Eleven of Ohio’s 13 large counties reported employment increases from March 2013 to March 2014, the U.S. Bureau of Labor Statistics reported today. (Large counties are defined as those with employment of 75,000 or more as measured by 2013 annual average employment.) Warren County had the largest gain, up 4.1 percent, followed by Butler County, 2.4 percent; and Franklin County, 1.9 percent. Regional Commissioner Charlene Peiffer noted that the employment increases in the other eight large counties in Ohio were less than the national increase.

Nationally, employment advanced 1.7 percent from March 2013 to March 2014 as 281 of the 339 largest U.S. counties registered increases. Weld County, Colo., recorded the largest percentage increase in the country, up 7.5 percent over the year. Peoria, Ill., registered the largest percentage employment decline, down 2.6 percent.

Among the 13 largest counties in Ohio, employment was highest in Cuyahoga County (696,500) in March 2014, followed by Franklin County (686,600). Four other counties—Hamilton (489,700), Summit (255,400), Montgomery (241,800), and Lucas (201,200)—had employment levels of more than 200,000. Collectively, Ohio's 13 large counties accounted for 65.2 percent of total employment within the state. Nationwide, the 339 largest counties made up 72.0 percent of total U.S. employment.

The average weekly wage in Franklin County rose 4.1 percent from the first quarter of 2013 to the first quarter of 2014, the largest increase among Ohio's large counties. Delaware County had the highest average weekly wage at $1,123, followed by Hamilton ($1,116) and Cuyahoga ($1,054). (See table 1.) Nationally, the average weekly wage rose 3.8 percent over the year to $1,027 in the first quarter of 2014.

Employment and wage levels (but not over-the-year changes) are also available for the 75 counties in Ohio with employment below 75,000. All of Ohio’s smaller counties had average weekly wages below the national average of $1,027. (See table 2.)

Large county wage changes

Four of Ohio’s large counties recorded wage growth greater than or equal to the national increase of 3.8 percent from the first quarter of 2013 to the first quarter of 2014. (See table 1.) As noted, Franklin County experienced the state’s largest average weekly wage increase of 4.1 percent, ranking 72nd in the nation. Cuyahoga and Delaware Counties both experienced wage growth of 4.0 percent, ranking 73rd. Summit County’s increase matched the nation and placed 84th. All four of these counties were in the top quartile for wage increase nationwide.

Nationally, 323 of the 339 largest counties registered over-the-year wage increases. Chester, Pa., had the largest wage gain, up 13.9 percent from the first quarter of 2013. New York, N.Y., was second with a wage increase of 12.0 percent, followed by the counties of Forsyth, N.C., and San Mateo, Calif. (both up 9.6 percent).

Among the nation’s 339 largest counties, 15 experienced over-the-year wage decreases. Benton, Ark., had the largest percentage decrease in average weekly wages, with a loss of 3.2 percent. Cumberland, N.C., had the second largest wage decline (-2.0 percent), followed by Dutchess, N.Y. (-1.6 percent), Ocean, N.J. (-1.3 percent), and McLean, Ill. (-1.0 percent).

Large county average weekly wages

Average weekly wages in 3 of Ohio’s 13 large counties were above the national average of $1,027 in the first quarter of 2014. As noted, Delaware County ($1,123) had the highest average weekly wage in the state and ranked 60th nationwide. This was followed by Hamilton ($1,116) and Cuyahoga ($1,054) Counties which ranked 64th and 81st, respectively, among the nation’s 339 large counties. Mahoning County ($686) reported the lowest average weekly wage among Ohio’s large counties and ranked 329th nationwide.

In the first quarter of 2014, nearly three-fourths of the largest U.S. counties (244) reported wages below the national weekly average of $1,027. Horry County, S.C., reported the lowest wage ($571), followed by the Texas counties of Cameron ($581) and Hidalgo ($597).

Among the nation’s 339 largest counties, 95 registered weekly wages above the U.S. average. New York, N.Y., held the top position with an average weekly wage of $2,749, more than four times the wage levels in the three lowest-paid counties. Santa Clara, Calif., was second-highest at $2,074 per week, followed by the counties of San Mateo, Calif. ($2,058) and Somerset, N.J. ($2,048).

Average weekly wages in Ohio's smaller counties

All 75 counties in Ohio with employment below 75,000 had average weekly wages lower than the national average of $1,027. Among these smaller counties, Union County had the highest average weekly wage at $1,020 and Meigs County had the lowest at $541. (See table 2.)

