Technical information: (202) 691-6567 USDL 02-650 http://www.bls.gov/cew/ For release: 10:00 A.M. EST Media contact: 691-5902 Thursday, November 21, 2002 EMPLOYMENT AND AVERAGE ANNUAL PAY FOR LARGE COUNTIES, 2001 Of the 248 largest counties in the United States, 128 had employment growth in 2001, 111 experienced declines in employment, and 9 had no changes, according to preliminary data released today by the Bureau of Labor Statistics of the U.S. Department of Labor. Average annual pay was higher than the national average of $36,214 in 101 of the largest 248 U.S. counties in 2001. Employment and annual pay data by county are compiled from reports sub- mitted by employers subject to state and federal unemployment insurance (UI) laws, covering 129.7 million full- and part-time workers. Average annual pay is computed by dividing total annual payrolls of employees covered by UI programs by the average monthly number of these employees. The attached tables and charts contain data for the nation and for the 248 U.S. counties with employment of 100,000 or more. Previous issues of this release included counties with employment of 75,000 or more. (Some areas defined as counties in this release are not officially designated as counties. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages. See Technical Note. The 2000 data used to calculate the 2000-01 changes presented in this release were adjusted for changes in county classification to make them comparable with data for 2001. As a result, the adjusted 2000 data differ to some extent from the data available on the BLS Web site and in last year's release.) Employment The 248 U.S. counties with 100,000 or more employees accounted for 66.2 percent of total U.S. covered employment, 73.0 percent of total wages, and 7.9 percent of the 3,140 U.S. counties. (San Juan, P.R., is not in- cluded in this grouping of U.S. counties.) The largest absolute gains in employment in 2001 were recorded in the counties of Harris, Texas (+30,999), San Diego, Calif. (+24,326), Los Angeles, Calif. (+22,633), Clark, Nev. (+22,362), and Orange, Calif. (+20,580). (See table A.) Placer, Calif., had the largest over-the-year percentage increase in employment (6.0 percent), followed by the counties of Collier, Fla. (5.9 percent), Collin, Texas (5.7 percent), Manatee, Fla. (5.1 percent), and Lee, Fla. (4.7 percent). (See table 1.) Employment declined in 111 counties from 2000 to 2001. The largest per- centage decline in employment was in Elkhart County, Ind. (-6.8 percent), followed by the counties of Lorain and Mahoning in Ohio (-3.5 percent each) and San Francisco, Calif., and Macomb, Mich. (-3.4 percent each). The lar- gest absolute declines in employment occurred in Cook County, Ill. (-37,351), New York County, N.Y. (-32,910), Wayne County, Mich. (-27,974), Santa Clara County, Calif. (-22,112), and San Francisco County, Calif. (-20,423). - 2 - Table A. Top 10 counties ranked by 2001 employment level, 2000-01 employment growth, and 2000-01 percentage growth in employment ------------------------------------------------------------------------------ Employment ------------------------------------------------------------------------------ | | 2001 Employment level | 2000-01 Employment growth| 2000-01 Percentage | |growth in employment | | ------------------------------------------------------------------------------ Los Angeles, Calif. 4,102,386|Harris, Texas 30,999|Placer, Calif. 6.0 Cook, Ill. 2,634,150|San Diego, Calif. 24,326|Collier, Fla. 5.9 New York, N.Y. 2,345,709|Los Angeles, Calif. 22,633|Collin, Texas 5.7 Harris, Texas 1,864,179|Clark, Nev. 22,362|Manatee, Fla. 5.1 Maricopa, Ariz. 1,562,034|Orange, Calif. 20,580|Lee, Fla. 4.7 Dallas, Texas 1,551,255|Riverside, Calif. 19,491|Sarasota, Fla. 4.5 Orange, Calif. 1,410,583|Palm Beach, Fla. 18,625|Lafayette, La. 4.5 San Diego, Calif. 1,219,159|Maricopa, Ariz. 18,587|Riverside, Calif. 4.1 King, Wash. 1,147,290|Sacramento, Calif. 16,815|Palm Beach, Fla. 3.9 Santa Clara, Calif. 1,003,811|Miami-Dade, Fla. 15,481|Ocean, N.J. 3.8 ------------------------------------------------------------------------------ Average Annual Pay Average annual pay in 2001 was higher than the national average of $36,214 in 101 of the largest 248 U.S. counties. New York County, N.Y., comprised entirely of the borough of Manhattan, regained the top position among the highest paid large counties after losing it for the first time in 2000. This county led the nation with average annual pay of $74,641. Santa Clara County, Calif., moved back into second place with average annual pay of $65,926. Fairfield, Conn., was third with average annual pay of $63,123. San Mateo, Calif., was fourth with $62,509, followed by San Francisco, Calif., at $61,122. (See table B.) There were 147 counties with average annual pay below the national average. The lowest level of average annual pay (excluding San Juan, Puerto Rico) was reported in Cameron County, Texas ($22,146), followed by the counties of Hidalgo, Texas ($22,317), Tulare, Calif. ($24,706), El Paso, Texas ($25,836), and Volusia, Fla. ($26,093). (See table 2.) Lafayette County, La., led the nation in growth in average annual pay with an increase of 8.2 percent from 2000 to 2001. Dutchess County, N.Y., was second with 7.4 percent growth, followed by the counties of Escambia, Fla. (7.1 