Employment, Hours, and Earnings--National (EE) ee.txt ****************************************************************************************** SPECIAL NOTICE: The Current Employment Statistics program will publish National data on a North American Industry Classification System (NAICS) basis beginning with the release of May 2003 data in June 2003. With the release of May 2003 data, SIC-based data will no longer be produced or published. Please see http://www.bls.gov/ces/cesnaics.htm for further details. ****************************************************************************************** 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: EMPLOYMENT, HOURS, AND EARNINGS--NATIONAL (EE) Survey Description: The Current Employment Statistics Program provides employment, paid hours, and earnings information on a national basis in considerable industrial detail. The Bureau of Labor Statistics cooperates with State agencies in collecting data each month from a sample of establishments in all nonfarm activities including government. The data include series for total employment, number of women employed, number of production or nonsupervisory workers, average hourly earnings, average weekly hours, average weekly earnings, and average weekly overtime hours in manufacturing industries. A sample of about 375,000 employer units with over 40 percent of total payroll employment is utilized for this monthly mail survey. For hours and earnings of production or nonsupervisory workers in private, nonagricultural industries, the sample contains about 300,000 employer units. All employment, hours and earnings series are classified according to the 1987 Standard Industrial Classification (SIC). The industry code used in the survey corresponds to the SIC code, except in those cases where more than one SIC has been combined. Summary Data Available: For all employees, women, and production or nonsupervisory workers, over 1,600 published monthly employment series are available. The series for all employees include over 600 industries at various levels of aggregation. Over 1,750 published monthly series for production workers' average weekly earnings, average hourly earnings, average weekly hours, and, in manufacturing, average weekly overtime hours are available. Hours and earnings data are available for about 475 industries. Most series begin in 1947, 1958, 1972, 1982, or 1988, although some are available from 1909 to the present. Employment by industry division is available since 1919. For industry divisions and major groups, about 200 series of seasonally adjusted data are available. Over 100 special derivative series such as indexes and constant dollar series are also available. Frequency of Observations: Monthly in almost all cases; quarterly averages available for total employment, average weekly hours, and average overtime hours, seasonally adjusted (datatypes 81, 82, and 83). Annual Averages: Annual averages are available for all series which are unadjusted for seasonality. Data Characteristics: Earnings are measured in dollars and are stored with two decimal places (three prior to 1957). Average weekly and overtime hours are measured in hours and are stored with one decimal place. Employment is measured in thousands of workers and is stored with one decimal place for two-digit SIC and lower-level industries when not adjusted for seasonality; other employment data are stored with no decimal place. Special characteristics of the data are footnoted where necessary. Updating Schedule: Updates are usually available on the third Friday following the reporting week (week containing the 12th) in the reference month. These updates contain first closing estimates for the reference month, second closing estimates for the month preceding the reference month, and third closing estimates for the month two months prior to the reference month. References: BLS Handbook of Methods, Chapter 2, "Employment, hours, and earnings from the establishment survey", Bulletin 2285 (1992). ================================================================================== Section 2 ================================================================================== The following Employment, Hours, and Earnings--National files are on the BLS internet in the sub-directory pub/time.series/ee: ee.data.1.CurrentSeasAE - Seasonal, All Employees (data_type_code = 01), 1988-Present ee.data.2.CurrentSeasPWWW - Seasonal, Women and Production Workers (data_type_code = 02, 03), 1988-Present ee.data.3.CurrentSeasOther - Seasonal, Other, 