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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Page 63
Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Page 64
Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Page 65
Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Page 66
Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Suggested Citation:"4 Toward a Retail Satellite Account." National Academies of Sciences, Engineering, and Medicine. 2021. A Satellite Account to Measure the Retail Transformation: Organizational, Conceptual, and Data Foundations. Washington, DC: The National Academies Press. doi: 10.17226/26101.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Prepublication copy, uncorrected proofs 4 Toward a Retail Satellite Account This chapter starts with a summary of what satellite accounts are and then describes optional approaches that might be considered for a satellite account to describe the broader retail sector. It goes on to describe existing satellite accounts and how some of their features might illuminate the development of a retail-related satellite account. Information concerning satellite accounts was derived from the relevant literature and, most importantly, from the workshop organized by the panel to gather information. This included a background paper on satellite accounts in Canada produced by Philip Smith, Satellite Accounting in Canada (Smith, 2020). The fourth workshop session, entitled, “Toward a BLS Satellite Account for Retail,”75 was of key importance to this discussion. Other sessions relevant to the discussion were the third session, “Data: Availability, Needs, Discrepancies and Gaps,”76 and the fifth session, “Uses of Bottom-up in Measuring Employment and Productivity.”77 The latter two sessions were also discussed in Chapter 3. WHAT ARE SATELLITE ACCOUNTS AND HOW ARE THEY USED? Satellite accounts are described by Eurostat as accounts that provide “a framework for exploring some aspect of the economy that is linked to the System of National Accounts (SNA), allowing attention to be focused on a certain field or aspect of economic and social life in the context of national accounts.”78 Eurostat cites as common examples satellite accounts that focus on the environment, tourism, or unpaid household work. As Philip Smith details in his background paper, over the last three decades this method of accounting has gradually become popular around the globe. It first emerged in the 1980s as an idea, was set out formally in 1993, and was fully established in 2008 (Smith, 2020, p. 1). It is described more fully in Text Box 4-1. 75 Discussants included Brian Chansky, BLS; Tina Highfill, BEA; Philip Smith, Statistics Canada (retired); and Marshall Reinsdorf, International Monetary Fund; as well as panel members Leonard Nakamura and Carol Corrado. 76 Discussants included Ken Robertson, BLS; Jon D. Samuels, BEA; Matthew Russell, BEA; Ian Thomas, Census Bureau; and Edward Watkins, Census Bureau. The moderator was panel member Wesley Yung, Statistics Canada. 77 Presentation by panel members Teresa Fort, Dartmouth College; and John Haltiwanger, University of Maryland. 78 See https://ec.europa.eu/eurostat/statistics- explained/index.php/Glossary:Satellite_account#:~:text=Satellite%20accounts%20provide%20a%20framework,tour ism%2C%20or%20unpaid%20household%20work, page 1. This link is to introductory lecture notes on satellite accounts by Eurostat. 57

Prepublication copy, uncorrected proofs Smith regards the SNA as “an enormously successful framework for describing the world economy and the national and sub-national economies,” while noting that “no system can be all things to all people and the SNA certainly has its limitations” (Smith, 2020, p. 1). Its central concept, gross domestic product, is perhaps the best known and most widely used economic statistic available. Smith goes on to say: Satellite accounts offer a means of borrowing some of the best features of the international SNA while giving freedom to depart from some of its restrictions. Often people want to know the size of a particular activity, such as tourism or the digital economy, in relation to the total market economy. Satellite accounts provide a way of determining this. Alternative valuations can be adopted and the production boundary can be redefined. Product and industry classes can be recombined in other ways that may be more convenient for some purposes. Alternative, more familiar vocabulary can be adopted. And all of this can be done while linking directly into the large, internally consistent and carefully curated databases offered by the SNA. (Smith, 2020, p 2). Smith also cautions that “there are costs as well as benefits from moving away from the international standard SNA into satellite accounts. One country’s satellite account may not be easily comparable to another’s, and it may not be possible to aggregate satellite accounts from different countries. The Organization for Economic Cooperation and Development (OECD) and the United Nations are working to encourage some standardization, but standardization takes time and also conflicts with one of the major benefits of satellite accounting: its flexibility. In addition, satellite accounts are more vulnerable to political influence, since they often depend on outside financial and other support from their main clients.” Smith (2020, p. 21). A recent survey administered by Statistics Canada for the United Nations Economic Commission for Europe (UNECE), covered more than 80 countries and identified 241 satellite accounts. It was part of the work program of the Conference of European Statisticians, and its main objectives were to determine the extent of satellite accounting around the world and explore why and in what directions satellite accounting studies are increasing. According to Smith, The UNECE survey found that the most common topics addressed were tourism, environment and health. Primary reasons mentioned for developing these accounts were (1) giving greater prominence to a particular activity, (2) bringing more detailed statistics to an activity than are directly available in the core national accounts and (3) extending the conceptual boundaries in the core national accounts for production, consumption and/or assets. (Smith, 2020, p. 2). BOX 4-1 System of National Accounts The System of National Accounts (SNA) is the internationally agreed standard set of recommendations on how to compile measures of economic activity. The SNA describes a coherent, consistent, and integrated set of macroeconomic accounts in the 58

