Template-Type: ReDIF-Paper 1.0
Title: Big Data and Inequality
Author-Name: Carl-Christian Groh
Author-Email: carlchristian.groh@gmail.com

Classification-JEL: D21, D81, E24, J24
Keywords: inequality, big data, uncertainty, wages

Abstract: This paper studies the distributional consequences of the increasing importance of (big)
data in modern economies. I consider a simple theoretical model in which firms produce
output using capital and labor. Firms can hire labor on the spot market, but
must choose their capital stock for a given period in advance and under uncertainty
regarding their future profitability. Access to data resolves this uncertainty, thereby
primarily increasing the aggregate demand for and the remuneration of capital. Furthermore,
the increased demand for capital crowds out labor demand by reducing the
price of the output goods, which reduces aggregate labor income. By an analogous
logic, the rising availability of data can also increase the skill premium, given that
firms can adjust their unskilled labor input more easily than their skilled labor input.

Note: 
Length: 48
Creation-Date: 2024-06
Revision-Date: 
File-URL: https://www.crctr224.de/research/discussion-papers/archive/dp555
File-Format: application/pdf
Handle: RePEc:bon:boncrc:CRCTR224_2024_555