Frequently Asked Questions (FAQ)
Question: Are gift certificates included in retail sales estimates?
Answer: Yes. According to generally accepted accounting principles, sales from gift certificates are included in the retail sales of firms at the time the gift certificate is redeemed.
Question: Does the Census Bureau publish data for number of retail establishments?
Answer: No. The Monthly Retail Trade Survey does not publish data for number of retail establishments by kind of business. The data are, however, available on a limited basis from the County Business Patterns Survey at (301) 763-2580 and from the 5-year Census of Retail Trade at (301) 763-2687.
Question: Are sales taxes included in published sales estimates?
Answer: No. Respondents are instructed to exclude sales taxes in their reported monthly sales. However, excise taxes are included.
Question: If a firm sells to both household consumers and businesses, are sales
to businesses excluded?
Answer: No. A firm is classified by its major source of receipts by establishment. Firms are instructed to report their total sales for a given month for all retail establishments even if they include some non-retail receipts. For example, if a firm operates an establishment engaged in both retail and wholesale operations, but the majority of sales are from the retail operation, the establishment is classified as retail.
Question: What is included in the grocery store estimate?
Answer: The grocery store estimate represents total receipts of stores that are primarily engaged in the sale of groceries. The estimate includes the value of all items sold by grocery stores and may include receipts for drugs, gasoline, stationery, beer and wine, household items, etc. sold by the grocery store. A retail operation is classified based on its major source of receipts.
Question: Does the Census Bureau publish data for individual commodities?
Answer: Some data by commodity are available in the Merchandise Line Sales report available in Census years. Data are available from the Census of Retail Trade at (301) 763-2687.
Question: When is a mail-order purchase included as a sale?
Answer: Mail-order sales are included at the time of purchase, regardless of the delivery date.
Question: Why don't the automotive sales agree with the automotive units published
by the Automobile Manufacturers Association?
Answer: The automotive sales data includes sales of other items not included in the automotive units information such as used cars, boats, motorcycles, recreational vehicles (RV's), parts, and repairs.
Question: Do the published sales include nonemployer firms?
Answer: Yes. The estimate includes both employer and nonemployer firms.
Question: Are sales of lottery tickets included in the retail sales estimates?
Answer: No. Sales and commissions from sales of government lottery tickets are excluded from the retail sales estimates.
Frequently Asked Questions (FAQ)
Question: What are e-commerce sales?
Answer: E-commerce sales are sales of goods and services over the Internet, an extranet, Electronic Data Interchange (EDI), or other online system. Payment may or may not be made online.
Question: Are e-commerce sales included in current monthly
retail sales estimates?
Answer: Yes. In addition, we are separately estimating e-commerce sales.
Question: Why was the e-commerce sales estimate for the prior
Answer: The e-commerce sales estimate for the prior quarter was revised to reflect additional response data.
Question: Are you estimating total retail sales differently
as a result of measuring e-commerce sales?
Answer: No. The Monthly Retail Trade Survey covers all sales of establishments primarily engaged in retail activities, including traditional retailers selling via the Internet and companies selling goods exclusively on-line. The survey excludes companies conducting non-retail operations such as travel, ticketing, and financial services.
Question: Are new retail businesses selling via the Internet
added to the monthly survey?
Answer: Yes. We update our sample regularly to account for new businesses, including retailers selling exclusively via the Internet. New businesses are identified when they notify the Federal Government of their intention to hire employees. The Bureau draws a sample of these new businesses and adds them to the survey each quarter.
Question: How does the monthly survey account for firms that
go out of business?
Answer: We drop firms from the monthly survey once we receive notification that a firm has ceased operation. The survey is updated each quarter to add new businesses and delete firms no longer in business.
Question: Do the e-commerce estimates include non-employer
Answer: Yes. Non-employer firms are not included in the sample. However, to account for e-commerce sales by non-employer firms, the estimates are statistically adjusted based on the retail sales of non-employers in the most recent annual survey.
Question: How are e-commerce sales data obtained from the
firms in the monthly survey?
Answer: Firms are asked to report e-commerce sales on the same questionnaire used to collect total retail sales.
Question: Are all businesses engaged in e-commerce sales covered
in the monthly survey?
Answer: No. The Monthly Retail Trade Survey includes only retail firms. It excludes non-retail operations such as travel agencies, financial services, manufacturers, and wholesalers.
Question: How do you know that the sample is representative
of all retail e-commerce?
Answer: All retail firms, including those engaged in e-commerce, are included in the sample selection process.
Do you have plans to release quarterly industry data?
