Full Report - Kossuth County Economic Development

Kossuth County, IowaLaborshed AnalysisA Study of Workforce CharacteristicsReleased March 2013

A Project of:Kossuth County Board of SupervisorsIn Partnership with:For more information regarding the Kossuth County Laborshed Analysis, contact:Kossuth/Palo Alto County Economic Development Corp.106 S Dodge St, Ste 210Algona, IA 50511Phone: 515-295-7979Fax: 515-295-8873Email: kcedc@kossuthia.comwww.kossuth-edc.comwww.paloaltoiowa.com

T CLaborshed Analysis 1Esmang the Total Labor Force Potenal 2Primary Industries of the Laborshed 5Workforce Stascs 6Analysis of Those Employed Willing to Change Employment 10Out‐Commuters 17Esmated Underemployed 18Willingness of Those Not Currently Employed to Accept Employment 21Unemployed 21Voluntarily Not Employed/Not Rered 24Rered Persons 24Laborshed MapsCommuter Concentraon by Place of Residence into Algona 25Labor Market Areas in Region: Kossuth County Laborshed Area 26Survey Zones by ZIP Code: Kossuth County Laborshed Area 27Commuter Concentraon by Place of Residence into Bancro 28Commuter Concentraon by Place of Residence into Burt 29Commuter Concentraon by Place of Residence into Swea City 30Commuter Concentraon by Place of Residence into Titonka 31Commuter Concentraon by Place of Residence into Wesley 32Commuter Concentraon by Place of Residence into West Bend 33Commuter Concentraon by Place of Residence into Whiemore 34AppendicesA. Background Informaon 36B. Survey Methodology and Data 37C. Current Methods for Esmang Employment and Unemployment 38D. Occupaonal Employment Stascs (OES) Category Structure 41Labor Market Informaon (Employer‐Based) Web Resources 42References 43Index of Figures 44Kossuth County Laborshed Analysis i Released March 2013

Kossuth County Laborshed Analysis ii Released March 2013

L AThe purpose of this Laborshed analysis is to measure the availability and characteriscs of workers within theregion by developing and conducng a telephone survey based on geographic principles. The Laborshed datagenerated will aid local development officials in their facilitaon of industry expansion and recruitment andtheir service to exisng industry in the area. All such enes require detailed data describing thecharacteriscs of the available labor force including current/desired wage rates and benefits, job qualificaonsand skills, age cohorts, residence/work locaon, employment requirements/obstacles and the distancesindividuals are willing to travel for employment.The first step in determining the potenal available labor supply requires an understanding of the Laborshed.Such an understanding will assist local development efforts by delineang the actual geographic boundariesfrom which communies are able to aract their workers. Determining the area’s Laborshed also builds thefoundaon for collecng valuable survey data and making esmates concerning the characteriscs of thearea’s potenal labor force.In order to determine the boundaries of the Laborshed area, Iowa Workforce Development (IWD) workedclosely with the Kossuth/Palo Alto County Economic Development Corp. to idenfy where current employeesreside. Employees were then aggregated into ZIP codes and placed into a geographic display for analysis (seeCommuter Concentraon by Place of Residence map).Applying the mapping funcon of ArcView Geographic Informaon System (GIS) soware produces thegeographic display. This GIS program has been ulized to overlay the ZIP code data set, the county data setand transportaon routes. IWD’s database of ZIP code data sets allows for numerous analyses andcomparisons of the potenal labor force, such as examining the complete demographic data for a ZIP code’sage cohorts (age groupings). Another benefit of applying GIS’s mapping funcon is the ability to idenfyvisually where the workers are located, concentraons of labor and transportaon routes used to travel towork. This representaon is a valuable tool in understanding the distribuon of the labor force within theregion.The GIS analysis of the Laborshed area illustrates that segments of the Kossuth County Laborshed area arelocated within a 30‐mile radii of the Albert Lea (MN), Emmetsburg (IA), Fairmont (MN), Forest City (IA), FortDodge (IA), Mason City (IA), Spencer (IA) and Webster City (IA) labor market areas (see Labor Market Areas inRegion map). These labor centers will have an impact on the size of the area’s labor force and on thearacon of workers from within the Laborshed area. The Laborshed complements exisng sources of labordata, such as the U.S. Department of Labor’s Bureau of Labor Stascs (BLS) and the Employment Stascs (ES)and Labor Force & Occupaonal Analysis Bureaus of IWD that concentrate on geographic areas based generallyon a county or groups of counes.The following secons of this report summarize the results of the Laborshed survey. Due to the magnitude ofthe survey results, it is not praccal to review each set of variables. Instead, IWD has focused on the factorsfound to be the most valuable to exisng and future businesses. However, IWD will certainly conductaddional analyses if the development corporaons and/or local businesses desire further review of specificvariable(s) or sets of responses.Kossuth County Laborshed Analysis 1 Released March 2013

E T L F PThe fundamental goal of any Laborshed analysis is to esmate the potenal availability of workers anddetermine how well the surrounding geographical areas are able to provide a stable supply of workers to thecentral Laborshed node (see Figure 1).Prior to applying the survey results for the Kossuth County Laborshed area, it was necessary to esmate thesize of the potenal labor force between the ages of 18 and 64 by ZIP code and survey zone. A variety ofsources: U.S. Census Bureau, Bureau of Labor Stascs (BLS), Iowa Workforce Development (IWD) and privatevendor publicaons and data sets are used to esmate the size and demographic details of the potenal laborforce of the Kossuth County Laborshed area.A number of adjustments are made to the Kossuth County Laborshed area. The first adjustment is to accountfor differences in the labor parcipaon rates within each of the zones. These adjusted rates are achieved bydividing the labor force cohort between the ages of 18 and 64 by the populaon cohort between the ages of 18and 64 (LFC/PC). The labor force cohort includes both employed and non‐employed persons that are lookingfor work. This rao is similar to the BLS labor force parcipaon rate (LFPR), except that the LFPR includes thetotal civilian non‐instuonalized populaon age 16 and above. Since most employers are more concernedwith the populaon between the ages of 18 and 64, cohort groups below age 18 and above age 64 areremoved.Employment demographic variables such as employment status, age, educaon level and miles driven to workare taken into consideraon when esmang the availability of workers. Of parcular interest is the ordinalvariable that rates a person’s desire to change employment on a 1‐4 scale (1=very likely to change; 4=veryunlikely to change).Factors are explored at both the micro (individual) level and at the macro (zip code or Laborshed) level. Theprobability of persons willing to accept or change employment is esmated using a logisc regression withpolytomous response model, which is based upon the above demographic variables drawn from survey data.This probability is then used to esmate the total number of persons willing to accept or change employmentwithin each ZIP code.Kossuth County Laborshed Analysis 2 Released March 2013

Figure 1Esmated Total Potenal Labor ForceKossuth County Laborshed AreaZIPCodeTotal Population18 to 64Total AdjustedLabor ForceTotal Willing toChange/AcceptEmployment*Zone 1Algona, IA 50511 3,967 3,765 1,840Total Zone 1 3,967 3,765 1,840Zone 2Britt, IA 50423 1,622 1,330 552Titonka, IA 50480 459 436 182Wesley, IA 50483 436 414 179Bancroft, IA 50517 536 509 216Bode, IA 50519 343 284 121Burt, IA 50522 495 470 207Cylinder, IA 50528 227 202 86Fenton, IA 50539 310 294 123Humboldt, IA 50548 3,183 2,639 1,093Livermore, IA 50558 373 309 131Lone Rock, IA 50559 202 192 81Lu Verne, IA 50560 340 323 136Ottosen, IA 50570 141 117 49West Bend, IA 50597 682 606 254Whittemore, IA 50598 517 491 214Total Zone 2 9,866 8,616 3,624Zone 3Mason City, IA 50401 18,228 15,732 533Buffalo Center, IA 50424 753 575 30Clear Lake, IA 50428 5,535 4,777 196Corwith, IA 50430 297 243 21Forest City, IA 50436 3,713 2,834 122Garner, IA 50438 2,367 1,940 107Kanawha, IA 50447 579 475 25Lakota, IA 50451 307 291 20Thompson, IA 50478 465 355 15Ventura, IA 50482 474 409 19Woden, IA 50484 241 198 13Zone 3 Continued on Next PageWeighted Labor Force*Total willing to Change/Accept Employment references those who would be willing to commute into Zone 1 from theirhome ZIP Code for an employment opportunity.Some ZIP codes may not be idenfied above due to lack of informaon from the U.S. Census Bureau.Kossuth County Laborshed Analysis 3 Released March 2013

Figure 1 (cont’d)Esmated Total Potenal Labor ForceKossuth County Laborshed AreaZIPCodeWeighted Labor ForceTotal Population18 to 64Total AdjustedLabor ForceTotal Willing toChange/AcceptEmployment*Zone 3 ContinuedFort Dodge, IA 50501 17,998 13,718 578Armstrong, IA 50514 825 734 38Badger, IA 50516 424 323 17Bradgate, IA 50520 94 78 5Clarion, IA 50525 1,984 1,696 64Dakota City, IA 50529 518 429 31Eagle Grove, IA 50533 2,337 1,998 84Emmetsburg, IA 50536 2,666 2,371 178Gilmore City, IA 50541 511 424 23Goldfield, IA 50542 561 480 22Hardy, IA 50545 121 100 7Ledyard, IA 50556 146 139 10Renwick, IA 50577 229 190 12Ringsted, IA 50578 361 321 20Rutland, IA 50582 147 122 9Swea City, IA 50590 494 469 33Woolstock, IA 50599 220 188 6Graettinger, IA 51342 709 630 30Ruthven, IA 51358 715 636 32Blue Earth, MN 56013 2,495 2,131 83Elmore, MN 56027 35 30 2Elmore, MN 56027 482 412 21Fairmont, MN 56031 7,050 6,055 205Total Zone 3 74,081 61,503 2,611Grand Total 87,914 73,884 8,075*Total willing to Change/Accept Employment references those who would be willing to commute into Zone 1 from theirhome ZIP Code for an employment opportunity.Some ZIP codes may not be idenfied above due to lack of informaon from the U.S. Census Bureau.Kossuth County Laborshed Analysis 4 Released March 2013

P I LI I T K C L A ‐ EIn order to provide consistency with other labor market informaon, the industrial categories idenfied in thisLaborshed analysis will follow a similar format of the Standard Industrial Classificaon Manual (1987).Survey respondents from the Kossuth County Laborshed area were asked to idenfy the industry they arecurrently working. The following informaon is based on the responses from those Laborshed respondentswho are currently employed (Figure 2).Figure 2Where the Employed are Working20.0%19.4%18.0%16.0%14.0%12.0%10.0%8.0%6.0%4.0%2.0%ManufacturingWholesale & Retail Trade15.8%Educaon14.6% 14.2%7.1%Healthcare & Social Services*FinancePersonal Services6.7%*Agriculture5.9%Professional Services5.1%Government & Public AdministraonTransportaon, Communicaons & Ulies4.3% 4.3%Construcon2.0%Entertainment & Recreaon0.6%0.0%*Finance, Insurance & Real Estate*Agriculture, Forestry & MiningKossuth County Laborshed Analysis 5 Released March 2013

