QCEW Supporting Statement B (1220-0012)

Supporting Statement

Employment, Wages, and Contributions Report (QCEW Program)

B. COLLECTION OF DATA EMPLOYING STATISTICAL METHODS

1a. Universe

The universe of respondents to the U.S. Bureau of Labor Statistics (BLS) for the Quarterly Census of Employment and Wages (QCEW) are the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. The ultimate source of data for these 53 entities is the Quarterly Contribution Reports (QCR) submitted to State Workforce Agencies (SWAs) by employers subject to State Unemployment Insurance (UI) laws. The QCEW data, which are compiled for each calendar quarter, provide a comprehensive business name and address file with employment and wage information by industry, at the six-digit North American Industry Classification System (NAICS) level, and at the national, State, Metropolitan Statistical Area (MSA), and county levels for employers subject to State UI laws. Similar data for Federal Government employees covered by the Unemployment Compensation for Federal Employees program (UCFE) also are included.

The QCEW program provides a virtual census of nonagricultural employees and their wages, with about 55 percent of the workers in agriculture covered as well. As shown in Table 1 in June 2010, the number of covered private business establishments (worksites) is about 8.71 million, and the number of covered employment is about 107.28 million. Additionally, about 67,000 Federal Government, 67,000 State government, and 164,000 local government establishments are covered. In June 2010, the total number of covered establishments is about 9.01 million, and the total number of covered employment is about 129.37 million. The QCEW series has broad economic significance in measuring labor trends and major industry developments, in time series analyses and industry comparisons, and in special studies, such as analyses of establishments, employment, and wages by size of establishment.

The BLS role in the QCEW program is to establish and enforce uniform methods and processes that yield a consistent level of data quality for the multifaceted uses of QCEW data. The BLS role is to take in raw UI administrative data, to understand error components, to address each with methods and processes to reduce resulting error, and to yield high quality economic data and sample frame. The improvement processes include but are not limited to: efficiency in data collection from large multi-establishment employers through Electronic Data Interchange (EDI); statistically valid procedures for editing, estimating missing reports and data elements, record linkage and standardized processing systems, training of staff; and quality controls procedures for data review (see Sections 2b and 2c on estimation procedures and reliability for details). After the data have gone through extensive review at the State, regional, and national levels, the BLS summarizes these data to produce totals for all counties, MSAs, the States, and the Nation by various industrial levels.

1b. Sample

The QCEW is a census of establishments; hence, every unit is in the sample and represents itself only. That is, each unit has a sampling weight of 1.00.

2a. Sample Design

The QCEW is a census. The sample design for the QCEW is very simple since all establishments are included with a sampling weight of 1.00 or with certainty. The sampling unit is the establishment or worksite.

2b. Estimation Procedure

The aggregated totals of employment and wages for each sub-domain (e.g., industry, geography, and size) are simply the sum of the micro records belonging to that sub-domain. Averages and other statistics for each sub-domain are derived by performing the appropriate arithmetic functions.

As mentioned above, the BLS role is to add quality to the raw data. One of these processes involves editing the data and conducting validation checks. The basic monthly employment edit consists of a six-step statistical test that includes the use of multiple t-test for: month-to-month change, over-the-year change, and a 12-month variation in data; some tests are conducted on levels while others are conducted on rate of change. The wage edit includes the use of an inter-quartile test developed by Hoaglin, Iglewicz, and Tukey. The Edit Conditions and Formulas are described in Appendix-F of the QCEW Operating Manual (2007).

Although the BLS receives the QCEW files from all 53 entities in a timely manner, the files contain estimates for late and missing respondents. Therefore, a step in the data process is estimation for late respondents and for missing respondents (i.e., unit non-response) and data elements (i.e., item non-response). As shown in Table 2a, about five percent of the establishments respond late or fail to respond to the QCEW in a timely manner; the corresponding figure for employment is about three percent as shown in Table 2b. The non-response rates for wages are about four percent as shown in Table 2c.