Answer: No. More detailed information, including industry and merchandise category detail, can be obtained from the annual surveys as part of the Census Bureauís E-Stats report. These data are available at www.census.gov/estats.
Do we have plans to release data monthly?
Answer: †No. The quarterly estimates appear to be meeting user needs.
Are e-commerce sales estimated for trade areas other than retail?
Answer: Yes. Using its annual surveys, the Census Bureau produces estimates of e-commerce activity for manufacturing; wholesale trade; retail trade; food service and accommodations; and information, finance, transportation, business, professional and personal services. These data are available at www.census.gov/estats.
Question: Will you release seasonally adjusted e-commerce
Answer: It will take several years to have enough historical e-commerce sales data to allow us to determine seasonal patterns.
Question: Are foreign sales included in the e-commerce estimate?
Answer: The e-commerce and total sales estimates include sales covering all store and non-store retail locations in the United States operated by a firm selected in the survey. Sales made to a customer in a foreign country through a U.S. web site are included in the estimates.
Question: How are gift certificates treated?
Answer: Following generally accepted accounting principles, sales from gift certificates are included in the retail sales of firms at the time the gift certificate is redeemed.
Question: How are returns of merchandise treated?
Answer: Firms are instructed to report sales net of returned merchandise.
Question: How are businesses selected for the monthly survey?
Answer: Businesses are categorized by their industrial activity and size. Within each of these groups, the Census Bureau selects a random sample of firms. Each quarter, new businesses undergo a similar procedure, and additional sampling units are selected and added to the survey. This methodology ensures that the sample contains businesses of all sizes and from each retail industry.
Question: How many firms are surveyed to estimate e-commerce
Answer: E-commerce sales are estimated based on the monthly activity of over 12,000 retail firms. All firms that receive the retail survey report form each month are asked to provide their e-commerce sales.
Question: Are sales at electronic auctions included in the e-commerce
Answer: Electronic auctions directed at individual consumers are classified as retail trade. However, commissions and fees,not sales, are included in the e-commerce estimate. This is similar to the way the Census Bureau treats sales at traditional auction houses.
Are sales of adult material included in the retail e-commerce estimates?
Answer: Sales from businesses primarily selling goods of any kind are included while businesses primarily providing services such as publishing and broadcasting are excluded.
Question: Are you planning to release an advance estimate
of retail e-commerce sales?
Answer: No. The sample used to provide an advance estimate of change in total monthly retail sales is not of adequate size to measure change in retail e-commerce sales.
Question: Are retailers willing and able to provide their
e-commerce sales values?
Answer: Yes. The retailers in the survey are very cooperative and in most cases were able to provide the dollar volume of their e-commerce sales.
to Monthly Retail Sales and Inventories Series
Frequently Asked Questions (FAQ)
Question: Why are the monthly retail estimates revised?
Answer: The monthly retail sales and inventory estimates are benchmarked each year to reflect the results from the latest Annual Retail Trade Survey and the latest Economic Census.
Question: Why do we use our annual surveys and censuses as
Answer: Participation in the economic census and the annual survey are required by law, therefore response rates are higher than in the monthly surveys. Respondents have more time to prepare their responses to the annual surveys than they do for the monthly survey. Data for the annual surveys are requested at a time when many firms have already compiled audited book figures. Respondents to our monthly survey have just a few weeks to provide their data. These data are sometimes based on unaudited records or include estimates. Also, we collect data from more businesses in the annual survey.
Question: How are the estimates benchmarked?
Answer: We benchmark the estimates in two stages. When the latest Economic Census becomes available we benchmark to set the annual sales and end-of-year inventory estimates equal to the results from the Economic Census and minimize revisions to the previously published year-to-year trends. After we benchmark the annual estimates to the Economic Census results, we benchmark the monthly estimates to equal the annual estimates and the Economic Census results and minimize revisions to previously published month-to-month trends.
Question: What determines the size of the annual revisions?
Answer: The size of the revision for the unadjusted estimates is based on revisions between the results of the 2005 Annual Retail Trade Survey and the previously published 2005 estimates derived from the monthly survey.
are the 1997 estimates different than the 1997 Economic Census data for some
Answer: Because of the implementation of the new classification rules in the 2002 Economic Census, some companies that were classified as retail trade in 1997 were re-classified to wholesale in 2002. In order to maintain the consistency of the time series, historic estimates from 1992 - 2001 were developed to reflect this change.
Seasonal, Trading Day, and Moving Holiday Adjustment
Frequently Asked Questions (FAQ)
Question: What is an economic time series?
Answer: An economic time series is a sequence of successive measurements of an economic activity (that is, variable) obtained at regular time intervals (such as every month or every quarter). The data must be comparable over time, so they must be consistent in the concept being measured and the way that concept is measured.