W SEssenally, when everything else is stripped away, it is the people that are the key to a business’ success(Expansion Management, January 2003) and in nearly all site locaon studies, labor constutes one of the most– if not the most – important criterion of the study (AreaDevelopment, April/May 2006). Profiling thecharacteriscs of a community’s Laborshed reveals a very dynamic and diverse collecon of skills, abilies,work experience and preferences among residents. It is important to analyze each grouping of respondents toidenfy and respect their uniqueness and contribuons to the Laborshed. The employed individuals who are“very likely” or “somewhat likely” to change jobs within their company or accept a posion with a differentemployer represent the primary pool of available labor. Many factors must be taken into account whenevaluang these workers, such as employment experiences, unused skills, educaon, wages and benefitsdesired and the distance individuals are willing to travel to work. Current literature does not suggest standardsby which to compare this Laborshed data, however, results from previous Laborshed studies conducted byIowa Workforce Development (IWD) and the University of Northern Iowa’s Instute for Decision Making (IDM)form a base of comparison for the study.D EThe gender breakdown of those respondents, who are employed, is 50.8 percent male and 49.2 percentfemale. The average age of the employed is 51 years old. A small poron (2.9%) of the employed respondentsspeak more than one language in their household. Of those respondents, 60.0 percent speak Spanish.E SThe results of this Laborshed survey show that 76.8 percent of all the respondents idenfied themselves asbeing employed at the me they were contacted (Figure 3). The majority (71.7%) of the employed are workingin posions that are considered full‐me (Figure 3).100%80%60%40%20%Figure 3Employment Status of Survey Respondents*Percent Willing to Change/Accept Employment76.8%58.3%34.8%21.5%14.3%Type of Employment0.4% Seasonal12.5%Part‐Time15.4%Self‐Employed71.7%Full‐Time0%8.9% 5.7% 8.6%Employed Unemployed Voluntarily Not RetiredEmployed/Not Retired*Employment status is self‐idenfied by the survey respondent. The unemployment percentage above does not reflect theunemployment rate published by the U.S. Bureau of Labor Stascs, which applies a stricter definion.Nearly one‐fih (15.4%) of the employed respondents are self‐employed. The types of businesses they areoperang include farming (36.6%), child care (12.2%), professional services (9.8%), personal services (7.3%),retail (7.3%), construcon/handyman (4.9%), healthcare/social services (4.9%), trucking/logiscs (4.9%), arst/wring/music/photography (2.4%), automove repair/service (2.4%), consulng (2.4%) or lawn care/snowremoval (2.4%). The self‐employed have been operang their businesses for an average of 21 years, rangingfrom one to 44 years.E TNearly three‐fourths (71.1%) of the employed residents in the Laborshed area have some level of educaon/training beyond high school, 6.1 percent are trade cerfied, 2.3 percent have completed vocaonal training,11.9 percent have an associate degree, 23.2 percent have an undergraduate degree and 9.6 percent have apostgraduate/professional degree.Kossuth County Laborshed Analysis 6 Released March 2013

Figure 4Educaonal Fields of StudyFields of StudyO E% ofLaborshedBusiness, Public Administration & Marketing 19.2%Social Sciences 16.1%Education 14.0%Vocational Trades 13.0%Business Administrative Support 11.9%Healthcare/Medical Studies 9.8%Agricultural Studies 5.7%Math & Science 3.1%Engineering & Architecture 2.6%General Studies/Liberal Arts 2.6%Computer Applications/Programming/Technology 2.0%Figure 4 provides an overview of the educaonalfields of study of those who are currentlyemployed in the Laborshed area.IWD recodes the respondents’ actual occupaons into one of the seven Occupaonal Employment Stascs(OES) categories. The occupaonal categories represent a variety of specific occupaons held by therespondents (see OES Category Structure ‐ Appendix D). Classifying the employed by occupaonal group,Figure 5 shows that the largest concentraon of the workforce are employed within the professional,paraprofessional & technical occupaonal category. The agricultural occupaonal category represents thesmallest sector of workers who are currently employed. The totals are based on the Total Adjusted LaborForce esmates found in Figure 1 and the percentage of employed in the Laborshed area.Figure 5Esmated Workforce by OccupaonOccupational CategoryPercent ofRespondentsPotential Totalin LaborshedProfessional, Paraprofessional & Technical 28.6% 16,228Production, Cons truction, Operating,Maintenance & Material Handling20.5% 11,632Managerial/Administrative 16.9% 9,590Sales 11.4% 6,469Clerical/Administrative Support 10.4% 5,901Service 7.1% 4,029Agriculture 5.1% 2,894Total 100% 56,743Figure 6 provides a comparison of the gender distribuon within each occupaonal category.Figure 6Occupaonal Categories by GenderOccupational Category Male FemaleManagerial/Administrative 67.2% 32.8%Professional, Paraprofessional & Technical 36.8% 63.2%Sales 42.5% 57.5%Clerical/Administrative Support 13.3% 86.7%Service 30.6% 69.4%Agriculture 68.4% 31.6%Production, Construction, Operating,Maintenance & Material Handling85.1% 14.9%Kossuth County Laborshed Analysis 7 Released March 2013

Figure 7 illustrates the percentage of respondents within each occupaonal category by zone of residence.The figure shows that occupaonal experiences are generally spread across the survey zones. Although Zone 1is the primary node in the Laborshed area, the figure illustrates the impact of the other zones on the extent ofavailable labor. Within most of the occupaonal categories, the largest percentage of workers may oenreside in outlying zones.W ROccupational CategoryZone 1% of ZoneZone 2% of ZoneZone 3% of ZoneManagerial/Administrative 24.1% 41.4% 34.5%Professional, Paraprofessional & Technical 38.6% 28.1% 33.3%Sales 27.5% 40.0% 32.5%Clerical/Administrative Support 37.8% 31.1% 31.1%Service 30.6% 36.1% 33.3%Agriculture 36.8% 42.1% 21.1%Production, Construction, Operating,Maintenance & Material Handling34.5% 31.0% 34.5%Equals 100% across the zonesFigure 7Occupaon Categories Across the ZonesRespondents are surveyed on either an hourly or salaried basis; hourly wages are not converted to annualsalaries. The Kossuth County Laborshed area has a higher concentraon of respondents who are currentlyreceiving an hourly wage (53.8%) versus those who are receiving an annual salary (35.2%). The current medianwage of those who are employed is $14.50 per hour and the median salary is $52,000 per year.Figure 8 provides the current median wages and salaries by industry of the respondents in the Laborshed area.This wage informaon is an overview of all employed within the Laborshed area without regard tooccupaonal categories or willingness to change employment. If businesses are in need of wage rates within adefined Laborshed area, the survey data can be queried by various aributes to provide addional analysis ofthe available labor supply. The actual wage levels required by prospecve workers will vary betweenindividuals, occupaonal categories, industries and economic cycles.Figure 8Median Wages & Salaries by IndustryIndustryNon Salary(per hour)Salary(per year)Agriculture * *Construction * *Manufacturing $ 19.15 $ 60,000Transportation, Communication & Utilities * *Wholesale & Retail Trade $ 11.00 $ 58,000Finance, Insurance & Real Estate * $ 50,000Professional Services * $ 46,000Healthcare & Social Services $ 14.25 $ 58,000Entertainment, Recreation & Personal Services $ 13.00 $ 46,750Government & Public Administration $ 16.00 $ 41,500Education $ 10.02 $ 52,500* Insufficient survey data/refusedKossuth County Laborshed Analysis 8 Released March 2013

Figure 9Median Wages & Salaries by Occupaonal CategoryFigure 9 illustrates current wage rates ofthose who are currently employed withineach defined occupaonal category.Occupational CategoryNon Salary(per hour)Salary(per year)Managerial/Administrative $ 17.82 $ 54,750Professional, Paraprofessional & Technical $ 15.35 $ 52,500Sales $ 9.55 $ 40,000Clerical/Administrative Support $ 14.50 $ 45,000Service $ 13.00 *Agriculture * *Production, Construction, Operating,Maintenance & Material Handling$ 17.87 $ 50,000* Insufficient survey data/refusedWages by gender differ in the Kossuth County Laborshed area. The current median hourly wage of employedfemales in the Laborshed area is $13.00 per hour and the current median hourly wage of employed males is$18.20 per hour. This $5.20 per hour wage difference has females in the Kossuth County Laborshed areareceiving an hourly wage of 28.6 percent less than males. Females who are receiving an annual salary also arefaced with gender wage disparity ($11,000 per year). Currently females are making a median annual salary of$45,000 per year while males are making a median salary of $56,000 a year. This results in an 19.6 percentdifference in annual salaries.E BThere are a variety of benefit packages being offered to employees within the Kossuth County Laborshed areain addion to wages. Current benefits are shown in Figure 10. Slightly over four‐fihs (80.3%) of therespondents in the Laborshed area state they are currently sharing the premium costs of health/medicalinsurance with their employer, 15.9 percent indicate their employer covers the enre cost of insurancepremiums while 3.8 percent indicate they have made other arrangements.C5.9%2.1%1.7%1.3%0.8%0.8%Figure 10Current Benefits Offered by EmployersHealth/Medical InsurancePension/Retirement Options 69.2%Dental Coverage48.1% 54.9% Paid VacationVision Coverage 35.9%Life Insurance28.7% 34.6%Paid HolidaysDisability Insurance 27.4%Paid Sick Leave 27.4%18.6% Prescription Drug CoveragePaid Time OffIncentive Reward ProgramsFlextimeTuition Assistance/ReimbursementShift Differential PayFlex Spending Accounts88.2%0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%Overall, individuals are commung an average of 7 miles one way for employment opportunies. Those wholive in Zone 1 are commung an average of 5 miles one way, while residents in Zone 2 are commung anaverage of 9 miles one way and Zone 3 residents are commung an average of 6 miles one way foremployment. Keep in mind that for those residing in Zones 2 and 3 commung distances of less than 20 milesone way may or may not get them into the nodal community (Algona).Kossuth County Laborshed Analysis 9 Released March 2013

A T EW C EAnalyzing the employed based on their willingness to change employment creates a profile of individualsinterested in changing from their current posion. The data shows that 21.5 percent of those who arecurrently employed within the Laborshed area indicated they are either “very likely” or “somewhat likely” tochange employers or employment if presented with the right job opportunity. Job sasfacon is the primaryreason that those who are currently employed are not willing to consider changing employment. A goodworking relaonship with current employer, age near rerement, wages, benefits, self‐employed, seniority,flexibility of work hours, job security, employment locaon close to home, family reasons, current hours/shis,a good working relaonship with current coworkers, lack of job opportunies, health issues and just started anew job are other reasons menoned but not as frequently.Total AdjustedLabor Force by ZoneFigure 11Totals by ZoneEstimated Total Willing toChange/Accept by Zone*Estimated Number ofEmployed Willing toChange by Zone*Zone 1 3,765 1,840 1,516Zone 2 8,616 3,624 2,988Zone 3 61,503 2,611 1,262Total 73,884 8,075 5,766*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 fromtheir home ZIP code for an employment opportunity.Figure 11 shows the employed willing to change employment residing throughout the survey zones.Respondents willing to change employment by zone are calculated using a logisc regression model weightedby mulple variables such as educaon level, gender, age, miles willing to travel and wages. This modelprovides an esmate for the total number of individuals “willing to change” by zone. The totals are based onthe Total Adjusted Labor Force esmates found in Figure 1.Slightly over one‐fourth (25.8%) of those who are employed, willing to change employment, are working twoor more jobs. This group would prefer to work full‐me hours for one employer versus working for mulpleemployers to accomplish full‐me employment. Those who are employed willing to change are currentlyworking an average of 46 hours per week. Over one‐tenth (13.4%) would consider employment offers thatrequire them to work more hours. Further analysis finds that 84.2 percent would prefer to work full‐meposions (35+ hrs./week), while 15.8 percent prefer posions with less than full‐me hours. Temporary andseasonal employment opportunies do not appeal to the majority of those who are currently employed andwilling to change employment. Seasonal employment would interest 32.8 percent, while 31.3 percent wouldconsider a temporary employment offer.When asked about their interest in entrepreneurship opportunies, 13.4 percent of the employed, that arewilling to change employment, expressed an interest in starng a business. The types of businesses they areprimarily interested in starng include trucking/logiscs (37.5%), automove repair/service (12.5%) andfarming (12.5%). However, the majority find access to capital/start‐up funds is the primary impediment ofoperang their own business venture followed by development of a business plan, concerns about theeconomy, finding a prime business locaon, insurance issues and risk involved.A G EThe gender breakdown of respondents willing to change employment is distributed 62.7 percent male and 37.3percent male. Figure 12 (on next page) compares the gender distribuon among the employed respondentswilling to change employment in each zone. These calculaons are based on the Esmated Number ofEmployed Willing to Change of 5,766 projecons found in Figure 11.Kossuth County Laborshed Analysis 10 Released March 2013

