Producer Price Index (PC) pc.txt Section Listing 1. Survey definition 2. Files listed in the survey directory. 3. Time series, series file, data file, and 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: PRODUCER PRICE INDEX REVISION-CURRENT SERIES (PC) Survey Description: The Producer Price Index Revision-Current Series indexes reflect price movements for the net output of producers organized according to the North American Industry Classification System (NAICS). The PC dataset is compatible with a wide assortment of NAICS-based economic time series including: productivity, production, employment, wages, and earnings. The PPI universe consists of the output of all industries in the goods-producing sectors of the U.S. economy- mining, manufacturing, agriculture, fishing, and forestry- as well as natural gas, electricity, construction, and goods competitive with those made in the producing sectors, such as waste and scrap materials. In addition, as of January 2011, the PPI program covered more than three-quarters of the service sector's output, publishing data for selected industries in the following industry sectors: wholesale and retail trade; transportation and warehousing; information; finance and insurance; real estate brokering, rental, and leasing; professional, scientific, and technical services; administrative, support, and waste management services; health care and social assistance; and accommodation. To the extent possible, prices used in constructing the indexes are the actual revenue or net transaction prices producers receive for sales of their outputs. Scientific (probability) sampling techniques are used to select reporting establishments, products, and transactions for all types and volumes of output (not just volume-sellers). Coverage includes roughly 500 mining and manufacturing industries and approximately 150 services industries. The PPI is meant to measure changes in prices received by domestic producers, import products are not priced in the survey. BLS collects over 100,000 price quotations each month covering over 600 industries and over 6,000 products and product categories. Frequency of Observations: Monthly in most cases. Annual Averages: Annual averages are available. Data Characteristics: All data through June 2021 are stored with one decimal place. Data after June 2021 are stored with 3 decimal places. Updating Schedule: Updates are usually available on or before the 15th day of the month following a given reference month. For example, January index data are usually made available on or before the 15th of February. Effective with the release of the January 2004 data, the PPI program converted from the SIC System to the NAIC System. Also effective with this release, the PPI's PD database contains the complete history of published SIC-based time series. With the release of indexes for July 2004, PPI produced a separate dataset for discontinued NAICS-based indexes. References: BLS Handbook of Methods, Chapter 14, "Producer Prices", Online at https://www.bls.gov/opub/hom/pdf/homch14.pdf ================================================================================== Section 2 ================================================================================== The following Producer Price Index files are on the BLS internet in the sub-directory pub/time.series/pc: pc.data.0.Current-All current series recent data pc.data.01.aggregates- Select cross-industry combinations pc.data.05.ForestryandLogging- (subsector 113)Forestry and logging pc.data.1.OilAndGas- (subsector 211)Oil and gas extraction pc.data.2.Mining- (subsector 212)Mining (except oil and gas) pc.data.3.MiningSupport- (subsector 213)Support activities for mining pc.data.4.Food- (subsector 311)Food manufacturing pc.data.5.BeverageTobacco- (subsector 312)Beverage and tobacco product mfg pc.data.6.Textile- (subsector 313)Textile mills pc.data.7.TextileProduct- (subsector 314)Textile product mills pc.data.8.Apparel- (subsector 315)Apparel manufacturing pc.data.9.Leather- (subsector 316)Leather and allied product manufacturing pc.data.10.Wood- (subsector 321)Wood product manufacturing pc.data.11.Paper- (subsector 322)Paper manufacturing pc.data.12.Printing- (subsector 323)Printing and related support activities pc.data.13.PetroleumCoalProducts- (subsector 324)Petroleum and coal products mfg pc.data.14.Chemicals- (subsector 325)Chemical manufacturing pc.data.15.PlasticsRubberProducts- (subsector 326)Plastics and rubber products mfg pc.data.16.NonmetallicMineral- (subsector 327)Nonmetallic mineral product mfg pc.data.17.PrimaryMetal- (subsector 331)Primary metal manufacturing pc.data.18.FabricatedMetalProduct- (subsector 332)Fabricated metal product mfg pc.data.19.Machinery- (subsector 333)Machinery manufacturing pc.data.20.ComputerProduct- (subsector 334)Computer and electronic product mfg pc.data.21.ElectricalMachinery- (subsector 335)Electrical equip, appliance, and component mfg pc.data.22.TransportationEquipment- (subsector 336)Transportation equipment mfg pc.data.23.Furniture- (subsector 337)Furniture and related product mfg pc.data.24.Miscellaneous- (subsector 339)Miscellaneous manufacturing pc.data.25.MotorVehicleDealers- (subsector 441) Motor vehicle and parts dealers pc.data.26.FurnitureStores- (subsector 449)Furniture and home furnishings stores pc.data.27.ElectronicsStores- (subsector 449)Electronics and appliance stores pc.data.28.BuildingGardenStores- (subsector 444)Building material and garden equipment and supplies dealers pc.data.29.FoodBeverageStores- (subsector 445)Food and beverage stores pc.data.30.HealthStores- (subsector 456)Health and personal care stores pc.data.31.GasolineStations- (subsector 457)Gasoline stations pc.data.32.ClothingStores- (subsector 458)Clothing and clothing accessories stores pc.data.33.SportsMusicStores- (subsector 459)Sporting goods, hobby, book, and music stores pc.data.34.GeneralStores- (subsector 455)General merchandise stores pc.data.35.NonstoreRetailers- (subsector 454)Nonstore retailers pc.data.36.AirTransportation- (subsector 481)Air transportation pc.data.37.RailTransportation- (subsector 482)Rail transportation pc.data.38.WaterTransportation- (subsector 483)Water transportation pc.data.39.TruckTransportation- (subsector 484)Truck transportation pc.data.40.PipelineTransportation- (subsector 486)Pipeline transportation