Job Openings and Labor Turnover Survey (JOLTS) jt.txt Section Listing 1. Survey Definition 2. FTP files listed in the survey directory 3. Time series, series file, data file, & mapping file definitions and relationships 4. Series file format and field definitions 5. Data file format and field definitions 6. Mapping file formats and field definitions 7. Data Element Dictionary ================================================================================ Section 1 ================================================================================ The following is a definition of: Job Openings and Labor Turnover Survey (JOLTS) Survey Description: The Job Openings and Labor Turnover Survey program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations. Unadjusted and seasonally adjusted levels and rates of all data elements are published by supersector and select sector based on the North American Industry Classification System (NAICS). These supersectors and select sectors include: mining and logging; construction; durable goods manufacturing; nondurable goods manufacturing; wholesale trade; retail trade; transportation, warehousing, and utilities; information; finance and insurance; real estate and rental and leasing; professional and business services; educational services; health care and social assistance; arts, entertainment, and recreation; accommodation and food services; other services; federal government; state and local government education; and state and local government, excluding education. Estimates are also available for four geographic regions (Northeast, Midwest, South, and West). The sample for the Job Openings and Labor Turnover Survey includes randomly selected nonfarm establishments such as factories, offices, and stores, as well as federal, state, and local government entities in the 50 states and the District of Columbia. The 16,000 establishments in the JOLTS survey are drawn from a universe of approximately nine million establishments compiled as part of the Quarterly Census of Employment and Wages, or ES-202, program. All data series are available from December 2000 to present on a monthly basis. Annual estimates are available for all industries for hires, quits, layoffs and discharges, other separations, and total separations. BLS seasonally adjusts series using the X-13-ARIMA-SEATS seasonal adjustment program. Seasonal adjustment is the process of estimating and removing periodic fluctuations caused by events such as weather, holidays, and the beginning and ending of the school year. Seasonal adjustment makes it easier to observe fundamental changes in the level of the series, particularly those associated with general economic expansions and contractions. A concurrent seasonal adjustment methodology is used in which new seasonal adjustment factors are calculated each month, using all relevant data, up to and including the data for the current month. JOLTS uses moving averages as seasonal filters in seasonal adjustment. JOLTS seasonal adjustment includes both additive and multiplicative seasonal adjustment models and REGARIMA (regression with auto-correlated errors) modeling to improve the seasonal adjustment factors at the beginning and end of the series and to detect and adjust for outliers in the series. All levels are published in thousands and all rates are published in percent to one decimal place. Special characteristics of the data are footnoted where necessary. Updating Schedule: First Closing estimates are usually available six weeks after the end of the reference month. At the same time, second closing estimates for the month prior to the reference month also are released. The month following the annual CES benchmark revision, all JOLTS pertinent estimates are retabulated. ================================================================================== Section 2 ================================================================================== The following Job Openings and Labor Turnover Survey files are on the BLS internet in the sub-directory pub/time.series/jt: jt.contacts - Contacts for JOLTS program jt.data.0.Current - Nine years of data plus year-to-date estimates jt.data.1.AllItems - All estimates jt.data.2.JobOpenings - Seasonally adjusted and Unadjusted, Job Openings levels and rates, 2000-present jt.data.3.Hires - Seasonally adjusted and Unadjusted, Hires levels and rates, 2000-present jt.data.4.TotalSeparations - Seasonally adjusted and Unadjusted, Total Separations levels and rates, 2000-present jt.data.5.Quits - Seasonally adjusted and Unadjusted, Quits levels and rates, 2000-present jt.data.6.LayoffsDischarges - Seasonally adjusted and Unadjusted, Layoffs and Discharges levels and rates, 2000-present jt.data.7.OtherSeparations - Seasonally adjusted and Unadjusted, Other Separations levels and rates, 2000-present jt.area - Metropolitan Statistical Area codes mapping file jt.dataelement - Data element codes mapping file jt.footnote - Footnote codes mapping file jt.industry - Industry codes mapping file jt.period - Period codes mapping file jt.ratelevel - Rate/Level codes mapping file jt.seasonal - Seasonality codes mapping file jt.sizeclass - Establishment size codes mapping file jt.state - State codes mapping file jt.series - Series codes jt.txt - General information ================================================================================= Section 3 ================================================================================= The definition of a time series, its relationship to and the interrelationship among series, data and mapping files is detailed below: A time series refers to a set of data observed over an extended period of time over consistent time intervals (i.e. monthly, quarterly, semi-annually, annually). BLS time series data are typically produced at monthly intervals and represent data ranging from a specific consumer item in a specific geographical area whose price is gathered monthly to a category of worker in a specific industry whose employment rate is being recorded monthly, etc. The FTP files are organized such that data users are provided with the following set of files to use in their efforts to interpret data files: a) a series file (only one series file per survey) b) mapping files c) data files The series file contains a set of codes which, together, compose a series identification code that serves to uniquely identify a single time series. Additionally, the series file also contains the following series-level information: a) the period and year corresponding to the first data observation b) the period and year corresponding to the most recent data observation. The mapping files are definition files that contain