To prepare 2007 Economic Census data for release to the public, the data are be processed in three primary ways:
Data captured in an economic census must be edited to identify and correct reporting errors and other problems. The data also must be adjusted to account for missing items and for businesses that do not respond. Data edits detect and validate data by considering factors such as historical reporting, industry/geographic ratios and averages and proper classification for a given record.
Computer programs subject the respondents’ responses to a series of data edit programs. They assign a valid kind-of-business or industry classification code to the establishment. Assigning a valid industry classification code depends on computer evaluation of the responses to specific items on the census report forms.
These items include:
If critical information is missing, the record is flagged and fixed before further processing occurs.
If critical information is available, the edit assigns the correct classification code. After classification codes are assigned, a "verification" operation is performed to validate the industry, geography and ZIP Codes.
The data edits also evaluate the response data for consistency and validity—for example, assuring that employment data are consistent with payroll or sales/receipts data. Response data is evaluated by industry. Additional checks compare current year data to data reported in previous censuses or from administrative sources.
Nonresponse is handled by estimating, or imputing, missing data.
There are two types of nonresponse:
Title 13 of the United States Code states that respondents are required to answer all questions to the best of their ability. Reported data are important because they represent the answers of similar establishments in a given industry. Incomplete forms, unclear data or nonresponse can affect data analyses and the quality of the published data.
Problems that arise from missing data include:
Although economic census nonresponse accounts for less than five percent of published figures, it is a significant source of nonsampling error.
Note: If a data cell contains too much imputation, the value will be suppressed with an ‘S’ flag.
Individual establishment records are tabulated in different ways based on data product and analytical needs. Tabulations include data summed by industry, specified geographic areas, establishment-size, products produced, materials used, fuels used and product lines sold.
The tabulations are subject to disclosure analysis prior to macro-analysis.
During macro-analysis: