June 12, Mike Horrigan Associate Commissioner Office of Employment and Unemployment Statistics

Transcription

1 C2ER - 55 TH ANNUAL CONFERENCE AND LMI INSTITUTE ANNUAL FORUM June 12, 2015 Mike Horrigan Associate Commissioner Office of Employment and Unemployment Statistics 1

2 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 2

3 Budget One of our major challenges is the budget: In FY 2013, sequestration required the difficult decision to eliminate some BLS products and programs: Measuring Green Jobs products Mass Layoff Statistics (MLS) program International Labor Comparisons (ILC) program In FY 2014 BLS curtailed QCEW and Export Price Indexes were defunded. 3

4 Budget In the FY 2015 Budget enacted by BLS, $592.2 million in funding to BLS. The funding level is $17.9 million below the FY 2015 President s Budget request. If funding is similarly constrained in FY 2016, the BLS will be forced to consider programmatic reductions or eliminations. 4

5 Budget FY 2016 President s Budget proposes $632.7 million in funding for the BLS--an increase of $40.5 million over the FY 2015 final enacted level: Includes new proposal for enhancements to the Job Openings and Labor Turnover Survey in order to improve JOLTS Timeliness, precision, and relevance Annual supplement to CPS to collect info relevant to labor force trends Modify Consumer Expenditure Survey to support the Census Bureau s development of a supplemental statistical poverty measure Restore funding for the International Price Program (IPP) Export Price Indexes. 5

6 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 6

7 Measuring the demand for a skilled workforce Measuring the training needs of the U.S. workforce is of critical importance to the entire labor market information system, including ETA, state Workforce Boards, state LMI shops, economic development and education to name a few BLS projections methodology and data have been an important input to measuring the demand for skilled workers In recent years, however, the BLS projections methods have received a lot of criticism from the Georgetown Center on Education for the Workforce 7

8 Table 2. Employment by educational requirement, 2012 and projected 2022 Education Employment Projected change Doctoral or professional Number Percent 4, , Master s 2, , Bachelor s 26, , , Associate s 5, , , Postsecondary nondegree Some college, no degree High school or equivalent Less than high school 8, , , , , , , , , , , Total 145, , ,

9 What we do and what we don t do For 2012, if you add the top five educational levels (Postsecondary nondegree award to Doctoral or professional degree), total employment in these occupations that generally require these levels of education for entry represents 32.3% of total jobs If you apply this same methodology to the projected number of jobs, which we do not endorse, you get 42.3% of the projected number of jobs is in occupations generally requiring education levels ranging from Postsecondary nondegree award to Doctoral or Professional degree 9

10 What we do and what we don t do BLS offers career advice for entry into occupations, we are not measuring the demand for skills by educational requirement For example, consider an occupation that the BLS classifies as requiring an Associates degree, such as Licensed Practical Nurse. Not all hiring by employers will be at the Associate degree level. The demand for skills within the occupation may result in a mixture of hires across the education spectrum BLS reevaluates the entry requirements of occupations every two years to keep the advice we provide current with changing labor market conditions 10

11 Georgetown Center on Education and the Workforce - criticisms of BLS BLS single assignment of education/training categories ignores the heterogeneity of education/training within occupations We agree, but that is not our objective The education/training categories should not be used to project how many jobs will require various levels of education and training We agree, and we don t, but we make it very tempting 11

12 Georgetown Center on Education and the Workforce (CEW) In their June 2010 report, the CEW concludes: By 2018, our forecasts shows that the economy will create 46.8 million openings Nearly two-thirds of these 46.8 million jobs some 63 percent will require workers with at least some college education. 12

13 Results from the Minnesota Vacancy Survey The latest evidence comes from the state Job Vacancy Survey, released in March (2015). The data show that since 2009, the share of the state s openings that require more than a high school education has dropped from 44 percent to 38 percent. 13

14 Who is right Hine,, has analyzed the BLS educational requirement data by comparing it with employer responses on what level of training their openings require. In contrast to Carnevale, he found the BLS classifications accurate 75 percent of the time. Milwaukee Star Tribune, April 27, 2015 Note that this analysis applies to current, not projected openings And note that jobs requiring a high school diploma or equivalent as advertised may in fact be filled by those with higher levels of education 14

15 What is the truth? This leads to the criticism of the CEW method, the so-called Ph.D. taxi cab driver problem The CEW has told BLS they are going to look at wage differentials within occupations to try to separate out the demand for different levels of education and training If there are small or no wage differentials by education (for entrants), the lower level of educational requirement may be appropriate Very promising approach 15

