

LOR

AD

O

REN

O

NES

S

FORD

BUTL

ER

GO

VE

FIN

NEY

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S

ELK

RIC

E

GRA

Y

LYO

N

BARB

ER

LOG

AN

CLA

RKSU

MN

ER

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H

MEA

DE

LAN

E

CO

WLE

Y

JEW

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RUSH

TREG

O

LIN

N

ROO

KS

CLA

YTH

OM

AS

RAW

LIN

S

CH

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Y

MA

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N

PRAT

T

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LIPS

RUSS

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RNY

SHER

MA

N

BART

ON

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WA

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CLO

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HA

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NO

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N

WA

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CE

SED

GW

ICK

CH

EYEN

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OSB

ORN

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DEC

ATU

R

PAW

NEE

HA

MILTO

N

GRE

ELEY

MO

RRIS

KIN

GM

AN

SHER

IDA

N

GRE

EN-

WO

OD

CO

FFEY

STEV

ENS

MA

RSH

ALL

WIC

HIT

A

NEM

AH

A

LIN

CO

LNO

TTAW

A

GRA

NT

ALL

EN

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N

REPU

BLIC

SEW

ARD

LABE

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BRO

WN

DIC

KIN

-SO

N

STA

FFO

RD

WIL

SON

MIT

CH

ELL

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KSO

N

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PHER

-SO

N

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EMA

N

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NTO

NN

EOSH

O

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HA

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L

CO

MA

NC

HE

WABA

UN

SEE

WA

SH-

ING

TON

BOU

RBO

NED

WA

RDS

GEA

RY

ELLS

WO

RTH

FRAN

KLIN

SHAW

NEE

CH

ERO

KEE

JEFF

ER-

SON

POTT

A-

WAT

OM

IE

AN

DER

-SO

N

CRA

WFO

RD

JOH

NSO

ND

OUG

LAS

WO

OD

-SO

N

CH

AU

T-A

UQ

UA

MO

NT-

GO

MER

YATCH

ISO

N

DO

NI-

PHA

N LEAV

-EN

W-

ORT

H

WYA

ND

OTT

E

Spat

ial D

ata

Sourc

e: U

.S.

Cen

sus

Bure

au,

Cen

sus

20

00

.St

atis

tica

l D

ata

Sourc

e: L

ongit

udin

al E

mplo

yer-

House

hold

Dyn

amic

s Pr

ogra

m,

U.S

. C

ensu

s Bu

reau

, 2

00

6.

02

55

07

51

00

Kilo

met

ers

02

55

07

51

00

Mile

s

Key

val

ues

may

not

refl

ect

pre

cise

cat

egory

bre

aks

due

to r

oundin

g.

Perc

enta

ge

Chan

ge

in N

um

ber

of

Work

ers

55

and O

lder

,Fr

om

20

01

to 2

00

4, by

County

Note

: A

ll boundar

ies

and n

ames

ar

e as

of

Januar

y 1

, 2

00

0.

STAT

EC

OU

NT

Y

20

.4 t

o 5

1.7

12

.1 t

o 2

0.3

4.0

to 1

2.0

-15

.8 t

o 3

.9

Figure

5.

Perc

en

tage C

han

ge i

n N

um

ber

of

Work

ers

55

an

d O

lder

by C

ou

nty

of

Work

pla

ce

in K

an

sas: 2

00

1 t

o 2

00

4

12 The Geographic Distribution and Characteristics of Older Workers in Kansas: 2004 U.S. Census Bureau

ADDITIONAL RESOURCES

Other data tables with informationabout older workers are availablefor download from the LED Web sitein a comma-separated value (.csv)format. Brief descriptions of theavailable tables are given below.See <http://lehd.did.census.gov>for additional details.

Characteristics andEmployment Dynamics ofOlder Workers

Age composition

A series of tables shows absoluteand relative shares of older workersdisaggregated into four standardage ranges. The county aggregationlevel and the metropolitan statisticalarea and nonmetropolitan areaworkplace aggregation levels arepresented for 2004.

Industry sectors with a highproportion of older workers

Two tables contain data on the topfive industry sectors for older work-ers in 2004 at the county aggrega-tion level and at the metropolitanstatistical area and nonmetropolitanarea workplace aggregation levels.

Most likely industry sectors ofemployment for older workers

A table contains the top five indus-try sectors most likely to employ

workers 55 and older. The aggre-gation level is the county of work-place for 2004.

Job gains and losses

A series of tables displays gains,losses, and net changes in jobs forolder workers disaggregated intofour standard age ranges. Theaggregation level is the workplacecounty for 2004.

Average monthly earnings of older workers

A series of tables displays averagemonthly earnings for workers 55and older across industry sectorsand aggregated at the county, met-ropolitan statistical area, and non-metropolitan area workplace lev-els. An additional table presentsearnings across the four standardage ranges.

Appendix tables

These tables contain all remainingdatasets—aggregated by county,metropolitan statistical area, andnonmetropolitan area workplacelevels and organized by industryand age. Notable data include:employment totals for 2001 to2004, quarterly job loss/gain com-position for 2004, and averagemonthly earnings and employmentby Workforce Investment Areas.

ACKNOWLEDGMENTS

Research for and production of thisreport was supported under aninteragency agreement with theBehavioral and Social ResearchProgram, National Institute onAging, Agreement No. Y1-AG-9415-07, and under Grant No. R01-AG018854.

Thanks to Heath Hayward for pro-duction of the state maps. Also,thanks to Liliana Sousa, CorinneProst, and Matthew Armstrong forassistance in the statistical analysis.

MORE INFORMATION

This report is one of a series ofreports on older workers in statesin the LED partnership. Additionaltables of data and other detailedinformation can be found at theLED Web site, <http://lehd.did.census.gov>. Other data tools andapplications, such as QWI Onlineand OnTheMap, based upon LEDpartnership data, can also befound on the LED Web site.

SUGGESTED CITATION

Taeuber, Cynthia and Matthew R.Graham, 2008. The GeographicDistribution and Characteristics ofOlder Workers in Kansas: 2004.LED Older Workers Profile, LED-OW04-KS. U.S. Census Bureau,Washington, DC.