Classical capital theory does not account for the properties of data — and that gap is increasingly a governance and policy problem.
The data-as-capital thesis is not settled in economic theory, and that theoretical gap is now producing material distortions in antitrust practice, national competitiveness policy, and firm valuation.
“Classical capital theory does not account for the properties of data, and that gap is increasingly a governance and policy problem”
Governments designing AI competitiveness strategies focus on compute infrastructure, talent pipelines, and R&D funding, inputs legible under existing capital accounting. The data accumulation advantage held by incumbent platform firms is structurally harder to address because no framework currently defines it as a policy variable. A jurisdiction solving for a partial version of the challenge will find that the compounding happened elsewhere.
Economy 4.0 demands new analytical frameworks, not adaptations of frameworks built for physical capital in an industrial economy. The research opportunity is specific: does data capital depreciate, and through what mechanism? What does differential accumulation imply for market concentration theory? How should data assets be valued for taxation and regulatory review? These are open questions with direct policy implications, and the rigour with which they are constructed will determine whether digital economy governance is fit for purpose.
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