Figure 12Esmated Totals by Zone & GenderFemale Male Female Male Female Male% of Zone 40.0% 60.0% 37.5% 62.5% 34.6% 65.4%Estimated Total by Zone 606 910 1,121 1,868 437 825Totals may vary due to rounding methods.Zone 1 Zone 2 Zone 3The average age of those willing to change employment is 49 years of age. Figure 13 provides a breakdown byage category of the employed respondents who are willing to change employment. These calculaons arebased on the Esmated Number of Employed Willing to Change of 5,766 projecons found in Figure 11.E TAge RangeFigure 13Age Range DistribuonThe survey results show that 70.1 percent of the respondents willing to change employment have some level ofeducaon/training beyond high school, 6.0 percent are trade cerfied, 1.5 percent have completed vocaonaltraining, 14.9 percent have an associate degree, 28.4 percent have an undergraduate degree and 6.0 percenthave a postgraduate/professional degree. As with other segments of the Laborshed study, educaon levelsvary by industrial and occupaonal categories, gender and age groups. Addional data can be provided forspecific inquiries regarding educaon and training by contacng the Kossuth/Palo Alto County EconomicDevelopment Corp.Figure 14 provides an overview of the educaonal fields of study for those who are employed and willing tochange employment.Fields of Study% ofRespondentsPotential Totalin Laborshed18 to 24 3.0% 17325 to 34 6.0% 34635 to 44 19.4% 1,11945 to 54 37.3% 2,15155 to 64 34.3% 1,978Total 100% 5,767Totals may vary due to rounding methods.Figure 14Educaonal Fields of Study% ofLaborshedSocial Sciences 25.0%Education 18.2%Vocational Trades 18.2%Business, Public Administration & Marketing 15.9%Business Administrative Support 6.8%Healthcare/Medical Studies 4.5%Math & Science 4.5%Agricultural Studies 2.3%Computer Applications/Programming/Technology 2.3%Engineering & Architecture 2.3%General Studies/Liberal Arts ** Insufficient survey data/refusedEducaon and training are the keys to successful careers and employment opportunies. Over two‐fihs(44.8%) of the employed, willing to change employment, realize to make a successful transion to newemployment or be promoted within their current organizaon, they will need addional educaon/training.Kossuth County Laborshed Analysis 11 Released March 2013

Those respondents desire to start/finish college degree (42.4%), aend computer courses (12.1%), aendvocaonal training (6.1%), obtain connuing educaon units “CEU’s” (6.1%) and parcipate in on‐the‐jobtraining (3.0%). The primary areas of computer training which they want to take are soware classes (Office,Word, etc.) (50.0%), general computer operaons (keyboarding, etc.) (25.0%) and programming (COBOL, JAVA,network administraon, etc.) (25.0%).One‐fourth (25.0%) are likely to seek addional training/educaon in their specified areas of study within thenext year. Age, lack of me (work scheduling conflicts) and financing are the primary obstacles to obtainingtheir educaonal/training needs.Community and economic developers, college/university professionals and human resource professionals mayuse this informaon as a guide for determining and enhancing their workforce educaon and trainingprograms.O EIWD recodes the respondents’ actual occupaons into one of the seven Occupaonal Employment Stascs(OES) categories. The occupaonal categories represent a variety of specific occupaons held by therespondents (see OES Category Structure ‐ Appendix D). Classifying the employed by current occupaons andlikeliness to change, Figure 15 shows that the largest concentraon of potenal available labor is employedwithin the producon, construcon & material moving occupaonal category. The agricultural occupaonalcategory represents the smallest sector of workers willing to change employment. The calculaons forpotenal available labor are based on the Esmated Number of Employed Willing to Change of 5,766projecons found in Figure 11.Figure 15Esmated Workforce by OccupaonOccupational Category% ofRespondentsPotentialTotal in LaborshedProduction, Construction, Operating,Maintenance & Material Handling31.8% 1,834Professional, Paraprofessional & Technical 27.3% 1,574Sales 16.7% 963Clerical/Administrative Support 10.6% 611Managerial/Administrative 9.1% 525Service 3.0% 173Agriculture 1.5% 86Total 100% 5,766Figure 16 provides a comparison of those willing to change employment by gender. The Kossuth CountyLaborshed area has a higher percentage of males who are employed willing to change than females (62.7% and37.3%, respecvely). Employers within the Laborshed area looking to fill posions can ulize this informaonto more efficiently focus their recruitment efforts in the occupaonal categories from which they plan to hire.The occupaonal categories encompass a widevariety of individual occupaons in whichworkers in the Laborshed area are employed. Insome cases, workers willing to change posionsmay be employed in jobs that do not maximizeall of their available skills and work experiences.Employees may possess talents that gounulized or unrecognized by their currentemployer. Employers tapping into this resourcemay be effecve in aracng employees todifferent posions or increasing their value tothe company. For a list of current or previousoccupaonal tles and experiences in theKossuth County Laborshed area, contact theKossuth/Palo Alto County Economic DevelopmentCorp.Occupational Category Male FemaleManagerial/Administrative 100.0% 0.0%Professional, Paraprofessional & Technical 55.6% 44.4%Sales 36.4% 63.6%Clerical/Administrative Support 28.6% 71.4%Service * *Agriculture * *Production, Construction, Operating,Maintenance & Material Handling* Insufficient survey data/refusedFigure 16Occupaonal Categories by Gender90.5% 9.5%Kossuth County Laborshed Analysis 12 Released March 2013

Employers may be aided in their recruing efforts by being able to idenfy the respondents by their occupaonand area of residence. Figure 17 illustrates the percentage of respondents in each occupaonal categorywithin each Laborshed zone.Occupational CategoryZone 1% of ZoneZone 2% of ZoneZone 3% of ZoneManagerial/Administrative 16.7% 16.7% 66.6%Professional, Paraprofessional & Technical 55.6% 16.7% 27.7%Sales 36.4% 27.3% 36.3%Clerical/Administrative Support 42.9% 28.6% 28.5%Service * * *Agriculture * * *Production, Construction, Operating,Maintenance & Material Handling33.3% 33.3% 33.4%Equals 100% across the zones* Insufficient survey data/refusedFigure 17Occupaonal Categories Across the ZonesThe figure shows that theoccupaonal experiences aregenerally spread across the surveyzones, but the outlying zones have asubstanal effect on a community’s in‐commute, thus affecng manyeconomic factors. For the most part,employers looking to fill posionswithin these occupaonal categoriesmay want to expand their recruitmentefforts to include communiessurrounding Algona.Figure 18 details the occupaonalcategories the residents wouldconsider seeking employment bysurvey zone of residence. Thisinformaon can provide businesses,community developers and leaders a“snapshot” for future communitygrowth.Figure 18Desired Occupaonal Categories Within the ZonesDesired Occupational CategoryZone 1% of ZoneZone 2% of ZoneZone 3% of ZoneManagerial/Administrative 5.0% 0.0% 13.6%Professional, Paraprofessional & Technical 60.0% 45.5% 36.4%Sales 10.0% 9.1% 4.6%Clerical/Administrative Support 5.0% 18.1% 9.1%Service 10.0% 9.1% 13.6%Agriculture 0.0% 9.1% 0.0%Production, Construction, Operating,Maintenance & Material Handling10.0% 9.1% 22.7%Equals 100% within the zoneAs Figure 18 notes, those who are employed within the Kossuth County Laborshed area who are willing tochange employment are looking for a wide variety of employment opportunies. However, the majority ofthose who reside in Zone 1 (Algona) are looking for posions within the professional, paraprofessional &technical occupaonal category (approximately 910 people). Those who reside in Zone 2 and Zone 3 are alsoprimarily looking for posions within the professional, paraprofessional & technical occupaonal category(approximately 1,360 people in Zone 2 and 459 people in Zone 3). Projecons are based on zone totalsobtained from Figure 11.W RFigure 19 provides data concerning the employed respondents’ current median wages and salaries, by theirlikeliness to change employment. Addional data from the survey can be analyzed to provide businesses abenchmark for determining wage rates in the Laborshed area. The actual wage levels required by prospecveworkers will vary between individuals, occupaonal categories, industries and economic cycles. Nearly threefihs(59.7%) are hourly wage earners.Figure 19Comparison of Current Wage DataCurrent MedianWage/SalaryAll EmployedHourly Wage 14.50Yearly Salary 52,000Those Likelyto ChangeThose Unlikelyto Change$ $ 14.50 $ 14.46$ $ 50,000 $ 54,000Kossuth County Laborshed Analysis 13 Released March 2013

As Figure 19, on the previous page, shows there is a disparity between the median annual salaries ofrespondents likely to change employment and those content with their current posion ($4,000/yr). Thosewho changed jobs in the past year cited employer layoff/relocaon (31.3%), beer wages (25.0%), familyreasons (12.5%), beer hours (6.3%), career change (6.3%), personality conflicts with former employer/coworkers (6.3%), respondent was fired from previous employment (6.3%) and working condions (6.3%) asthe primary reasons for change.Figure 20 reflects those who are currently employed willing to change and the esmated wage range requiredto aract 66 percent to 75 percent of the hourly wage applicants by industry. The wage threshold of allemployed residents who are “very likely” or “somewhat likely” to change employment is esmated to be$18.72 to $20.00 per hour regardless of industry. Salaried employees willing to change employment have athreshold of $50,000 to $60,000 per year.Figure 20Wage Threshold by IndustryIndustryWage ThresholdNon Salary(per hour)Agriculture *Construction *Manufacturing $20.00 ‐ $21.00Transportation, Communication & Utilities *Wholesale & Retail Trade $11.88 ‐ $12.71Finance, Insurance, Real Estate & Professional *Healthcare & Social Services *Entertainment, Recreation & Personal Services *Government & Public Administration *Education $12.30 ‐ $12.75* Insufficient survey data/refusedAnother comparison to consider is the employed respondents’ lowest wages considered based on gender.Figure 21 provides the lowest wages considered between the genders.Figure 21Comparison of Lowest Wages Considered by GenderLowest Median Wage/SalaryCons ideredMale FemaleLowest Median Hourly Wage $ 19.00 $ 11.50Lowest Median Yearly Salary $ 50,000 $ 40,000In many Laborshed areas, there is a discrepancy between the lowest wages considered of males and females.This holds true in the Kossuth County Laborshed area when looking at hourly wage rates of those who arewilling to change employment without regard to specific industry. The lowest median hourly wage thatfemales would consider is 39.5 percent less than that of males. Likewise, the median salary females wouldconsider is 20.0 percent less than that of males. Some of the disparity may be explained by the differences inthe occupaonal and industrial categories of the respondents, nevertheless discrepancies sll exist.Kossuth County Laborshed Analysis 14 Released March 2013