Question: What is seasonal adjustment?
Answer: Seasonal adjustment is the process of estimating and removing seasonal effects from a time series in order to better reveal certain non-seasonal features. Examples of seasonal effects include a July drop in automobile production as factories retool for new models and increases in heating oil production during September in anticipation of the winter heating season. (Seasonal effects are defined more precisely below.) Sometimes we also estimate and remove trading day effects and moving holiday effects (Holiday effects are defined more precisely below.) during the seasonal adjustment process.
Question: Why do you seasonally adjust data?
Answer: Seasonal movements are often large enough that they mask other characteristics of the data that are of interest to analysts of current economic trends. For example, if each month has a different seasonal tendency toward high or low values it can be difficult to detect the general direction of a time series' recent monthly movement (increase, decrease, turning point, no change, consistency with another economic indicator, etc.). Seasonal adjustment produces data in which the values of neighboring months are usually easier to compare. Many data users prefer seasonally adjusted data because they want to see those characteristics that seasonal movements tend to mask, especially changes in the direction of the series.
Question: In the original (unadjusted) series, this year's
April value is larger than the March value. But the seasonally adjusted series
shows a decrease from March to April this year. What does this discrepancy mean?
Answer: This difference in direction can happen only when the seasonal factor for April is larger than the seasonal factor for March, indicating that when the underlying level of the series isn't changing, the April value will typically be larger than the March value. This year, the original series' April increase over the March value must be smaller than usual, either because the underlying level of the series is decreasing or because some special event or events abnormally increased the March value somewhat, or decreased the April value somewhat. (When trading day or moving holiday effects are present and are being adjusted out, other explanations are possible.)
Question: What kinds of seasonal effects are removed during
Answer: Seasonal adjustment procedures for monthly time series estimate effects that occur in the same calendar month with similar magnitude and direction from year to year. In series whose seasonal effects come primarily from weather (rather than from, say, Christmas sales or economic activity tied to the school year or the travel season), the seasonal factors are estimates of average weather effects for each month, for example, the average January decrease in new home construction in the Northeastern region of the U.S. due to cold and storms. Seasonal adjustment does not account for abnormal weather conditions or for year-to-year changes in weather. It is important to note that seasonal factors are estimates based on present and past experience and that future data may show a different pattern of seasonal factors.
Question: What is the seasonal adjustment process?
Answer: The mechanics of seasonal adjustment involve breaking down a series into trend-cycle, seasonal, and irregular components.
Trend-Cycle: Level estimate for each month (quarter) derived from the surrounding year-or-two of observations.
Seasonal Effects: Effects that are reasonably stable in terms of annual timing, direction, and magnitude. Possible causes include natural factors (the weather), administrative measures (starting and ending dates of the school year), and social/cultural/religious traditions (fixed holidays such as Christmas). Effects associated with the dates of moving holidays like Easter are not seasonal in this sense, because they occur in different calendar months depending on the date of the holiday.
Irregular Component: Anything not included in the trend-cycle or the seasonal effects (or in estimated trading day or holiday effects). Its values are unpredictable as regards timing, impact, and duration. It can arise from sampling error, non-sampling error, unseasonable weather, natural disasters, strikes, etc.
Question: What are trading day effects and trading day adjustments?
Answer: Monthly (or quarterly) time series that are totals of daily activities can be influenced by each calendar month's weekday composition. This influence is revealed when monthly values consistently depend on which days of the week occur five times in the month. Recurring effects associated with individual days of the week are called trading-day effects.
Trading-day effects can make it difficult to compare series values or to compare movements in one series with movements in another. For this reason, when estimates of trading-day effects are statistically significant, we adjust them out of the series. The removal of such estimates is called trading day adjustment.
Question: How is the seasonal adjustment derived?
Answer: We use a computer program called X-12-ARIMA to derive our seasonal adjustment and produce seasonal factors.
It is difficult to estimate seasonal effects when the underlying level of the series changes over time. For this reason, the program starts by detrending the series with a crude estimate of the trend-cycle. It then derives crude seasonal factors from the detrended series. It uses these to obtain a better trend-cycle and detrended series from which a more refined seasonal component is obtained. This iterative procedure, involving successive improvements, is used because seasonal effects make it difficult to determine the underlying level of the series required for the first step. Crude and more refined irregular components are used to identify and compensate for data that are so extreme that they can distort the estimates of trend-cycle and seasonal factors.