The current method of imputation applies the missing establishment a-year-ago change to the previous month’s employment or quarterly wages to estimate the current month’s employment or quarterly wages. That is, missing establishment current month’s employment is equal to the previous month’s employment multiplied by its a-year-ago change; similar procedure is applied to estimate total quarterly wages. A drawback to this procedure is that it uses a-year-ago trend rather than the current trend. The current Imputation Formulas are described in Chapter 8 and Appendix-J of the QCEW Operating Manual.

The BLS conducted extensive research on alternative imputation methods for both employment and wages. The findings of the research indicate the use of current trends of the reported data from similar cells as non–respondents. The BLS defines this procedure as the ratio method. Where, the ratio of a particular estimation cell is computed as the sum of current month’s reported employment divided by the sum of previous month’s reported employment. To impute this month’s employment for a non-respondent, the ratio is then multiplied by the non-respondent’s previous month employment. A similar procedure is applied to impute average quarterly wages. This ratio method of imputation will be implemented in the new QCEW processing system. The details of the method including various exceptions are available in Attachment-1.

Another data processing step is to link the QCEW data across quarters for various purposes including: 1) editing and imputation; 2) separation of establishments into new establishments (openings or births), continuous establishments (existing businesses), and out-of-business establishments (closings or deaths); and 3) longitudinal research. The BLS has employed the Felligi and Sunter record linkage methodology. See the paper by Kenneth Robertson, et al. (1997).

2c. Reliability

Since the QCEW is a census, the data are only subject to non-sampling errors. To control for these non-sampling errors, the BLS has extensive quality control procedures that include: 1) improved data collection methods especially for large multi-establishment employers through EDI; 2) standardized data processing systems that include edits, imputation, record linkages including address standardization and industrial classification coding; and 3) standardized training of staff at State, regional, and national levels in the review of data according to the guidelines provided by the QCEW policy council and stated in official memorandums (available upon request). Records that fail these edits are individually reviewed. Respondent contact is frequently used to validate significant movements or to correct the data.

The three most important initiatives undertaken by the BLS to enhance the quality of QCEW data are the establishment of the Multiple Worksites Report (MWR) Survey, the Annual Re-filing Survey (ARS), and the development of a new comprehensive processing system for States use. Two separate OMB clearances are obtained for the ARS and MWRSurvey. The MWR form is sent quarterly to multi-establishment employers for the purpose of asking them to break out their consolidated reports to the establishment level. For example, some employers provide data for all of their operations within a State or at the county level; the MWR asks the employer to provide information for each establishment so that all records on the file can be at the establishment level, which is generally the sampling unit for most BLS surveys. This also improves the quality of local economic data by more accurately reporting the location and type of economic activity.

The ARS is conducted annually on about one-fourth of the establishments on the frame for the purpose of updating the industrial classification, business name, reporting and physical location addresses, and auxiliary status. These establishments are selected randomly. State and regional staff are trained extensively in the industrial classification coding. Additionally, standardized systems are provided to the State and regions to process the data.

Among other things, the new State processing system will have improved data editing, imputation, and record linkage procedures.

2d. Revisions

For the first quarter of each year, QCEW data are published five times; the original data are first released in October of the same year followed by revisions in January, April, July, and October of the following year. For example, March 2009 data were first published in October 2009, then in January, April, July, and October of 2010. The 2^nd quarter data is published four times; the 3^rd quarter data is published three times; and the 4^th quarter data is published twice. Table 3a provides data for the initial publication of each quarter in 2009 to their final publication in October 2010. As shown in Table 3b, the largest revision generally occurs from initial publication to the first revision, as missing reports, including out-of-business reports, for late responding employers come in. The magnitude of revisions is relatively small; that is, less than 0.05 percentage point.

2e. Specialized Procedures

None.

2f. Data Collection Cycles

The QCEW program is quarterly, as the employers are required to file Quarterly Contribution reports (UI reports) on a quarterly basis.

