The Geographic Distribution and Characteristics of Older ...level. The most jobs lost by that age...

HIGHLIGHTS

The statistics about older workers in NewMexico 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 New Mexico.2

U.S.Department of CommerceEconomics and Statistics Administration

U.S. CENSUS BUREAU

Issued September 2008

LED-OW04-NM

The Geographic Distribution andCharacteristics of Older Workers in New Mexico: 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 by Agein Metropolitan StatisticalAreas and NonmetropolitanArea Workplaces in NewMexico: 2004

Figure 1— New Mexico Workforce byAge Group: 1995 to 2004

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

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

Figure 4— Percentage of Workers 65 andOlder by County of Workplacein New Mexico: 2004

Figure 5— Percentage Change inNumber of Workers 55 andOlder by County of Workplacein New Mexico: 2001 to 2004

ADDITIONAL RESOURCES

2 The Geographic Distribution and Characteristics of Older Workers in New Mexico: 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 New Mexicoof three groups of older workers areshown: those who may be receivingpension income but who are work-ing (65 and older) and two pre-retirement groups of workers (thoseaged 45 to 54 and aged 55 to 64),who may start collecting pensionsand social security over the nexttwo decades.

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

Following are highlights from thedetailed statistics.

Age Composition of the Workforce

• Of the 33 counties in NewMexico, 20.0 percent or more ofthe total workforce in 5 countieswas 55 and older.

• Statewide, 14.1 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

Hidalgo . . . . . . . . . . . . . 22.3

Union . . . . . . . . . . . . . . 22.1

Sierra . . . . . . . . . . . . . . . 19.5

Mora . . . . . . . . . . . . . . . 19.0

Lincoln . . . . . . . . . . . . . 18.0

• Statewide, 3.2 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

Lincoln . . . . . . . . . . . . . 5.1

Chaves . . . . . . . . . . . . . 4.3

Socorro . . . . . . . . . . . . . 4.3

Rio Arriba . . . . . . . . . . . 4.2

Luna . . . . . . . . . . . . . . . 4.1

• Of the 33 counties in NewMexico, 32 counties experi-enced an increase from 2001 to2004 in the percentage of thecounty workforce that was 55and older. The largest increasewas in Mora County.

• Of the total workforce employedin metropolitan statistical areas,about 13.7 percent was 55 andolder; in nonmetropolitan areaworkplaces, the proportion was15.2 percent.

Industry Sectors With theHighest Proportions of OlderWorkers in 20045

• Statewide, among industry sec-tors that employed 100 or moreworkers 55 and older, Educa-tional Services (NAICS 61) hadthe highest proportion of work-ers in this age group. This sec-tor had the highest percentageof workers 55 and older in 1 county.

• Statewide, the only industry sec-tor with more than 1 in 5 work-ers 55 and older that employedat least 100 or more workersfrom that age group was:

Percentage Industry of workforce

Educational Services . . . 22.0

• In metropolitan statistical areasof the state, the industry sectorthat employed the largest per-centage of workers 55 and olderwas Educational Services (NAICS61), with 21.7 percent; theindustry sector with the highestproportion of workers 65 andolder was Agriculture, Forestry,Fishing, and Hunting (NAICS 11),with 6.4 percent.

• In nonmetropolitan area work-places in New Mexico, the indus-try sector that employed thelargest percentage of workers 55and older was EducationalServices (NAICS 61), with 23.1percent. Agriculture, Forestry,Fishing, and Hunting (NAICS 11)was the industry sector with thehighest proportion of workers 65and older, with 6.8 percent.3 Counties with low employment (fewer

than 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 New Mexico: 2004 3

Industry Sectors Most Likelyto Employ Older Workers in 2004

• Of the workers in the state 55and older, 16.9 percent wereemployed in Health Care andSocial Assistance (NAICS 62), thehighest proportion for that agegroup of any industry sector inthe state. This industry wasranked number one in 10 of 33 counties.

• Of the workers 55 and older inthe state’s metropolitan statisti-cal areas, 16.0 percent wereemployed in Health Care andSocial Assistance (NAICS 62), thehighest proportion for that agegroup statewide among indus-trial sectors.

• Of the workers 55 and older inthe state’s nonmetropolitan areaworkplaces, 19.1 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, 4,849 jobs werecreated quarterly and 5,400jobs were lost quarterly. Forworkers 65 and older, the num-bers were 1,733 and 2,162,respectively.

• The county with the largestshare of job gains for workers55 to 64 years old wasBernalillo County, with 36.7 per-cent. The largest share of joblosses for such workers wasalso in Bernalillo County, with40.7 percent.

• The county with the largest shareof job gains for workers 65 andolder was Bernalillo County, with36.0 percent. The largest shareof job losses for such workerswas also in Bernalillo County,with 40.3 percent.

