The Current Employment Statistics (CES) survey,

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1 Busness Brths and Deaths Impact of busness brths and deaths n the payroll survey The CES probablty-based sample redesgn accounts for most busness brth employment through the mputaton of busness deaths, wth the remanng porton estmated by a net brth/death model Krk Mueller Krk Mueller s a supervsory statstcan n the Dvson of Current Employment Statstcs, Bureau of Labor Statstcs. E-mal: mueller.krk@bls.gov The Current Employment Statstcs (CES) survey, conducted by the Bureau of Labor Statstcs (BLS), s a monthly survey of more than 4, busness establshments. The CES program provdes estmates on employment, hours, and earnngs by ndustry detal for the Naton, States, and metropoltan areas. The CES s wdely consdered one of the most tmely and accurate economc ndcators publshed by the Federal Government. The CES sample-based employment estmates for March of each year are benchmarked, or reanchored, annually to the March unverse count derved prncpally from the Quarterly Census of Employment and Wages (QCEW) program. These QCEW populaton counts are much less tmely than sample-based estmates and are used to provde an annual pont-n-tme census for employment. For natonal seres, only the March sample-based estmates are replaced wth the populaton counts. BLS completed a comprehensve redesgn of the CES sample n 23, changng the survey from a quota-based sample to a probablty-based sample. 2 The probablty-based sample redesgn addressed one of the major lmtatons of the prevous quotabased sample: the absence of a method to drectly measure new busness brths. The new probablty-based sample accounts for most busness brth employment through the mputaton of busness deaths, wth the remanng porton estmated by a net brth/death model that calculates the effect of the mputaton, measures the mputaton error, and generates a forecast of ths error to adjust the current estmate. Wth the ntroducton of the redesgn, many questons have arsen wth respect to the new model-based estmaton of the net of brths and deaths. Ths artcle dscusses the underlyng assumptons of the model and the ratonale behnd them. It also dscusses the reasons why the total accountng for busness brths s cyclcally senstve, n spte of the use of the forecast net brth/ death values. Lastly, t draws comparsons between the bas adjustment model of the quota sample desgn and the net brth/death model of the probablty sample desgn. The models dffer n the porton of the populaton that they are meant to measure. Probablty sample desgn From ts ncepton n the 93s untl the redesgn, the payroll survey was collected as a quota-based sample. A bas adjustment model was used to account for the employment movement each month not captured by the sample, ncludng employment growth because of the brth of new establshments. Over tme, both nternal and external revews of the CES program concluded that a probabltybased sample would beneft the program by ntroducng a more standard survey desgn and decreasng the relance of model-based adjustments. After several years of research, BLS began n June 2 to mplement n the CES a probablty-based sample, phased n by ndustry. Ths process was 28 Monthly Labor Revew May 26

2 completed wth the 22 benchmark release n June 23, when the last ndustry was converted to a probablty bass. Durng the redesgn phase n perod, BLS conducted producton tests of the new sample desgn and made parallel estmates each year for ndustres pror to ther offcal mplementaton wth the subsequent benchmark. The new survey desgn ncludes both the new sample composton and the use of a two-step process to account for the employment assocated wth busness brths. Ths process frst mputes a porton of the brth employment from the employment assocated wth busness deaths. The second step models the hstorcal dfference between the mputaton and the actual relatonshp between busness brth and busness death employments; ths step s referred to as the net brth/death model. The establshments that make up the populaton of nterest for the CES can be broken up nto three segments relatve to a benchmark month. Those segments are ) establshments that contnue to employ workers after the benchmark, 2) establshments that go out-of-busness after the benchmark, and 3) establshments that begn to employ workers after the benchmark. Wth the probablty sample mplementaton, the entre populaton of establshments that are n busness n the benchmark month s approprately represented for the perod from whch the sample s selected. As a result, the sample accounts for the frst two segments establshments that are contnung n nature and establshments that go out of busness. The populaton employment for these unts s moved forward through the use of weghted lnk relatve estmaton. If t s assumed that there s lttle dfference n the response rates