Credit Alex Robbins
Credit Alex Robbins
Statistics are a means, not an end, that should serve the public by helping us see the world more clearly and make better decisions
We live in a galaxy of data. From satellites and smartwatches to social media and swipes at a register, we have ways to measure the economy to an extent that would have seemed like science fiction just a generation ago. New data sources and techniques are challenging not only how we see the economy, but how we make sense of it.
The data deluge raises important questions: How can we distinguish meaningful signals of economic activity from noise in the age of artificial intelligence, and how should we use them to inform policy decisions? To what extent can new sources of data complement or even replace official statistics? And, at a more fundamental level, are we even measuring the metrics that matter most in today’s increasingly digital economy? Or are we simply tracking what we looked at in the past? This issue of Finance & Development explores these questions.
Author Kenneth Cukier suggests that harnessing alternative data requires a new mindset. He likens today’s economists to radiologists who once resisted having clearer MRI scans because they were trained to read fuzzier ones. Are we clinging to outdated metrics even as new data offers faster, granular, and sharper insights into economic reality and a better reflection of “ground truth”?
More data doesn’t automatically mean better insights or decisions. New or alternative data is often a by-product of private business activity, with all the biases of that environment. It may lack the long continuity and robust methods that underpin official economic indicators. That’s why official statistics remain essential.
Claudia Sahm shows how central banks are tapping new sources of data to fill gaps—including falling response rates to national surveys—but always in tandem with trusted official sources. To improve data quality, she calls for strong ties between statistical agencies, private providers, government officials, and academics. Relying on data sources not available to the public erodes transparency, which is critical to central bank accountability, she cautions.
For the IMF’s Bert Kroese, reliance on private data must not diminish resources available for official number crunching. Without strong, independent national statistical agencies, the integrity of economic data, and the policies built on it, could falter.
That’s not to say government agencies always get it right. Rebecca Riley argues that core economic metrics like GDP and productivity are increasingly misaligned with a rewired, data-driven economy. She calls for a modernization of measurement systems to better reflect the growth of intangible assets such as digital services, and the evolving structure of global production.
Better data collection serves the public good only if the data is widely available. Viktor Mayer-Schönberger warns that the concentration of data collection among a handful of Big Tech companies threatens competition and innovation. He makes the case for policies that mandate broader data sharing. Thijs Van de Graaf adds a geopolitical lens, revealing the material demands behind AI’s data hunger, from energy and chips to minerals and water, and how these pressures are reshaping global power dynamics.
Elsewhere, Laura Veldkamp discusses the value of data, raising questions about how we price, use, and share information, and proposes novel approaches to turn intangible data into something we can count. Jeff Kearns shows how innovative approaches like nowcasting are helping developing economies close information gaps. And the head of India’s statistical agency, Saurabh Garg, explains in an interview how he is tackling challenges of scale as public demand for real-time data grows.
This issue serves as a reminder that better measurement is not just about more data—it’s about using it wisely. In an era where AI amplifies both possibilities and noise, that challenge becomes even more urgent. To serve the public good, data must help us see the world more clearly, respond intelligently to complexity, and make better decisions. Data, after all, is a means not an end.
I hope the insights in this issue help you better understand the profound forces at play in our data-driven world. Thanks, as ever, for reading us.
To read the full issue, click here (pdf).