percent), Fresno, Calif. (6.6 percent), San Francisco, Calif., Will, Ill., and Baltimore, Md. (6.2 percent each). Fifteen large counties showed declines in average annual pay from 2000 to 2001. Santa Clara County, Calif., had the largest decrease, registering a 13.5 percent decline. Morris County, N.J., was second with a 10.9 percent decline, followed by the counties of San Mateo, Calif. (-6.8 percent), Wash- ington, Ore. (-5.2 percent), and Ada, Idaho (-4.0 percent). These sharp declines in pay growth followed extraordinary growth in 2000. From 1999 to 2000, pay growth increased by 24.5 percent in Santa Clara County, 19.0 percent in Morris County, 30.2 percent in San Mateo County, 13.2 percent in Washington County, and 10.0 percent in Ada County. - 3 - Table B. Top 10 counties ranked by 2001 pay level, 2000-01 growth in pay, and 2000-01 percentage growth in pay -------------------------------------------------------------------------------- Average annual pay -------------------------------------------------------------------------------- | | | | 2000-01 Percentage 2001 Pay level | 2000-01 Growth in pay | growth in pay | | -------------------------------------------------------------------------------- New York, N.Y. $74,641|San Francisco, Calif.$3,561|Lafayette, La. 8.2 Santa Clara, Calif. 65,926|Washington, D.C. 3,059|Dutchess, N.Y. 7.4 Fairfield, Conn. 63,123|Dutchess, N.Y. 2,679|Escambia, Fla. 7.1 San Mateo, Calif. 62,509|Arlington, Va. 2,463|Fresno, Calif. 6.6 San Francisco, Calif.61,122|Lafayette, La. 2,448|San Francisco, Calif.6.2 Suffolk, Mass. 58,905|Contra Costa, Calif. 2,445|Will, Ill. 6.2 Washington, D.C. 56,024|New Castle, Del. 2,372|Baltimore, Md. 6.2 Somerset, N.J. 55,598|Howard, Md. 2,287|Peoria, Ill. 6.0 Arlington, Va. 55,310|Suffolk, Mass. 2,245|Howard, Md. 6.0 Morris, N.J. 53,871|St. Louis City, Mo. 2,224|Monterey, Calif. 5.9 -------------------------------------------------------------------------------- U.S. 36,214|U.S. 894|U.S. 2.5 -------------------------------------------------------------------------------- Change in Industry Classification Systems Beginning with the release of data for 2001, publications presenting data from the Covered Employment and Wages program use the 2002 version of the North American Industry Classification System (NAICS) as the basis for the assignment and tabulation of economic data by industry. NAICS is the product of a cooperative effort on the part of the statistical agencies of the United States, Canada, and Mexico. Due to differences in NAICS and SIC structures, industry data for 2001 are not comparable to the SIC-based data for earlier years. NAICS uses a production-oriented approach to categorize economic units. Units with similar production processes are classified in the same industry. NAICS focuses on how products and services are created, as opposed to the SIC focus on what is produced. This approach yields significantly different indus- try groupings than those produced by the SIC approach. Data users will be able to work with new NAICS industrial groupings that better reflect the workings of the U.S. economy. For example, a new industry sector called Information brings together units which turn infor- mation into a commodity with units which distribute that commodity. Infor- mation's major components are publishing, broadcasting, telecommunications, information services, and data processing. Under the SIC system, these units were spread across the manufacturing, communications, business services, and amusement services groups. Another new sector of interest is Professional and technical services. This sector is comprised of establishments engaged in activities where human capital is the major input. Users interested in more information about NAICS can access the Bureau of Labor Statistics Web page at http://www.bls.gov/bls/naics.htm and the Bureau of Census Web page at http://www.census.gov/epcd/www/naics.html. The NAICS 2002 manual is available from the National Technical Information Service (NTIS) Web page at http://www.ntis.gov/. ---------------------------------------------------------------- | Average annual pay for 2001 and other data from the Covered | | Employment and Wages (CEW) program is available on the BLS Web | | site at http://www.bls.gov/cew/. | ---------------------------------------------------------------- Technical Note These data are the product of a federal-state cooperative program known as Covered Employment and Wages, or the ES-202 program. The data are de- rived from summaries of employment and total pay of workers covered by unemployment insurance (UI) legislation and provided by State Employment Security Agencies (SESAs). The summaries are a byproduct of the admini- stration of state unemployment insurance programs that require most em- ployers to pay quarterly taxes based on the employment and wages of workers covered by UI. Data for 2001 are preliminary and subject to revision. The 2000 data used to calculate the 2000-01 changes presented in this release were adjusted for changes in county classification to make them comparable to data for 2001. As a result, the adjusted 2000 data differ to some ex- tent from the data available on the BLS Web site. Coverage Employment and wage data for workers covered by state UI laws and for federal civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program are compiled from quarterly contribution reports submitted to the SESAs by employers. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state complete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establishments. Average annual employment and pay data included in this release are derived from microdata summaries of 8.0 million employer reports of employment and wages submitted by states to the Bureau of Labor Statistics. These reports are based on place of employment rather than place of residence. UI and UCFE coverage is broad and basically comparable from state to state. In 2001, UI and UCFE programs covered workers in 129.7 million jobs. The estimated 124.8 million workers in these jobs (after adjust- ment for multiple jobholders) represented 99.7 percent of wage and salary civilian employment. Multiple jobholder estimates are produced by the Current Population Survey. Covered workers received $4.695 trillion in pay, representing 94.8 percent of the wage and salary component of per- sonal income and 46.6 percent of the gross domestic product. Major exclusions from UI coverage during 2001 are self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and employees of certain small nonprofit organizations. Concepts and methodology Average annual pay was computed by dividing total annual pay of employees covered by UI programs by the average monthly number of these employees. In addition to salaries, average pay data include bonuses, the cash value of meals and lodging when supplied, tips and other gratuities, and, in some states, employer contributions to certain deferred compensation plans, such as 401(k) plans and stock options. Monthly employment is based on the num- ber of workers who worked during or received pay for the pay period includ- ing the 12th day of the month. With few exceptions, all employees of covered firms are reported, including production and sales workers, corporation offi- cials, executives, supervisory personnel, and clerical workers. Workers on paid vacation and part-time workers also are included. Percent changes in average annual pay were computed using preliminary North American Industry Classification System (NAICS)-based 2000 data as the base. These prelimin- ary NAICS-based 2000 data will differ from the Standard Industrial Classifi- cation (SIC)-based 2000 data previously published. Average annual pay is affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations. When comparing average annual pay levels between counties, these factors should be taken into consideration. Annual pay data only approximate annual earnings because an individual may not be employed by the same employer all year or may work for more than one employer. Also, year-to-year changes in average annual pay can result from a change in the proportion of employment in high- and low-wage jobs, as well as from changes in the level of average annual pay. In order to insure the highest possible quality of data, SESAs verify with employers and update, if necessary, the industry, location, and own- ership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from the verification process are introduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. For these reasons, some data, especi- ally at more detailed geographic levels, may not be strictly comparable with earlier years. The 2000 data have been adjusted for code changes in order to be comparable with 2001 data. County definitions are assigned according to Federal Information Pro- cessing Standards Publications (FIPS PUBS) as issued by the National In- stitute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Manage- ment Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as inde- pendent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive infor- mation by detailed industry on establishments, employment, and wages for the nation and all states. Employment and Wages Annual Averages, 2001 will be available for sale in late 2002 from the BLS Publications Sales Center, P.O. Box 2145, Chicago, Illinois 60690. News releases providing 2001 average annual pay data by state and industry and by metropolitan areas also are available from the Bureau of Labor Statistics. Average annual industry employment and pay data at the national, state, Conso- lidated Metropolitan Statistical Area, Metropolitan Statistical Area, and county levels are available upon request from the Division of Admin- istrative Statistics and Labor Turnover, Bureau of Labor Statistics, U.S. Department of Labor, Washington, DC 20212, telephone 202-691-6567 (e-mail: CEWInfo@bls.gov). Also available from BLS is a news release of first quarter 2002 employment and wage data at the national industry subsector level. First quarter 2002 data at the state total level will be available on the BLS web site on November 22. Information in this release will be made available to sensory impaired individuals upon request. Voice phone: 202-691-5200; TDD message referral phone number: 1-800-877-8339. Table 1. Employment and average annual pay for 2001 and 2000-01 percent changes for all covered workers(1) in the 249 largest counties Employment(3) Average annual pay(3) County(2) Percent Ranked by Percent 2001 change, percent 2001 change, 2000-01(4) change, 2000-01(4) 2000-01 United States(5)........ - - - $36,214 2.5 Jefferson, AL........... 380,706 -0.9 196 35,449 4.2 Madison, AL............. 156,248 1.4 51 37,071 3.4 Mobile, AL.............. 167,047 -1.4 211 29,491 3.0 Montgomery, AL.......... 130,029 -0.8 186 29,948 3.6 Anchorage, AK........... 133,521 2.8 20 37,826 3.2 Maricopa, AZ............ 1,562,034 1.2 59 35,681 1.6 Pima, AZ................ 326,931 -0.6 173 30,696 5.1 Pulaski, AR............. 240,690 -0.7 178 32,256 4.7 Alameda, CA............. 697,291 -0.1 138 46,511 3.1 Contra Costa, CA........ 337,354 0.7 81 44,774 5.8 Fresno, CA.............. 322,071 -0.1 139 27,891 6.6 Kern, CA................ 242,151 1.5 47 30,120 5.4 Los Angeles, CA......... 4,102,386 0.6 88 40,907 3.1 Marin, CA............... 111,897 1.3 53 43,548 2.2 Monterey, CA............ 166,234 0.8 76 31,743 5.9 Orange, CA.............. 1,410,583 1.5 48 40,280 2.6 Placer, CA.............. 116,002 6.0 1 34,672 3.8 Riverside, CA........... 491,295 4.1 8 30,011 3.0 Sacramento, CA.......... 588,306 2.9 19 39,196 3.8 San Bernardino, CA...... 545,139 2.8 21 30,991 3.6 San Diego, CA........... 1,219,159 2.0 36 38,424 2.3 San Francisco, CA....... 585,458 -3.4 245 61,122 6.2 San Joaquin, CA......... 204,474 1.9 38 30,816 5.3 San Mateo, CA........... 370,148 0.1 122 62,509 -6.8 Santa Barbara, CA....... 177,337 0.9 66 33,609 3.2 Santa Clara, CA......... 1,003,811 -2.2 232 65,926 -13.5 Santa Cruz, CA.......... 102,676 0.9 67 35,023 -2.2 Solano, CA.............. 121,474 3.1 17 33,470 5.6 Sonoma, CA.............. 194,963 2.1 31 36,150 1.1 Stanislaus, CA.......... 164,370 2.2 30 29,523 4.6 Tulare, CA.............. 133,055 0.1 123 24,706 4.1 Ventura, CA............. 293,265 1.5 49 37,795 1.9 Adams, CO............... 146,002 0.5 94 34,760 4.0 Arapahoe, CO............ 285,844 -0.2 146 44,997 -2.7 Boulder, CO............. 184,751 3.2 14 44,313 -2.7 Denver, CO.............. 462,131 -0.6 174 46,126 4.0 El Paso, CO............. 240,083 0.9 68 34,381 4.1 Jefferson, CO........... 210,391 0.1 124 37,817 4.5 Larimer, CO............. 121,870 2.3 29 33,249 2.6 Fairfield, CT........... 421,447 -1.0 197 63,123 3.2 Hartford, CT............ 497,115 -0.5 167 45,049 3.2 New Haven, CT........... 363,361 -1.1 200 39,481 2.9 New London, CT.......... 124,732 1.6 44 38,201 3.9 New Castle, DE.......... 282,166 0.1 125 42,863 5.9 Washington, DC.......... 635,583 -0.3 153 56,024 5.8 Alachua, FL............. 119,079 0.7 82 26,915 2.9 Brevard, FL............. 184,887 1.8 41 32,786 2.1 Broward, FL............. 664,095 2.1 32 33,964 2.2 Collier, FL............. 110,220 5.9 2 30,842 2.9 Duval, FL............... 436,089 1.6 45 33,766 3.0 Escambia, FL............ 121,382 0.9 69 28,594 7.1 Hillsborough, FL........ 596,521 1.9 39 32,868 3.7 Lee, FL................. 172,243 4.7 5 29,397 4.4 Leon, FL................ 142,865 0.8 77 30,267 3.5 Manatee, FL............. 118,697 5.1 4 26,629 4.4 Miami-Dade, FL.......... 993,913 1.6 46 34,531 3.6 Orange, FL.............. 602,698 0.2 112 32,226 3.5 Palm Beach, FL.......... 499,532 3.9 9 35,962 2.1 Pinellas, FL............ 449,459 3.4 12 31,740 1.5 Polk, FL................ 184,900 0.3 105 28,803 3.3 Sarasota, FL............ 147,207 4.5 6 29,029 1.9 Seminole, FL............ 144,830 1.9 40 31,923 3.5 Volusia, FL............. 142,479 -0.2 147 26,093 4.0 Chatham, GA............. 122,798 0.0 129 30,522 2.9 Clayton, GA............. 115,028 -0.2 148 38,309 4.2 Cobb, GA................ 301,743 0.0 130 40,196 3.6 Dekalb, GA.............. 306,822 -0.4 159 39,548 2.4 Fulton, GA.............. 755,986 0.2 113 47,747 1.5 Gwinnett, GA............ 290,610 3.3 13 39,328 0.7 Richmond, GA............ 104,867 -0.7 179 29,399 2.8 Honolulu, HI............ 409,415 0.4 100 32,527 2.0 Ada, ID................. 182,401 2.8 22 33,070 -4.0 Cook, IL................ 2,634,150 -1.4 212 44,044 2.7 Du Page, IL............. 581,011 -0.2 149 43,479 2.1 Kane, IL................ 194,339 -0.1 140 33,353 3.7 Lake, IL................ 316,225 -0.3 154 43,966 3.2 Peoria, IL.............. 102,799 -1.8 222 33,276 6.0 Sangamon, IL............ 145,150 0.2 114 36,265 4.3 Will, IL................ 145,434 0.0 131 34,305 6.2 Winnebago, IL........... 139,862 -2.9 239 31,943 1.4 Allen, IN............... 183,371 -2.3 234 32,824 1.7 Elkhart, IN............. 113,550 -6.8 249 30,797 1.5 Lake, IN................ 194,618 -1.9 226 32,018 1.4 Marion, IN.............. 591,478 -1.3 210 37,881 3.8 St. Joseph, IN.......... 125,006 -3.1 241 30,773 3.8 Vanderburgh, IN......... 109,416 0.1 126 30,495 3.1 Linn, IA................ 119,995 -1.6 216 34,672 1.7 Polk, IA................ 263,443 -0.2 150 34,944 3.8 Johnson, KS............. 293,002 2.4 27 37,214 -0.1 Sedgwick, KS............ 249,938 0.2 115 33,932 3.8 Shawnee, KS............. 100,528 0.3 106 30,503 3.8 Fayette, KY............. 167,873 -2.3 235 32,214 4.9 Jefferson, KY........... 431,473 -1.7 219 34,681 4.0 Caddo, LA............... 120,858 1.3 54 29,409 2.2 East Baton Rouge, LA.... 243,496 -1.0 198 30,371 3.8 Jefferson, LA........... 213,875 -0.5 168 29,312 4.5 Lafayette, LA........... 119,308 4.5 7 32,359 8.2 Orleans, LA............. 263,455 0.1 127 32,886 3.8 Cumberland, ME.......... 168,147 1.3 55 32,327 5.1 Anne Arundel, MD........ 200,180 2.8 23 37,189 4.9 Baltimore, MD........... 360,086 0.2 116 36,240 6.2 Howard, MD.............. 132,944 1.3 56 40,184 6.0 Montgomery, MD.......... 449,838 0.9 70 45,892 5.0 Prince