between the contnung unts n the sample and the unts that go out of busness n the sample, then the monthly estmate based on the establshments n the sample should approprately capture the employment movements wthn these two segments of the unverse of establshments. (The accuracy of the assumpton of smlar response rates s addressed later n the artcle.) Accountng for the thrd segment establshments that are brths stll requres addtonal steps. To understand how the employment estmates are moved forward wth the weghted lnk relatve, t s necessary to consder the form of the estmator. The basc formula for estmatng all employees s: c = p ( w aec, ) ( ) w aep, where ÂE c = estmate of all employees for the current month ÂE p = estmate of all employees for the prevous month = the -th sample unt w = the weght for the -th sample unt ae c, = -th sample unt that reports for the current month ae p, = -th sample unt that reports for the prevous month The estmator requres that the busness reports data for both the prevous and current months f ts data are to be used. Ths s referred to as a matched sample. Ths estmator uses the trend n the matched sample to move the prevous month s estmated employment forward. As mentoned prevously, the thrd segment of the CES populaton of nterest s establshments that open after the benchmark, or busness brths. Lke many establshment surveys, the CES has dffculty wth obtanng and developng a tmely sample frame for busness brths. Ths s because a lag exsts between an establshment openng for busness and ts appearance on the unverse frame, where t would be avalable for samplng. Ths lag currently s about 7 months. In contrast, the lag from the reference month to the CES frst publcaton of the employment estmates for that reference month s 3 weeks. Absent a sample, some form of modelng of ths employment s necessary to account for the busness brths and ther assocated employment growth. Early research assocated wth the redesgn efforts ndcated a strong relatonshp between the employment assocated wth busness brths and that assocated wth busness deaths. Ths relatonshp can be seen n the Busness Employment Dynamcs (BED) data when a comparson s made between the employment assocated wth quarterly busness openngs and that assocated wth quarterly busness closngs. 3 (See chart.) The prmary dfference between the BED data and the CES concepts s that the BED data track brths over a quarter. The brth employment relevant to the CES s the employment assocated wth brths snce the last benchmark. Imputaton of deaths As was mentoned earler, the probablty sample wth the weghted lnk relatve estmator wll accurately represent the movement of the populaton. However, as a practcal matter, unts that have gone out of busness generally do not report ther data for the month n whch they go out of busness. There are two prmary reasons. Frst, the CES s a voluntary survey and not all frms respond. Second, companes by defnton have no employees once they are out of busness, and there may be no one to report ther data. 4 As a result, these unreported sample events are not ncluded n the calculaton of the weghted lnk relatve and are counter to the assumpton dscussed earler that there were no large dfferences between the response rates of contnuous unts and those that go out of busness. Monthly Labor Revew May 26 29

3 Chart. Mllons Prvate sector components of gross job gans and gross job losses, Busness Employment Dynamcs data, September 992 June 25, seasonally adjusted Mllons Expansons Contractons Contractons Openngs Openngs Closngs To resolve ths, a rather ntensve followup wth all nonresponders would be requred each month to attempt to dstngush between nonrespondents and busness deaths. Even f ths could be accomplshed successfully, a model would stll be needed for all of the employment assocated wth busness brths. Instead, BLS decded to use the underlyng relatonshp between busness brth employment and busness death employment that was descrbed n the prevous secton to at least partally account for the employment assocated wth busness brths. Rather than dentfyng all the deaths for the estmaton process, the logc s adjusted to exclude all busness deaths from the sample lnk. Deaths that are nonrespondents are automatcally excluded from the matched sample as they have no current month data, and establshments that report that they are out of busness are treated as nonrespondents for the current month and are also excluded from the lnk. As a result, the lnk calculaton s based solely on contnung unts. Whle ths frst step accounts for a large porton of the brth employment, t does not account for t all. To understand what s occurrng wth ths frst step, t s helpful to break down the estmaton process. Conceptually, the prevous month s employment can be broken nto two parts: ) the prevous month s employment for frms that contnued to employ workers