• The industry sector with thelargest gain in jobs for workers55 to 64 years old was RetailTrade (NAICS 44–45), with anaverage of 667 jobs gained perquarter at the state level. Themost jobs lost by that agegroup were also in Retail Trade(NAICS 44–45), with an averageof 698 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 235 jobsgained per quarter at the statelevel. The most jobs lost by thatage group were also in RetailTrade (NAICS 44–45), with 287jobs lost per quarter at the state level.

Average Earnings of OlderWorkers in 2004

• Statewide, on average, workers55 and older earned $3,196 amonth.

• Of industry sectors employing atleast 100 workers 55 and older,the highest paying wasProfessional, Scientific, andTechnical Services (NAICS 54).Workers in that sector earned, onaverage, $5,920 per month. Thelowest paying was Accom-modation and Food Services(NAICS 72). Workers in this sec-tor earned, on average, $1,379per 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]

Professional, scientific,

and technical services . . . . 5,920

Utilities . . . . . . . . . . . . . . . . 5,068

Mining . . . . . . . . . . . . . . . . . 4,856

Management of companies

and enterprises . . . . . . . . . 4,485

Finance and insurance . . . . . 4,455

Manufacturing . . . . . . . . . . . 3,770

Information . . . . . . . . . . . . . 3,567

Wholesale trade . . . . . . . . . . 3,551

Construction . . . . . . . . . . . . 3,275

Health care and

social assistance . . . . . . . . 3,129

Transportation and

warehousing . . . . . . . . . . . 2,960

Educational services . . . . . . 2,554

Administrative and support

and waste management

and remediation services . . 2,473

Real estate and rental

and leasing . . . . . . . . . . . . 2,251

Retail trade . . . . . . . . . . . . . 2,245

Other services (except

public administration) . . . . 1,944

Agriculture, forestry,

fishing, and hunting . . . . . 1,731

Arts, entertainment,

and recreation . . . . . . . . . . 1,686

Accommodation and

food services . . . . . . . . . . 1,379


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

Educational services . . . . 21.7

Agriculture, forestry,

fishing, and hunting . . . 20.6

Real estate and rental

and leasing . . . . . . . . . . 18.9


and technical services . . 18.4

Utilities . . . . . . . . . . . . . . 18.4

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

Percentage Industry of workers

Educational services . . . . 23.1

Transportation and

warehousing . . . . . . . . . 21.4


and technical services . . 20.9

Other services (except

public administration) . . 20.1

Arts, entertainment,

and recreation . . . . . . . 19.5

• In metropolitan statistical areas,of industry sectors employing atleast 100 workers 55 and older,the highest paying for workers55 and older was Professional,Scientific, and Technical Services(NAICS 54), which paid, on aver-age, $6,252 a month. The low-est paying was Accommodation

and Food Services (NAICS 72),which paid, on average, $1,478a month.

• In nonmetropolitan area work-places, of industry sectorsemploying at least 100 workers55 and older, the highest payingfor workers 55 and older wasMining (NAICS 21), which paid,on average, $4,508 a month.The lowest paying wasAccommodation and FoodServices (NAICS 72), which paid,on average, $1,186 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, the

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.


total number of workers who wereemployed by the same employer inthe reference quarter and theprevious quarter.

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 the UIwage records and the QCEW recordsare subjected to longitudinal editingevery quarter. A set of quality assur-ance tests is applied to the inte-grated data. These tests detectproblems known to cause nonsam-pling errors—primarily, tests formissing records of various types(based on estimates of the numberof expected records from alterna-tive sources), tests for incompletewage or earnings information, andtests for changes in the structure ofidentifiers or entities. Problemsdetected by these quality assurancetests are investigated and corrected

before data integration and produc-tion of the QWI are allowed to con-tinue.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 jobs held:

• 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 isused in this report for averageearnings because it reflects the

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.


earnings 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 cen-sus.

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 suppres-sion methodology and statisticalnoise, thereby controlling keymeasures to county employmentlevels as reported by the Bureau ofLabor Statistics. In other words,the Census Bureau uses statisticaltechniques in which the actual

statistics are not shown if the num-bers in a cell are small. In addition,the statistics that are shown are“fuzzy,” meaning close to theactual information 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>.


CHARACTERISTICS AND EMPLOYMENT DYNAMICS OF OLDER WORKERS

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

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New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.6 11.0 3.2 14.1Albuquerque, NM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.5 10.8 2.9 13.7Farmington, NM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 9.8 2.5 12.3Las Cruces, NM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.8 10.1 2.9 13.0Santa Fe, NM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 12.2 3.7 15.9

All metropolitan areas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.5 10.8 3.0 13.7All nonmetropolitan area workplaces. . . . . . . . . . . . . . . . . . . . . 21.7 11.4 3.7 15.2

Note: Discrepancies may occur due to rounding.

Source: U.S. Census Bureau and the state of New Mexico, 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.New Mexico Workforce by Age Group: 1995 to 2004

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

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

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4


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 the LED Web site,<http://lehd.did.census.gov>. Otherdata tools and applications, such asQWI Online and OnTheMap, basedupon LED partnership data, can alsobe found on the LED Web site.

SUGGESTED CITATION

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

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