3. Methods to Maximize Response Rates

Since employers are required to file Quarterly Contributions Reports under the UI law for each State, the response rates are generally very high. The unit response rates for employment are about 95 percent (Table 2a) and about 96 percent (Table 2c) for wages as reporting of wages are required by UI law. The response rates based on total covered employment are about 97 percent (Table 2b), as the non-response is mostly concentrated among the small establishments.

Growth of EDI, the direct transfer of data from the firm to the BLS, also provides a high level of response and stability. The BLS currently collects over 80,000 reports from nearly 100 large firms with about 10 million employees via EDI. For final estimates, virtually all of these firms provide data.

4. Tests

The BLS has undertaken several new initiatives in the area of research on control and measurement of non-sampling error. The 1991 benchmark of Current Employment Statistics Survey’s (CES) estimate of employment to the QCEW revealed a substantial non-sampling error problem caused by payroll processing firms. The American Statistical Association formed a committee to review BLS procedures and issued a report in January 1994 (American Statistical Association, 1994). The BLS has adopted most of the report’s recommendations. The BLS also has conducted a Response Analysis Survey of Payroll Processing Firms (Goldenberg, Moore, and Rosen, 1994). The purpose of the survey was to identify practices that can affect the data collected by the CES and QCEW programs (the benchmark source data) and educate payroll processors on proper reporting procedures. The BLS also has conducted a Response Analysis Survey (RAS) of CES and QCEW covering employment reporting (Werking, Clayton, and Rosen, 1995). The survey identified factors affecting both CES and QCEW reporting within the same firm. Based on these RAS studies, the BLS has undertaken an extensive education program with CES respondents. This includes highlighting correct reporting of problem items on the CES report form and the inclusion of special notices on correct reporting on the monthly advance notice fax message. A new RAS was conducted in 2008; an Executive Summary of the report detailing new findings is in Attachment 2.

5. Statistical and Analytical Responsibility

Ms. Shail Butani, Chief, Statistical Methods Division of the Office of Employment and Unemployment Statistics, is responsible for the statistical aspects of the QCEW program. Ms. Butani can be reached on 202-691-6347. As mentioned in the above paragraph, the BLS seeks consultation with other outside experts on an as needed basis. The QCEW Policy Council, composed of ten representatives of the SWAs and BLS staff, has been consulted on the content, uses, and methodology of the program.

6. References

American Statistical Association (1994). "A Research Agenda to Guide and Improve the Current Employment Statistics Survey." American Statistical Association Panel for the Bureau of Labor Statistics' Current Employment Statistics Survey, January, 1994. Alexandria, VA: American Statistical Association (available upon request).

Bureau of Labor Statistics. BLS Handbook of Methods Chapter 5: Employment and Wages Covered by Unemployment Insurance. Washington DC: Bureau of Labor Statistics, 2004, p.42-47.

http://www.bls.gov/opub/hom/pdf/homch5.pdf

http://www.bls.gov/opub/hom/homch5_d.htm

Bureau of Labor Statistics. Official memorandums to the States and Regional staff on QCEW program (available upon request).

David C. Hoaglin, Boris Iglewicz, John W Tukey (1996). "Performance of Some Resistant Rules for Outlier Labeling." Journal of the American Statistical Association, Vol. 81 No. 396. (Dec., 1986), pp 991-999.

http://www.jstor.org/stable/2289073

Edit Conditions and Formulas. Appendix-F QCEW Operating Manual (2007). Bureau of Labor Statistics, Washington, DC-20212 (available on CD).