n the current month, and 2) the prevous month s employment for frms that go out of busness, that s report zero employment, n the current month. Next, consder the applcaton of the weghted current-to-prevous month employment rato for sample unts to the prevous month employment level for each of the two peces. Ths weghted rato s the same used n the weghted lnk relatve estmator. The employment at establshments that employed workers the pror month and contnue to employ workers durng the current month s moved forward by the lnk of the contnuous sample unts. Applyng the lnk of the contnuous unts to the employment assocated wth busness deaths effectvely mputes a level of brth employment and the growth of prevous brths for the current month. Based on the relatonshp shown n the BED data, ths mputaton should account for a large porton of the busness brth employment. The degree to whch ths mputaton s dfferent from the brth employment s left to be modeled and represents the second step n the accountng for busness brth employment. Modelng resdual brth employment The busness brth employment not accounted for by the mputaton of busness deaths n the sample s modeled as an AutoRegressve Intergrated Movng Average (ARIMA) tme 3 Monthly Labor Revew May 26

4 seres. 5 Ths model s referred to as the net brth/death model. The Bureau s Longtudnal Database (LDB) s the bass for developng the hstorcal relatonshp to be modeled. The LDB lnks establshments over tme, whch allows for the dentfcaton of the contnuous establshments, establshments that go out of busness, and brths of establshments. To develop the hstory for modelng, the same handlng of busness deaths as descrbed for the CES sample data s appled to the populaton data. Establshments that go out of busness have employment mputed for them based on the rate of change of the contnuous unts. The employment assocated wth contnuous unts and the employment mputed from deaths are summed. The dfference s compared wth the actual populaton level to create the seres modeled by the brth/ death models. 6 To date, the resdual net brth/death component has shown to be a relatvely stable porton of the populaton employment regardless of the pont n the busness cycle. Ths may seem counterntutve untl the mpact of the mputaton of the busness deaths s consdered n more detal. However, the BED data show that the majorty of the employment change n the populaton s explaned by changes n the contnung unts rather than the relatonshp between the employment assocated wth busness brths and that assocated wth busness deaths. Furthermore, the BED brth/death relatonshp s somewhat cyclcal lke the contnuous unt populaton. The CES applcaton of ths relatonshp takes a step further wth the applcaton of the contnuous unt lnk to the employment assocated wth busness deaths. Ths mputaton of employment from busness deaths does not provde an exact one-toone relatonshp between employment from establshment brths and deaths; rather, t s dependant upon the movement of the contnuous unts. To complete the estmaton formula for the entre populaton, a net brth/death value must be added to the weghted lnk relatve descrbed earler. The fnal formula s as follows: c = p Cyclcal senstvty ( w aec, ) ( ) w aep, + net brth/death The total busness brth employment s accounted for by both the mputaton of busness deaths and the net brth/death value. Whle the net brth/death value s a fxed, projected value, the mputaton of deaths s dependent upon current sample nformaton. The mpact of the mputaton s best seen n the followng seres of examples. (See table.) For the examples, assume that there s full response assocated wth the sample. Ths allows for the evaluaton of the mputaton process, wthout the complcaton of nonresponse. In these examples, the sample s broken down to llustrate the mpact of the mputaton of busness deaths and the estmate of total busness brth employment. For each of these examples, assume that the prevous month s employment level s 2, and the net brth/death factor for the cell s. In each of the examples, a table shows the prevous month reported employment for each sample reporter n column, the current month reported employment for each sample reporter n column 2, the sample weght for each sample reporter n column 3, the prevous month weghted employment (weght tmes the prevous month employment) for each sample reporter n column 4, and the current month weghted employment (weght tmes the current month employment) for each sample reporter n column 5. The last two rows n each table show the weghted prevous and current month employment totals for the sample both ncludng the sample member that went out-of-busness and excludng the sample member. For each example, three calculatons are computed. ) An estmate ncludng the sample member that goes out of busness (report zero employment) 2) An estmate excludng the sample member that