Prepublication copy, uncorrected proofs context of a set of internationally agreed concepts, definitions classifications, and accounting rules. In addition, the SNA provides an overview of economic processes, recording how production is distributed among consumers, businesses, government, and foreign nations. Consequently, the national accounts are one of the building blocks of macroeconomic statistics, forming a basis for economic analysis and policy formulation. The SNA is intended for use by all countries. SOURCE: From https://unstats.un.org/unsd/nationalaccount/sna.asp#:~:text=The%20System%20of%20N ational%20Accounts%20(SNA)%20is%20the%20internationally%20agreed,compile%20 measures%20of%20economic%20activity.&text=In%20addition%2C%20the%20SNA% 20provides,businesses%2C%20government%20and%20foreign%20nations. It may also be useful to consider how Eurostat, the statistical agency of the European Union, defines satellite accounts in its on-line glossary: Satellite accounts are one way in which the SNA may be adapted to meet differing circumstances and needs. They are closely linked to the main system but are not bound to employ exactly the same concepts or restrict themselves to data expressed in monetary terms. Satellite accounts are intended for special purposes such as monitoring the community’s health or the state of the environment. They may also be used to explore new methodologies and to work out new accounting procedures that, when fully developed and accepted, might become absorbed into the main system over time. Satellite accounts can meet specific data needs by providing more detail, by rearranging concepts from the central framework or by providing supplementary information. They can range from simple tables to an extended set of accounts in special areas like [for example,] environment or education.”79 An important question in setting up such an account is how to ensure that it is a place to experiment with new data and methodology while maintaining acceptable levels of error from a data user’s perspective. It is, by definition, a derived data product measuring selected economic concepts. The proposed development of a retail-related satellite account has a data quality objective: to improve the relevance of employment and productivity measures for retail. Another critical aspect of data quality is transparency. This argues for keeping users of the satellite account engaged and informed, and for providing them with information so that they can determine whether the data are fit for their use and provide feedback to further the development of the account. At the workshop, Steve Landefeld, former director of BEA, which has a long history of developing satellite accounts, noted that it is most important to address the underlying data from a statistical viewpoint, such as standard errors and replicability, as part of preparing such an 79 See https://ec.europa.eu/eurostat/statistics- explained/index.php/Glossary:Satellite_account#:~:text=Satellite%20accounts%20provide%20a%20framework,tour ism%2C%20or%20unpaid%20household%20work, page 1. 59

Prepublication copy, uncorrected proofs account for production. In BEA’s experience, useful questions to ask in addressing this include these: Can this be done in the new account with the same data quality as the current employment, productivity, or GDP? Does the new account get the trend right? If yes, does it get whether growth is high or low right? In its own development of satellite accounts, BEA employs the following criteria to assess data quality (see Box 4-2). BOX 4-2 AUDIENCES FOR A RETAIL RELATED SATELLITE ACCOUNT AND MEASURES OF EMPLOYMENT AND PRODUCTIVITY A primary concern among potential users of employment and productivity data is to be able to capture the transformational shifts in the sector, which is the same concern that has motivated BLS to consider a satellite account. Primary users of current statistics on the retail sector want to understand how retail productivity is changing and how it contributes to overall productivity; a retail-related satellite account could provide a perspective on these questions that better reflects the transformational shifts in the sector. These primary potential users of newly formulated estimates for employment and productivity include the following: Monetary, administration, and congressional authorities, who rely on data tracking changes in retail trade productivity. Monetary authorities use them in making projections of sustainable growth when formulating monetary policy. Administration and congressional authorities use them to assess sources of growth in the economy for making budget projections. For example, Triplett and Bosworth (2004, abstract) 60

