The Annual Survey of Manufactures (ASM) is a sample survey of approximately 50,000 establishments. A new sample is selected at 5-year intervals beginning the second survey year subsequent to the Economic Census - Manufacturing. The current sample was selected in 2014, the second year following the 2012 Economic Census – Manufacturing. The sample is supplemented by new manufacturing establishments entering business in 2013 – 2016.
The Annual Survey of Manufactures (ASM) is conducted on an establishment basis. Reports are filed for those establishments selected in the sample. Companies engaged in distinctly different lines of activity at one location are requested to submit separate reports, if the plant records permit such a separation and if the activities are substantial in size. Estimates are based on the reports from a representative sample of manufacturing establishments. These estimates represent the portion of the manufacturing population accounted for by establishments with paid employees. Nonemployers are defined as out-of-scope of the ASM with the exception of those that are known to use solely leased employees to manufacture goods. The tables provide estimates for employment, plant hours, payrolls, value added by manufacture, capital expenditures, cost of materials, inventories, value of industry shipments, and fuels and electric energy consumed for most manufacturing industries.
The ASM excludes data for central administrative offices (CAOs). These would include separately operated administrative offices, warehouses, garages, and other auxiliary units that service manufacturing establishments of the same company. These data are published in a separate report series.
The 2012 Economic Census- Manufacturing contained approximately 294,600 active manufacturing establishments. For sample efficiency and cost considerations, the population was partitioned into two groups: (1) establishments eligible to be mailed a questionnaire and (2) establishments not eligible to be mailed a questionnaire. The following is a description of the 2014 ASM sample design:
Estimates for the capital expenditures variables are not generated using the difference estimator because the year-to-year correlations are considerably weaker. The standard linear estimator is used for these variables.
For the nonmail stratum, estimates for payroll are directly tabulated from the administrative-record data provided by the IRS and the SSA. Estimates of the other data variables are developed from industry averages. Although the establishments in the nonmail stratum are far more numerous than those in the mail stratum, they account for less than 6 percent of the value of shipments estimate at the total manufacturing level.
Corresponding estimates for the mail and nonmail components are combined to produce the estimates included in this publication.
The estimates developed from the sample are likely to differ from the results of a complete canvassing of all eligible establishments in the population. The particular sample selected for the ASM is one of many probability samples that could have been selected under identical circumstances. Each of the possible samples would yield a slightly different set of results. The derived standard errors are measures of the variation of all the possible sample estimates around the true population statistic. Estimates with low standard errors are generally felt to be more accurate than those associated with high standard errors. Estimates of the standard errors are computed from the sample data for selected ASM statistics in this report. They are represented in the form of relative standard errors (the standard error divided by the corresponding estimate). In conjunction with its associated estimate, the relative standard error may be used to define confidence intervals (ranges that would include the comparable, complete-coverage value for specified percentages of all the possible samples). The complete-coverage value would be included in the range:
An inference that the comparable, complete-survey result would be within the indicated ranges would be correct in approximately the relative frequencies shown. Those proportions, therefore, may be interpreted as defining the confidence that the estimates from a particular sample would differ from complete-coverage results by as much as one, two, or three standard errors, respectively.
For example, suppose an estimated total is shown as 50,000 with an associated relative standard error of 2 percent, that is, a standard error of 1,000 (2 percent of 50,000). There is approximately 67 percent confidence that the interval 49,000 to 51,000 includes the complete-coverage total, about 95 percent confidence that the interval 48,000 to 52,000 includes the complete-coverage total, and almost certain confidence that the interval 47,000 to 53,000 includes the complete-coverage total.
In addition to the sampling errors, the estimates are subject to various response and operational errors: errors of collection, reporting, coding, transcription, imputation for nonresponse, etc. These nonsampling, or operational, errors also would occur if a complete canvass were to be conducted under the same conditions as the survey. Explicit measures of their effects generally are not available. However, it is believed that most of the important operational errors are detected and corrected during the Census Bureau’s review of the data for reasonableness and consistency. The small operational errors usually remain. To some extent, they are compensating in the aggregated totals shown. When important operational errors are detected too late to correct the estimates, the data are suppressed or are specifically qualified in the tables.
The total errors, which depend upon the joint effect of the sampling and nonsampling errors, are usually of the order of size indicated by the standard error, or moderately higher. However, for particular estimates, the total error may considerably exceed the standard errors shown. Any figures shown in the tables in this publication having an associated standard error exceeding 15 percent may be combined with higher level totals, creating a broader aggregate, which then may be of acceptable reliability.
Two types of response rates are computed for the ASM: unit response rate and weighted item response rate. The unit response rate is computed using unweighted counts and is defined as the percentage of eligible reporting units that respond to the survey. To be considered a respondent to the ASM, a reporting unit must provide the key items of value of shipments, total payroll, and total employment. The unit response rate for the 2014 ASM was about 74%.
The weighted item response rate is defined as the percentage of the estimated item total that is obtained from directly reported data and administrative record data. The weighted item response rates for the key ASM data items, in the 2014 ASM, have exceeded 70%.
For additional information on ASM response rates call (301) 763-5154.
Data for cost of materials and value of shipments include varying amounts of duplication, especially at higher levels of aggregation. This is because the products of one establishment may be the materials of another. The value added statistics avoid this duplication and are, for most purposes, the best measure for comparing the relative economic importance of industries and geographic areas.
The Annual Survey of Manufactures (ASM) shows value of shipments data for industries and products. In the industry statistics tables and files, these data represent the total value of shipments of all establishments classified in a particular industry. The data include the shipments of the products classified in the industry (primary to the industry), products classified in other industries (secondary to the industry), and miscellaneous receipts (resales, contract receipts, repair work, etc.). Value of product shipments shown in the products statistics tables and files represent the total value of all products shipped that are classified as primary to an industry regardless of the classification of the producing establishment.
In accordance with federal law governing census reports (Title 13 of the United States Code), no data are published that would disclose the operations of an individual establishment or company. Techniques employed to limit disclosure are discussed at: https://www.census.gov/econ/census/help/methodology_disclosure/
Disclosure analysis is performed at the field level, i.e., disclosure analysis performed for each variable independent of other variables for that NAICS-based industry or product class. When data for a NAICS-based industry or product class are suppressed, these data still are included in higher-level totals.
Sector 31: Annual Survey of Manufactures: General Statistics: Statistics for Industry Groups and Industries
Sector 31: Annual Survey of Manufactures: Value of Products Shipments: Value of Shipments for Product Classes
Sector 31: Annual Survey of Manufactures: Geographic Area Statistics: Statistics for All Manufacturing by State
Sector 31: Annual Survey of Manufactures: Geographic Area Statistics: Supplemental Statistics for the United States and States
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