Statistical Work on Digital Economy for the U.S. National Accounts
UNSD‐NBS Seminar on The Digital Economy: A Policy and Statistical Perspective
Beijing, China
November 15‐17, 2018
Presented by Dylan G. Rassier
Focus on Two Areas of Preliminary Work
• Digital Economy Satellite Account
• Treatment of Data in National Accounts
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Digital Economy Satellite Account(Barefoot, Curtis, Jolliff, Nicholson, Omohundro 2018)
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Step 1: Conceptual Definition
• Digital‐enabling infrastructure: Goods and services needed for an interconnected computer network to exist and operate
– Computer hardware – Software– Telecom equipment and services – Structures– Internet of Things (IoT) – Support services
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Step 1: Conceptual Definition
• Digital‐enabling infrastructure: Goods and services needed for an interconnected computer network to exist and operate
– Computer hardware – Software– Telecom equipment and services – Structures– Internet of Things (IoT) – Support services
• E‐commerce: Digital transactions that use the computer system– Business‐to‐business (B2B) – Peer‐to‐peer (P2P)– Business‐to‐consumer (B2C)
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Step 1: Conceptual Definition
• Digital‐enabling infrastructure: Goods and services needed for an interconnected computer network to exist and operate
– Computer hardware – Software– Telecom equipment and services – Structures– Internet of Things (IoT) – Support services
• E‐commerce: Digital transactions that use the computer system– Business‐to‐business (B2B) – Peer‐to‐peer (P2P)– Business‐to‐consumer (B2C)
• Digital media: Content that users create and access– Direct sale – Big data– Free
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Steps 2 and 3: Identification
• Step 2: Identify digital goods and services– 200 categories of primarily digital products
• Exclude categories that include digital and non‐digital• Exclude structures and IoT infrastructure• Exclude P2P transactions• Exclude advertising‐supported “free” digital media and big data
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Steps 2 and 3: Identification
• Step 2: Identify digital goods and services– 200 categories of primarily digital products
• Exclude categories that include digital and non‐digital• Exclude structures and IoT infrastructure• Exclude P2P transactions• Exclude advertising‐supported “free” digital media and big data
• Step 3: Identify digital industries– Gross output: Sum of gross output for all in‐scope products– Value‐added– Compensation– Employment– Price and quantity indexes: Double deflation method
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Derived from ratios of digital economy gross output to total gross output
Results: Growth Rates
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Total Economy Digital Economy
Gross Output 1.1% 4.4%Value‐Added 1.5% 5.6%Prices 1.5% ‐0.4%Employment 1.7% 3.7%U.S. Bureau of Economic Analysis
Average Annual Growth
0% 2% 4% 6% 8% 10% 12% 14%
Agriculture, forestry, fishing, and hunting Arts, entertainment, and recreation
Educational services Mining Utilities
Management of companies and enterprises Other services, except government Accommodation and food services
Transportation and warehousing Administrative and waste management services
Construction Information Retail trade
Wholesale trade Digital economy
Professional, scientific, and technical services Health care and social assistance
Finance and insurance Manufacturing Government
Real estate and rental and leasing
U.S. Bureau of Economic Analysis
Results: Share of GDP
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Share of total gross domestic product, 2016
The digital economy accounted for 6.5% ($1.21 trillion) of total U.S. GDP in 2016.
Results: Employment
110% 5% 10% 15% 20%
Utilities
Mining
Agriculture, forestry, fishing, and hunting
Real estate and rental and leasing
Management of companies and enterprises
Arts, entertainment, and recreation
Information
Educational services
Transportation and warehousing
Digital economy
Wholesale trade
Finance and insurance
Construction
Other services, except government
Professional, scientific, and technical services
Administrative and waste management services
Manufacturing
Accommodation and food services
Retail trade
Health care and social assistance
Government
U.S. Bureau of Economic Analysis
Share of total employment, 2016
In 2016, the digital economy supported 5.9 million jobs, or 3.9 percent of total U.S. employment.
$0 $50,000 $100,000 $150,000
Accommodation and food services
Retail trade
Agriculture, forestry, fishing, and hunting
Other services, except government
Administrative and waste management services
Arts, entertainment, and recreation
Educational services
Health care and social assistance
Real estate and rental and leasing
Transportation and warehousing
Construction
Government
Manufacturing
Wholesale trade
Professional, scientific, and technical services
Digital economy
Information
Finance and insurance
Mining
Management of companies and enterprises
Utilities
U.S. Bureau of Economic Analysis
Results: Compensation of Employees
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Average annual compensation per employee in the digital economy totaled $114,275 in 2016 compared to $66,498 for the total economy.
Average annual employee compensation, 2016
Treatment of Data in National Accounts
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SNA Recommendations on Data
• Databases are within scope of the SNA asset boundary– Exclude value of data in own‐account databases– Include value of data in market purchases of databases
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SNA Recommendations on Data
• Databases are within scope of the SNA asset boundary– Exclude value of data in own‐account databases– Include value of data in market purchases of databases
• Data as capital formation– Canberra II Group focused on data as a knowledge asset (Ahmad 2004, 2005 and Ahmad and Schreyer 2016)
– Is data a knowledge asset or an information asset like R&D?