Prepublication copy, uncorrected proofs analyzed services sector productivity, including communications, transportation, and the wholesale and retail trade, demonstrating the role of information technology in accelerating services sector productivity. The authors also highlighted the importance of making improvements within the U.S. statistical system to provide the more accurate and relevant measures essential for analyzing productivity and economic growth. Federal, state, and local government officials, who use federal data to assess issues related to tax policies and government regulations. For example, retail trade data are key to understanding the impact of COVID-19 and policies to assisted afflicted workers. Professional and trade associations, which use federal data to represent the retail industry in discussions about such areas as taxation and regulation. Institutional investors, which use federal data to provide a reality check on the short- and long-term prospects for an industry. Individual companies, which use federal data on retail trade to provide information on industry trends as a reality check for expansions, mergers and acquisitions, and other long-term investments. In addition to these primary uses of the newly formulated employment and productivity measures, a satellite account could support more detailed analyses that would benefit particular users and potentially lead to long-term improvements in the relevant employment and productivity statistics. Researchers use federal data to identify economic relationships that are not directly reflected in the reported statistics, such as contrasts related to firm size or between domestic and foreign-owned establishments. Macroeconomists are interested in measures that capture the dynamics of broad sectors of the economy. Individual retail companies may be interested in using the newly formulated measures in benchmarking themselves against the industry. In summary, a satellite account provides a useful and flexible mechanism for studying the expanded retail-related sector. CONCLUSION 4-1: A satellite account provides a framework to explore a specific aspect of the economy that is linked to the System of National Accounts while deviating in ways that help address important questions about that aspect of the economy. These deviations may involve grouping or valuing economic activities in different ways than the national accounts or providing more detailed statistics than are provided in the national accounts. DEFINING A RETAIL-SUPPORTING SECTOR Box 4-3 summarizes the options that were provided in advance of the workshop to participants in the session entitled, Towards a BLS satellite account for retail. These options 61

Prepublication copy, uncorrected proofs were initially presented in BLS (2020) to stimulate thought about how a satellite account might be structured. BLS observed that other options should also be considered. BOX-4-3 Four Alternative Definitions of a Retail-Related Sector The fundamental issue raised by the transformations in retail and the BLS charge to the panel involves the increasing integration of a range of wholesale, warehouse, and delivery functions into the services provided by retailers: here are four options for defining a retail-related satellite account. Distributional retail would include much or all of wholesale, retail, warehousing, and freight transportation. It might be defined as follows: All establishments engaged in the business of distributing goods from manufacturers, agriculture, resource extraction, and importers to users (including both firms and final consumers). It might include the following NAICS sectors: retail (44-45), wholesale (42), and transportation and warehousing (48, 49). A retail-supporting sector would include retail trade plus some elements of transportation, warehousing, wholesale trade, and business services that serve retail trade firms. It could be defined as all establishments in retail trade and establishments in specific NAICS codes in other sectors that primarily serve retail activities or customers. It might include retail (44, 45) plus the more detailed NAICS codes from 42, 48, and 49 that are specifically related to retail. It would likely require splitting some NAICS codes into retail-trade supporting and other. A retail-controlled sector would include retail trade establishments and other establishments, regardless of how classified, in enterprises primarily engaged in retail trade. Includes retail trade establishments (NAICS 42) as well as other establishments in enterprises classified into retail trade. Finally, an enterprise-based retail trade sector would include all establishments that are part of enterprises or firms primarily engaged in retail trade. Includes all enterprises classified in retail trade and their establishments, regardless of how classified. SOURCE: BLS (2020). Figure 4-1a is a diagram with a comparison of the distributional and retail-related sectors. It illustrates that these two options are related only to those NAICS codes that best describe the establishments within each option, not to the classification of their enterprises. Distributional is the simpler concept since it includes only major-sector NAICS designations. Figure 4-1b compares the retail-controlled and enterprise-based sectors. Both of these options make use of the classification of an enterprise as part of the definition. Here enterprise-based is the simpler concept, since it includes only those establishments located within a retail enterprise. Discussants observed that a distributional retail definition may be overly broad even though it would be the most straightforward to implement from a data point of view. However, starting with a distributional account and moving toward a version of retail-supporting may be a 62

Prepublication copy, uncorrected proofs good strategy, because starting with the simplest option helps to inform next steps and develop expertise. It could be called a case study to get initial results out so that users could provide input. One difficulty of this may be separating passenger transportation services from goods transportation, particularly for air travel. FIGURE 4-1a Comparison of distributional and retail-supporting industry codes. FIGURE 4-1b Comparison of retail-controlled and enterprise-based industry codes. 63

