IMPLEMENTATION OF THE CURRENT EMPLOYMENT STATISTICS REDESIGN:

DATA COLLECTION

Richard L. Clayton, Bureau of Labor Statistics

2 Massachusetts Avenue, NE, Suite 4840, Washington, D.C. 20212

Key Words: CASIC, Employment, Redesign,

Touchtone Data Entry

I. Introduction

The Current Employment Statistics (CES) survey

is undergoing a complete redesign. Since its inception,

over 50 years ago, the CES has been a panel survey.

The CES Redesign (CES-R) is instituting a probability

sample design, see Werking (1997). The new sample

design holds new challenges for the data collection

activity of the survey. This paper profiles the existing

and planned data collection environment and discusses

the major issues involved in implementing the new

sample design.

II. The Current Employment Statistics (CES)

Survey

The CES is an ongoing monthly survey of about

390,000 non-agricultural establishments. The CES

preliminary estimates, released on the first Friday of

each month, which receive vast media coverage, are

considered among the most influential data series for

economic policy purposes, and are a driving force

behind the financial markets. For over 50 years, the

CES has been conducted in a cooperative Federal-State

system under which BLS provides specifications and

methodology which are implemented by the States.

States have solicited new respondents, collected and

edited the monthly data and made the State and MSA

estimates. The same edited microdata are transmitted

to BLS for compilation into the national estimates.

The data collection environment allows only about 2

weeks to collect data before the preliminary estimates.

Existing Data Collection Environment

For most of the history of the CES, data collection

was conducted via a mailed form shuttled between each

of the States and respondents. The form provides 12

blank rows for each month of the year. Each month,

the respondents fills in the 5 to 6 data items and mails

the completed form to the state for key entry, editing.

The form was then returned to the respondent for the

next month.

This process, while simple, yielded very low

response rate for preliminary estimates, about 50%,

which lead to frequent, and often large, revisions to the

preliminary estimates. To address this problem, the

CES has invested heavily in the automation of data

collection since 1984 to address long-standing

problems of slow reporting and high costs.

The CES is well-suited for CASIC methods

because it has a very short collection period (between 2

to 2.5 weeks) and collects a small number (5 or 6) of

numeric, commonly available payroll-related data

items. Since 1982, the CES staff has researched and

implemented Computer Assisted Telephone

Interviewing (CATI), Computer Assisted Personal

Interviewing (CAPI), Touchtone Data Entry (TDE),

Voice Recognition (VR), and Electronic Data

Interchange (EDI) as replacements for traditional mail

collection, see Werking and Clayton 1995 for a

complete description of these methods and their role in

changing CES data collection. At this writing, about

250,000 respondents reported monthly using TDE with

thousands more in transition. The largest, multi-unit

companies report through EDI. Under this array of

methods, the average response rates for preliminary

estimates have been raised by 20 percentage points and

the average monthly revisions to the preliminary

estimates have been reduced by 38 percent.

Over the ensuing 15 years, the CES has developed

a dynamic collection scheme incorporating CATI,

TDE, FAX, EDI. The basic approach was to convert

mail respondents to CATI for a short period. During

the CATI collection period, usually 6 months,

interviewers educated respondents on the importance

of the CES, its timeliness requirements and reviewed

data quality definitions. Then, respondents were

converted to the most appropriate ongoing collection

mode. Over 90 percent of respondents are converted to

TDE, about 7 percent to FAX and the remaining were

returned to mail reporting if no automated method was

acceptable. This mixed mode system raised response

rates for the preliminary estimates from about 50

percent to 80 percent for the treated units. Revisions to

the preliminary estimates were reduced by 39

percentage points.

Each of the automated methods represented a

separate set of systems and procedures, targeting

different sample groups based on the number of

reports, the available technology and their willingness.
III. Profile of Old and New CES

Sampling Unit - UI versus Individual Location:

Under the old CES, sample units were generally

individual business locations. Under the CES-R, the

sampling unit is an individual Unemployment

Insurance (UI) number. Every employer covered by UI

must apply for a UI number from the respective state.