Georges, MD...... 305,191 0.9 71 38,831 4.8 Baltimore City, MD...... 381,209 0.4 101 40,501 5.0 Bristol, MA............. 218,781 -1.2 207 32,012 4.1 Essex, MA............... 306,115 0.2 117 39,244 0.5 Hampden, MA............. 204,814 0.9 72 33,357 3.6 Middlesex, MA........... 850,199 1.4 52 51,736 0.0 Norfolk, MA............. 327,014 0.7 83 44,178 2.2 Plymouth, MA............ 166,453 0.8 78 34,931 3.4 Suffolk, MA............. 602,945 0.1 128 58,905 4.0 Worcester, MA........... 321,029 0.3 107 37,300 -0.9 Genesee, MI............. 160,137 -3.2 243 36,030 -0.8 Ingham, MI.............. 174,008 -0.4 160 35,773 2.3 Kalamazoo, MI........... 116,589 -1.8 223 33,926 3.8 Kent, MI................ 339,410 -1.8 224 34,576 1.7 Macomb, MI.............. 326,001 -3.4 246 40,508 -1.0 Oakland, MI............. 752,905 -1.8 225 45,070 1.3 Ottawa, MI.............. 115,781 -2.6 238 32,249 0.9 Washtenaw, MI........... 195,090 0.0 132 40,193 0.0 Wayne, MI............... 841,621 -3.2 244 42,714 0.6 Anoka, MN............... 109,494 -0.3 155 34,588 1.9 Dakota, MN.............. 155,560 1.2 60 35,701 3.9 Hennepin, MN............ 864,006 -0.8 187 45,498 3.8 Ramsey, MN.............. 333,292 -0.1 141 40,377 3.3 Hinds, MS............... 134,373 -0.8 188 31,135 1.8 Greene, MO.............. 140,823 -0.8 189 28,077 4.1 Jackson, MO............. 385,096 -2.2 233 37,397 3.7 St. Louis, MO........... 640,845 -0.8 190 38,943 2.1 St. Louis City, MO...... 245,360 -2.1 229 40,836 5.8 Douglas, NE............. 325,676 -0.6 175 32,851 1.5 Lancaster, NE........... 148,264 1.0 63 29,353 3.0 Clark, NV............... 720,074 3.2 15 32,650 1.6 Washoe, NV.............. 193,566 2.4 28 34,230 4.5 Hillsborough, NH........ 192,677 -0.1 142 39,313 0.3 Rockingham, NH.......... 130,880 0.7 84 36,648 2.3 Atlantic, NJ............ 141,207 0.9 73 32,476 4.5 Bergen, NJ.............. 451,763 1.1 61 46,814 1.1 Burlington, NJ.......... 187,339 3.6 11 38,729 3.0 Camden, NJ.............. 199,847 0.5 95 36,484 3.9 Essex, NJ............... 362,267 -0.3 156 46,489 4.1 Hudson, NJ.............. 237,272 0.0 133 47,621 0.4 Mercer, NJ.............. 215,558 2.7 25 45,746 2.4 Middlesex, NJ........... 399,503 1.3 57 47,636 2.5 Monmouth, NJ............ 240,748 3.2 16 40,375 1.7 Morris, NJ.............. 278,261 0.6 89 53,871 -10.9 Ocean, NJ............... 133,758 3.8 10 31,028 1.9 Passaic, NJ............. 175,044 -1.2 208 39,126 3.6 Somerset, NJ............ 176,467 1.5 50 55,598 1.5 Union, NJ............... 236,653 -0.1 143 46,185 2.0 Bernalillo, NM.......... 309,340 0.7 85 31,654 4.9 Albany, NY.............. 229,995 -0.5 169 37,859 5.8 Bronx, NY............... 214,492 0.5 96 34,359 4.6 Dutchess, NY............ 112,973 2.6 26 38,744 7.4 Erie, NY................ 454,555 -1.1 201 32,098 1.9 Kings, NY............... 439,461 -0.1 144 31,939 3.8 Monroe, NY.............. 395,038 -0.4 161 36,595 3.3 Nassau, NY.............. 594,478 -0.6 176 40,586 1.4 New York, NY............ 2,345,709 -1.4 213 74,641 2.9 Oneida, NY.............. 108,714 -1.7 220 28,361 3.9 Onondaga, NY............ 249,661 -1.1 202 33,510 3.1 Orange, NY.............. 120,792 0.6 90 30,225 3.0 Queens, NY.............. 478,590 -0.7 180 36,974 5.7 Rockland, NY............ 107,229 0.2 118 38,745 4.0 Suffolk, NY............. 582,174 0.2 119 38,692 2.2 Westchester, NY......... 405,040 -0.4 162 48,584 3.2 Buncombe, NC............ 105,196 -0.4 163 28,714 3.8 Cumberland, NC.......... 106,260 -2.9 240 26,993 3.4 Durham, NC.............. 169,677 0.4 102 48,055 -2.6 Forsyth, NC............. 180,008 -0.8 191 34,697 2.0 Guilford, NC............ 274,038 -2.1 230 33,202 3.1 Mecklenburg, NC......... 513,815 0.3 108 41,795 3.1 Wake, NC................ 385,399 0.8 79 36,981 4.5 Butler, OH.............. 126,865 -0.5 170 32,325 2.6 Cuyahoga, OH............ 796,430 -1.6 217 37,532 2.8 Franklin, OH............ 702,623 0.2 120 36,089 3.2 Hamilton, OH............ 559,876 -1.1 203 38,331 1.9 Lorain, OH.............. 103,115 -3.5 247 32,190 0.6 Lucas, OH............... 234,677 -1.7 221 33,089 2.6 Mahoning, OH............ 109,005 -3.5 248 26,852 3.4 Montgomery, OH.......... 298,981 -1.5 214 34,783 0.7 Stark, OH............... 173,891 -1.6 218 29,197 2.4 Summit, OH.............. 261,166 -2.1 231 33,405 2.0 Oklahoma, OK............ 415,294 0.3 109 30,161 3.2 Tulsa, OK............... 342,021 0.4 103 32,777 5.2 Clackamas, OR........... 133,961 -0.2 151 33,706 3.8 Lane, OR................ 137,593 -1.9 227 28,976 3.9 Marion, OR.............. 126,945 -0.7 181 28,779 2.4 Multnomah, OR........... 444,183 -1.1 204 37,658 2.3 Washington, OR.......... 228,253 1.3 58 42,168 -5.2 Allegheny, PA........... 711,540 0.3 110 38,085 3.7 Berks, PA............... 165,261 -0.7 182 32,810 2.5 Bucks, PA............... 246,474 0.6 91 35,236 3.5 Chester, PA............. 217,156 0.6 92 44,214 1.0 Cumberland, PA.......... 122,668 -0.6 177 33,997 3.6 Dauphin, PA............. 173,307 0.3 111 34,854 3.5 Delaware, PA............ 213,963 0.9 74 38,486 4.5 Erie, PA................ 128,905 -2.3 236 29,290 3.3 Lancaster, PA........... 218,435 -0.3 157 31,486 2.2 Lehigh, PA.............. 172,875 0.2 121 35,562 0.8 Luzerne, PA............. 141,927 -0.8 192 28,918 3.8 Montgomery, PA.......... 485,911 0.5 97 44,364 1.3 Philadelphia, PA........ 658,898 -0.7 183 40,810 2.8 Westmoreland, PA........ 134,151 -0.4 164 28,831 3.0 York, PA................ 165,868 -1.0 199 31,937 3.3 Providence, RI.......... 288,438 -0.8 193 34,554 3.4 Charleston, SC.......... 180,505 -1.1 205 29,020 4.8 Greenville, SC.......... 226,112 -3.1 242 32,631 4.3 Richland, SC............ 205,671 -0.5 171 30,590 3.3 Spartanburg, SC......... 117,177 -2.3 237 31,849 4.1 Minnehaha, SD........... 106,718 1.1 62 29,203 3.5 Davidson, TN............ 434,574 0.0 134 35,391 1.5 Hamilton, TN............ 187,760 -0.3 158 31,218 2.1 Knox, TN................ 203,632 0.7 86 30,748 2.2 Shelby, TN.............. 497,052 -0.4 165 35,760 4.1 Bexar, TX............... 655,490 1.0 64 31,022 3.7 Cameron, TX............. 111,359 2.1 33 22,146 2.8 Collin, TX.............. 181,095 5.7 3 41,317 2.0 Dallas, TX.............. 1,551,255 -0.5 172 44,897 1.2 Denton, TX.............. 122,572 1.0 65 30,785 5.1 El Paso, TX............. 248,663 -1.1 206 25,836 3.1 Harris, TX.............. 1,864,179 1.7 43 43,747 4.5 Hidalgo, TX............. 168,637 3.1 18 22,317 2.9 Jefferson, TX........... 118,762 -1.9 228 32,565 4.1 Lubbock, TX............. 118,029 2.1 34 26,581 1.1 Nueces, TX.............. 143,502 0.7 87 29,403 4.3 Tarrant, TX............. 709,041 0.5 98 37,290 5.2 Travis, TX.............. 534,887 -0.7 184 41,692 0.9 Salt Lake, UT........... 530,616 0.0 135 33,197 3.1 Utah, UT................ 143,443 0.5 99 28,275 1.4 Arlington, VA........... 159,394 0.4 104 55,310 4.7 Chesterfield, VA........ 107,700 -0.1 145 32,953 3.4 Fairfax, VA............. 543,271 2.8 24 52,610 2.0 Henrico, VA............. 169,820 2.0 37 37,868 4.8 Norfolk, VA............. 146,428 0.8 80 33,501 4.1 Richmond, VA............ 165,016 -0.7 185 40,154 3.9 Virginia Beach, VA...... 166,050 0.9 75 26,740 5.2 Clark, WA............... 114,686 2.1 35 33,122 2.9 King, WA................ 1,147,290 -0.8 194 47,224 -0.5 Pierce, WA.............. 238,565 -1.5 215 31,255 4.6 Snohomish, WA........... 209,881 -0.2 152 36,360 3.6 Spokane, WA............. 190,042 0.0 136 29,323 -1.5 Kanawha, WV............. 111,594 -0.8 195 31,581 4.7 Brown, WI............... 142,499 0.0 137 32,500 3.1 Dane, WI................ 279,031 1.8 42 34,107 3.9 Milwaukee, WI........... 519,880 -1.2 209 35,819 3.1 Waukesha, WI............ 224,660 0.6 93 37,093 3.7 San Juan, PR............ 324,827 -0.4 166 22,182 4.1 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. The 248 U.S. counties comprise 66.2 percent of the total covered workers in the U.S. 2 Includes areas not officially designated as counties. See Technical Note. 3 Data are preliminary. 4 Percent changes were computed from annual employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Totals for the United States do not include data for Puerto Rico. Table 2. County rankings of employment and average annual pay for 2001 and 2000-01 percent changes for all covered workers(1) in the 249 largest counties Employment(3) Average annual pay(3) County(2) Net Ranked by 2001 change, 2001 Ranked by percent 2000-01(4) 2001 level change, 2000-01 Los Angeles, CA....... 4,102,386 22,633 $40,907 47 133 Cook, IL.............. 2,634,150 -37,351 44,044 36 160 New York, NY.......... 2,345,709 -32,910 74,641 1 153 Harris, TX............ 1,864,179 30,999 43,747 38 46 Maricopa, AZ.......... 1,562,034 18,587 35,681 110 204 Dallas, TX............ 1,551,255 -8,348 44,897 30 218 Orange, CA............ 1,410,583 20,580 40,280 55 161 San Diego, CA......... 1,219,159 24,326 38,424 74 171 King, WA.............. 1,147,290 -9,537 47,224 18 236 Santa Clara, CA....... 1,003,811 -22,112 65,926 2 249 Miami-Dade, FL........ 993,913 15,481 34,531 128 100 Hennepin, MN.......... 864,006 -6,548 45,498 26 87 Middlesex, MA......... 850,199 11,404 51,736 12 233 Wayne, MI............. 841,621 -27,974 42,714 42 228 Cuyahoga, OH.......... 796,430 -13,147 37,532 86 157 Fulton, GA............ 755,986 1,823 47,747 15 207 Oakland, MI........... 752,905 -13,608 45,070 27 216 Clark, NV............. 720,074 22,362 32,650 162 205 Allegheny, PA......... 711,540 2,342 38,085 78 95 Tarrant, TX........... 709,041 3,564 37,290 89 21 Franklin, OH.......... 702,623 1,660 36,089 103 130 Alameda, CA........... 697,291 -783 46,511 20 132 Broward, FL........... 664,095 13,693 33,964 135 176 Philadelphia, PA...... 658,898 -4,902 40,810 49 158 Bexar, TX............. 655,490 6,261 31,022 193 96 St. Louis, MO......... 640,845 -5,222 38,943 67 185 Washington, DC........ 635,583 -1,701 56,024 7 13 Suffolk, MA........... 602,945 809 58,905 6 68 Orange, FL............ 602,698 1,174 32,226 173 107 Hillsborough, FL...... 596,521 11,213 32,868 156 92 Nassau, NY............ 594,478 -3,788 40,586 50 214 Marion, IN............ 591,478 -7,791 37,881 79 79 Sacramento, CA........ 588,306 16,815 39,196 65 78 San Francisco, CA..... 585,458 -20,423 61,122 5 5 Suffolk, NY........... 582,174 1,084 38,692 72 179 Du Page, IL........... 581,011 -962 43,479 40 184 Hamilton, OH.......... 559,876 -6,290 38,331 75 198 San Bernardino, CA.... 545,139 14,973 30,991 194 99 Fairfax, VA........... 543,271 14,656 52,610 11 192 Travis, TX............ 534,887 -3,871 41,692 45 224 Salt Lake, UT......... 530,616 -210 33,197 150 139 Milwaukee, WI......... 519,880 -6,267 35,819 106 141 Mecklenburg, NC....... 513,815 1,509 41,795 44 137 Palm Beach, FL........ 499,532 18,625 35,962 105 183 Hartford, CT.......... 497,115 -2,439 45,049 28 127 Shelby, TN............ 497,052 -2,184 35,760 108 60 