E BThe survey provides the respondents an opportunity to idenfy employment benefits that would influencetheir decision to change employment. Desired benefits are shown in Figure 22. For some respondents,benefits offered in lieu of higher wages can be the driving force to change employment. Some respondentsassume that parcular benefits, such as health/medical insurance, would be incorporated into most standardemployment packages; therefore, they did not select health/medical as an influenal benefit opon.Figure 22Benefits Desired by Respondents4.8%1.6%1.6%1.6%Paid Sick LeaveLife InsuranceDisability Insurance25.8%24.2%22.6%19.4%17.7%Paid Time OffFlextimeStock OptionsPension/Retirement OptionsDental CoveragePaid VacationVision CoveragePaid Holidays41.9%40.3%40.3%Prescription Drug CoverageTuition Assistance/Reimbursement56.5%Health/Medical Insurance93.5%0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%When contemplang a change in employment, nearly one‐third (31.6%) of those surveyed would prefer to lookfor offers where the employer covers all the premium costs of health/medical insurance while the majority(61.4%) would be willing to cost share the premium for health/medical insurance with their employer. Themajority (90.0%) of those who are employed willing to change state they are currently sharing the premiumcosts of health/medical insurance with their employer and 5.0 percent indicate their employer is covering theenre cost of health/medical insurance. When it comes to considering influenal benefit opons toemployment offers, there is a difference between those who currently share in the costs of medical insurancepremiums to that of those who desire cost sharing of medical insurance premiums. This leads to the belief thatcost sharing versus employer paid would influence the employed to change posions or companies.F A WThe Laborshed area residents are very recepve to various work environments. Most respondents (68.7%)would prefer to work in an environment that offers cross‐training opportunies, training to do more than onejob; 68.7 percent are willing to work in team environments, groups of individuals coming together toaccomplish a common goal; and slightly over one‐fourth (25.4%) would consider job sharing workarrangements, involving two or more individuals spling one full‐me job. As such arrangements becomemore common in the workplace; more and more employees are expressing greater interest. Employmentopportunies that require a variety of work schedules (combinaons of 2 nd , 3 rd or split shis) would pique theinterest of 29.9 percent of the employed that are willing to change employment.J S TEmployers who have a clear understanding of the job search resources used by workers will improve theirability to maximize their effecveness and efficiency in aracng qualified applicants. Residents living in theKossuth County Laborshed area are undoubtedly exposed to numerous sources by which employerscommunicate job openings and new hiring. Therefore, it is important to understand what sources potenalworkers rely on when looking for jobs. The most frequently idenfied job search resources are idenfied inFigure 23 (next page).Kossuth County Laborshed Analysis 15 Released March 2013

Those ulizing the local newspaper tend to seekemployment opportunies by searching in their hometownnews publicaon. The most popular local/regionalnewspaper sources include The Messenger ‐ Fort Dodge,The Des Moines Register and Algona Upper Des Moines.The internet is host to many sources for employmentopportunies, the most commonly used sites to look foremployment opportunies in the Kossuth CountyLaborshed are www.monster.com andwww.careerbuilder.com. The type of industry theindividual is seeking to be employed may determine thesources used. Businesses wanng more detailedadversing sources may contact the Kossuth/Palo AltoCounty Economic Development Corp. Understanding andulizing tradional and non‐tradional adversing mediawill provide employers a more focused and effecverecruitment tool.CCommung data collected by the Laborshed survey assistsdevelopers and employers in understanding how employed 20%residents, willing to change employment, can/couldcommute within/out of the area. Overall, the employed10%willing to change would commute an average of 24 milesone way for employment opportunies. Those who live inZone 1 and Zone 2 are also willing to commute an average 0%of 24 miles one way and Zone 3 residents are willing tocommute an average of 23 miles one way for the rightemployment opportunity. To provide a comparison, those employed willing to change are currentlycommung 8 miles one way and those currently employed but not willing to change, commute an average of 7miles one way to work.Where individuals live within the Laborshed will influence their desire to commute to the node community.The node community may be the largest economic center for many of the smaller communies in the area.Individuals from the surrounding communies seeking job opportunies and compeve wages/benefits maybe resigned to the fact that they will have to commute some distance to a new employer. In these cases, thewillingness of the Zone 2 and 3 respondents to commute a substanal distance increases the likelihood thatthey may be interested in commung (or interested in connuing to commute) to the node community.However, the willingness of Zone 1 residents to commute represents a potenal out commute from the nodecommunity. This point illustrates the influence of surrounding labor on the individual Laborsheds ‐ potenallydrawing workers out of the node (see Labor Market Areas in Region map).90%80%70%60%50%40%30%84.1%Internet42.9%Local NewspapersFigure 23Job Search Media Used25.4%NetworkingRegional Newspapers19.0%Local IowaWORKS Centers14.3%Private Employment Services6.3%Walk-In (Door-to-Door) Solicitation4.8%Radio1.6%Television1.6%Trade Publications1.6%Kossuth County Laborshed Analysis 16 Released March 2013

O CThe out commute of a community represents the percentage of residents living in the node community(Algona), but working for employers located in other communies. The out commute for Algona is esmatedat 8.7 percent – approximately 252 people living in Algona who work in other communies. Most of those whoare out commung are working in West Bend or Emmetsburg. Of those who are commung to othercommunies for employment opportunies, 22.2 percent are willing to change employment (approximately 56people) if presented with the right employment offer. The calculaons for potenal available labor are basedon adjusted labor force zone totals obtained from Figure 11.As a group, they are primarily employed within the managerial occupaonal category. They are primarilyworking within the wholesale trade; healthcare/social services; and manufacturing industries.For those who out commute, 88.9 percent have educaon/technical training beyond high school, 11.1 percentare trade cerfied, 11.1 percent have an associate degree, 55.6 percent have an undergraduate degree and11.1 percent have a postgraduate/professional degree. Areas of emphasis include agricultural studies,business/public administraon, markeng, medical studies, and vocaonal trades.Over two‐fihs (44.4) of those who are commung out of Algona for employment are hourly wage employeeswhose current median wage is $15.88 per hour.Out commuters are currently commung an average of 31 miles one way to work and are willing to commute22 miles one way for a “new opportunity”. Two‐thirds (66.7%) of out commuters are male. The average age ofout commuters is 49 with one‐third (33.3%) between the ages of 45 and 54 and one‐third (33.3%) between theages 55 and 64.Figure 24Out Commuters by Place of EmploymentOBLESArea ShownJACKSONMARTINLegendFentonForest City§¨¦ 90 £¤ 65FARIBAULT FREEBORN MOWER^_AlgonaInterstates4-Lane HighwaysUS HighwaysSCEOLADICKINSONEMMETKOSSUTHBurtCLAYEmmetsburg^_Algona£¤ 169 £¤ 18WINNEBAGOState HighwaysWORTHIowa CountyMITCHELLMinnesota CountyBRIENPALO ALTOHANCOCKCERRO GORDOFLOYD£¤ 71 £¤ 20 AldenWest BendHEROKEEBUENA VISTAPOCAHONTAS£¤ 169HUMBOLDT§¨¦ 35WRIGHTFRANKLINBUTLEROut Commute Concentrationby Place of Employment (per ZIP Code)0.1% - 11.1%SACCALHOUNIDA11.2% - 33.3%WEBSTERGRUNDYHAMILTONHARDIN10 Mile Interval Between RingsKossuth County Laborshed Analysis 17 Released March 2013

E UUnderemployment is a recent point of interest in popular literature, but has actually been an issue studied andaddressed by economists for nearly 20 years. While there is no one widely accepted definion ofunderemployment, for the purpose of this Laborshed study, underemployment is defined in the followingthree ways:1. Inadequate hours worked ‐ individuals working less than 35 hours per week and desiring more hours.2. Mismatch of skills ‐ workers are denoted as “mismatched” if their completed years of educaon areabove the number needed for their current occupaonal group, they have significant technicalskills beyond those currently being ulized or if they have held previous jobs with a higher wage orsalary.3. Low income ‐ individuals working full‐me but at wages insufficient enough to keep them above thepoverty level.Each of these categories of underemployment can be very difficult to esmate; however, it appears as thoughelements of each of these categories exist in this Laborshed area.U D I H WIn order to assess the impact of underemployment by inadequate hours worked in the Laborshed area, werefer to tabulaons of the employed willing to change employment working 34 hours or less from the surveyresponses. The survey data shows that underemployment due to inadequate hours is esmated to be 0.5percent within the Laborshed area (Figure 25).Figure 25Underemployed ‐ Inadequate Hours WorkedPercent UnderemployedLow HoursEstimated UnderemployedDesiring More Hours0.5% 29The calculaon for esmated underemployed desiring more hours is based on the Esmated Number ofEmployed Willing to Change 5,766 projecons found in Figure 11.U D M SUnderemployment may also be calculated by examining individuals that are employed in posions that do notmaximize their previous experience, skills and educaon or that do not adequately compensate them based ontheir qualificaons. IWD’s Laborshed survey of the region aempts to provide the best esmate of this“mismatch” of skills by asking respondents if they believe that they are underemployed and if so, why.Respondents first answered the queson, “Are you qualified for a beer job?” Individuals answering “yes” arethen asked to classify why they are qualified based on categories relang to previously held jobs that requiredmore skill and educaon, acquiring addional job training and educaon at their current job, current job doesnot require their level of training or educaon and greater pay at a previous job. Respondents selected alldescriptors that applied to their situaon.The choices provided on the survey are not an exhausve list of explanaons of why the respondent isoverqualified, but a collecon of the most likely responses based on prior surveys and research.Kossuth County Laborshed Analysis 18 Released March 2013