16 Why this is important and what is needed? Directing significant amounts of resources to the provision of training requires strong theoretical and empirical foundations for the measurement of employers demand for skills BLS is criticized for what it does not do We need to take a hard look at what we can do to inform the debate 16

17 Measuring in-demand occupations Attempt to resolve the debate on the basis of direct statistical evidence. My hypothesis is that this is a classic stock/flow problem Flows into and out of entry level positions requiring high school or less may be far greater and of shorter duration than similar flows for entrants into jobs with higher education requirements I plan to use CPS gross flows data to see if this is true and if the differing flow rates can be consistent with actual observed stocks over time 17

18 Measuring in-demand occupations Define education/training levels associated with prime age workers BLS provides advice on entry into an occupation but it may be useful to add advice on career pathways Examine new CPS data on certification and training Unlock the black box of some college Examine earnings differentials of new entrants by educational attainment 18

19 Measuring in-demand OES Time Series occupations Comparative static analysis of changes in employment and real wages over time Define in-demand ( hot ) occupations based on pre-defined thresholds for employment increases and real wage increases In a time series, these thresholds could be based on growth rates in employment and real wages over several years 19

20 An equilibrium wage/employment approach This approach focuses on strong labor markets in which we observe rising real wages and either positive employment growth or non-declining growth Real wages C A B S D D Employment 20

21 OES time series A true time series, not just year-to-year comparisons, defined down to the MSA level, will provide significant insight into the demand for skills Another benefit of OES time series is that it will provide better statistical basis for change factors in projections models OES time series will provide an important complement connecting actual short-term trends and long-term projections 21

22 Webscraping job postings Currently BLS is beginning research to learn about the nature and quality of on-line job postings Can webscraping methods be used to trace changing skill requirements of job postings How do distributions of job openings by industry (using unduplicated on-line data sets) compare to JOLTS data We have also begun discussions with NASWA to explore the use of National Labor Exchange data and with the Conference Board to use their Help- Wanted OnLine data to explore these issues 22

23 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 23

24 Autocoding Ask establishments to report two items, job title and wage, for each employee Can job titles be autocoded into the SOC with statistical reliability? Lower response burden on firms Role of states This is still a data collection enterprise Autocoding is not perfect, you still need to reconcile the harder cases 24

25 Autocoding Another advantage of occupation autocoding is that failures to code can help identify new and emerging occupations Point wage estimates are critical for the use of OES time series to more precisely identify in-demand occupations OES time series, autocoding, and point wage estimates all require strong IT systems I view this as an extremely high priority 25

26 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 26

27 A vision for the future - CES Consistency of benchmarking methodologies between National and State/Area CES Replacements versus Wedging back Improvements to the birth-death model On-going research Estimates by firm age and size class What is the point of reference for size class size at a beginning point or size at an ending point 27

28 A vision for the future - CES Estimation of domestic outsourcing Location of industry of placement of the temporary help industry Fissured work arrangements On call workers Temporary help workers Self employed contractors Lack of data on the changing mix of employerworker arrangements Potential effects on productivity and GDP growth estimates Potential value of a quick response survey capability 28

29 Total nonfarm employment Temporary help services employment Employment in temporary help services is considered a leading indicator for total nonfarm employment. However, one of the largest gaps in our data is not knowing the industry placement for workers in this industry. 142,000 4, ,000 3, ,000 Jan-08 3, ,000 2, ,000 Aug-06 2,400 Feb ,000 Total nonfarm 2,000 Temporary help services Aug ,000 1,600 Jan-03 Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Bureau of Labor Statistics, Current Employment Statisitics survey, May 08, Shaded area represents recession as denoted by the National Bureau of Economic Research. Most recent 2 months of data are preliminary.