Fellegi, I. P. and Sunter, A. B. (1969). A theory for record Linkage, Journal of the American Statistical Association, 64, 1183-1210.

http://www.jstor.org/stable/2286061

Goldenberg, Karen L., Susan E. Moore, and Richard J. Rosen (1994), "Commercial Payroll Software and the Quality of Employment Data." Proceedings of the Survey Research Methods Section, American Statistical Association, 13-18 August, 1994. Toronto: American Statistical Association, 1994.

http://www.amstat.org/sections/SRMS/Proceedings/papers/1994_178.pdf

Imputation Formulas. Chapter 8 and Appendix J, QCEW Operating Manual (2007). Bureau of Labor Statistics, Washington, DC-20212 (available on CD).

Kenneth Robertson, Larry Huff, Gordon Mikkelson, Timothy Pivetz, and Alice Winkler (1997). “Improvement in Record Linkage Processes for the Bureau of Labor Statistics’ Business Establishment List.” In Record Linkage Techniques (1997). Proceedings of an International Workshop and Exposition. Edited by; Wendy Alvey and Bettye Jamerson, Federal Committee on Statistical Methodology, Office of Management and Budget, Washington, DC.

http://www.fcsm.gov/working-papers/robertson.pdf

Werking, George S., Richard L. Clayton, and Richard J. Rosen (1995). "Studying the Causes of Employment Count Differences Reported in Two BLS Programs." Proceedings of the Survey Research Methods Section, American Statistical Association, 13-17 August, 1995. Orlando: American Statistical Association, 1995.

http://www.amstat.org/sections/SRMS/Proceedings/papers/1995_137.pdf

Table 1--QCEW summary data for 50 States, D.C., Puerto Rico, and Virgin Island on NAICS basis
(April, May, June  2010, in thousands)
Description	No. of Establishments	Employment Apr-10	Employment May-10	Employment Jun-10
Total	9,010	127,749	129,141	129,372
Total Private	8,712	105,529	106,434	107,283
Agriculture, forestry, fishing and hunting	95	1,105	1,199	1,283
Mining	31	635	645	657
Utilities	17	551	552	554
Construction	801	5,432	5,549	5,657
Manufacturing	344	11,401	11,462	11,549
Wholesale trade	616	5,440	5,469	5,493
Retail Trade	1,028	14,274	14,401	14,495
Transportation and Warehousing	216	3,901	3,931	3,946
Information	144	2,694	2,703	2,724
Finance and insurance	469	5,469	5,472	5,492
Real estate and rental and leasing	352	1,910	1,923	1,948
Professional, Scientific and  Technical Services	1,019	7,492	7,372	7,419
Management of companies and enterprises	52	1,849	1,850	1,861
Administrative and support and waste management services	468	7,272	7,431	7,520
Educational services	93	2,547	2,516	2,401
Health care and social assistance	794	16,124	16,183	16,188
Arts, entertainment, and recreation	125	1,882	1,987	2,136
Accommodation and food services	620	11,069	11,260	11,383
Other services, except public administration	1,246	4,331	4,367	4,405
Unclassified	181	151	161	169
Federal Government	67	2,997	3,415	3,214
State Government	67	4,669	4,654	4,583
Local Government	164	14,554	14,638	14,292