The respondents’ results are then applied to the enre Laborshed area to analyze why underemployment bymismatch of skills exists. IWD then conducts a second method of validang whether or not underemploymentby mismatch of skills actually exists. Each me a respondent lists a reason for why he or she is qualified for abeer job, other survey quesons are analyzed to esmate whether the person is truly underemployed orsimply overstang their skills and educaon or underesmang the requirements of the labor market. Forexample, if a respondent states that they are underemployed because they previously held a job that requiredmore skill and educaon, IWD evaluates the person’s current employer type, occupaon type, skills unused attheir current posion, age, employment status, educaon, years in current posion and the type of job theywould consider to see if they are consistent with the person’s underemployment.Figure 26 shows that 2.0 percent are underemployed due to mismatch of skills. If a respondent is determinedto be underemployed due to mismatch of skills for more than one of the four reasons, that individual is onlycounted once for the Esmated Underemployed and for the Potenal Total figures. The calculaon forPotenal Total in Laborshed figure is based on the Esmated Number of Employed Willing to Change of 5,766projecons found in Figure 11. Addionally, all employed respondents are filtered to include only those thatidenfied that they are “very or somewhat likely” to accept employment when calculang underemployment.This filtering reflects the belief that a respondent is not accurately represenng himself or herself asunderemployed when they are unwilling to accept new employment opportunies that could improve theirstatus.Percent UnderemployedMismatch of SkillsEstimated UnderemployedDesiring Better Skills Match2.0% 115Zone 1 contains 37.5 percent of those who are underemployed due to mismatch of skills, Zone 2 contains 25.0percent and Zone 3 contains 37.5 percent in the Kossuth County Laborshed area. In many rural areas,mismatch of skills tends to be higher because of the desire to maintain a certain level of quality of life issues.Three‐fourths (75.0%) of those who are considered to be underemployed due to mismatch of skills in theKossuth County Laborshed are female. The educaon level obtained compared to occupaon previously heldprovides the greatest discrepancy when looking at mismatch of skills. Three‐fourths (75.0%) have someeducaon beyond high school, 12.5 have an associate degree and 62.5 percent have an undergraduate degree.They are willing to commute an average of 22 miles one way for employment opportunies within theprofessional, paraprofessional & technical; clerical; and service occupaonal categories.U D L IFigure 26Underemployed ‐ Mismatch of SkillsMeasuring underemployment by low income is accomplished by determining how many households in theLaborshed area fall below the poverty level. A total of 1.0 percent of the respondents answering thehousehold income queson fall below the 2013 federal poverty thresholds based on their household incomeand number of members living in the household (i.e., based on a family of four, the annual household incomeguideline is $23,550). Figure 27 provides an overview of the survey respondents who fall below the 2013federal poverty level and the potenal number affected in the Laborshed area that are underemployed due tolow income. The calculaon for potenal underemployment due to low income is based on the EsmatedNumber of Employed Willing to Change of 5,766 employment projecons found in Figure 11.Figure 27Underemployed ‐ Low IncomePercent UnderemployedLow IncomeEstimated UnderemployedDesiring Higher Income1.0% 58Kossuth County Laborshed Analysis 19 Released March 2013

T E UAll three measures of underemployment result in an esmated total underemployment rate of 3.2 percent inthe Laborshed area (Figure 28). It is important to emphasize that these underemployment percentages areonly esmates; however, IWD has filtered the data to eliminate double counng of respondents within andbetween the three categories. A person underemployed due to inadequate hours and mismatch of skills is onlycounted once.Figure 28Underemployed ‐ Esmated TotalPercent UnderemployedEstimated TotalEstimated TotalUnderemployed3.2% 185The wage threshold needed to aract 66 percent to 75 percent of the underemployed is $12.00 to $12.50 perhour with a lowest median considered wage of $10.50 per hour. When looking for employment opportuniesthe underemployed use the internet (84.6%); local newspapers (61.5%); networking through friends, familyand/or acquaintances (38.5%); regional newspapers (30.8%); local IowaWORKS Centers (23.1%); privateemployment services (23.1%); radio (7.7%); television (7.7%); or walk‐in (door‐to‐door) solicitaon (7.7%) asthe preferred job search media.Kossuth County Laborshed Analysis 20 Released March 2013

W T N CE A EThe BLS defines unemployed persons as individuals who are currently not employed but are acvely seekingemployment. Using only this definion overlooks sources of potenal labor, specifically those who arevoluntarily not employed/not rered and rerees who, though currently not employed, would considerentering or re‐entering the workforce if the right opportunity arose. IWD uses an alternave definion “notemployed” for its Laborshed studies which includes the unemployed, voluntarily not employed/not rered andrerees as subsets of the category. The survey asks the respondents to idenfy whether they are unemployed,voluntarily not employed/not rered or rered. It is useful to look at the specific characteriscs of each ofthese subsets of “not employed” persons.The inclusion of these subset groups into the analysis provides a more accurate assessment of the potenallabor force in the Laborshed area. Of the respondents surveyed, 23.2 percent reported that they are “notemployed”. By quesoning these respondents about their willingness to re‐enter or accept a job offer, thesurvey idenfied 36.2 percent who stated they are “very likely” or “somewhat likely” to accept employment.Aggregated totals for the “not employed” may be achieved by combining the data from any or all of Figures 29,34 and 35.Each of the “not employed” subsets has their own unique characteriscs that define their contribuon to theLaborshed area. Recognizing and understanding these factors will aid in efforts to target and tap into this oenunrecognized and underulized labor resource. The following secons provide a profile of the unemployed,voluntarily not employed/not rered and rered respondents.UOf those who responded to being unemployed, 58.3 percent are “very likely” or “somewhat likely” to acceptemployment if the right opportunity arose. Figure 29 shows that the unemployed, who are willing to acceptemployment, reside across all three zones of the Laborshed area. Respondents willing to accept employmentby zone are calculated using a logisc regression model weighted by mulple variables such as educaon level,gender, age, miles willing to travel and wages. This model provides an esmate for the total number ofindividuals “willing to change” by zone. The totals are based on the Total Adjusted Labor Force esmatesfound in Figure 1 (approximately 374 unemployed persons).Figure 29Unemployed ‐ Willing to Accept EmploymentTotal AdjustedLabor Force by ZoneEstimated Total Willing toChange/Accept by Zone*Estimated Number ofUnemployed Willing toAccept by Zone*Zone 1 3,765 1,840 85Zone 2 8,616 3,624 134Zone 3 61,503 2,611 155Total 73,884 8,075 374*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 fromtheir home ZIP code for an employment opportunity.The current methods to determine the unemployment rate exclude those who have been unemployed longerthan six months, those who did not register with the unemployment office and students who are seekingemployment. The Laborshed unemployed percent includes anyone who stated they were unemployed thenincorporates all counes within the Laborshed area, where as the unemployment rate only takes intoconsideraon individual counes.D O T UThe average age of this group is 47 years old. The unemployed respondents are distributed amongst all of theage range groups, 18 to 24 (14.3%), 25 to 34 (9.5%), 35 to 44 (14.3%), 45 to 54 (23.8%) and 55 to 64 (38.1%).The gender breakdown of those unemployed is 71.4 percent male and 28.6 percent female.Kossuth County Laborshed Analysis 21 Released March 2013

E TNearly half (47.6%) of the unemployed respondents in the Kossuth County Laborshed area have some post highschool educaon, 4.8 percent are trade cerfied, 4.8 percent have vocaonal training, 19.0 percent have anassociate degree and 9.5 percent have an undergraduatedegree.Nearly one‐fourth (23.8%) of those who are unemployed andwilling to re‐enter the workforce feel they need addionaltraining/educaon in order to make a successful transionback into the workforce. Figure 30 shows what type oftraining the unemployed would like to receive. Financing, ageand disability issues are the main obstacles prevenng themfrom pursing addional educaon/training.W E EFigure 30Desired Addional TrainingAdditional Training Desired% ofUnemployedCollege Degree 60.0%Vocational Training 20.0%Other 20.0%Nearly two‐thirds (65.0%) of the respondents became unemployed within the last year with the majority(66.7%) of those having held full‐me posions, while 23.8 percent held part‐me posions in their previousemployment and 9.5 percent were seasonally employed. These individuals have diverse work experiences; themajority held posions within the producon, construcon & material handling; service; or professional,paraprofessional & technical occupaonal categories.A variety of explanaons were given as to why the respondents are unemployed at this me. The mostfrequently menoned responses are shown in Figure 31.Figure 31Reasons for Being UnemployedReasons for Being Unemployed% ofUnemployedEmployer Layoff, Downsizing, Relocation or Closing 35.0%Lack of Work Opportunities 25.0%Health Reasons 15.0%Quit Previous Employment 10.0%Transportation Issues 10.0%Contract Concluded 5.0%Disability Issues 5.0%Personality Conflict with Employer/Co‐workers 5.0%Terminated by Employer 5.0%Wanted to Further Education 5.0%Nearly three‐fihs (57.1%) of the respondents who are unemployed are seeking/have sought services to gainemployment. Of those, all are ulizing the local IowaWORKS Centers to assist in seeking qualified offers andplan to seek jobs within the producon, construcon & material handling; professional, paraprofessional &technical; service; clerical; and managerial occupaonal categories.The unemployed respondents can accommodate a variety of work environments. Over three‐fihs (61.9%) ofthe respondents would prefer employment opportunies that provide job team work environments; 57.1percent of the respondents expressed an interest in cross‐training; and 52.4 percent would be interested in jobsharing posions ‐ two people sharing one full‐me posion. Nearly half (47.6%) of the unemployed expressedan interest in working a variety of work schedules (combinaons of 2 nd , 3 rd or split shis). Seasonalemployment opportunies would interest 61.9 percent of those who are unemployed, while temporaryemployment would be a consideraon for 42.9 percent of the unemployed looking to re‐enter the workforce.Over one‐tenth (11.1%) of those who are unemployed, willing to re‐enter, would consider starng their ownbusiness. The businesses they are primarily interested in starng include construcon/handyman (33.3%),lawn care/snow removal (33.3%) and personal services (33.3%). Access to start‐up funds is the primaryobstacle prevenng them from pursuing their entrepreneurial venture. Keep in mind that not all of those whostated they had an interest will actually pursue an entrepreneurial venture. What this does show is that acertain level of entrepreneurial ambion is present in the area that can be captured in the workplaceenvironment.Kossuth County Laborshed Analysis 22 Released March 2013

W BWage levels, hours available and employee benefits are important factors for unemployed individuals. Theesmated wage threshold for the unemployed willing to re‐enter employment is $10.00 to $14.25 per hour.This threshold should serve as a base recommendaon for obtaining the most qualified applicants for hiring.The median of the lowest hourly wage that unemployed respondents are willing to accept is $8.50 per hour. Attheir prior employment, the unemployed received a median hourly wage of $12.58 per hour. In addion tosalary/wages and hours, some of the unemployed could be influenced by certain benefits. Those benefits mostfrequently menoned are idenfied in Figure 32.5.9%5.9%5.9%5.9%Figure 32Desired Benefits of the Unemployed41.2%35.3%29.4%29.4%Paid VacationDental CoveragePension/Retirement OptionsVision CoverageDisability Insurance 17.6%Paid Holidays 17.6%11.8% Life Insurance11.8% Paid Sick Leave11.8% Paid Time OffIncentive Reward ProgramsFlextimePrescription Drug CoverageStock OptionsHealth/Medical Insurance70.6%0% 10% 20% 30% 40% 50% 60% 70% 80%J S TWhen looking for employment opportunies, unemployedpersons generally rely on common and easily accessiblesources of informaon; however, non‐tradional methodsare also being ulized in order to locate the “rightopportunity”. The most frequently idenfied job searchmedia are idenfied in Figure 33. To provide businessesand community leaders with a more in‐depth focus onadversing sources currently being used by the unemployedwilling to re‐enter the workforce, The Messenger ‐ FortDodge and Globe‐Gazee ‐ Mason City are the primary printsources, while www.iowajobs.org and www.monster.comare the primary internet sources viewed by those seekingemployment in the Kossuth County Laborshed area.CThe average number of miles that unemployed respondentsare willing to travel one way to work is 20 miles. Zone 1respondents are willing to commute an average of 17 milesone way to work, Zone 2 respondents are willing tocommute an average of 19 miles one way to work and Zone3 respondents are willing to commute an average of 22miles one way to work. Since some Zone 1 unemployedresidents are willing to commute great distances, onceemployed, they could become part of the out commung ofthe nodal community. The unemployed in the Laborshedoffer a variety of past work experiences to apply to newemployment opportunies.80%70%60%50%40%30%20%10%0%66.7%InternetFigure 33Job Search Media Used38.1%Local Newspapers33.3%NetworkingRegional Newspapers19.0%Walk-In (Door-to-Door) Solicitation19.0%Local IowaWORKS Centers14.3%Bulletin Boards4.8%College/University Career Centers4.8%Radio4.8%Kossuth County Laborshed Analysis 23 Released March 2013