1988-Present ee.data.4.HistorySeasAE - Seasonal, All Employees (data_type_code = 01), Pre-1988 ee.data.5.HistorySeasPWWW - Seasonal, Women and Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.6.HistorySeasOther - Seasonal, Other, Pre-1988 ee.data.7.TotsAECurr - Unseasonal, Total, Tot priv, Goods prod, Mining, Construction (division 00, 10, 20), All Employees code = (data_type_code = 01), 1988-Present ee.data.8.ManufactureAECurr - Unseasonal, Manufacturing (division code = 30 - 32), All Employees (data_type_code = 01), 1988-Present ee.data.9.ServiceProdTPUAECurr - Unseasonal, Service prod, TPU (division code = 39, 40-42), All Employees (data_type_code = 01), 1988-Present ee.data.10.TradeAECurr - Unseasonal, Trade (division code = 50-53, 60), All Employees (data_type_code = 01), 1988-Present ee.data.11.FireAECurr - Unseasonal, FIRE (industry code = 70-73), All Employees (data_type_code = 01), 1988-Present ee.data.12.ServicesAECurr - Unseasonal, Services (division code = 80), All Employees (data_type_code = 01), 1988-Present ee.data.13.GovtAECurr - Unseasonal, Government (division code = 90-95), All Employees (data_type_code = 01), 1988-Present ee.data.14.TotsWWPWCurr - Unseasonal, Total, Tot priv, Goods prod, Mining, Construction (division code = 00, 10, 20), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.15.ManufactureWWPWCurr - Unseasonal, Manufacturing (division code = 30 - 32), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.16.ServiceProdTPUWWPWCurr - Unseasonal, Service prod, TPU (division code = 39, 40-42), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.17.TradeWWPWCurr - Unseasonal, Trade (division code = 50-53, 60), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.18.FireWWPWCurr - Unseasonal, FIRE (division code = 70-73), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.19.ServicesWWPWCurr - Unseasonal, Services (division code = 80), Women, Production Workers (data_type_code = 02, 03), 1988-Present ee.data.20.GovtWWCurr - Unseasonal, Government (division code = 90-95), Women, (data_type_code = 02), 1988-Present ee.data.21.TotsAHECurr - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Avg Hourly Earnings (data_type_code = 06), 1988-Present ee.data.22.ManufactureAHECurr - Unseasonal, Manufacturing (division code = 30 - 32), Avg Hourly Earnings, Hourly Earnings Excluding Overtime (data_type_code = 06, 60), 1988-Present ee.data.23.ServiceProdTPUAHECurr - Unseasonal, Service prod, TPU (division code = 39, 40-42), Avg Hourly Earnings (data_type_code = 06), 1988-Present ee.data.24.TradeAHECurr - Unseasonal, Trade (division code = 50-53, 60), Avg Hourly Earnings (data_type_code = 06), 1988-Present ee.data.25.FireAHECurr - Unseasonal, FIRE (division code = 70-73), Avg Hourly Earnings (data_type_code = 06), 1988-Present ee.data.26.ServicesAHECurr - Unseasonal, Services (division code = 80), Avg Hourly Earnings (data_type_code = 06), 1988-Present ee.data.27.TotsAWCurr - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), 1988-Present ee.data.28.ManufactureAWCurr - Unseasonal, Manufacturing (division code = 30 - 32), Avg Weekly Hours, Avg Weekly Earnings, Avg Weekly Overtime Hours (data_type_code = 04, 05, 07), 1988-Present ee.data.29.ServiceProdTPUAWCurr - Unseasonal, Service prod, TPU (division code = 39, 40-42), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), 1988-Present ee.data.30.TradeAWCurr - Unseasonal, Trade (division code = 50-53, 60), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), 1988-Present ee.data.31.FireAWCurr - Unseasonal, FIRE (division code = 70-73), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), 1988-Present ee.data.32.ServicesAWCurr - Unseasonal, Services (division code = 80), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), 1988-Present ee.data.33.TotsOtherCurr - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls, Diffusion Index (12-month) (data_type_code = 40, 45, 68), 1988-Present ee.data.34.ManufactureOtherCurr - Unseasonal, Manufacturing (division code = 30 - 32), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls, Diffusion Index (12-month) (data_type_code = 40, 45, 68) 1988-Present ee.data.35.ServiceProdTPUOtherCurr- Unseasonal, Service prod, TPU (division code = 39, 40-42), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45) 1988-Present ee.data.36.TradeOtherCurr - Unseasonal, Trade (division code = 50-53, 60), Other, Index of Average Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45) 1988-Present ee.data.37.FireOtherCurr - Unseasonal, FIRE (division code = 70-73), Other, Index