goes out of busness (ths estmate s the CES estmate based upon the exstng estmaton algorthm) 3) A calculaton of the employment assocated wth the mputaton of busness deaths (t s the dfference between the two estmates lsted above) The dfferences n the total brth employments n the three examples llustrate the mpact of the mputaton of busness deaths. They also ndcate that the total accountng for busness brth employment s senstve to current busness cycle nformaton. The frst example provdes a case where the contnuous unts are relatvely flat. (See table, example a.) Applyng the lnk relatve estmaton formula wth the sample death ncluded results n an employment estmate of (2,*7,59./7,84.9) = 9,36. Applyng the lnk relatve estmaton formula wth the sample death excluded results n an employment estmate of (2,*7,59./ 7,52.) = 2,235. In ths case, the mputaton of the death added 875 n employment assocated wth busness brths. In the second example, the contnuous unts are expandng. (See table, example b.) Applyng the weghted lnk relatve estmaton formula wth the sample death ncluded results n an employment estmate of (2,*8,425.4/ 7,84.9) = 2,49. Applyng the weghted lnk relatve estmaton formula wth the sample death excluded results n Monthly Labor Revew May 26 3

5 Table. Example a: contnuous unts are relatvely flat Prevous month sample employment Current month sample employment Sample weght Prevous month weghted employment Current month weghted employment ,72. 2, ,2., ,84.9 7, , ,59. Example b: contnuous unts are growng ,72. 2, ,2., ,84.9 8, , ,425.4 Example c: contnuous unts are declnng ,72. 2, ,2., ,84.9 7, , ,54.56 Total wth busness death ncluded. 2 Total wthout busness death ncluded. an employment estmate of (2,*8,425.4/7,52.) = 22,462. In ths case, the mputaton of the death added 97 n busness brth employment. In the last example, the contnuous unts are contractng. (See table, example c.) Applyng the lnk relatve estmaton formula wth the sample death ncluded results n an employment estmate of (2,*7,54.56/7,84.9) = 7,994. Applyng the lnk relatve estmaton formula wth the sample death excluded results n an employment estmate of (2,*7,54.56/7,52.) = 8,87. In ths case, the mputaton of the death added 83 n employment. In other words, the employment level from the mputaton dffers dependng upon the movement of the contnuous sample. Ths s mportant when consderng how the CES ac- 32 Monthly Labor Revew May 26

6 counts for busness brths and ther employment. Whle the net brth/death fgure s a forecasted value, there s current nformaton beng used through the mputaton of busness deaths. As a result, there s senstvty to current economc condtons n the assumptons for accountng for busness brth employment. If each of these examples s changed to assume that there are sample nonrespondents, then the total amount of brth employment accounted for by each example s mputaton s a lower bound for the total brths employment n the populaton. Ths s because some of the nonrespondents may be deaths wth employment mputed for them. For the nonrespondents that are stll n busness, the lnk from contnuous unts s approprate. If some of the nonrespondents are out of busness, then n the estmaton process, they also have employment mputed for them. Bas adjustment vs. net brth/death Hstorcally, the CES has reled on modelng of some segment of the populaton to complete the most accurate and current employment pcture possble. Under the old quota-based desgn, whch was dscontnued n 23, ths modelng was referred to as bas adjustment. A comparson between the bas adjustment and the brth/death adjustment s frequently made by CES data users. However, there are several dstnctons between the two models. Both models account for the only nonsample-based adjustment to the CES estmates; however, the brth/death model s not smply an mproved bas adjustment model. Bas adjustment was a total error correcton model that was used to account for several defcences n the quota sample ncludng a nonrandom sample and response errors. As a result, the bas adjustment models were drectly drven by revsons to the estmates wth the prevous benchmark and assumed all error and varablty n the estmate should be corrected by the model. Under the current probablty-based desgn of the CES survey, only the busness brths are not drectly accounted for through the sample desgn. The resdual net brth/death model can have error assocated wth t that s not drectly ted to benchmark revsons. The model values are affected by defned portons of the populaton busness brths and busness deaths. Benchmark revsons can be attrbutable to nonresponse error, reportng error, sample error or smple sample varablty, and the error assocated wth the modelng for the net of brths and deaths. Wth the new desgn, each of these components can be examned separately and corrected as the need arses. As a result, t s possble for net brth/death