The value of data

The value of data Jan Eeckhout www.TheProfitParadox.com UPF Barcelona

OECD June 3, 2021

Data as Intangible Assets

• Data and Intangibles are increasingly important • Rise over time • Increasingly dispersed (few firms account for most investment in data)

• Data are also a tool to build market power • Far-reaching policy implications

Data and Intangibles: SG&A Broad category: R&D, advertising, marketing,... → data intensive .22

.2

.18

.16

.14

.12 1960

1970

1980

1990

2000

2010

Market Power No Change... in median markup

1.6

1.5

1.4

1.3

1.2

1.1 1960

1970

1980

1990

2000

2010

Market Power Increase in Average Markup since 1980

1.6

Average P50

1.5

1.4

1.3

1.2

1.1 1960

1970

1980

1990

2000

2010

Market Power All Action in Upper Half Distribution

2.5

Average P90 P75 P50

2

1.5

1 1960

1970

1980

1990

2000

2010

Market Power Profit Rate

.1

.08

.06

.04

.02

0 1980

1990

2000

2010

Market Power and Data

• Market power in all sectors, not just in the IT sector • But: the high markup firms in all sectors use IT/Data • Teulings-Van ’t Klooster (2021): natural language processing to classify firms • IT/Data firms: Amazon (retail), Inditex (textiles), Uber (transportation)

• The situation is even more pronounced due to accounting rules: • Firms with high Intangibles/Data have lower accounting profits – Gu, Lev, Zhu (2021) • R&D, Intangibles are booked as consumables, not investment

→ the high data firms increasingly have the most market power

Role of Intangibles: profit share .6

P25 P50 P75

2016

.4

.2

2000

1980

19802016

0

1990

1980 2016 2000 1990

2000

1990

-.2 .1

.2

.3

SG&A and Data Markups, Profits and SG&A

SG&A (log) R&D Exp. (log) Advertising Exp. (log)

(1) 0.56 (0.01)

Markup (log) (2) (3)

0.16 (0.01) 0.05 (0.00)

R&D dummy Advertising dummy R2 N

0.61 0.07 26,743

0.06 (0.01) -0.00 (0.03) 0.43 247,615

Profit Rate (log) (4) (5) 0.15 (0.03) 0.10 (0.01) 0.03 (0.01)

0.04 0.05 26,743

Market Power and Data • Firms use Data and Intangibles to build market power 1.

2.

3. →

High upfront investments (e.g. driverless cars) Creates huge dispersion in productivity (e.g. Inditex and Amazon) Consumers sell data at zero price Data is hero and villain

Market Power and Data • Firms use Data and Intangibles to build market power 1.

2.

3. →

High upfront investments (e.g. driverless cars) Creates huge dispersion in productivity (e.g. Inditex and Amazon) Consumers sell data at zero price Data is hero and villain

• Productivity mis-measured when market power: there is more productivity growth!

Market Power and Data • Firms use Data and Intangibles to build market power 1.

2.

3. →

High upfront investments (e.g. driverless cars) Creates huge dispersion in productivity (e.g. Inditex and Amazon) Consumers sell data at zero price Data is hero and villain

• Productivity mis-measured when market power: there is more productivity growth!

• Policy Proposal: 1. Data Openness – especially for firm-level data • Better functioning markets: more competition, transparency, trust (and reduces fraud) • Example: should have real time, detailed accounting data

2. Reverse Data Patent

Market Power and Data • Firms use Data and Intangibles to build market power 1.

2.

3. →

High upfront investments (e.g. driverless cars) Creates huge dispersion in productivity (e.g. Inditex and Amazon) Consumers sell data at zero price Data is hero and villain

• Productivity mis-measured when market power: there is more productivity growth!

• Policy Proposal: 1. Data Openness – especially for firm-level data • Better functioning markets: more competition, transparency, trust (and reduces fraud) • Example: should have real time, detailed accounting data

2. Reverse Data Patent

→ Data hoarding is the biggest threat to competitive markets

The value of data Jan Eeckhout www.TheProfitParadox.com UPF Barcelona

OECD June 3, 2021