V N E/N ROf those who responded as voluntarily not employed/not rered, 34.8 percent are “very or somewhat likely”to accept employment if the right opportunity is presented. Figure 34 shows that the Kossuth CountyLaborshed area is esmated to contain 425 individuals who are voluntarily not employed/not rered andwilling to work if presented with the right opportunity. This group may represent a quality source of potenalavailable labor in the Laborshed area for certain industries/businesses looking to fill non‐tradional workarrangements.Figure 34Voluntarily Not Employed/Not Rered ‐ Willing to Accept EmploymentTotal AdjustedLabor Force by ZoneEstimated Total Willing toChange/Accept by Zone*Estimated Number of VoluntarilyNot Employed/Not RetiredWilling to Accept by Zone*Zone 1 3,765 1,840 88Zone 2 8,616 3,624 199Zone 3 61,503 2,611 138Total 73,884 8,075 425*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 from their homeZIP code for an employment opportunity.Respondents willing to accept employment by zone are calculated using a regression model weighted bymulple variables such as educaon level, gender, age, miles willing to travel and wages. This model providesan esmate for the total number of individuals “willing to change” by zone. The totals are based on the TotalAdjusted Labor Force esmates found in Figure 1.For more informaon regarding those who are voluntarily not employed/not rered, please contact theKossuth/Palo Alto County Economic Development Corp.R PRered individuals (18‐64 years of age) represent an underulized and knowledgeable pool of workers in someLaborshed areas. In the Kossuth County Laborshed area, 14.3 percent of those who are rered are willing to re‐enter the workforce at some capacity. Figure 35 illustrates that those who are rered and willing to re‐enterthe workforce reside throughout the survey zones (approximately 1,510).Figure 35Rered (18‐64) ‐ Willing to Accept EmploymentTotal AdjustedLabor Force by ZoneEstimated Total Willing toChange/Accept by Zone*Estimated Number ofRetired Willing toAccept by Zone*Zone 1 3,765 1,840 151Zone 2 8,616 3,624 303Zone 3 61,503 2,611 1,056Total 73,884 8,075 1,510*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 fromtheir home ZIP code for an employment opportunity.Respondents willing to accept employment by zone are calculated using a regression model weighted bymulple variables such as educaon level, gender, age, miles willing to travel and wages. This model providesan esmate for the total number of individuals “willing to change” by zone. The totals are based on the TotalAdjusted Labor Force esmates found in Figure 1.For more informaon regarding rerees, please contact the Kossuth/Palo Alto County Economic DevelopmentCorp.Kossuth County Laborshed Analysis 24 Released March 2013

Commuter Concentrationby Place of Residence into AlgonaNOBLESJACKSONMARTINFairmontFARIBAULTBlue EarthFREEBORNMOWERSpirit LakeSpirit LakeOSCEOLAOkobojiDICKINSONMilfordTerrilEsthervilleEMMETWallingfordArmstrongRingstedLedyardSwea CityBuffalo Center ThompsonLakotaWINNEBAGO LelandBancroft§¨¦ 90 £¤ 65Lake MillsWORTHKensettMITCHELLRakeOBRIENCHEROKEEGraettingerSpencerRuthvenCylinder£¤ 169 £¤ 18TitonkaForest CityFentonWodenCrystal LakeLone RockBurtKOSSUTHEmmetsburgBrittWesleyCLAYAlgonaPALO ALTOHANCOCKWhittemore ^_Ayrshire£¤ 71 WebbMallard West BendCorwithLu Verne£¤ 20BodeKanawhaOttosenLaurensRolfeLivermore RenwickBradgate £¤ 169Rutland HardyHUMBOLDTGoldfieldBUENA VISTAPOCAHONTASGilmore City HumboldtDakota CityWRIGHT ClarionGarnerClear LakeMason CityCERRO GORDO§¨¦ 35FRANKLINFLOYDBUTLERClareThorBadgerEagle GroveWoolstockFort DodgeWEBSTERIDASACCALHOUNDuncombeWebster CityHAMILTONHARDINGRUNDY10 Mile Interval Between RingsLehighMiles0 10 20 40 60 80Area ShownLegend^_AlgonaInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 1819 - 5960 - 137138 - 1,509Kossuth County Laborshed Analysis 25 Released March 2013

Labor Market Areas in RegionKossuth County Laborshed AreaNOBLESJACKSONMARTINFairmont, MNLabor Market AreaFairmontFARIBAULTBlue EarthSpencer, IALabor Market Area^_£¤ 169 £¤ 18§¨¦ 90 £¤ 65Albert Lea, MNLabor Market AreaFREEBORNMOWEROSCEOLAOBRIENDICKINSONCLAYRuthvenGraettingerEMMETEmmetsburgPALO ALTOEmmetsburg, IALabor Market AreaRingstedArmstrongCylinderFentonWhittemoreWest BendSwea CityLone RockKOSSUTHOttosenBodeElmoreLedyardBancroftBurtAlgonaElmoreLakotaLu VerneTitonkaBuffalo Center ThompsonWINNEBAGOWesleyCorwithWodenBrittHANCOCKKanawhaForest City, IALabor Market AreaForest CityGarnerMason City, IALabor Market AreaClear LakeWORTHMason CityCERRO GORDOMITCHELLFLOYDCHEROKEEBUENA VISTAPOCAHONTASBradgateGilmore City£¤ 71 £¤ 20 £¤ 69£¤ 169RutlandHUMBOLDTHumboldtDakota CityHardyGoldfieldWRIGHTClarion§¨¦ 35FRANKLINBUTLERLivermoreRenwickFort Dodge, IALabor Market AreaWEBSTERFort DodgeBadgerEagle GroveWoolstockWebster City, IALabor Market AreaIDASACCALHOUNHAMILTONHARDINGRUNDYMiles0 10 20 40 60 80Area ShownLegend^_ AlgonaKossuth County Laborshed AreaSmall Labor Market Area (30 Mile Radius)Interstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyKossuth County Laborshed Analysis 26 Released March 2013

Survey Zones by ZIP CodeKossuth County Laborshed AreaJACKSONMARTINFairmontFARIBAULTBlue EarthFREEBORNMOWERElmoreElmoreLedyardOSCEOLADICKINSONEMMETArmstrongSwea CityLakotaBuffalo Center§¨¦ 90 £¤ 65ThompsonWINNEBAGOWORTHMITCHELLRingstedBancroftGraettingerFentonLone RockKOSSUTHBurtTitonka£¤ 169 £¤ 18WodenForest CityOBRIENCLAYRuthvenEmmetsburgPALO ALTOCylinderWhittemore^_AlgonaWesleyBrittHANCOCKGarnerVenturaClear LakeMason CityCERRO GORDOFLOYD£¤ 71 £¤ 20 £¤ 69West BendOttosenBodeLu VerneCorwithKanawhaCHEROKEEBradgate£¤ 169RutlandHUMBOLDTHardyGoldfield§¨¦ 35LivermoreRenwickBUENA VISTAPOCAHONTASGilmore CityHumboldtDakota CityWRIGHTClarionFRANKLINBUTLERBadgerEagle GroveWoolstockFort DodgeSACCALHOUNWEBSTERHAMILTONHARDINGRUNDYIDA10 Mile Interval Between RingsMiles0 10 20 40 60 80Area ShownLegend^_AlgonaInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)Zone 3 (1 - 24)Zone 2 (25 - 137)Zone 1 (138 - 1,509)Kossuth County Laborshed Analysis 27 Released March 2013

Commuter Concentrationby Place of Residence into BancroftElmore£¤ 169§¨¦ 90 £¤ 6JACKSONMARTIN FARIBAULT FREEBORNFairmontElmoreDICKINSONEMMETSwea CityLakotaBuffalo CenterWINNEBAGOWORTHCLAYWallingfordRingstedBancroft^_TitonkaFentonWodenKOSSUTH BurtLone Rock£¤ 69£¤ 18 BrittWhittemore£¤ 169PALO ALTOAlgonaHANCOCKCERRO GORDO§¨¦ 35BUENA VISTAAlbert CityPOCAHONTASHUMBOLDTWRIGHTFRANKLIN10 Mile Interval Between RingsHumboldtMiles0 10 20 40 60 80Area ShownLegend^_BancroftInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 23 - 56 - 89 - 81Kossuth County Laborshed Analysis 28 Released March 2013

Commuter Concentrationby Place of Residence into BurtJACKSONMARTINFARIBAULTBlue EarthFREEBORNMOWERDICKINSONMilfordEMMETArmstrongRingsted£¤ 169RakeLedyardSwea CityBuffalo CenterLakotaBancroftWINNEBAGO§¨¦ 90 £¤ 65WORTHMITCHELLCylinderFentonLone RockKOSSUTHBrittWesleyCLAYPALO ALTO£¤ 18 WhittemoreAlgonaHANCOCKWest BendCorwithLu Verne£¤ 71 £¤ 169HUMBOLDT£¤ 69£¤ 30^_BurtTitonkaWodenGarner§¨¦ 35CERRO GORDOFLOYDBUENA VISTAPOCAHONTASWRIGHTFRANKLINBUTLERFort DodgeWEBSTERIDASAC10 Mile Interval Between RingsCALHOUNHAMILTONHARDINGRUNDYMiles0 10 20 40 60 80Area ShownLegend^_BurtInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 34 - 78 - 3132 - 96Kossuth County Laborshed Analysis 29 Released March 2013

Commuter Concentrationby Place of Residence into Swea CityCOTTONWOODWATONWANBLUE EARTHWASECASTEELEJACKSONMARTINFairmontCeylon£¤ 71LedyardFARIBAULT£¤ 169§¨¦ 90FREEBORNDICKINSONEMMETArmstrongSwea City^_LakotaWINNEBAGOWORTHRingstedBancroftFentonTitonkaForest CityKOSSUTHLone RockEmmetsburgCLAYPALO ALTOAlgonaHANCOCKCERRO GORDO§¨¦ 35BUENA VISTA10 Mile Interval Between RingsPOCAHONTAS£¤ 18 £¤ 169HUMBOLDTWRIGHTFRANKLINMiles0 10 20 40 60 80Area ShownLegend^_Swea CityInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 34 - 1617 - 30Kossuth County Laborshed Analysis 30 Released March 2013

Commuter Concentrationby Place of Residence into TitonkaJACKSONMARTINFARIBAULTFREEBORNMOWER£¤ 169DICKINSONEMMETLakotaBuffalo CenterThompsonWINNEBAGOWORTHMITCHELLBancroft§¨¦ 90 £¤ 65KOSSUTHBurt^_TitonkaWoden Crystal LakeSACPALO ALTOWesley£¤ 18 AlgonaHANCOCK£¤ 69£¤ 20 BrittGarnerBelmondHUMBOLDTPOCAHONTASWRIGHTMansonWEBSTERCALHOUN10 Mile Interval Between RingsHAMILTON§¨¦ 35CERRO GORDOFRANKLINHARDINFLOYDGreeneBUTLERGRUNDYMiles0 10 20 40 60 80Area ShownLegend^_TitonkaInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 23 - 56 - 64Kossuth County Laborshed Analysis 31 Released March 2013

