Working Paper: CEPR ID: DP18668
Authors: Orlando Manuel da Costa Gomes; Roxana Mihet; Kumar Rishabh
Abstract: In today’s modern economy, data stands as a critical asset for firms, yet it is fraught with risks including loss and destruction. In this paper, we examine how data risk impacts firm growth, financial outcomes, and innovation activities. Examining the universe of U.S. publicly listed firms from 2000 to 2022, we find that higher data risk reduces knowledge stocks, decreases productivity, and lows growth for the average firm in the U.S. economy. Notwithstanding, there exists a select group of AI-intensive firms, highly exposed to data risk, which develop data protection strategies that enhance productivity in other domains. This positive spillover leads to higher innovation and profitability for these firms. The mechanism is that the same data engineers who develop data protection at these firms are also among the same inventors doing product innovation for these firms. In a second stage, we develop a structural heterogeneous-firm growth model of the data economy to rationalise the empirical findings and to provide some comparative statics exercises.
Keywords: data economy; data theft; data breaches; cyberrisk; growth; artificial intelligence; innovation
JEL Codes: D8; O3; O4; G3; L1; L2; M1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| cybercrime risk (K24) | lower economic performance (P17) |
| cybercrime risk (K24) | reduced knowledge stocks (D89) |
| cybercrime risk (K24) | decreased productivity (O49) |
| cybercrime risk (K24) | innovation rates (O39) |
| cybercrime risk (K24) | higher innovation outputs (O36) |
| innovation (O35) | increased productivity (O49) |
| cybercrime risk (K24) | slower overall economic growth (F69) |
| innovation in response to cybercrime risk (K24) | profitability outcomes (L21) |