30 Drop in part-time due to slack work is driving the decline in involuntary part-time employment Numbers in thousands 10,000 9, CPS redesign 8,000 7,000 Total involuntary part time 6,000 5,000 4,000 3,000 Part time due to slack work 2,000 1,000 Could only find part time work NOTE: Shaded areas represent recessions as determined by the National Bureau of Economic Research (NBER). Beginning in 1994, data reflect the introduction of a major redesign of the Current Population Survey. Additional adjustments to population controls were incorporated into the data in January of various years. These changes can affect comparability with data for prior periods. SOURCE: Bureau of Labor Statistics, Current Population Survey, May 8,

31 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages (QCEW) factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 31

32 Factoryless goods production Factoryless Goods Producing (FGP) Outsources all the transformation steps but undertakes all the entrepreneurial steps and arranges for all required capital, labor, & material inputs required to make a good Global supply chains 2008 study by Dedrick, Kraemer, and Linden showed that the value added of assembly of Apple Ipods by China was $4 of the retail value of $299 Levi Jeans makes no jeans in the U.S. In the world of global supply chains are FGPs an establishment or enterprise concept? 32

33 Creating matched files with the QCEW I recently began a BLS wide team to look at opportunities to match BLS data sets to the QCEW to develop new, insightful products The recent publication of QCEW sample frame data on profit/nonprofit status using IRS data matched at the EIN level is a good example 33

34 Creating matched files with the QCEW Matching OES to QCEW has enormous potential Analysis of occupational staffing patterns of establishments by industry over the business cycle For example. which patterns were associated with strong employment growth coming out of the Great Recession? 34

35 Creating matched files with the QCEW Matching to non-bls data sets also has great potential Joint BLS/BEA research matching enterprises using BEA company data on Foreign Direct Investment Potential to match QCEW to the Customs Bureau sample frame on establishment receipt of export revenue Our early exploration into this project has convinced us of the importance of developing an enterprise frame from the QCEW 35

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37 Wage record pilot I have been incredibly impressed by the innovative work being done by states using wage records Labor shed analysis Impact of worker migration out of state after plant closing or completion of training WIC sponsored group on enhanced wage records led by Raj Jindal and Steve Saxon 37

38 Wage record pilot The states have faced the challenge that under current arrangements they do not have access to wage records from other states through the LEHD program This has led to efforts to create separate agreements between states to share data In a similar way, there have been various complexities in terms of allowing ETA and the DOL Chief Evaluation Office access to wage records for their analytical needs 38

39 Wage record pilot Recently, following the passage of WIOA, there has been a significant interest on the part of OMB, ETA, the DOL Chief Evaluation Office, BLS and the Department of Education to expand access to wage records to all parties, including allowing states that agree, to share data with each other Although multiple routes exist for providing access, such as through the Cooperative Agreements in the pilot, the primary route that is being explored in these conversations is to modify the existing LEHD agreements to create these sharing arrangements 39

40 Wage record pilot The wage record pilot that BLS hopes to conduct with 7 states is an idea that was discussed at the WIC meeting in Idaho Louisiana, Texas, Idaho, Oregon, Washington, Alaska and New Mexico The idea is to create a proof of concept on how to transmit large volumes of data from each state, how to store and process these large data files, and how to share these data back with states that agree to share their data 40

41 Wage record pilot What do participating states get out of this? Hopefully an easy way to share data for a variety of important labor market analyses such as labor shed analysis and labor migration impact studies What does BLS get out of this? The pilot has a concrete set of objectives in terms of understanding the complexities of transmission, storage, data cleaning, software requirements and resource needs 41

42 Wage record pilot What does BLS get out of this? Longer run I see three principle areas of benefit to BLS research, improving our existing data products, and the creation of new products Research - Churn in the JOLTS data, career pathways Improvements: LAUS estimates of unemployment duration, validation of hires and separations in JOLTS 42

43 Wage record pilot Creation of new products Greater detail by industry for hires and separations in JOLTS Development of industry replacement rates for Projections Development of wage distributions by industry 43

44 Outline BLS budget A vision for the future Measuring the demand for a skilled workforce Autocoding in the Occupational Employment Statistics (OES) Survey Current Employment Statistics (CES) Survey benchmarking, firm age and size, and domestic outsourcing Quarterly Census of Employment and Wages (QCEW) factoryless goods production, matching, and wage records Improvements to Local Area Unemployment Statistics and the Job Openings and Labor Turnover Survey 44

45 A vision for the future: LAUS Continued enhancements to our models The promise of PROMIS Lessons for storing wage records? Continuing to explore the potential of the PROMIS system 45

46 A vision for the future: JOLTS Release JOLTS data at the same time as monthly Employment Situation release of CES and national unemployment data Expand JOLTS sample size and coverage to include detailed geography (State) and industry (2-3 NAICS digit) 46

47 Contact Information Mike Horrigan Associate Commissioner Office of Employment and Unemployment Statistics