Working Paper: NBER ID: w28427
Authors: Maryam Farboodi; Laura Veldkamp
Abstract: In a data economy, transactions of goods and services generate information, which is stored, traded and depreciates. How are the economics of this economy different from traditional production or innovation economies? How do these differences matter for measurement of GDP, firm values, depreciation rates, welfare and externalities? Despite incorporating active experimentation and data as an intangible asset, we devise a tractable recursive representation. Because the resulting model maps to many observable macro and finance measures, it can be calibrated and estimated like its old-economy DSGE counterpart. The model also delivers insights: It rationalizes why apps are often “free,” why firm size is diverging and why even non-digital economic activity might be greater than GDP suggests.
Keywords: Data Economy; GDP Measurement; Firm Valuation; Welfare; Externalities
JEL Codes: O3; O4
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| data accumulation (C80) | firm output (D21) |
| firm actions (L10) | data generation (C80) |
| data generation (C80) | future production capabilities (D25) |
| data (Y10) | productivity (O49) |
| data feedback loop (C45) | increasing returns (I26) |
| data (Y10) | economic growth (O49) |
| excessive data production (D20) | welfare concerns (I30) |
| data (Y10) | diminishing returns (D29) |