of Aggregate Weekly Hours, Index of Aggreage Weekly Payrolls (data_type_code = 40, 45) 1988-Present ee.data.38.ServicesOtherCurr - Unseasonal, Services (division code = 80), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45), 1988-Present ee.data.39.TotsAEHist - Unseasonal, Total, Tot priv, Goods prod, Mining, Construction (division code = 00, 10, 20), All Employees (data_type_code = 01), Pre-1988 ee.data.40a.ManufactureAEHist - Unseasonal, Manufacturing (division code = 30 - 32), All Employees (data_type_code = 01), Pre-1988 ee.data.40b.ManufactureAEHist - Unseasonal, Manufacturing (division code = 30 - 32), All Employees (data_type_code = 01), Pre-1988 ee.data.41.ServiceProdTPUAEHist - Unseasonal, Service prod, TPU (division code = 39, 40-42), All Employees (data_type_code = 01), Pre-1988 ee.data.42.TradeAEHist - Unseasonal, Trade (division code = 50-53, 60), All Employees (data_type_code = 01), Pre-1988 ee.data.43.FireAEHist - Unseasonal, FIRE (division code = 70-73), All Employees (data_type_code = 01), Pre-1988 ee.data.44.ServicesAEHist - Unseasonal, Services (division code = 80), All Employees (data_type_code = 01), Pre-1988 ee.data.45.GovtAEHist - Unseasonal, Government (division code = 90-95), All Employees (data_type_code = 01), Pre-1988 ee.data.46.TotsWWPWHist - Unseasonal, Total, Tot priv, Goods, prod, Mining, Construction (division code = 00, 10, 20), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.47a.ManufactureWWPWHist - Unseasonal, Manufacturing (division code = 30 - 32), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.47b.ManufactureWWPWHist - Unseasonal, Manufacturing (division code = 30 - 32), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.48.ServiceProdTPUWWPWHist - Unseasonal, Service prod, TPU (division code = 39, 40-42), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.49.TradeWWPWHist - Unseasonal, Trade (division code = 50-53, 60), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.50.FireWWPWHist - Unseasonal, FIRE (division code = 70-73), Women, Production Workers(data_type_code = 02, 03), Pre-1988 ee.data.51.ServicesWWPWHist - Unseasonal, Services (division code = 80), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.52.GovtWWHist - Unseasonal, Government (division code = 90-95), Women, Production Workers (data_type_code = 02, 03), Pre-1988 ee.data.53.TotsAHEHist - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Avg Hourly Earnings (data_type_code = 06), Pre-1988 ee.data.54a.ManufactureAHEHist - Unseasonal, Manufacturing (division code = 30 - 32), Avg Hourly Earnings, Hourly Earnings Excluding Overtime (data_type_code = 06, 60), Pre-1988 ee.data.54b.ManufactureAHEHist - Unseasonal, Manufacturing (division code = 30 - 32), Avg Hourly Earnings, Hourly Earnings Excluding Overtime (data_type_code = 06, 60), Pre-1988 ee.data.55.ServiceProdTPUAHEHist - Unseasonal, Service prod, TPU (division code = 39, 40-42), Avg Hourly Earnings (data_type_code = 06), Pre-1988 ee.data.56.TradeAHEHist - Unseasonal, Trade (division code = 50-53, 60), Avg Hourly Earnings (data_type_code = 06), Pre-1988 ee.data.57.FireAHEHist - Unseasonal, FIRE (division code = 70-73), Avg Hourly Earnings (data_type_code = 06), Pre-1988 ee.data.58.ServicesAHEHist - Unseasonal, Services (division code = 80), Avg Hourly Earnings (data_type_code = 06), Pre-1988 ee.data.59.TotsAWHist - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), Pre-1988 ee.data.60a.ManufactureAWHist - Unseasonal, Manufacturing (division code = 30 - 32), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05, 07), Pre-1988 ee.data.60b.ManufactureAWHist - Unseasonal, Manufacturing (division code = 30 - 32), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05, 07), Pre-1988 ee.data.61.ServiceProdTPUAWHist - Unseasonal, Service prod, TPU (division code = 39, 40-42), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), Pre-1988 ee.data.62.TradeAWHist - Unseasonal, Trade (division code = 50-53, 60), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), Pre-1988 ee.data.63.FireAWHist - Unseasonal, FIRE (division code = 70-73), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), Pre-1988 ee.data.64.ServicesAWHist - Unseasonal, Services (division code = 80), Avg Weekly Hours, Avg Weekly Earnings (data_type_code = 04, 05), Pre-1988 ee.data.65.TotsOtherHist - Unseasonal, Total private, Goods prod, Mining, Construction (division code = 00, 10, 20), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls, Diffusion Index (12-month) (data_type_code = 40, 45, 68) Pre-1988 