pc.data.42.TransportationSupport- (subsector 488)Support activites for transportation pc.data.43.PostalService- (subsector 491)Postal service pc.data.44.CouriersAndMessengers- (subsector 492)Couriers and messengers pc.data.45.WarehousingStorage- (subsector 493)Warehousing and storage pc.data.46.Utilities- (subsector 221)Utilities pc.data.47.AmbulatoryHealthCareServices- (subsector 621)Ambulatory health care services pc.data.50.Hospitals- (subsector 622)Hospitals pc.data.51.NursingResidentialCareFacil- (subsector 623)Nursing and residential care facilities pc.data.53.Publishing- (subsector 511)Publishing industries (except internet) pc.data.54.Broadcasting- (subsector 515)Broadcasting (except internet) pc.data.55.Telecommunications- (subsector 517)Telecommunications pc.data.56.ISPsSearchPortandDataProcess- (subsector 518)Internet search providers, web search portals, and data processing services pc.data.57.Finance- (subsector 523)Securities, commodity contracts, and other financial investements and related activities pc.data.58.InsuranceCarriers- (subsector 524)Insurance carriers and related activities pc.data.59.RealEstate- (subsector 531)Real estate pc.data.62.RentalandLeasingServices- (subsector 532)Rental and leasing services pc.data.63.ProfessionalandTechnicalServ- (subsector 541)Professional, scientific, and technical services pc.data.67.AdministrativeandSupportServ- (subsector 561)Administrative and support services pc.data.70.WasteMgtandRemediationServ- (subsector 562)Waste management and remediation services pc.data.71.Accommodation- (subsector 721)Accommodation pc.data.72.RecyclableMaterials- (industry 423930)Recyclable materials wholesalers pc.data.73.MiscellaneousStoreRetailers- (subsector 453)Miscellaneous store retailers pc.data.74.PremiumsforPropandCasualtyIns- (code 924126) Premiums for property and casualty insurance pc.data.75.Construction- (sector 23)Construction and material inputs to contstruction pc.data.76.WholesaleTrade- (sector 42)Wholesale trade pc.data.77.Recreation- (subsector 713)Amusement and recreation industries pc.contacts- Contacts for pc survey pc.footnote- Footnote codes key pc.industry- Industry titles for pc industry codes pc.period- Period abbreviation key pc.product- Industry and product titles to pc codes pc.series- List of all series codes, titles, and their beginning and end dates pc.txt- General information ================================================================================= Section 3 ================================================================================= The term time series, and the series file, data file, and mapping file definitions and relationships are 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 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 pc.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 30 PCU113310113310P 2. industry_code 6 113310 3. product_code 15 113310P 4. seasonal 1 U 5. base_date 6 198112 6. series_title 256 PPI industry data for Logging-Primary products, not seasonally adjusted 7. begin_year 4 1981 8. begin_period 3 M12 9. end_year 4 2017 10. end_period 3 M11 The series_id (PCU11330011330041300) can be broken out into: Code Value survey abbreviation = PC seasonal (code) = U industry_code = 113310 product_code = 113310P ================================================================================== 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 pc.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 30 PCU11330011330041300 2. year 4 1994 3. period 3 M01 4. value 12 82.0 5. footnote_codes 10 It varies The series_id (PCU11330011330041300) can be broken out into: Code Value survey abbreviation = PC seasonal (code) = U industry_code = 113300 product_code = 11330041300 ================================================================================ 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: pc.footnote Field #/Data Element Length Value(Example) 1. footnote_code 2 P 2. footnote_text 200 Text File Name: pc.industry Field #/Data Element Length Value(Example) 1. industry_code 6 113300 2. industry_text 150 Text File Name: pc.period Field #/Data Element Length Value(Example) 1. period 3 M01 2. period_abbr 5 JAN 3. period_name 20 Text File Name: pc.product Field #/Data Element Length Value(Example) 1. industry_code 6 113300 2. product_code 15 11330041300 3. product_text 150 Text ========================================================================================= Section 7 ========================================================================================= PRODUCER PRICE INDEX REVISION (PC) DATABASE ELEMENTS Data Element Length Value(Example) Description begin_period 3 M01-M13 Identifies first data observation Ex: MO6=June within the first year for which (M=Monthly, M13=Annual data is available for a given Avg) time series. begin_year 4 YYYY Identifies first year for which Ex: 1975 data is available for a given time series. base_date 6 YYYYMM The base year used in Ex: 8412 (year=1984, calculating the index. month=12,i.e. December) end_period 3 M01-M13 Identifies last data observation Ex: M06=June within the last year for which (M=Monthly, M13=Annual data is available for a given Avg) time series. end_year 4 YYYY Identifies last year for which Ex: 1980 data is available for a given time series. footnote_code 2 P Identifies footnote for the data series. footnote_codes 10 It varies Identifies footnotes for the data series. footnote_text 200 Text Contains the text of the footnote. industry_code 6 113300 NAICS code for the industry. industry_text 150 Text Name of the industry. Ex: Natural and processed cheese period_abbr 5 Period name Abbreviation of period name. abbreviation Ex: JUN period 3 M01-M13 Identifies period for which Ex: M06=June data is observed. (M=Monthly, M13=Annual Avg) period name 20 Text Full name of period to which Ex: June the data observation refers. product_code 15 Ex: 11330041300 Code identifying the product to which the data observation refers. product_text 150 Text Name of the product to which Ex: cheddar cheese the data observation refers. seasonal 1 S=Seasonally Code identifying whether the Adjusted data are seasonally adjusted. U=Unadjusted series_id 30 Code series identifier Code identifying the specific Ex:PCU11330011330041300 series. value 12 Index Price index for item. Ex: 82.0 year 4 YYYY Identifies year of observation. Ex: 1990