Riverside, CA......... 491,295 19,491 30,011 211 143 Montgomery, PA........ 485,911 2,440 44,364 32 217 Queens, NY............ 478,590 -3,229 36,974 95 16 Denver, CO............ 462,131 -2,822 46,126 23 65 Erie, NY.............. 454,555 -5,182 32,098 176 197 Bergen, NJ............ 451,763 4,905 46,814 19 220 Montgomery, MD........ 449,838 3,925 45,892 24 26 Pinellas, FL.......... 449,459 14,944 31,740 185 206 Multnomah, OR......... 444,183 -5,148 37,658 85 174 Kings, NY............. 439,461 -309 31,939 180 88 Duval, FL............. 436,089 6,972 33,766 138 144 Davidson, TN.......... 434,574 72 35,391 113 211 Jefferson, KY......... 431,473 -7,535 34,681 122 67 Fairfield, CT......... 421,447 -4,206 63,123 3 126 Oklahoma, OK.......... 415,294 1,340 30,161 209 131 Honolulu, HI.......... 409,415 1,497 32,527 165 187 Westchester, NY....... 405,040 -1,461 48,584 13 129 Middlesex, NJ......... 399,503 5,193 47,636 16 165 Monroe, NY............ 395,038 -1,393 36,595 97 120 Wake, NC.............. 385,399 3,221 36,981 94 44 Jackson, MO........... 385,096 -8,860 37,397 87 94 Baltimore City, MD.... 381,209 1,449 40,501 52 27 Jefferson, AL......... 380,706 -3,635 35,449 112 52 San Mateo, CA......... 370,148 490 62,509 4 247 New Haven, CT......... 363,361 -3,874 39,481 61 149 Essex, NJ............. 362,267 -941 46,489 21 58 Baltimore, MD......... 360,086 744 36,240 101 7 Tulsa, OK............. 342,021 1,532 32,777 161 20 Kent, MI.............. 339,410 -6,383 34,576 126 202 Contra Costa, CA...... 337,354 2,226 44,774 31 12 Ramsey, MN............ 333,292 -254 40,377 53 119 Norfolk, MA........... 327,014 2,142 44,178 35 178 Pima, AZ.............. 326,931 -1,905 30,696 201 23 Macomb, MI............ 326,001 -11,352 40,508 51 239 Douglas, NE........... 325,676 -2,085 32,851 157 209 San Juan, PR.......... 324,827 -1,464 22,182 248 63 Fresno, CA............ 322,071 -340 27,891 237 4 Worcester, MA......... 321,029 1,067 37,300 88 238 Lake, IL.............. 316,225 -870 43,966 37 128 Bernalillo, NM........ 309,340 2,252 31,654 186 30 Dekalb, GA............ 306,822 -1,124 39,548 60 167 Essex, MA............. 306,115 606 39,244 64 230 Prince Georges, MD.... 305,191 2,715 38,831 68 31 Cobb, GA.............. 301,743 -36 40,196 56 101 Montgomery, OH........ 298,981 -4,630 34,783 119 227 Ventura, CA........... 293,265 4,407 37,795 84 193 Johnson, KS........... 293,002 6,758 37,214 90 235 Gwinnett, GA.......... 290,610 9,255 39,328 62 226 Providence, RI........ 288,438 -2,337 34,554 127 116 Arapahoe, CO.......... 285,844 -604 44,997 29 243 New Castle, DE........ 282,166 325 42,863 41 11 Dane, WI.............. 279,031 5,010 34,107 133 76 Morris, NJ............ 278,261 1,616 53,871 10 248 Guilford, NC.......... 274,038 -5,758 33,202 149 136 Orleans, LA........... 263,455 334 32,886 155 85 Polk, IA.............. 263,443 -633 34,944 116 81 Summit, OH............ 261,166 -5,592 33,405 144 190 Sedgwick, KS.......... 249,938 422 33,932 136 82 Onondaga, NY.......... 249,661 -2,760 33,510 141 135 El Paso, TX........... 248,663 -2,880 25,836 245 138 Bucks, PA............. 246,474 1,517 35,236 114 109 St. Louis City, MO.... 245,360 -5,242 40,836 48 14 East Baton Rouge, LA.. 243,496 -2,532 30,371 206 84 Kern, CA.............. 242,151 3,560 30,120 210 18 Monmouth, NJ.......... 240,748 7,455 40,375 54 203 Pulaski, AR........... 240,690 -1,744 32,256 171 34 El Paso, CO........... 240,083 2,035 34,381 129 55 Pierce, WA............ 238,565 -3,617 31,255 189 39 Hudson, NJ............ 237,272 115 47,621 17 231 Union, NJ............. 236,653 -278 46,185 22 188 Lucas, OH............. 234,677 -3,959 33,089 152 164 Albany, NY............ 229,995 -1,145 37,859 81 15 Washington, OR........ 228,253 2,897 42,168 43 246 Greenville, SC........ 226,112 -7,300 32,631 163 50 Waukesha, WI.......... 224,660 1,307 37,093 92 97 Bristol, MA........... 218,781 -2,573 32,012 178 56 Lancaster, PA......... 218,435 -735 31,486 188 180 Chester, PA........... 217,156 1,263 44,214 34 222 Mercer, NJ............ 215,558 5,578 45,746 25 168 Bronx, NY............. 214,492 1,089 34,359 130 38 Delaware, PA.......... 213,963 1,978 38,486 73 45 Jefferson, LA......... 213,875 -982 29,312 221 41 Jefferson, CO......... 210,391 167 37,817 83 40 Snohomish, WA......... 209,881 -397 36,360 99 105 Richland, SC.......... 205,671 -1,124 30,590 202 123 Hampden, MA........... 204,814 1,824 33,357 145 102 San Joaquin, CA....... 204,474 3,782 30,816 196 19 Knox, TN.............. 203,632 1,451 30,748 200 181 Anne Arundel, MD...... 200,180 5,484 37,189 91 29 Camden, NJ............ 199,847 934 36,484 98 72 Washtenaw, MI......... 195,090 -49 40,193 57 234 Sonoma, CA............ 194,963 4,063 36,150 102 219 Lake, IN.............. 194,618 -3,770 32,018 177 213 Kane, IL.............. 194,339 -255 33,353 146 93 Washoe, NV............ 193,566 4,612 34,230 132 42 Hillsborough, NH...... 192,677 -123 39,313 63 232 Spokane, WA........... 190,042 75 29,323 220 240 Hamilton, TN.......... 187,760 -597 31,218 190 186 Burlington, NJ........ 187,339 6,496 38,729 71 146 Polk, FL.............. 184,900 554 28,803 230 118 Brevard, FL........... 184,887 3,302 32,786 160 182 Boulder, CO........... 184,751 5,747 44,313 33 244 Allen, IN............. 183,371 -4,251 32,824 158 200 Ada, ID............... 182,401 4,931 33,070 153 245 Collin, TX............ 181,095 9,778 41,317 46 191 Charleston, SC........ 