Prepublication copy, uncorrected proofs There are three major disadvantages of retail-controlled and retail-enterprise-based options. First, BLS does not have the information to develop enterprise-based statistics comparable to those produced by the Census Bureau. Second, an enterprise-based retail trade account would be outside the NAICS framework. Third, the sector definition would depend on vertical integration. Enterprise classifications, especially among complex firms, can change from year to year. This alone would make defining accounts based on enterprise classification undesirable for tracking trends. Additionally, discussants observed that the retail-controlled definition seemed too narrow, even though an enterprise-based one might be of interest to data users. Data issues with these two options are due to the fact that the data on enterprise classifications and links to their establishments are available only for approved projects through the Census Bureau at Federal Statistical Research Data Centers (FSRDCs). While data are available to approved outside researchers, obtaining a new data product for use in a satellite account would require collaboration, interagency agreements, and time. CONCLUSION 4-2: None of the four options on which to base a satellite account is perfect as it stands; however, a definition based on retail supporting is closest to what is needed according to the statement of work and most practical. Elements of the broader option, distributional, will also need to be incorporated into the newly defined retail-supporting sector, such as auxiliary establishments and parts of other industries, such as computing, intangibles, leasing, and importing. Identifying the precise definition(s) to be used for the retail-supporting sector will require exploration and experimentation. CONCLUSION 4-3: To better understand the changes in retail-trade-related industries, a collaborative effort between BLS, BEA, and Census staff could make use of microdata as a laboratory to better understand many of the complicated aspects of developing a retail-related satellite account. The purpose would be to use the concepts and data to gain a better understanding of key issues, such as assessing the structural changes associated with the retail trade transformation by size of enterprise; understanding the role of auxiliaries and other nonretail establishments within retail trade enterprises; and assessing data gaps and approaches to solving them. Splitting NAICS Codes Into Retail- and Non-Retail-Supporting As described under “retail-supporting” in Box 4-3, implementing a satellite account will likely require estimating the portion of the output and the portion of the input under some detailed NAICS codes in wholesale, transportation, warehousing, and others that are retail- related versus non-retail-related. In some cases, the contrasts between detailed NAICS codes can provide an indication of whether an industry is likely to support the retail sector. For industries that support several sectors, such as wholesale trade and transportation, there is some information available about the portion of output directed to retail in the NAICS classification system. Four-digit NAICS codes for wholesale trade often differentiate between consumer products (e.g., groceries, furniture and 64

Prepublication copy, uncorrected proofs home furnishing, motor vehicles, apparel, beer, and wine) and producer products (e.g., chemicals, farm raw materials, and raw metals and materials). An NAICS designation alone is not always sufficient to identify the contribution of retail- related establishments that partly support retail and partly support something else. For example, NAICS 481112 comprises establishments primarily engaged in providing air transportation of cargo (not passengers) over regular routes and on regular schedules. However, this cargo transportation may also support retail, wholesale, mail delivery, or something else. Beyond the NAICS codes of the establishments themselves, data from the Census Bureau’s economic surveys provide some information about the commodities an establishment deals in as part of its sources of revenue. Canada’s satellite accounts usually rely on Statistics Canada’s input-output tables. These satellite accounts typically rearrange information from those tables and add in additional detail from other sources. Statistical products based on input-output tables may have substantial delays in publication, so satellite accounts also need to be supplemented with more current indicators and projections. BEA satellite accounts are also typically developed from BEA input-output tables.80 These accounts are developed by first looking through the list of 5,000 goods and services to determine which are in-scope for the new project. Then BEA seeks to determine whether the whole commodity is within scope or only part of the commodity is. As described in the next section (“Existing Satellite Accounts”), one example is bicycles for the outdoor recreation account. As determined from an outside source survey, 93 percent of people who buy bicycles purchase them for outdoor recreation, the others may be purchasing them for business use, such as courier work. Input-output tables (in particular, the use tables) provide estimates of the proportion of output in services such as wholesale and trucking that are attributable to retail and the shares of intermediate inputs of goods and services purchased by the retail trade. They also provide estimates for changes in these proportions over time. The BEA input-output table starts with a gross output measure (gross margins for trade industries and gross sales for other industries) and uses the relationships found in the input-output table to determine a value-added number and then an employment number. This distribution of intermediate goods and services purchased by the retail trade could be used to develop a definition of retail-supporting industries, though it might not have the full NAICS code detail needed. While this provides one way to identify the split between retail and nonretail output, the proportions are unlikely to be the same for the labor that goes into those categories. It was observed that questions have been raised about the net impact of e-commerce on jobs and employment. Estimating how many people are working in retail and retail-supporting sectors, as well as estimating the net change in jobs and pay, would be very helpful by itself and useful for measuring productivity. Estimation of the split between retail-related and nonretail-related inputs will likely require some creative use of alternative data sources. Some companies81 may have internal 80 See https://www.bea.gov/resources/learning-center/what-to-know-industries. Input-output data are updated each year and provide information on 71 industry categories. Detailed benchmark input-output statistics, produced roughly every five years, are further subdivided into 405 industries. Data sources include the economic census, including a special tabulation on auxiliaries, ARTS, and other sources. The manual for input-output accounts is found here: https://apps.bea.gov/papers/pdf/IOmanual_092906.pdf. 81 Reported by Richard Phillips at the workshop. 65

