U.S. flag
              An official website of the United States governmentSkip to main content
end of header


Census.gov
                                    >                                
                                Business and Economy    >Retail - Monthly    >How the Data are Collected    >Quarterly E-Commerce Report Methodology
 Skip to looking for section Main	About	Information for Respondents	Data	Time Series/Trend Charts	Technical Documentation	Release Schedule	Definitions	FAQs	Contact Us Back to Our Surveys & Programs
 Main	About	Information for Respondents	Data	Time Series/Trend Charts	Technical Documentation	Release Schedule	Definitions	FAQs	Contact Us
                                Back to Our Surveys & Programs
  Quarterly E-Commerce Report Methodology Confidentiality The Census Bureau is required by Section 9 of Title 13 United States Code to keep respondents' information confidential and can use the information only to produce statistics. The Census Bureau is not permitted to publicly release a respondent's information in a way that could identify a business, organization, or institution. Per the Federal Cybersecurity Enhancement Act of 2015, submitted data are protected from cybersecurity risks through screening of the systems that transmit data. Disclosure Avoidance Disclosure is the release of data that reveals information or permits deduction of information about a particular survey unit through the release of either tables or microdata. Disclosure avoidance is the process used to protect each survey unit's identity and data from disclosure. Using disclosure avoidance procedures, the Census Bureau modifies or removes the characteristics that put information at risk of disclosure. Although it may appear that a table shows information about a specific survey unit, the Census Bureau has taken steps to disguise or suppress a unit's data that may be “at risk” of disclosure while making sure the results are still useful. The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504206, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0003). Survey Description Retail e-commerce sales are estimated from the same sample used for the Monthly Retail Trade Survey (MRTS) to estimate preliminary and final U.S. retail sales. Advance U.S. retail sales are estimated from a subsample of the MRTS sample that is not of adequate size to measure changes in retail e-commerce sales. A stratified simple random sampling method is used to select approximately 10,800 retail firms whose sales are then weighted and benchmarked to represent the complete universe of retail firms. The MRTS sample is probability based and represents all employer firms engaged in retail activities as defined by the North American Industry Classification System (NAICS). Coverage includes all retailers whether or not they are engaged in e-commerce. Online travel services, financial brokers and dealers, and ticket sales agencies are not classified as retail and are not included in either the total retail or retail e-commerce sales estimates. Nonemployers are represented in the estimates through benchmarking to prior annual survey estimates that include nonemployer sales based on administrative records. E-commerce sales are included in the total monthly sales estimates. The MRTS sample is updated on an ongoing basis to account for new retail employer businesses (including those selling via the Internet), business deaths, and other changes to the retail business universe. Firms are asked each month to report e-commerce sales separately. For each month of the quarter, data for nonresponding sampling units are imputed from responding sampling units falling within the same kind of business and sales size category. Responding firms account for approximately 71 percent of the e-commerce sales estimate and about 71 percent of the estimate of U.S. retail sales for any quarter. For each month of the quarter, Horvitz-Thompson estimates are obtained by summing weighted e-commerce sales (either reported or imputed). Benchmarked monthly estimates are computed by multiplying each Horvitz-Thompson estimate by the carry-forward factor calculated during the most recent benchmarking. For more information on the benchmark process, click here. For companies with separate store and e-commerce components, the e-commerce components are tabbed in MRTS under NAICS 4541. To get the sales and e-commerce estimates in the experimental quarterly e-commerce table, first subtotal Horvitz-Thompson estimates are obtained by summing weighted sales and e-commerce sales within 4541 by the primary kind-of-business of the company. To ensure the overall total retail estimates are consistent with MRTS, these kind-of-business subtotals are raked to the benchmarked monthly estimate for NAICS 4541 from MRTS. This is done by calculating the proportion of each kind of business to the Horvitz-Thompson estimate of NAICS 4541, then applying each of these proportions to the benchmarked monthly estimate for NAICS 4541 to get the corresponding benchmarked monthly estimate for that kind of business subtotal. Finally, these kind-of-business nonstore subtotals are added to the MRTS estimate for that kind of business to get a total store and nonstore estimate. Estimates for the quarter are obtained by summing the monthly benchmarked estimates.The estimate for the most recent quarter is a preliminary estimate. Therefore, the estimate is subject to revision. Data users who create their own estimates using data from this report should cite the Census Bureau as the source of the input data only. Adjusted Estimates This report publishes estimates that have been adjusted for seasonal variation and holiday and trading-day differences, but not for price changes. We use quarterly e-commerce sales estimates for 4th quarter 1999 to the current quarter as input to the X-13ARIMA-SEATS program, using the X-11 filter-based adjustment procedure, to derive the adjusted quarterly e-commerce estimates. We derive quarterly adjusted sales estimates by summing the adjusted monthly sales estimates for each respective quarter from the Monthly Retail Trade Survey. Reliability of Estimates Because the estimates in this report are based on a sample survey, they may contain sampling error and nonsampling error. Sampling error is the difference between the estimate and the result that would be obtained from a complete enumeration of the population conducted under the same survey conditions. This error occurs because only a subset of the entire population is measured in a sample survey. Standard errors and coefficients of variation, as given in Table 2 of the report, are estimated measures of sampling variation. The margin of error gives a range about the estimate which is a 90 percent confidence interval. If, for example, the estimated percent change is -11.4% and its estimated standard error is 1.2%, then the margin of error is 1.753 x 1.2% or 2.1%, and the 90 percent confidence interval is -13.5% to -9.3%. Confidence intervals are computed based on the particular sample selected and canvassed. If one repeats the process of drawing all possible samples and forming all corresponding confidence intervals, approximately 90 percent of these individual confidence intervals would contain the estimate computed from a complete enumeration of all units on the sampling frame. If the confidence interval contains 0%, then one does not have sufficient evidence to conclude that at the 90 percent confidence level that the estimated change is different from zero. Nonsampling error encompasses all other factors that contribute to the total error of a sample survey estimate. This type of error can occur because of nonresponse, insufficient coverage of the universe of retail businesses with e-commerce sales, mistakes in the recording and coding of data, and other errors of collection, response, coverage, or processing. Although not directly measured, precautionary steps are taken to minimize the effects of nonsampling error.


CONNECT WITH US

Information Quality
                    Data Linkage Infrastructure
                    Data Protection and Privacy Policy
                    Accessibility      
                    FOIA
                    Inspector General
                    No FEAR Act
                    U.S. Department of Commerce
                    USA.gov
                   Measuring America's People, Places, and Economy