## THE PULSE OF THE PLANET ## Source details **Canonical URL:** [THE PULSE OF THE PLANET](https://www.imf.org/-/media/files/publications/fandd/article/2025/12/cukier.pdf) ## Other formats - [Markdown version](/-/media/files/publications/fandd/article/2025/12/cukier.pdf.md) - [Structured JSON version](/-/media/files/publications/fandd/article/2025/12/cukier.pdf.json) --- The explosion of data offers new ways to understand the economy—and change what gets measured, not just how Kenneth Cukier ### Big data and the need for a new mindset - Economists must move beyond a “déformation professionelle” that views the economy through the constraints of a “small data” world; the variety, frequency, and granularity of modern data require a new mindset. - Digitization means activities that could not be easily rendered into data before now can be measured, enabling indicators that are: - More accurate (a better reflection of ground truth) - Faster (potentially quasi real time) - More granular (down to small segments or even individuals) - The rise of private-sector data producers implies statistical agencies may need to shift responsibilities from sole generators of information to partners that work with firms to bolster and validate data integrity. ### Historical analogy and resistance to better measurement - Analogy: General Electric’s 1990 MRI software update produced more accurate images that radiologists resisted because their skills had been honed to the older, compressed scans—illustrating how practitioners can prefer familiar, less-accurate information. - The article poses the risk that economists may similarly resist improved data and new indicators. ### Alternative indicators ("alt‑data") and examples - Alt-data often lack the academically rigorous methods of state statistical agencies and may be compiled from private-sector activities (data exhaust). - Examples and specific figures: - ADP handles one in six US workers and provides a monthly jobs report used to supplement the US Bureau of Labor Statistics. - LinkedIn’s “economic graph” measures the work activities of 1.2 billion people, 67 million companies, 15 million jobs, 41,000 skills, and 133,000 schools. - PriceStats tracks changes in 800,000 daily prices from among 40 million products in 25 economies. - Carlyle, a private equity fund, managed 277 companies with 730,000 employees and provided employment trends during the US government shutdown in October 2025. - Intuit produced a small-business index based on QuickBooks data, discontinued it in 2015, and relaunched with a different methodology in 2023. - Alt-data can detect early signs of economic stress (examples given: declines in new employees from payroll firms, slowdown in Google searches related to home purchases, recruitment ad pulls on LinkedIn/Indeed). ### Performance of official statistics versus alt‑data (2008 example) - During the 2008 financial crisis, anecdotal signals (“anecdata”) preceded official revisions: - Initial US GDP release for Q4 2008: decline of 3.8 percent. - First revision a month later: drop of 6.2 percent. - Final revision in July 2011: recalculated as a fall of 8.9 percent—the largest downward revision of GDP on record. - The piece argues alternative indicators might have provided faster and more-detailed early warnings. ### Uses in crises and transparency - Alt-data flourished at the outset of the COVID-19 pandemic: GPS in Apple and Android phones measured declines in visits to retailers and identified compliance with lockdowns. - During data outages (example: US government shutdown in October 2025), private-sector sources filled reporting gaps. - Alt-data can hold governments accountable where official statistics are questioned (example: The Economist using PriceStats when Argentina’s official inflation data were unreliable; concerns about US data integrity after the head of the Bureau of Labor Statistics was fired by President Donald Trump in August 2025). ### Potential in developing economies - Private-sector data can help overcome institutional and funding constraints in low-income settings. - Example innovation: using mobile operators’ cell tower signal weakening in rain as a proxy for measuring rainfall where meteorological equipment is unaffordable. ### Limits, biases, and durability of corporate data - Corporate data often constitute “data exhaust” and carry the biases of their originating environment: - Carlyle’s portfolio firms may not be representative if weaker or privately owned. - LinkedIn likely skews toward professionals and may underrepresent working-class populations. - ADP data do not reflect the gray economy (nannies, house cleaners, car washers). - Corporate data sources can disappear or change methodology (example: Intuit’s discontinuation in 2015 and relaunch in 2023). - The article emphasizes the future will rely on complementary official and unofficial sources, not alt-data alone. ### Privacy-preserving techniques and limits - Advanced techniques can enable analysis without exposing individual records: - Federated learning - Homomorphic encryption - Secure multiparty computation - Differential privacy - These methods are nascent and technically challenging, but companies and statistical offices are experimenting with them. ### Modern metrics, ethical considerations, and privacy tradeoffs - Proposal for a “modern metric” of individual economic distress that aggregates granular signals: - Shifts in spending patterns (e.g., switching from steak to ramen) - Missed utility bills and overdue car payments - Incidents of road rage, erratic driving, and fender benders at the individual level - Biometric and behavioral indicators (Apple Watch sleep and stress metrics, CCTV facial-recognition emotion tracking, toilets with biosensors measuring hormones like cortisol and epinephrine) - The article highlights the proximity of such data to “ground truth” and notes severe privacy implications; such intrusive measures raise ethical questions about state intervention and individual protection. - Cultural and political resistance ("techlash") may slow adoption; paradigms change slowly. ### Policy implications and practitioner guidance - Statistical offices and economists should: - Reimagine what truth to record, not just how to record it. - Partner with the private sector to validate and bolster the integrity of corporate data for public use. - Combine official statistics with alt-data to improve timeliness, granularity, and coverage—especially during crises and in developing economies. - Experiment with privacy-preserving analytics to balance usefulness with individual privacy. - Remain mindful of biases inherent in corporate data and the risk of overreliance on sources that may be temporary or unrepresentative. *Kenneth Cukier, “The Pulse of the Planet,” F&D, December 2025.* --- _Source: https://www.imf.org/-/media/files/publications/fandd/article/2025/12/cukier.pdf_