Commuter Concentrationby Place of Residence into Wesley£¤ 169§¨¦ 90 £¤ 65Albert LeaMARTINFARIBAULTFREEBORNMOWEREMMETWINNEBAGOWORTHMITCHELLTitonkaKOSSUTHPALO ALTOAlgona£¤ 18 £¤ 69Wesley^_BrittHANCOCKGarnerCERRO GORDOFLOYDLu VernePOCAHONTASHUMBOLDT10 Mile Interval Between RingsWRIGHTFRANKLIN§¨¦ 35BUTLERMiles0 1020 40 60 80Area ShownLegend^_WesleyInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1335Kossuth County Laborshed Analysis 32 Released March 2013

Commuter Concentrationby Place of Residence into West BendNOBLESJACKSONMARTINGranadaFARIBAULTFREEBORN£¤ 169OSCEOLADICKINSONEMMETBuffalo Center§¨¦ 90 £¤ 65WINNEBAGOWORTHRingstedFentonKOSSUTHBurtOBRIENCLAYRuthvenEmmetsburgPALO ALTOCylinderAlgonaWesleyHANCOCKCERRO GORDOWhittemore£¤ 71 £¤ 69Mallard£¤ 18 £¤ 169West Bend^_OttosenBodeLaurensRolfeCHEROKEEBUENA VISTAPOCAHONTASPocahontasBradgateGilmore CityRutlandHUMBOLDTHumboldtWRIGHT§¨¦ 35FRANKLINIDASAC10 Mile Interval Between RingsCALHOUNWEBSTERHAMILTONHARDINMiles0 10 20 40 60 80Area ShownLegend^_West BendInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyMinnesota CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 34 - 78 - 1415 - 44Kossuth County Laborshed Analysis 33 Released March 2013

Commuter Concentrationby Place of Residence into WhittemoreDICKINSONEMMETWINNEBAGOKOSSUTHCLAYEmmetsburgPALO ALTOCylinderWhittemoreAlgona^_ £¤ 18HANCOCKWest Bend£¤ 169 £¤ 69HUMBOLDTPOCAHONTASHumboldtWRIGHTSAC£¤ 71 £¤ 30BUENA VISTAWEBSTERCALHOUNHAMILTON10 Mile Interval Between RingsMiles0 5 10 20 30 40Area ShownLegend^_WhittemoreInterstates4-Lane HighwaysUS HighwaysState HighwaysIowa CountyCommuter Concentrationby Place of Residence (per ZIP Code)1 - 45 - 89 - 20Kossuth County Laborshed Analysis 34 Released March 2013

AKossuth County Laborshed Analysis 35 Released March 2013

B IIn early 1998, the Instute for Decision Making (IDM) at the University of Northern Iowa (UNI) completed thefirst pilot Laborshed study. The Laborshed approach and methodology was developed to meet the specificneeds of economic development groups trying to understand and detail the unique characteriscs of their arealabor force. From 1998 to June, 2001, IDM completed 24 Laborshed studies for Iowa communies and gainednaonal aenon for its innovave approach. Beginning in 1999, Laborshed studies were completed inpartnership with the Iowa Department of Economic Development (IDED) and Iowa Workforce Development(IWD) for communies that met specific criteria and for “immediate opportunies” (expansion projects orprospects).During the 2000 legislave session, the General Assembly mandated that as of July 1, 2001, IWD would assumethe responsibilies for conducng Laborshed studies for Iowa communies. IDM staff worked with membersof IWD to train them in IDM’s Laborshed process and methodology. Beginning in July, 2001, IWD assumed allresponsibilies for scheduling and conducng all future Laborshed projects in Iowa.The availability of a well‐trained and educated labor force is among the top three important locaon factors forbusinesses considering expansions or relocaons (Area Development, December 2000). Previously faced withhistorically low unemployment rates, local economic development officials throughout Iowa needed access toobtain mely and tailored data to help define their available labor force and its characteriscs. Iowa’s lowrates of unemployment oen lead to the incorrect assumpon that economic growth cannot occur within thestate. It was presumed that employers will be unable to aract employees from Iowa communies becausethe areas have reached full employment. Even in today’s economy, employers desire a higher skilled and/oreducated worker. Employers also do not have the excess resources to blanket an area for employmentopportunity recruitment. The Laborshed study addresses both of these issues and more to assist employersand communies with expansion efforts.Contrary to these assumpons, many companies currently expanding or locang in Iowa are receiving betweenfive and ten applicants for each new posion that they have open. The discrepancy between the assumponsand the reality of these measurements indicates that a problem exists in the way unemployment data isdefined, measured, reported and used. When unemployment stascs are ulized as the sole method fordetermining labor availability, they appear to lead to inaccurate conclusions regarding the potenal availablelabor supply within a “Laborshed” or sub‐labor market area (sub‐LMA). A Laborshed is defined as the actualarea or nodal region from which an area draws its commung workers. This region has been found to extendbeyond the confines of county and state boundaries typically used to delineate labor informaon. Thelimitaons of current labor data have significant implicaons for local economic development officials as theystrive to create addional jobs and enhance wealth within their region.Appendix AKossuth County Laborshed Analysis 36 Released March 2013

S M DUnderstanding what Iowa employment and unemployment figures represent requires a familiarity with howesmates are calculated and how data differs at the naonal, state and sub‐state levels. The U.S. Departmentof Labor’s Bureau of Labor Stascs (BLS) calculates the labor force stascs for the naon, while state and sub‐state data are computed through a cooperave agreement between the BLS and the state workforce agencies.BLS is responsible for the concepts, definions, technical procedures, validaon and publicaon of theesmates. Appendix C reviews the methodology currently in place.In order to obtain current and accurate labor force informaon for the Laborshed area, NCS Pearsonadministered a random household telephone survey to individuals residing within the Laborshed boundariesduring February 2013. The survey was designed by IDM with assistance from the Center for Social andBehavioral Research at UNI. The overall goal of the process, to collect a minimum of 405 valid phone surveyscompleted by respondents 18 to 64 years of age, was achieved. Validity of survey results is esmated at aconfidence of +/‐ 5 percent of the 405 responses analyzed in this report.To ensure that an even distribuon of respondents is achieved, an equal number of calls are completed tothree separate survey zones (see Survey Zones by ZIP Code – Kossuth County Laborshed area map). The threezones created are classified as Zone 1) Algona, Zone 2) ZIP codes adjacent or near Zone 1 that have a moderatenumber of residents working in Algona and Zone 3) the ZIP codes in outlying areas with a low concentraon ofresidents working in Algona. This distribuon of surveys is an aempt to avoid a clustering of respondents inKossuth County or in the surrounding rural areas. Ulizing this survey distribuon method also provides thebasis for comparisons among the zones and offers a more valid means of applying the survey results withineach individual zone.Survey administrators posed quesons to determine the respondents’ gender, age, educaon level, place ofresidence and current employment status. Employed respondents also idenfied the locaon of theiremployer, employer type, occupaon, years of employment in their occupaon, employment status, currentsalary or wage, addional educaon/skills possessed, number of jobs currently held, distance traveled to workand the hours worked per week. Employed respondents were then asked how likely they were to changeemployers or employment, how far they would be willing to travel for employment, the wage required forthem to change employment and the benefits desired for new employment. Underemployment was esmatedby examining those employees desiring more hours of work than offered in their current posion, those whostated they possessed addional educaon/skills that they do not ulize in their current posion and wagesinsufficient enough to keep them above the poverty level.Respondents in the 18‐64 year age range self‐idenfying themselves as unemployed, voluntarily not employed/not rered or rered were asked a series of quesons to determine what job characteriscs and benefits weremost important to them when considering employment, the reasons for unemployment, obstacles toemployment and how far they would be willing to travel to accept employment. Informaon on previousemployers and skills was also gathered for these sectors.Once completed, the results of the survey were compiled and cross‐tabulated to determine the relaonshipbetween the variables in each zone and the enre survey sample. Documenng and analyzing the Laborshedsurvey results by zone and by characteriscs, provides new insight into the labor force that is currentlyunavailable in any other form.Appendix BKossuth County Laborshed Analysis 37 Released March 2013

Appendix CC M EE UThe federal government and the state of Iowa esmate an area’s labor force by drawing from the poron ofthe civilian populaon that is non‐instuonalized, 16 years of age or older and currently employed orunemployed (BLS Handbook, Chapter 1, p. 5). The BLS defines employed persons in the following two ways:1. Did any work as paid employees, for their own business, profession, on their own farm or worked 15hours or more as unpaid workers in a family‐operated enterprise (BLS Handbook, Chapter 1, p. 5).2. Did not work but had jobs or businesses from which they were temporarily absent due to illness, badweather, vacaon, child‐care problems, labor dispute, maternity or paternity leave or other family orpersonal obligaons ‐‐ whether or not they were paid by their employers for the me off and whetheror not they are seeking other jobs. Individuals volunteering or engaged in housework, painng andhome repair around their own residence are not considered employed (BLS Handbook, Chapter 1, p. 5).Unemployed persons are defined as those individuals that were not employed on a given reference week priorto quesoning and who made an effort to find work by contacng prospecve employers. These individualsidenfied that they are ready to work with the excepon of inability due to a temporary illness. Individuals arealso classified as unemployed if they have been laid off and are awaing recall back to their posions (BLSHandbook, Chapter 1, p. 5). The unemployed are grouped into job losers (both temporarily and permanentlylaid off), quit/terminated and looking for work, re‐entrants to the job market aer an extended absence andnew entrants that have never worked (BLS Handbook, Chapter 1, p. 5).Those individuals that are not classified as employed or unemployed are not considered to be part of the laborforce by BLS. The non‐working designaon may be due to a variety of reasons; however, the underlying factoris that the individuals have not sought employment within the past four weeks (BLS Handbook, Chapter 1, p. 6).Because the BLS ulizes a mulple step process to esmate employment and underemployment stascs on amonthly basis, this process cannot be described in only a few paragraphs. A complete summary of the processused to generate naonal esmates and an outline of the process used to generate state and sub‐stateprojecons is available through IWD.METHODS FOR ESTIMATING EMPLOYMENTThe BLS uses the employed and unemployed persons to calculate the civilian labor force, the unemploymentrate and labor force parcipaon rate.The labor force is:employed + unemployed = labor forceThe labor force parcipaon rate is:labor force / non‐instuonalized cizens 16+ years of age = LFPRThe unemployment rate is the percentage of the civilian labor force that is unemployed:unemployed / total labor force = unemployment rate (BLS Handbook, Chapter 1, p. 5)A proper interpretaon of the unemployment rate requires an understanding of the processes used togenerate the data on which the calculaons are based. The BLS uses the monthly Current Populaon Survey(CPS) to collect data from a sample of 59,000 households, taken from 754 sample areas located throughout thecountry. The purpose of the survey is to collect informaon on earnings, employment, hours of work,occupaon, demographics, industry and socio‐economic class. The data is obtained through personal andtelephone interviews. Of the 59,000 households, only about 50,000 are generally available for tesng due toabsence and illness. The 50,000 households generate informaon on 94,000 individuals (BLS Handbook,Chapter 1, p. 8). Each household is interviewed for two, four‐month periods, with an eight‐month breakbetween the periods. The pool of respondents is divided into 8 panels, with a new panel being rotated eachmonth (BLS Handbook, Chapter 1, p. 10).Kossuth County Laborshed Analysis 38 Released March 2013