Prepublication copy, uncorrected proofs worker-level data about what workers were doing—such as handling aircraft engines versus clothing. There may also be trade associations of delivery firms that collect this type of information. CONCLUSION 4-4: The retail-supporting sector definition will likely require splitting the currently measured input and output for some NAICS codes into retail- related and “other.” Options are available for splitting retail-related outputs. Using existing BEA’s input-output tables as well as those available in the BLS/BEA Integrated Labor Productivity Account may provide a start, and approaches that use existing data on commodities transported from the Commodities Flow Survey are also likely to be useful. However, this account will also need to develop new methods and data to estimate the split in input between retail-related and other, which will likely require experimentation and the development of new data sources. CONCLUSION 4-5: It is important to start with a relatively simple sector definition to develop expertise and communicate with users. The distributional option was mentioned as a possible starting point, but it was viewed as overly broad. Another useful starting point might be to start from the list of NAICS codes to be included in the expanded retail-supporting option, identifying those that are entirely retail-supporting or partly retail- supporting. An account that includes only those codes that are entirely retail-supporting and an account that includes all codes with some retail-supporting activity provide upper and lower bounds for what might be gained by a careful development of estimates for splitting the input and output of industries that are partly retail-supporting. The distribution of intermediate goods and services purchased by retail trade as measured in the BEA input-output tables could also be used to start the development of a definition of retail-supporting industries. The discussion of satellite accounts reinforced the importance of filling the data gaps identified in Chapter 3. The major new data gap identified during the discussion in Chapter 4 is the need to identify the proportion of input and output in selected NAICS codes that is retail- related, along with the key observation that the proportion is likely not the same for input and output. Developing the split for input will likely require new data sources and approaches. It is possible to start the project using the simple assumption that the input and output can be split using the same proportion, but it will be important to develop data to either confirm that assumption or to replace it with better estimates. EXISTING SATELLITE ACCOUNTS WITH POTENTIALLY USEFUL FEATURES BEA has prepared many of the satellite accounts in the United States.82 Similarly, Statistics Canada has prepared most of the satellite accounts in Canada (which are summarized in Smith, 2020). The workshop discussion identified the BEA satellite accounts discussed next as having features that may prove valuable in the design and implementation of a retail-related satellite account. 82 See https://www.bea.gov/data/special-topics for links to the BEA satellite accounts. 66