The seasonal factors are divided into the original series to get the seasonally adjusted series. For example, suppose for a particular January, a series has a value of 100,000 and a seasonal factor of 0.80. The seasonally adjusted value for this January is 100,000/0.80=125,000.
If trading day or moving holiday effects are detected, their estimated factors are divided out of the series before seasonal factor estimation begins. The resulting seasonally adjusted series is therefore the result of dividing by the product of the trading day, holiday, and seasonal factors. The product factors are usually called the combined factors, although some tables refer to them as the seasonal factors for simplicity.
Question: What is X-12-ARIMA?
Answer: X-12-ARIMA is a seasonal adjustment program developed at the U.S. Census Bureau. The program is based on the Bureau's earlier X-11 program and the X-11-ARIMA/88 program developed at Statistics Canada.
Improvements to X-12-ARIMA include:
Use of ARIMA models to forecast the series, allowing us to use better, symmetric moving averages that give us generally smaller revisions to the seasonal factors;
New diagnostic tools; Wider variety of moving average options; and
New user interface.
For more information see X-12-ARIMA.
Question: What indicates a good quality seasonal adjustment?
Answer: No residual seasonal effect. Once we adjust the series for seasonality, there should be no remaining seasonal effect in the adjusted series. The seasonally adjusted series is the combination of the trend-cycle and the irregular. Neither of these components should contain seasonality.
Passing values for quality assessment diagnostics. We look for M7 and Q statistics less than 1.0. These diagnostics help us decide if X-12-ARIMA can adequately adjust the series. Stability (small revisions) of the estimates X-12-ARIMA contains several different stability diagnostics to help us select X-12-ARIMA options to keep revisions of the estimates low. Besides selecting the best X-12-ARIMA options, we can also reduce revisions by running X-12-ARIMA every month to get concurrent seasonal factors and by using ARIMA forecasts that make it possible to use symmetrical averaging formulas in the calculation of the seasonal factors, trend-cycle, and irregulars.
Question: Why do you revise seasonal factors?
Answer: There are two reasons that we revise seasonal factors:
We revise factors when we revise the unadjusted data to achieve a better fit to the revised data.
The estimate of a seasonal factor for a given month, say January 2005, is most strongly influenced by the data from surrounding Januaries (especially from 2004 and 2006). In 2005, when the January data for 2006 and later are not available, the seasonal factor estimate for January 2005 will be of reduced quality, unless X-12-ARIMA has calculated good forecasts of data for 2006 and later years and has used them in place of the data that is not yet available. In any case, when future data become available, we use them to obtain improved seasonal factor estimates for the most recent years of the series. These revised factors lead to revised seasonal adjustments of higher quality.
Question: Why can't I get the annual total by summing the
seasonally adjusted monthly values or by summing the annual rates for each month
or quarter of the year and dividing by 12 or 4?
Answer: When seasonal adjustment is done by dividing the time series by seasonal factors (or combined seasonal-trading day-holiday factors) it is arithmetically impossible for the adjusted series to have the same annual totals as the unadjusted series (except in the uninteresting case in which the time series values repeat perfectly from year to year). "Benchmarking" procedures can be used to modify the adjusted series so as to force the adjusted series to have the same totals as the unadjusted series, but these procedures do not account for evolving seasonal effects or for trading day differences due to the differing weekday compositions of different years.
Question: What is an indirect adjustment? Why is it used?
Answer: If an aggregate time series is a sum (or other composite) of component series that are seasonally adjusted, then the sum of the adjusted component series provides a seasonal adjustment of the aggregate series that is called the indirect adjustment. This adjustment is usually different from the direct adjustment that is obtained by applying the seasonal adjustment program to the aggregate (or composite) series. When the component series have quite distinct seasonal patterns and have adjustments of good quality, indirect seasonal adjustment is usually of better quality. Indirect seasonal adjustments are preferred by many data users because they are consistent with the adjustments of the component series.
Question: Does the Census Bureau make any adjustments to its
monthly retail estimates to account for leap year?
Answer: Yes. The Census Bureau's seasonal adjustment software, X-12 ARIMA, handles leap year as part of the trading-day adjustment for the monthly retail sales estimates. When using a multiplicative model and the td (trading day) option, the February estimates are rescaled before applying the log transformation. This rescaling multiplies a given February's estimate by the ratio of the average length of February (28.25 days) to the length of the given February (28 or 29 days). No trading day adjustments are applied to end-of-month retail inventory estimates; therefore, these estimates are not adjusted for leap year.
Page 39 of the X-12 ARIMA documentation (link below) provides a similar description of the leap year adjustment.
Source: Retail Indicators Branch, U.S. Census Bureau
Last Revised: April 30, 2009