Employers can retain a UI number for the life of their

business or sometimes they will find it useful or

necessary to change their UI. Common reasons for

changing UI numbers are to incorporate, in

acquisitions of other businesses, or other changes in

ownership, such as adding “& sons”. Each such

change presents challenges for data collection.

Specific rules have been designed for the range of

known UI changes. Interviewers are trained in

tracking down a knowledgeable respondent. However,

often our respondent does not know their UI number,

the scope of the business or other information

regarding the UI system. This severely complicates

the interaction and our ability to correctly identify and

track the UI numbers selected for the sample.

Implications of the UI as a Sampling Unit: The

UI number as a sampling unit poses significant

challenges for data collection. The most difficult is

identifying and capturing the creation of a new

expansion unit and the surge of employment in a new

location. Thus, it is crucial to immediately identify the

existence of the new location. Only if the new site can

be readily identified upon opening its doors, or even

earlier for hiring and training, can the CES hope to

accurately capture the new employment and thus depict

the turning points in the economy.

The timely and accurate capture of the new unit,

under any collection mode, is based on the

respondents’ actual knowledge of the event. We

cannot assume that our respondents, typically payroll

clerks, know about every opening, especially in large

multi-unit firms.

It is important to note that the CES estimates are

benchmarked annually to the entire universe count

derived from the UI system. The quarterly UI filing

process includes 3 monthly employment figures. The

total of these figures across the US provides a universe

count of UI covered employment. This annual event

can also result in significant revision to the level of

employment. One method of reducing such differences

is to obtain the monthly CES data from the same

respondents. Thus, the enrolling interviewers are

targeting the UI respondent as the likely best sources of

consistent monthly data. In a previous study (targeting

units which some differences between CES and UI

data), we have determined that existing CES

respondents are the UI reporters in about 50% of the

cases.

Under CATI, interviewers can ask each

respondent each month whether a new unit was

opened, its employment and insure that the new

location is actually under the selected UI number. As

already mentioned, many respondents have this

knowledge, but some do not.

Importance of Expansion Units: There are two

major sources of employment growth in the economy;

business births and the expansion of existing

businesses (Getz, et al, 1997). Capturing new births

will be handled by direct solicitation of new UI

accounts or by modeling. As for capturing the

expansion of business expansion, there are two sources

of expansion. First, individual locations can grow.

This growth is relatively easy to capture for units

participating in the survey. As they grow, their

employment figures reflect this growth.

Second and much more difficult, is the expansion

of businesses into new locations. The new employment

created at the new location must be captured in the first

month it is opened, or even earlier if hiring and

training precede its opening. Thus, the data collection

environment must specifically focus attention to the

monthly potential of each sampled business, as a

selected UI number, to add new units. Just because a

business has not added units in months or years does

not preclude it from expanding in any particular

month. It is estimated that 1.5% of existing units open

a new location in any single month.

Identifying and Collecting Expansion Units:

Each of the CES collection modes must allow for the

timely capture of new units. Each method has

strengths and weaknesses in this regard. It is

important to maximize the effectiveness of each of the

modes to avoid a bias due to the ability or inability to

capture new units. Under CATI, interviewers must

simply ask whether new units, under the targeted UI,

have opened or whether new units are being planned.

Also, when editing for increases in employment,

respondents should be asked whether there the increase

is due to new units.

TDE reporting presents the most difficult

environment. The TDE script will be expanded asking

each unit each month whether a new unit was added,

or closed. The recorded answer (1 for yes, 0 for no)

will cause an interviewer to initiate a call to verify that

the new unit is in the same states as the parent UI

number, is under a CES-R sample UI number (and

thus is in the same state as the UI number), and

actually has employment. Since the strength of TDE is
very inexpensive data collection, the addition of these

follow-up calls may dramatically change the costeffectiveness of this method. We will strive to find

ways to improve the cost effectiveness of this feature,

such as automating these follow-up questions or only

asking the “expansion unit questions” of a subsample

of units.