180,505 -2,002 29,020 226 32 Forsyth, NC........... 180,008 -1,465 34,697 121 189 Santa Barbara, CA..... 177,337 1,513 33,609 140 125 Somerset, NJ.......... 176,467 2,667 55,598 8 210 Passaic, NJ........... 175,044 -2,082 39,126 66 103 Ingham, MI............ 174,008 -739 35,773 107 172 Stark, OH............. 173,891 -2,742 29,197 224 169 Dauphin, PA........... 173,307 485 34,854 118 110 Lehigh, PA............ 172,875 387 35,562 111 225 Lee, FL............... 172,243 7,789 29,397 218 47 Henrico, VA........... 169,820 3,370 37,868 80 33 Durham, NC............ 169,677 633 48,055 14 242 Hidalgo, TX........... 168,637 5,123 22,317 247 154 Cumberland, ME........ 168,147 2,185 32,327 169 24 Fayette, KY........... 167,873 -3,898 32,214 174 28 Mobile, AL............ 167,047 -2,450 29,491 214 142 Plymouth, MA.......... 166,453 1,253 34,931 117 113 Monterey, CA.......... 166,234 1,332 31,743 184 10 Virginia Beach, VA.... 166,050 1,555 26,740 241 22 York, PA.............. 165,868 -1,711 31,937 181 122 Berks, PA............. 165,261 -1,223 32,810 159 166 Richmond, VA.......... 165,016 -1,085 40,154 59 75 Stanislaus, CA........ 164,370 3,511 29,523 213 37 Genesee, MI........... 160,137 -5,317 36,030 104 237 Arlington, VA......... 159,394 675 55,310 9 35 Madison, AL........... 156,248 2,093 37,071 93 112 Dakota, MN............ 155,560 1,823 35,701 109 71 Lancaster, NE......... 148,264 1,445 29,353 219 145 Sarasota, FL.......... 147,207 6,361 29,029 225 194 Norfolk, VA........... 146,428 1,162 33,501 142 62 Adams, CO............. 146,002 780 34,760 120 64 Will, IL.............. 145,434 -2 34,305 131 6 Sangamon, IL.......... 145,150 227 36,265 100 49 Seminole, FL.......... 144,830 2,757 31,923 182 108 Nueces, TX............ 143,502 1,032 29,403 216 51 Utah, UT.............. 143,443 731 28,275 235 215 Leon, FL.............. 142,865 1,191 30,267 207 106 Brown, WI............. 142,499 57 32,500 166 140 Volusia, FL........... 142,479 -327 26,093 244 66 Luzerne, PA........... 141,927 -1,202 28,918 228 91 Atlantic, NJ.......... 141,207 1,218 32,476 167 43 Greene, MO............ 140,823 -1,142 28,077 236 57 Winnebago, IL......... 139,862 -4,156 31,943 179 212 Lane, OR.............. 137,593 -2,712 28,976 227 74 Hinds, MS............. 134,373 -1,097 31,135 191 199 Westmoreland, PA...... 134,151 -510 28,831 229 148 Clackamas, OR......... 133,961 -255 33,706 139 90 Ocean, NJ............. 133,758 4,846 31,028 192 196 Anchorage, AK......... 133,521 3,650 37,826 82 124 Tulare, CA............ 133,055 156 24,706 246 54 Howard, MD............ 132,944 1,667 40,184 58 9 Rockingham, NH........ 130,880 875 36,648 96 173 Montgomery, AL........ 130,029 -1,069 29,948 212 98 Erie, PA.............. 128,905 -3,019 29,290 222 121 Marion, OR............ 126,945 -844 28,779 231 170 Butler, OH............ 126,865 -699 32,325 170 163 St. Joseph, IN........ 125,006 -3,939 30,773 199 80 New London, CT........ 124,732 1,989 38,201 77 70 Chatham, GA........... 122,798 -33 30,522 203 152 Cumberland, PA........ 122,668 -752 33,997 134 104 Denton, TX............ 122,572 1,171 30,785 198 25 Larimer, CO........... 121,870 2,775 33,249 148 162 Solano, CA............ 121,474 3,638 33,470 143 17 Escambia, FL.......... 121,382 1,033 28,594 233 3 Caddo, LA............. 120,858 1,576 29,409 215 177 Orange, NY............ 120,792 674 30,225 208 147 Linn, IA.............. 119,995 -1,988 34,672 124 201 Lafayette, LA......... 119,308 5,147 32,359 168 1 Alachua, FL........... 119,079 788 26,915 239 150 Jefferson, TX......... 118,762 -2,349 32,565 164 61 Manatee, FL........... 118,697 5,800 26,629 242 48 Lubbock, TX........... 118,029 2,410 26,581 243 221 Spartanburg, SC....... 117,177 -2,745 31,849 183 59 Kalamazoo, MI......... 116,589 -2,112 33,926 137 86 Placer, CA............ 116,002 6,532 34,672 123 77 Ottawa, MI............ 115,781 -3,080 32,249 172 223 Clayton, GA........... 115,028 -264 38,309 76 53 Clark, WA............. 114,686 2,362 33,122 151 155 Elkhart, IN........... 113,550 -8,293 30,797 197 208 Dutchess, NY.......... 112,973 2,844 38,744 70 2 Marin, CA............. 111,897 1,389 43,548 39 175 Kanawha, WV........... 111,594 -854 31,581 187 36 Cameron, TX........... 111,359 2,278 22,146 249 159 Collier, FL........... 110,220 6,153 30,842 195 151 Anoka, MN............. 109,494 -376 34,588 125 195 Vanderburgh, IN....... 109,416 105 30,495 205 134 Mahoning, OH.......... 109,005 -3,979 26,852 240 115 Oneida, NY............ 108,714 -1,912 28,361 234 73 Chesterfield, VA...... 107,700 -111 32,953 154 117 Rockland, NY.......... 107,229 258 38,745 69 69 Minnehaha, SD......... 106,718 1,193 29,203 223 111 Cumberland, NC........ 106,260 -3,189 26,993 238 114 Buncombe, NC.......... 105,196 -475 28,714 232 89 Richmond, GA.......... 104,867 -784 29,399 217 156 Lorain, OH............ 103,115 -3,705 32,190 175 229 Peoria, IL............ 102,799 -1,839 33,276 147 8 Santa Cruz, CA........ 102,676 882 35,023 115 241 Shawnee, KS........... 100,528 318 30,503 204 83 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. The 248 U.S. counties comprise 66.2 percent of the total covered workers in the U.S. 2 Includes areas not officially designated as counties. See Technical Note. 3 Data are preliminary. 4 Net changes were computed from annual employment data adjusted for noneconomic county reclassifications. See Technical Note.