The Economics of Data

IMF Blog, September 23, 2019

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Authors: Yan Carrière-Swallow, Vikram Haksar
Date: September 23, 2019
Central observation: Many valuable modern economic activities across industries and countries rely on the same indispensable input: data.
Illustrative examples from the text:
- An American company developing the next generation of driverless cars.
- A Chinese financier extending loans to “mom-and-pop” stores that used to lack access to credit.
- Researchers at a Swiss pharmaceutical company developing a treatment for a chronic health condition.
Noted firms and question: The value of data-intensive companies like Alibaba, Alphabet, and Facebook has shot up. Some ask whether data is the new oil?

Data as an economic input:
- Data is information; collecting and trading it creates and shifts information across companies and consumers.
- Data has become a key input in modern economic production alongside land, capital, labor, and oil.
- Data feeds artificial intelligence algorithms whose predictions power applications from driverless cars to drug testing to credit provision to ad targeting.
Ways data differs from other inputs:
- Non-rivalry: The same data can be used by many people simultaneously without being depleted, which means its accumulation stands a better chance of boosting productivity and long-run growth.
- Externalities on privacy and individual welfare: When personal data about someone is exchanged by two companies, the transaction impacts the person’s privacy and can leave them at a strategic disadvantage; if the person isn’t compensated or made aware, the data market can generate undue harm.
- Security and trust externalities: It is expensive to prevent theft or misuse of data. While firms have reputational incentives to avoid breaches, individual firms are unlikely to consider the impact of their decisions on the public’s trust in the broader data economy.

Access to more data can level the playing field (examples: a small startup getting a loan; a consumer informing themselves before purchasing a used car).
Data access can also produce harms (example: someone getting rejected for health insurance coverage or a mortgage because of their personal characteristics).
The value of data is unlocked when it can be accessed by many firms or researchers who then compete to innovate and generate knowledge.
Individual firm incentives may not align with socially optimal investment in data protection and with maintaining public trust in the data economy.

Opacity of data markets:
- Most people participate in the data economy daily but are not fully aware of how their data is used, transferred, and processed.
- Result: Too much data collection and too little privacy.
- Policy implication: Governments must clarify rights and obligations over data for markets to function efficiently.
Data hoarding and its competitive effects:
- Companies that build large datasets have an incentive to hoard them, potentially stifling competition and reducing social benefits from wider data access.
- Policy implication: Governments can deploy policies to encourage data sharing that promote competition and innovation, while respecting privacy.
Inadequate protection against theft and misuse:
- It is unclear that companies are doing enough to protect the data they hold, threatening public trust and creating risks to stability.
- Policy implication: Policy measures should mitigate these risks to ensure adequate investment in cybersecurity.

Modernize data policies to tackle three growing challenges: opacity, hoarding, and inadequate protection.
Clarify legal rights and obligations over data to reduce market opacity and improve privacy outcomes.
Encourage data sharing policies that promote competition and innovation, with privacy safeguards.
Strengthen measures to ensure adequate investment in cybersecurity and to protect public trust.
Integrated governance:
- Managing trade-offs across growth, privacy, competition, and stability will require cooperation among domestic agencies and an integrated approach.
International cooperation:
- Global cooperation is needed to ward off the risk that the digital economy becomes fragmented, with data access limited by national borders.
- Risk if countries don’t trust how global partners handle data: they may erect digital barriers that impede international data sharing, undermining innovation and efficiency.

The economics of data point to a promising future, provided policies are modernized and implemented to manage trade-offs and preserve cross-border data flows and trust.

Source: The Economics of Data — Yan Carrière-Swallow and Vikram Haksar, September 23, 2019.