ee.data.66.ManufactureOtherHist - Unseasonal, Manufacturing (division code = 30 - 32), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls, Diffusion Index (12-month) (data_type_code = 40, 45, 68) Pre-1988 ee.data.67.ServiceProdTPUOtherHist- Unseasonal, Service prod, TPU (division code = 39, 40-42), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45) Pre-1988 ee.data.68.TradeOtherHist - Unseasonal, Trade (division code = 50-53, 60), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45) Pre-1988 ee.data.69.FireOtherHist - Unseasonal, FIRE (division code = 70-73), Other, Index of Aggregate Weekly Hours, Index of Aggregate Weekly Payrolls (data_type_code = 40, 45) Pre-1988 ee.data.70.ServicesOtherHist - Unseasonal, Services (division code = 80), Other, Index of Aggregate Weekly Hours, Index of Aggreate Weekly Payrolls (data_type_code = 40, 45) Pre-1988 ee.data.71.WeeklyEarnings - Unseasonal, All, Real Average Hourly Earnings, Real Average Weekly Earnings (data_type_code = 49, 51) 1988-Present ee.data.72.WeeklyEarningsHist - Unseasonal, All, Real Average Hourly Earnings, Real Average Weekly Earnings (data_type_code = 49, 51) Pre-1988 ee.contacts - Contacts for ee survey ee.datatype - Data_type_code mapping file ee.doc - General information ee.footnote - Footnote codes mapping file ee.industry - Industry codes mapping file ee.period - Period codes mapping file ee.series - All series and their beginning and end dates ================================================================================= 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 ee.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 17 EES00000001 2. industry_code 6 005000 3. data_type_code 2 01 4. seasonal 1 S or U 5. begin_year 4 1939 6. begin_period 3 M01 7. end_year 4 2002 8. end_period 3 M02 The series_id (EES00000001) can be broken out into: Code Value survey abbreviation = EE seasonal (code) = S industry_code = 000000 data_type_code = 01 ================================================================================== 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 ee.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 17 EES00000001 2. year 4 1988 3. period 3 M01 4. value 12 103623 5. footnote_codes 10 It varies The series_id (EES00000001) can be broken out into: Code Value survey abbreviation = EE seasonal (code) = S industry_code = 000000 data_type_code = 01 ================================================================================ 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: ee.datatype Field #/Data Element Length Value(Example) 1. data_type_code 2 60 2. data_type_text 60 Text File Name: ee.footnote Field #/Data Element Length Value(Example) 1. footnote_code 1 C 2. footnote_text 100 Text File Name: ee.industry Field #/Data Element Length Value(Example) 1. industry_code 6 101440 2. SIC_code 13 102 3. publishing_status 2 Internal Use Only 4. industry_name 60 Text File Name: ee.period Field #/Data Element Length Value(Example) 1. period 3 M01 2. period_abbr 5 JUN 3. period_name 20 Text ========================================================================================= Section 7 ========================================================================================= EMPLOYMENT, HOURS, AND EARNINGS--NATIONAL (EE) DATABASE ELEMENTS Data Element Length Value(Example) Description 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: 1976 data is available for a given time series. data_type_code 2 00 Code identifying the datatype of the observation. data_type_text 60 Text Datatype name of the observation. Ex: Total employment 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: 1992 data is available for a given time series. footnote_code 1 C Identifies footnote for the data 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 101440 Code identifying industry. industry_name 60 Text Name of industry. Ex: Grocery Stores period_abbr 5 Period name Abbreviation of period name. abbreviation Ex: JUN period 3 M01-M13 Identifies period for which Q01-Q04 data is observed. Ex: M06=June (M=Monthly, M13=Annual Avg, Q=Quarterly, Q05= Annual Avg) period_name 20 Text Full name of period to which Ex: June the data observation refers. publishing_ 2 Internal Use only Internal Use Only status seasonal 1 S=Seasonally Code identifying whether the Adjusted data are seasonally adjusted. U=Unadjusted series_id 17 EES00000001 Code identifying the specific series. SIC_code 13 102 Standard Industrial Classification code. value 12 103623 Data value for series. year 4 YYYY Identifies year of observation. Ex: 1990