When all 88 counties in Ohio were considered, all but 3 had wages below the national average of $1,027. Two reported average weekly wages below $600, 16 reported wages from $600 to $649, 21 reported wages from $650 to $699, 16 reported wages from $700 to $749, and 33 reported wages of $750 or more. (See chart 1.)

Additional statistics and other information

QCEW data for states have been included in this release in table 3 For additional information about quarterly employment and wages data, please read the Technical Note or visit www.bls.gov/cew/.

Employment and Wages Annual Averages Online features comprehensive information by detailed industry on establishments, employment, and wages for the nation and all states. The 2013 edition of this publication contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the fourth quarter 2013 version of the news release. Tables and additional content from Employment and Wages Annual Averages 2013 are now available online at https://www.bls.gov/cew/publications/employment-and-wages-annual-averages/2013/home.htm.

Information in this release will be made available to sensory impaired individuals upon request. Voice phone: 202-691-5200; Federal Relay Service: 1-800-877-8339.

Technical Note

Average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and total pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The 9.4 million employer reports cover 134.6 million full- and part-time workers. The average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels of those covered by UI programs. The result is then divided by 13, the number of weeks in a quarter. It is to be noted, therefore, that over-the-year wage changes for geographic areas may reflect shifts in the composition of employment by industry, occupation, and such other factors as hours of work. Thus, wages may vary among counties, metropolitan areas, or states for reasons other than changes in the average wage level. Data for all states, Metropolitan Statistical Areas (MSAs), counties, and the nation are available on the BLS Web site at www.bls.gov/cew/; however, data in QCEW press releases have been revised (see Technical Note below) and may not match the data contained on the Bureau’s Web site.

QCEW data are not designed as a time series. QCEW data are simply the sums of individual establishment records reflecting the number of establishments that exist in a county or industry at a point in time. Establishments can move in or out of a county or industry for a number of reasons–some reflecting economic events, others reflecting administrative changes.

The preliminary QCEW data presented in this release may differ from data released by the individual states as well as from the data presented on the BLS Web site. These potential differences result from the states’ continuing receipt, review and editing of UI data over time. On the other hand, differences between data in this release and the data found on the BLS Web site are the result of adjustments made to improve over-the-year comparisons. Specifically, these adjustments account for administrative (noneconomic) changes such as a correction to a previously reported location or industry classification. Adjusting for these administrative changes allows users to more accurately assess changes of an economic nature (such as a firm moving from one county to another or changing its primary economic activity) over a 12-month period. Currently, adjusted data are available only from BLS press releases.

Table 1. Covered employment and wages in the United States and the 13 largest counties in Ohio, first quarter 2014

Area	Employment			Average weekly wage (1)
	March 2014 (thousands)	Percent change, March 2013-14 (2)	National ranking by percent change (3)	Average weekly wage	National ranking by level (3)	Percent change, first quarter 2013-14 (2)	National ranking by percent change (3)
United States (4)	134,555.0	1.7	--	$1,027	--	3.8	--
Ohio	5,071.5	1.3	--	909	24	2.8	32
Butler, Ohio	140.1	2.4	97	872	192	2.7	159
Cuyahoga, Ohio	696.5	0.0	282	1,054	81	4.0	73
Delaware, Ohio	79.6	0.4	260	1,123	60	4.0	73
Franklin, Ohio	686.6	1.9	128	1,024	97	4.1	72
Hamilton, Ohio	489.7	1.2	177	1,116	64	0.8	296
Lake, Ohio	92.2	-0.3	297	824	245	0.2	319
Lorain, Ohio	93.4	0.6	238	807	259	1.9	224
Lucas, Ohio	201.2	1.4	162	867	198	2.0	215
Mahoning, Ohio	95.9	0.4	260	686	329	2.5	174
Montgomery, Ohio	241.8	0.9	207	854	219	2.2	199
Stark, Ohio	155.1	0.9	207	751	306	2.2	199
Summit, Ohio	255.4	1.5	153	926	154	3.8	84
Warren, Ohio	80.1	4.1	25	862	208	2.7	159
Footnotes: (1) Average weekly wages were calculated using unrounded data. (2) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. (3) Ranking does not include data for Puerto Rico or the Virgin Islands. (4) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
NOTE: Covered employment and wages includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. Data are preliminary.