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SNA Recommendations on Data
• Databases are within scope of the SNA asset boundary– Exclude value of data in own‐account databases– Include value of data in market purchases of databases
• Data as capital formation– Canberra II Group focused on data as a knowledge asset (Ahmad 2004, 2005 and Ahmad and Schreyer 2016)
– Is data a knowledge asset or an information asset like R&D?
• No guidance on data as intermediate consumption– May be exchanged in traditional B2B transactions– May be exchanged in non‐traditional C2B transactions
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Considerations for Data
• Ownership of data may depend on institutional factors– Who should have access?– How should access be managed?
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Considerations for Data
• Ownership of data may depend on institutional factors– Who should have access?– How should access be managed?
• Non‐rival features of data– Supply‐use identity does not hold (Mandel 2017)– Non‐scarcity: fusion, no wear and tear
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Considerations for Data
• Ownership of data may depend on institutional factors– Who should have access?– How should access be managed?
• Non‐rival features of data– Supply‐use identity does not hold (Mandel 2017)– Non‐scarcity: fusion, no wear and tear
• Third product category for data (Mandel 2012, 2017)– Goods: tangible and storable– Services: intangible and non‐storable– Data: intangible and storable
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Roles of Data
• Marketing– Users exchange data for “free” content
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Roles of Data
• Marketing– Users exchange data for “free” content
• Artificial intelligence– Output = f(capital, labor, data)
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Roles of Data
• Marketing– Users exchange data for “free” content
• Artificial intelligence– Output = f(capital, labor, data)
• Internet of Things (IoT)– “Smart” devices
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Roles of Data
• Marketing– Users exchange data for “free” content
• Artificial intelligence– Output = f(capital, labor, data)
• Internet of Things (IoT)– “Smart” devices
• Online platforms (Li, Nirei, Yamana 2018)– Summarize business models for 8 types of platforms
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Data Value Chain
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Source: Moro Visconti et al. 2017
Financials for FATWINs and MAGAs
• Facebook• Twitter• Netflix
• Microsoft• Amazon• Google• Apple
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Source: SEC filings and YCharts
B2C:social media,entertainment
B2B:cloud computing,hardware
Stats Canada‐BEA Collaboration on Data
• Five Questions– What is the role of data in a modern economy?– What is an appropriate typology of data?– What is the current state of play in valuing data in the national accounts and how are data valued by the private and public sectors?
– What are the different methods that national statisticians could use to assign a value to data?
– What specifically is the value of data in Canada and the United States?
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Stats Canada‐BEA Collaboration on Data
• Five Questions– What is the role of data in a modern economy?– What is an appropriate typology of data?– What is the current state of play in valuing data in the national accounts and how are data valued by the private and public sectors?
– What are the different methods that national statisticians could use to assign a value to data?
– What specifically is the value of data in Canada and the United States?
• Typology for online platforms (Li, Nirei, Yamana 2018)27
References
• Ahmad, Nadim. 2004. “The Measurement of Databases in the National Accounts.” Issue paper prepared for the December 2004 Meeting of the Advisory Expert Group on National Accounts.
• Ahmad, Nadim. 2005. “Follow‐Up to the Measurement of Databases in the National Accounts.” Issue paper prepared for the July 2005 SNA Update Issue 12.
• Ahmad, Nadim and Paul Schreyer. 2016. “Measuring GDP in a Digitalized Economy.” OECD Statistics Working Paper 2016/07.
• Barefoot, Kevin, Dave Curtis, William Jolliff, Jessica R. Nicholson, and Robert Omohundro. 2018. “Defining and Measuring the Digital Economy.” BEA Working Paper: https://www.bea.gov/system/files/papers/WP2018‐4.pdf.
• Li, Wendy, Makoto Nirei, and Kazufumi Yamana. 2018. “Value of Data: There is no such thing as a free lunch in the digital economy.” Paper prepared for the 2018 IP Statistics for Decision Makers Conference.
• Mandel, Michael. 2012. “Beyond Goods and Services: The (Unmeasured) Rise of the Data‐Driven Economy.” Policy Memo of the Progressive Policy Institute.
• Mandel, Michael. 2017. “The Economic Impact of Data: Why Data is not Like Oil.” Paper of the Progressive Policy Institute.
• Moro Visconti, Roberto, Alberto Larocca, and Michele Marconi. 2017. “Big Data‐Driven Value Chains and Digital Platforms: From value co‐creation to monetization,” in Big Data Analytics, Arun K. Somani and Ganesh Chandra Deka, eds., Chapter 16.
• Nijmeijer, Henk. 2018. “Issue Paper on Databases.” Paper prepared for the Joint Eurostat‐OECD Task Force on Land and Other Non‐Financial Assets.
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