This paper proposes a Narrative Daily Economic Index (NDEI) constructed from high-frequency economic news to measure economic conditions in near real time, addressing the lag inherent in standard macro indicators such as GDP or employment.
What is interesting from a macro perspective is that the contribution is not only informational, but structural: economic “state” is treated as something that evolves continuously in time, rather than being observed episodically through delayed aggregates.
This raises a broader question for macroeconomic modeling and measurement:
should time — and changes in time allocation, attention, and activity — be treated as an explicit object of measurement rather than remaining implicit or residual in aggregate statistics?
The paper fits into a growing literature questioning whether low-frequency aggregates are sufficient to capture structural change when non-market and behavioral components evolve faster than traditional indicators can reflect.
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This paper proposes a Narrative Daily Economic Index (NDEI) constructed from high-frequency economic news to measure economic conditions in near real time, addressing the lag inherent in standard macro indicators such as GDP or employment.
What is interesting from a macro perspective is that the contribution is not only informational, but structural: economic “state” is treated as something that evolves continuously in time, rather than being observed episodically through delayed aggregates.
This raises a broader question for macroeconomic modeling and measurement:
should time — and changes in time allocation, attention, and activity — be treated as an explicit object of measurement rather than remaining implicit or residual in aggregate statistics?
The paper fits into a growing literature questioning whether low-frequency aggregates are sufficient to capture structural change when non-market and behavioral components evolve faster than traditional indicators can reflect.