Table 2a. U.S. Percentage of  imputed establishments by year and month
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2001	6.02	6.03	6.06	5.78	5.78	5.87	5.08	5.10	5.13	5.03	5.06	5.10
2002	5.57	5.58	5.58	5.11	5.11	5.18	4.99	4.99	5.04	4.71	4.75	4.79
2003	6.20	6.22	6.22	5.53	5.50	5.58	5.21	5.21	5.23	5.46	5.48	5.54
2004	5.93	5.93	5.93	5.78	5.75	5.88	5.43	5.42	5.55	5.28	5.30	5.40
2005	5.61	5.63	5.70	5.06	5.04	5.21	5.17	5.19	5.20	4.58	4.64	4.73
2006	5.91	5.93	5.96	4.87	4.83	4.93	4.82	4.91	4.95	4.37	4.48	4.52
2007	5.08	5.23	5.25	4.50	4.62	4.70	4.29	4.31	4.37	4.08	4.11	4.19
2008	5.28	5.25	5.31	4.12	4.10	4.24	4.12	4.11	4.18	3.75	3.80	3.92
2009	4.86	4.88	4.97	4.06	4.03	4.15	3.62	3.62	3.70	3.52	3.54	3.70
2010	4.72	4.73	4.75	4.72	4.72	4.91
Table 2b. U.S. Percentage of imputed employment by year and month
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2001	5.59	5.59	5.57	5.27	5.24	5.22	4.92	4.92	5.02	5.17	5.17	5.18
2002	4.87	4.86	4.85	4.71	4.69	4.66	5.05	5.07	5.16	4.78	4.77	4.76
2003	5.39	5.39	5.38	4.98	4.96	4.9	5.16	5.17	5.22	5.12	5.12	5.12
2004	4.97	4.96	4.94	5.45	5.43	5.33	5.95	5.96	6.06	5.04	5.04	5.03
2005	4.69	4.69	4.68	4.72	4.71	4.61	4.52	4.57	4.60	4.32	4.31	4.30
2006	4.24	4.24	4.22	3.60	3.58	3.54	3.82	3.82	3.91	3.75	3.75	3.76
2007	3.75	3.75	3.74	3.47	3.46	3.42	3.60	3.61	3.70	3.31	3.31	3.31
2008	3.47	3.47	3.47	3.11	3.10	3.08	3.21	3.22	3.30	2.92	2.92	2.92
2009	3.63	3.65	3.66	2.79	2.76	2.73	2.86	2.88	2.95	2.68	2.67	2.67
2010	3.15	3.15	3.13	3.08	3.06	3.04

Note: Table 2a, 2b and 2c are for total private establishments only. It excludes Puerto Rico, Virgin Islands and households.

Table 2c: Percentage of imputed wage units by year and quarter
Year/qtr	ImputedUnits	Total Units	%of imputed units
2009Q1	316,316	8,417,511	3.76
2009Q2	242,934	8,375,322	2.90
2009Q3	225,212	8,360,108	2.69
2009Q4	208,507	8,363,063	2.49
2010Q1	290,355	8,312,057	3.49
2010Q2	309,752	8,304,066	3.73

Table 3a: Revisions in published data, U.S. total

March 2009 (October 2009 release)

March 2009 (January 2010 Release)

March 2009 (April 2010 Release)

March 2009 (July 2010 Release)

March 2009 (October 2010 Release)

Total

Revision

First

Second

Third

Fourth

(since

revision

revision

revision

revision

October 2009)

128,992,170

128,935,247

128,927,469

128,923,128

128,928,399

-56,923

-7,778

-4,341

5,271

-63,771

June 2009 (January 2010 Release)

June 2009 (April 2010 Release)

June 2009 (July 2010 Release)

June 2009 (October 2010 Release)

Revision

First

Second

Third

since

revision

revision

revision

January '2010

129,674,842

129,644,468

129,636,842

129,648,129

-30,374

-7,626

11,287

-26,713

September 2009 (April 2010 Release)

September 2009 (July 2010 Release)

September 2009 (October 2010 Release)

Revision

First

Second

since

revision

revision

April '2010

128,088,742

128,117,140

128,129,562

28,398

12,422

40,820

December 2009 (July 2010 Release)

December 2009 (Oct-2010 Release

First

revision

128,334,933

128,312,441

-22,492

Table 3b: Percentage of revision from original to next publication

Preliminary Publication

March 2009 (January 2010 release)

June 2009 (April 2010 release)

September 2009 (July 2010 release)

December 2009 (October 2010 release)

%Revision from preliminary published data

-0.0441

-0.0234

0.0222

-0.0175

Table 3c: Percentage of revision from original to final publication

Preliminary Publication

March 2009 (October 2010 release)

June 2009 (October 20100 release)

September 2009 (October 2010 release)

December 2009 (October 2010 release)

%Revision from preliminary published data

-0.0494

-0.0206

0.0319

-0.0175

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