August 13, 2025: When Power Decides What Counts
The authority of economic statistics rests on a fragile arrangement. The data must be produced inside the government but outside the reach of day-to-day political calculation. This separation is not decorative.
It recognises that the value of the numbers lies in their credibility — in the belief that they describe conditions as they are, not as those in power wish them to be.
That credibility is always in tension with political incentives. Economic indicators are, by design, a public scorecard on the performance of leadership. They shape markets, inform policy, and influence voters. For a political leader, a flattering number can be brandished as proof of competence; an unfavourable one can undermine the narrative of control. The temptation to cast doubt on inconvenient data, or to remove those responsible for producing it, is built into the structure.
The official line is that statistical agencies are neutral instruments. Their role is to apply consistent methods to consistent sources, delivering figures that can be compared over time. But the reality is more complex. Every measure rests on decisions about what to count, how to adjust, and when to publish.
Revisions are a feature of the process, not a flaw — an effort to reconcile timeliness with accuracy as more complete information arrives. In the hands of those seeking advantage, however, these revisions can be recast as proof of bias, their technical origins drowned out by political accusation.
The deeper danger is not that a single figure is altered but that the legitimacy of the entire apparatus is corroded. Once the perception takes hold that statistics are manipulated, even accurate data loses its authority.
Policymakers begin to second-guess the numbers they need to guide decisions. Markets become less certain about the reality they are pricing. The public, already inclined to distrust indicators that fail to match lived experience, is given another reason to see them as political artefacts.
Removing the leadership of a statistical agency in response to unfavourable results is a direct strike at the boundary between political authority and statistical integrity. It signals that the measure of economic reality is subject to the same pressures as any other political appointment.
Even if the machinery of data production remains intact — thousands of career staff applying established methods — the act shifts the balance. It teaches that those in power may attempt to define reality by selecting and discarding the people who oversee its measurement.
This incentive is amplified in periods of economic stress, when the divergence between official figures and public sentiment is most acute. A slowing economy, rising prices, or weak job growth can be explained away more easily if the trustworthiness of the statistics themselves is put in question.
The short-term political gain is obvious: reframe the problem as one of biased measurement rather than poor performance. But the long-term cost is a collapse in the shared framework that makes economic governance possible.
A statistical system that cannot be trusted will not be used. Without a common set of facts, there is no neutral ground on which to debate policy or judge outcomes. What replaces that ground is a contest of competing narratives, each armed with selective evidence, each claiming to be the true account. In such a contest, the question is no longer how the economy is doing, but who has the power to say what the economy is.