factors to ncrease n ndustres wth downward benchmark revsons or n ndustres wth upward revsons. The bas model and the brth/death model are expected to capture dfferent portons of the populaton movement and, under the current survey, more of the populaton movement s captured over tme through the sample and less s captured through modelng. Wth the ntroducton of the new desgn, parallel estmates were made for a 2-month perod n each dvson. Offcal quota-based estmates and the probabltybased estmates performed smlarly; however, generally less brth/death adjustment was appled to the probablty estmates than was appled by the bas adjustment model used wth the quota-based sample. (See table 2.) Brth/death model performance Wth the full converson of the CES sample to a probablty and NAICS bass, an analyss of the performance of the brth/ death model aganst populaton data can be performed wth the refttng of the models each year. Whle benchmark revsons have been small n recent years, t s possble that the small revsons could be a result of offsettng errors wthn the CES-estmaton process rather than the qualty of the brth/ death model. An examnaton of the forecasted net brth/ death factors compared wth the actual net of busness brths and deaths shows that the two dd not dffer greatly for the Aprl 22 March 24 perod at the total prvate level. (See chart 2.) Table 2. Bas and brth/death factors for parallel estmaton perods Industry Industry mplemented 2-month bas total 2-month brth/death total Mnng... June 2 8, Constructon... June 2 44, 9, Manufacturng... June 2 96, 7, Wholesale trade... June 2 53, 37, Retal trade... June 22 22, 87, Transportaton and publc utltes... June 22 9, 23, Fnance, nsurance, and real estate... June 22 25, 9, NOTE: Servces estmates were not produced n parallel because of the converson to NAICS n June 23. Monthly Labor Revew May 26 33

7 Chart 2. Total prvate forecasted versus actual net of busness brths and deaths, not seasonally adjusted, Aprl 22 March 24 Employment (n thousands) Forecasted Forecasted net of busness brths and deaths Actual net of busness brths and deaths Employment (n thousands) Aprl July October January Aprl July October January Addtonal research The complete accountng of busness brth employment does contan a cyclcal component that results from the mputaton process, and analyss of both the benchmark revsons and the comparsons of the brth/death factors wth populaton data ndcates that the mputaton and model combnaton are performng well. However, there are no varables n the net brth/death model that provde nformaton that s more current than the most recent benchmark. Future research wth respect to the brth/death model wll nvolve the examnaton of varables that can be ncorporated on a concurrent or lagged bass. These varables may provde more recent nformaton than what s currently present n the model. Notes The Bureau s unemployment nsurance ( UI) unverse count s a quarterly tabulaton, from admnstratve records, of the number of employees covered by unemployment nsurance laws. UI unverse counts, avalable on a lagged bass, contan ndvdual employer records for more than 8 mllon establshments and cover a lttle more than 97 percent of total nonfarm employment; they thus provde a benchmark for the sample-based estmates. For the small segment of the populaton not covered by UI, BLS develops employment benchmarks from several alternatve sources. More nformaton on benchmarkng of the CES estmates can be found on the Internet at 2 A probablty-based sample s selected through a random process, and the probabltes of selecton are known for each unt n the populaton. A quota-based sample s derved through a samplng process that s repeated, untl a mnmum respondng sample, or quota, s obtaned for each characterstc of nterest. Detals on the mplementaton of the CES redesgn are avalable n an artcle by Sharon Strfas, Revsons to the Current Employment Statstcs Natonal Estmates Effectve May 23, Employment and Earnngs, June 23, pp The Busness Employment Dynamcs data are a set of statstcs generated from the Quarterly Census of Employment and Wages, or ES 22, program. These quarterly data seres consst of gross job gans and gross job losses statstcs from 992 forward. These data help to provde a pcture of the dynamc state of the labor market. More nformaton on the Busness Employment Dynamcs data can be found on the Internet at / 4 Exceptons occur when all workstes are reported n ether an aggregate sngle report or to the Electronc Data Interchange Center; then the locaton gong out-of-busness s reported. 5 ARIMA modelng uses lags and shfts n the hstorcal data to uncover patterns, such as movng averages and seasonalty. 6 More detaled techncal model descrptons have been publshed n the Statstcal Proceedngs of the Amercan Statstcal Assocaton and are avalable on the Internet at st29.htm. 34 Monthly Labor Revew May 26