Data in the Digital Age
IMF News, November 17, 2017
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- Published: November 17, 2017
New statistical challenges from digitalization
- Rapid technical advancement: reference to "In the 90s" and Moore’s Law reaching physical limits, while digital possibilities expand (cloud computing, big data, the internet of things).
- Examples of scale and change:
- Amazon amassing $135 billion in revenue last year.
- Twitter character limits: 140, and now 280 character tweets.
- Third-party mobile payments are growing toward $9 trillion dollars a year in China.
- The existence of 5 million smartphone apps and uncertainty whether they are reflected in volume indexes for software.
- Key measurement issues identified:
- Need to include online platforms and businesses they enable promptly in source data for economic statistics.
- Need for effective data-sharing arrangements between statistical agencies and other government producers of administrative data, such as tax authorities and regulators.
- Need for more data on the digital economy for national accounts and trade statistics.
- Update international classification systems for industries and products to guide incorporation of digital-economy source data and development of new statistics.
- Renewed push to update and maintain quality adjustment procedures of price statistics for ICT-related goods and services, including mobile telephony, broadband internet, streaming videos, international calling and messaging, and time spent online.
- Criticism that GDP and productivity statistics omit consumption of free services from digital platforms and neglect household production that uses digital technologies; this suggests a need for data on the welfare effects of digitalization.
- Statisticians must update compilation practices and develop new forms of data to capture non-market production in households (e.g., gig economy, sharing economy).
Role for developing countries
- Developing countries must be included in research on welfare effects of digitalization.
- Observation that impacts may be larger where prior access to phones and financial services was limited (example: East Africa).
- Implications for inequality are important and require measurement.
New statistical opportunities from Big Data
- Digitalization provides new opportunities beyond measurement improvements: use Big Data to explore economic relationships and policy effectiveness in ways previously impossible.
- Examples of large-scale research leveraging administrative data:
- Professor Raj Chetty’s work with vast databases from the Census Bureau and Social Security Administration tracking income trends of millions of people over 20-30 years.
- Findings include quantifying effects of moving neighborhoods on escaping poverty and influence of a third-grade teacher on lifetime earnings.
- Sources of information: troves held by governments, banks, internet companies, and others—some accessible, some not.
- Potential within the IMF:
- The Fund’s economists and statisticians do “superb work” with available data, and the Statistics Department helps governments develop compilation and analytical capabilities.
- The Fund needs to give serious thought to how Big Data will transform its work and may attract future students and specialists to help harness these data.
Measurement and valuation issues for GDP and transactions
- Quality versus price changes in ICT: example where a more powerful device costs the same as previous generation—question whether quality upgrade is adequately reflected in GDP numbers.
- Metadata and online retail: every purchase yields both a monetary transaction and an information-for-service exchange; each click and purchase produces vast information magnified across billions of transactions.
- Challenge: How to value transactions that include free internet services or information-provided-for-free—whether to treat them as the cost of a book or shoes or something of broader economic significance.
- Measuring free internet services and information-provided-for-free may represent significant value-added that is not currently captured in standard revenue or GDP measures.
Resource, collaboration, and communication needs
- Measuring the digital economy and capturing Big Data opportunities will require resources and collaboration:
- Need for budget and human capital resources well beyond current "old economy" capacities.
- Need for better communication between compilers and users of statistics.
- Need for data-reporting requirements for e-money transactions, including cross-border payments, to illuminate the unobserved economy.
Summary recommendations and priorities (as summarized by IMF First Deputy Managing Director David Lipton)
- Promptly include online platforms and platform-enabled businesses in source data.
- Establish effective data-sharing arrangements with administrative data producers (tax authorities, regulators).
- Provide more data for national accounts and trade statistics on the digital economy.
- Update international classification systems for industries and products for digital incorporation.
- Update and maintain quality adjustment procedures for ICT-related price statistics.
- Improve measurement of free digital services and household digital production; gather data on welfare effects of digitalization.
- Include developing countries in research on digitalization’s welfare and inequality impacts.
- Leverage Big Data to enhance understanding of economic relationships and policy effectiveness.
- Allocate increased budgetary and human capital resources and promote collaboration to realize these measurement and analytical advances.
IMF First Deputy Managing Director David Lipton — Speech, November 17, 2017