explanatory text descriptions that correspond to each of the various codes contained within each series identification code. The data file contains one line of data for each observation period pertaining to a specific time series. Each line contains a reference to the following: a) a series identification code b) year in which data is observed c) period for which data is observed (M13, Q05, and S03 indicate annual averages) d) value e) footnote code (if available) ================================================================================= Section 4 ================================================================================= File Structure and Format: The following represents the file format used to define jt.series. Note that the Field Numbers are for reference only; they do not exist in the database. Data files are in ASCII text format. Data elements are separated by spaces; the first record of each file contains the column headers for the data elements stored in each field. Each record ends with a new line character. Field #/Data Element Length Value(Example) 1. series_id 21 JTS000000000000000JOR 2. seasonal 1 S or U 3. industry_code 6 000000 4. state_code 2 00 5. area_code 5 00000 6. sizeclass_code 2 00 7. dataelement_code 2 JO 8. ratelevel_code 1 R 9. footnote_codes 10 Text 10. begin_year 4 2000 11. begin_period 3 M12 12. end_year 4 2020 13. end_period 3 M08 The series_id (JTS000000000000000JOR) can be broken out into: Code Value survey abbreviation = JT seasonal (code) = S industry_code = 000000 state_code = 00 area_code = 00000 sizeclass_code = 00 dataelement_code = JO ratelevel_code = R ================================================================================== Section 5 ================================================================================== File Structure and Format: The following represents the file format used to define each data file. Note that the field numbers are for reference only; they do not exist in the database. Data files are in ASCII text format. Data elements are separated by spaces; the first record of each file contains the column headers for the data elements stored in each field. Each record ends with a new line character. The jt.data file is partitioned into a number of separate files: See Section 2 The above-referenced data files have the following format: Field #/Data Element Length Value(Example) 1. series_id 21 JTS000000000000000JOR 2. year 4 2000 3. period 3 M12 4. value 12 4868 5. footnote_codes 10 It varies The series_id (JTS000000000000000JOR) can be broken out into: Code Value survey abbreviation = JT seasonal (code) = S industry_code = 000000 state_code = 00 area_code = 00000 sizeclass_code = 00 dataelement_code = JO ratelevel_code = R ================================================================================ Section 6 ================================================================================ File Structure and Format: The following represents the file format used to define each mapping file. Note that the field numbers are for reference only; they do not exist in the database. Mapping files are in ASCII text format. Data elements are separated by tabs; the first record of each file contains the column headers for the data elements stored in each field. Each record ends with a new line character. File Name: jt.area Field #/Data Element Length Value(Example) 1. area_code 5 00000 2. area_text 100 Text File Name: jt.dataelement Field #/Data Element Length Value(Example) 1. dataelement_code 2 JO 2. dataelement_text 100 Text File Name: jt.footnote Field #/Data Element Length Value(Example) 1. footnote_code 2 P 2. footnote_text 200 Text File Name: jt.industry Field #/Data Element Length Value(Example) 1. industry_code 6 000000 2. industry_text 100 Text File Name: jt.period Field #/Data Element Length Value(Example) 1. period 3 M01 2. period_abbr 5 JUN 3. period_name 20 Text File Name: jt.ratelevel Field #/Data Element Length Value(Example) 1. ratelevel_code 1 R 2. ratelevel_text 100 Text File Name: jt.seasonal Field #/Data Element Length Value(Example) 1. seasonal_code 2 S 2. seasonal_text 100 Text File Name: jt.sizeclass Field #/Data Element Length Value(Example) 1. sizeclass_code 2 00 2. sizeclass_text 100 Text File Name: jt.state Field #/Data Element Length Value(Example) 1. state_code 2 00 2. state_text 100 Text ========================================================================================= Section 7 ========================================================================================= JOB OPENINGS AND LABOR TURNOVER SURVEY (JOLTS) DATABASE ELEMENTS Data Element Length Value(Example) Description area_code 5 Ex: 00000 Code identifying Metropolitan Statistical Area. area_text 100 Text Description of Metropolitan Statistical Area. Ex: All areas begin_period 3 M01-M13 Identifies first data observation Q01-Q05 within the first year for which Ex: M06=June data is available for a given (M=Monthly, M13=Annual time series. Avg, Q=Quarterly, Q05= Annual Avg) begin_year 4 YYYY Identifies first year for which Ex: 2000 data is available for a given time series. dataelement_code 2 JO Code identifying type of data. dataelement_text 100 Text Description of type of data. Ex: Job Openings end_period 3 M01-M13 Identifies last data observation Q01-Q04 within the last year for which Ex: M06=June data is available for a given (M=Monthly, M13=Annual time series. Avg, Q=Quarterly, Q05= Annual Avg) end_year 4 YYYY Identifies last year for which Ex: 2019 data is available for a given time series. footnote_codes 10 It varies Identifies footnotes for the data series. footnote_text 100 Text Contains the text of the footnote. industry_code 6 000000 Code identifying industry. industry_text 100 Text Name of industry. Ex: Total nonfarm period_abbr 5 Period name Abbreviation of period name. abbreviation Ex: JUN period 3 M01-M13 Identifies period for which Q01-Q04 data are observed. Ex: M06=June (M=Monthly, M13=Annual Avg, Q=Quarterly, Q05= Annual Avg) period_text 20 Text Full name of period to which Ex: June the data observation refers. ratelevel_code 1 R Code identifying rate or level. ratelevel_text 100 Text Decription of ratelevel_code. Ex: Rate seasonal 1 S=Seasonally Code identifying whether the Adjusted data are seasonally adjusted. U=Unadjusted series_id 21 JTS000000000000000JOR Code identifying the specific series. sizeclass_code 2 Ex: 00 Code identifying size class. sizeclass_text 100 Text Description of size class. Ex: All size classes state_code 2 Ex: 00 Code identifying state or region. state_text 100 Text Description of state or region. Ex: Total US value 12 Ex: 103623 Data value for series. year 4 YYYY Identifies year of observation. Ex: 2000