WWW reporting (Clayton and Werking, 1998) is

well-suited to this task, or virtually any other special

task. Its interactive properties will allow prompting of

respondents each month and on-line follow up

questions. EDI is the best suited for capturing new

locations. The data files received via EDI usually

contain records for all units under that business, thus

new locations tend to automatically be included.

We expect a few residual units reporting by mail.

Again, forms will be modified to accommodate these

additional questions, and positive responses will cause

telephone follow-up to categorize the special events at

the business.

Reporting Level: The level at which a

respondent agrees to report also plays into our ability to

capture new expansion units. Multi unit reporters can

agree to participate in the CES for all of their

individual locations under the targeted UI(s) either

individually or at some aggregated level, such as a

county or state level. Such aggregations not only

reduce reporting burden and costs, but help insure that

new expansion units are automatically captured in the

report. State wide reporting may adversely affect the

accuracy of the MSA estimates in that the new

employment may not be accurately attributed to the

correct county and thus the MSA. Currently, about 4

percent of CES units are reported at either the countywide or state-wide level.

When initially solicited or enrolled in the CES,

interviewers will have to balance reporting burden,

costs and the willingness of respondents to provide

potentially large amounts of data if there are many

individual locations.

Solicitation: The solicitation or enrollment

function has traditionally been the domain of each of

the states. Under the CES-R, BLS will conduct

enrollment through the production tess, about the first

18 months of implementation. Thus, BLS had to

develop and test enrollment methods for the first time.

CATI is used as the primary solicitation vehicle.

CATI will be used for a period of a few, generally 6

months until the timeliness of monthly data reporting

is well established, the maximum number of data items

have been obtained and the respondent is fully aware of

the CES and its role in the national economic is welllinked to monthly publications and the media uses. A

two year test of methods of methods was conducted

with the assistance of the University of Michigan

Center for Survey Methods. These tests lead to some

significant improvements to the original enrollment

methodology. The implementation of the CES-R will

continue to include ongoing research capabilities

including both Michigan and Westat.

Ongoing Collection: Based on the technology

available to the respondent, the number of reports and

respondent preferences, ongoing collection will be

either by TDE, FAX, mail or EDI. For ongoing

collection, attrition reduction will be essential. The

basic TDE non-response prompting methods involving

carefully timed fax and postcard prompts will likely be

enlarged to include targeted CATI prompts for cases

meeting predictive criteria for likely attrition.

Conclusion: The CES Redesign poses significant

challenges to the existing series of available data

collection modes and procedures. Changes to

sampling unit, a variety of collection vehicles and the

increased rigor implicit in probability sampling has

caused a complete review of existing methods,

including a complete re-engineering of the existing

processes, including systems, forms, and each

opportunity for respondent contact. Based on the wide

array of collection modes available and features

available by integrating the strengths of each, the

redesigned CES will remain a state of the art collection

environment.

References:

Getz, P., Kropf, J, and Strifas, S. (1997), Measuring

the Contribution of Business Births and Deaths to

Overall Employment Movements, ASA Proceedings of

the Section on Survey Research Methods, in print.

Stamas, G., Levin, K., Cantor, D, and Goldenberg, K.

(1997) Sampling For Employment at New

Establishments in a Monthly Business Survey, ASA

Proceedings of the Section on Survey Research

Methods, in print.

Clayton, R., and Werking, G., “Business Surveys of

the Future: The World Wide Web as a Data

Collection Methodology”, Monograph for International

Conference on Computer Assisted Survey Information

Collection, San Antonio, Texas, December 1996.

Clayton, R., and Werking, G. (1995) “Automated

Telephone Methods for Business Surveys,” Business

Survey Methods, New York: Wiley, pp 317-337.

Werking, George S. (1997), “Overview Of the CES

Redesign”, Proceedings of the Section on Survey
Research Methods, American Statistical Association,

in print.