From the perspective of benchmarking fragility, comparing GDP figures derived from two different statistical series is not sufficient by itself to establish which figure is more representative of the underlying economy. The crucial question is whether the measured GDP and its growth rate are robust to the methodology, data construction, weighting scheme, deflators, and reference/base year used to produce the series.
A higher-order sensitivity analysis therefore needs to examine how much the reported GDP figure changes when these underlying measurement choices change. If a significant change occurs, the difference may reflect methodological or reference-point sensitivity rather than a fundamental change in the underlying economic activity.
Thus, the benchmark itself should also be treated as a model whose fragility must be tested. A GDP growth number should ideally be evaluated not only as a point estimate, but also for its stability across reasonable alternative methodologies and reference systems.
In this sense, the key issue is not simply “Which GDP series is correct?”, but rather:
“How robust is the reported GDP figure to the methodology and reference system used to construct it?”
This is the central benchmarking-fragility perspective: a statistical benchmark should not automatically be regarded as methodology-independent merely because it is officially calculated; its sensitivity to the measurement methodology framework should itself be tested.
Based on my published research work earlier
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