Appendix CThe 754 sample areas from which the households are selected represent 3,141 counes and cies broken into2,007 populaon sample units (PSU’s). A PSU can consist of a combinaon of counes, urban and rural areasor enre metropolitan areas that are contained within a single state. The PSU’s for each state are categorizedinto the 754 sample groups of similar populaon, households, average wages and industry. The 754 sampleareas consist of 428 PSU’s that are large and diverse enough to be considered an independent PSU and 326groupings of PSU’s (BLS Handbook, Chapter 1, p. 9).The sample calculates an unemployment esmate with a 1.9 percent coefficient of co‐variaon. This is thestandard error of the esmate divided by the esmate, expressed as a percentage. This translates into a 0.2percent change in unemployment being significant at the 90 percent confidence level. The respondent’sinformaon is weighted to represent the group’s populaon, age, race, sex and the state from which itoriginates. Using a composite esmaon procedure minimizes the standard of error for the esmate. Thisesmate is based on the two‐stage rotaon esmate on data obtained from the enre sample for the currentmonth and the composite esmate for the previous month, adjusted by an esmate of the month‐to‐monthchange based on the six rotaon groups common to both months (BLS Handbook, Chapter 1, p. 8). Theesmates are also seasonally adjusted to minimize the influence of trends in seasonal employment.IOWA & SUB‐STATE UNEMPLOYMENT RATESThe CPS produces reliable naonal unemployment esmates; however due to the small sample size of the CPSsurvey, BLS applies a Time Series Model to increase reliability. The regression techniques used in the modelare based on historical and current relaonships found within each state’s economy. The primary componentsof the state esmaon models are the results from state residents’ responses to the household survey (CPS),the current esmate of nonfarm jobs in the state (CES) and the number of individuals filing claims forUnemployment Insurance (UI). Iowa’s Labor Market Area consists of nine metropolitan areas, 15 micropolitanareas and 62 small labor market areas. For further definion of counes included in micropolitan stascalareas, visit: www.iowaworkforce.org/lmi/pressrelease/iowamicro.pdf and for counes included inmetropolitan stascal areas, visit www.iowaworkforce.org/lmi/pressrelease/iowamsa.pdf.A me series model is used to esmate state labor force stascs and a Handbook method is used for substateprojecons. The state unemployment esmates are based on a me series to reduce the high variabilityfound in the CPU esmates caused by small sample size. The me series combines historical relaonships inthe monthly CPS esmates along with Unemployment Insurance and Current Employment Stascs (CES) data.Each State has two models designed for it that measure the employment to work rao and the unemploymentrate (BLS Handbook, Chapter 4, p. 37).The CES is a monthly survey of employers conducted by the BLS and state employment agencies. Employment,hours/overme and earning informaon for 400,000 workers are obtained from employer payroll records.Annually, the monthly unemployment esmates are benchmarked to the CPS esmate so that the annualaverage of the final benchmarked series equals the annual average and to preserve the paern of the modelseries (BLS Handbook, Chapter 4, p. 38).The sub‐state unemployment esmates are calculated by using the BLS Handbook Method. The HandbookMethod accounts for the previous status of the unemployed worker and divides the workers into twocategories: those who were last employed in industries covered by State Unemployment Insurance (UI) lawsand workers who either entered the labor force for the first me or reentered aer a period of separaon (BLSHandbook, Chapter 4, p. 38).Individuals considered covered by UI are those currently collecng UI benefits and those that have exhaustedtheir benefits. The data for those that are insured is collected from State UI, Federal and Railroad programs.The esmate for those who have exhausted their funds is based on the number who stopped receiving benefitsat that me and an esmate of the individuals who remain unemployed (BLS Handbook, Chapter 4, p. 39).Kossuth County Laborshed Analysis 39 Released March 2013

Appendix CThe 754 sample new entrants and reentrants into the labor force are esmated based on the naonal historicalrelaonship of entrants to the experienced unemployed and the experienced labor force. The Department ofLabor states that the Handbook esmate of entrants into the labor force is a funcon of (1) the month of theyear, (2) the level of the experienced unemployed, (3) the level of the experienced labor force and (4) theproporon of the working age populaon (BLS Handbook, Chapter 4, p. 39). The total entrants are esmatedby:where:ENT = A(X+E)+BXENT = total entrant unemploymentE = total employmentX = total experienced unemploymentA,B = synthec factors incorporang both seasonal variaons and the assumed relaonshipbetween the proporon of youth in the working‐age populaon and the historical rela‐onship of entrants, either the experienced unemployed or the experienced labor forceKossuth County Laborshed Analysis 40 Released March 2013

Appendix DManagerial/Administrave OccupaonsProfessional, Paraprofessional & Technical OccupaonsEngineersNatural ScienstsComputer, Mathemacal and Operaons ResearchSocial ScienstsTeachersHealth PraconersWriters, Arsts, Entertainers and AthletesSales OccupaonsClerical/Administrave Support OccupaonsSecretarialElectronic Data ProcessingService OccupaonsProtecve ServiceFood and BeverageHealth ServiceCleaning and Building ServicePersonal ServiceAgricultural OccupaonsO E S (OES)C SProducon, Construcon, Operang, Maintenance & Material Handling OccupaonsConstrucon Trades and ExtraconPrecision ProduconMachine Seers, Set‐Up Operators, Operators and TendersHand Working OccupaonsPlant and SystemTransportaon and Material MovingHelpers, Laborers and Material Movers, HandKossuth County Laborshed Analysis 41 Released March 2013

Iowa Wage Surveyhp://www.iowaworkforce.org/lmi/occupaons/wages/index.htmAffirmave Aconhp://www.iowaworkforce.org/lmi/publicaons/affirm/Condion of Employmenthp://www.iowaworkforce.org/lmi/condempl.pdfCovered Employment & Wages by Couneshp://www.iowaworkforce.org/lmi/empstat/coveredemp.htmlIowa Job Outlook Statewidehp://www.iowaworkforce.org/lmi/outlook/index.htmlIowa Licensed Occupaonshp://www.iowaworkforce.org/lmi/publicaons/licocc/Iowa Workforce Development Trendshp://www.iowaworkforce.org/trendsL M I(E‐B) W R:Iowa Works – Iowa Workforce Development’s Portal for Iowa Businesseshp://www.iowaworks.orgLabor Force Summarieshp://www.iowaworkforce.org/lmi/laborforce/index.htmlLabor Market Informaon Directoryhp://www.iowaworkforce.org/lmi/lmidirectoryOccupaonal Projecons & Job Outlookshp://www.iowaworkforce.org/lmi/occupaons/index.htmlKossuth County Laborshed Analysis 42 Released March 2013

RBreslow, Marc & Howard, Mahew. “The Real Underemployment Rate,” Monthly Labor Review May/June(1995): 35.Canup, Dr. C.R. (Buzz), President. “Ranked #3, Availability of Skilled Labor.” AreaDevelopment (April/May2006).Census Summary File 1 2010 CD (Version 1.0) [CD‐ROM]. (2010). East Brunswick, NJ: GeoLycs, Inc. [Producerand Distributor].Clogg, Clifford D. Measuring Underemployment. New York: Academic Press, 1979.Ecker, Dr. Mark (2001). “Esmang the Potenal Workforce for Iowa Laborsheds.” Instute for DecisionMaking, University of Northern Iowa.Fleisher, Belton M. & Knieser, Thomas J. (1984). Labor Economics: Theory, Evidence and Policy, Third Edion.Englewood Cliffs: Prence‐Hall.GeoSystems Global Corporaon. (1999). MapQuest [On‐line]. Available: www.mapquest.com.Glass, Robert H., Krider, Charles E. & Nelson, Kevin. (1996). “The Effecve Labor Force in Kansas:Employment, Unemployment and Underemployment.” The University of Kansas Instute of Public Policy andBusiness Research, School of Business, Department of Economics, Research Papers. Report No. 227, January1996.Google Maps. (2012). Google [On‐line]. Available: www.maps.google.com.Hedgcoth, Rachael, Senior Editor. “America’s 50 Hoest Cies for Manufacturing Expansions and Relocaons.”Expansion Management (January 2003).How the Government Measures Unemployment, Report 864, Bureau of Labor Stascs, U.S. Department ofLabor, February 1994.Kahn, Linda J. & Morrow, Paula C. “Objecve and Subjecve Underemployment Relaonships to JobSasfacon.” Journal of Business Research 22(1991): 211‐218.Leys, Tony. “A Lot of Job‐Seekers Are Already Working,” The Des Moines Register, July 28, 1996.“Labor Force Data Derived from the Current Populaon Survey,” BLS Handbook of Methods, Chapter 1, Bureauof Labor Stascs, U.S. Department of Labor, April 1997.“Measurement of Unemployment in States and Local Areas,” BLS Handbook of Methods, Chapter 4, Bureau ofLabor Stascs, U.S. Department of Labor, April 1997.Method for Obtaining Local Area Unemployment Esmates, Iowa Workforce Development.Tolbert, Charles M. & Killian, Molly S. “Labor Market Areas for the United States.” Agriculture and RuralEconomy Division Research Service, U.S. Department of Agriculture Staff Report No. AGES870721 (August1987).Kossuth County Laborshed Analysis 43 Released March 2013

I FESTIMATING THE TOTAL LABORFORCE POTENTIALFigure 1 Esmated Total Potenal Labor Force ‐ Kossuth County Laborshed Area 3PRIMARY INDUSTRIES OF THE LABORSHEDFigure 2 Where the Employed are Working 5WORKFORCE STATISTICSFigure 3 Employment Status of Survey Respondents & Type of Employment 6Figure 4 Educaonal Fields of Study 7Figure 5 Esmated Workforce by Occupaon 7Figure 6 Occupaonal Categories by Gender 7Figure 7 Occupaon Categories Across the Zones 8Figure 8 Median Wages & Salaries by Industry 8Figure 9 Median Wages & Salaries by Occupaonal Category 9Figure 10 Current Benefits offered by Employers 9ANALYSIS OF THOSE EMPLOYED WILLING TO CHANGE EMPLOYMENTFigure 11 Totals by Zones 10Figure 12 Esmated Totals by Zone & Gender 11Figure 13 Age Range Distribuon 11Figure 14 Educaonal Fields of Study 11Figure 15 Esmated Workforce by Occupaon 12Figure 16 Occupaonal Categories by Gender 12Figure 17 Occupaonal Categories Across the Zones 13Figure 18 Desired Occupaonal Categories Within the Zones 13Figure 19 Comparison of Current Wage Data 13Figure 20 Wage Threshold by Industry 14Figure 21 Comparison of Lowest Wages Considered by Gender 14Figure 22 Benefits Desired by Respondents 15Figure 23 Job Search Media Used 16Figure 24 Out Commuters by Place of Employment 17Figure 25 Underemployment ‐ Inadequate Hours Worked 18Figure 26 Underemployment ‐ Mismatch of Skills 19Figure 27 Underemployment ‐ Low Income 19Figure 28 Underemployment ‐ Esmated Total 20WILLINGNESS OF THOSE NOT CURRENTLY EMPLOYED TO ACCEPT EMPLOYMENTFigure 29 Unemployed ‐ Willing to Accept Employment 21Figure 30 Desired Addional Training 22Figure 31 Reasons for Being Unemployed 22Figure 32 Desired Benefits of the Unemployed 23Figure 33 Job Search Media Used 23Figure 34 Voluntarily Not Employed/Not Rered ‐ Willing to Accept Employment 24Figure 35 Rered (18‐64) ‐ Willing to Accept Employment 24Kossuth County Laborshed Analysis 44 Released March 2013

Publication of:Iowa Workforce DevelopmentLabor Market & Workforce Information DivisionRegional Research & Analysis Bureau1000 E. Grand AvenueDes Moines, Iowa 50319(515) 281-7505www.iowaworkforce.org