Prepublication copy, uncorrected proofs BEA states83 that it developed the digital economy satellite account to better capture the effects of fast-changing technologies on the U.S. economy and on global supply chains. The project calculates the digital economy’s contribution to U.S. GDP and improved measures of high-tech goods and services, and it offers a more complete picture of international trade. Other goals are to advance research for digital goods and services, the sharing economy, and free digital content, and to explore economic measures beyond GDP to better understand Americans’ well-being. BEA includes in its definition of the digital economy three major types of goods and services: Infrastructure, or the basic physical materials and organizational arrangements that support the existence and use of computer networks and the digital economy; primarily information and communications technology (ICT) goods and services; E-commerce, or the remote sale of goods and services over computer networks; and Priced digital services, or those services related to computing and communication and that are performed for a fee charged to the consumer. The BEA digital economy satellite account already addresses some retail areas and illustrates a flexible use of sources to allocate different industries into digital and nondigital pieces. This account required the organization of a new sector from the ground up. The OECD has guidance for developing a digital economy satellite account that may be worth reviewing in developing a satellite account for retail trade.84 As summarized by BEA,85 BEA developed a set of supplemental statistics called the health care satellite account to better measure spending trends and treatment prices. This satellite account measures U.S. health care spending by the diseases being treated (for example, cancer or diabetes) instead of by the types of goods and services purchased (such as doctor’s office visits or drugs). At the same time, BEA continues to produce the traditional goods-and-services health care estimates that are part of its core statistics, such as GDP. Within this satellite account, there are two different sets of disease-based statistics. One version uses data from the Medical Expenditure Panel Survey, the only nationally representative survey that contains detailed expenditure information by disease. BEA calls this the MEPS Account. Because of its relatively small sample size, the MEPS Account produces more volatile estimates across years. To address this issue, BEA also produces a ‘Blended Account,’ which blends together data from multiple sources, including large claims databases that cover millions of enrollees and billions of claims. The BEA outdoor recreation satellite account “measures the economic activity as well as the sales or receipts generated by outdoor recreational activities, such as fishing and vacation travel by recreational vehicle. These statistics also measure each industry’s production of 83 See https://www.bea.gov/data/special-topics/digital-economy. 84 See https://www.oecd.org/sdd/its/Handbook-on-Measuring-Digital-Trade-Version-1.pdf. 85 See https://www.bea.gov/data/special-topics/health-care. 67

Prepublication copy, uncorrected proofs outdoor goods and services and its contribution to U.S. GDP. Industry breakdowns of outdoor employment and compensation are also included.”86 The BEA outdoor recreation satellite account had to apportion many commodities between “recreation” and “something else,” in ways similar to what will be needed in the retail- related satellite account. BEA used about two dozen data sources to do this, including a survey that measured whether purchased bicycles were for recreational or business use. This satellite account may be especially relevant because there was no precedent about how an outdoor recreation sector should be defined, but there were strong views. BEA ended up having two definitions, one narrow and one broad. The outdoor recreation account might be a guide in how to allocate output according to input-output relationships versus outside sources. Finally, a new satellite account is being developed by BEA, the Small Business Administration, Statistics Canada, and the University of Pennsylvania (Highfill et al., 2020) to better track the overall growth and relative contributions of small business in the U.S. economy. A main challenge with this account is identifying the portion of gross output from manufacturing firms attributable to very small businesses. Tina Highfill, of BEA, highlighted this account because some users wanted enterprise-level statistics, which pose data challenges. While some data are available, data on enterprises and their establishments are only available in the Census Bureau’s business register, which makes them challenging to access except for approved projects through an FSRDC. Another set of satellite accounts that may provide guidance on splitting transportation NAICS codes into retail-supporting vs. other is the Bureau of Transportation Statistics’ (BTS) Transportation Satellite Accounts, prepared by BTS in collaboration with BEA.87 CONCLUSION 4-6: Several existing BEA satellite accounts may provide useful models for developing a retail satellite account, given the measurement challenges posed by the retail transformation. The digital economy satellite account includes e-commerce and digital services, which are both important aspects of the retail transformation. The health care satellite account involves a reconceptualization of health care spending, which might suggest novel ways to reflect the changing cost structure of retail. The outdoor recreation satellite account addresses the challenge of dividing up statistics from several industries to combine some of them in a new grouping that is useful to the field. The small business satellite account addresses the challenge of identifying establishments of different sizes, which may also be an important way to divide the data for the retail sector. 86 See https://www.bea.gov/data/special-topics/outdoor-recreation. 87 See https://www.bts.gov/satellite-accounts. 68

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Retail trade has experienced dramatic changes over the past several decades in the United States, with changes in the types of outlets where goods are sold, the nature of the transactions that provide goods to consumers, and the structure of retail operations behind the scenes. The recent changes include the rise of warehouse stores and e-commerce and the further growth of imports and large retail chains. These changes highlight and typify many aspects of the broader evolution of the economy as a whole in recent years - with the growing role of large firms and information technology - while taking place in a sector that directly serves the vast majority of the American population and provides substantial employment.

Despite the everyday experience of these dramatic changes in retail, there is concern that the most transformational aspects of those changes may not be captured well by the economic indicators about the sector. In order to develop appropriate economic policies, we need to be able to capture more detailed data, including data about changes to productivity.

At the request of the U.S. Bureau of Labor Statistics, this report evaluates changes in the retail trade sector, assesses measures of employment and labor productivity for the sector, and recommends a new satellite account that could measure retail-related employment and labor productivity in ways that would better capture the transformation.

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