Project description
Utilising the knowledge of past technological changes to understand future impacts
The transformational power of innovation in information technology over the production process of firms is an undeniable fact. When this change affects the size and structure of a firm, it is called quantity-biased technological change (QBTC). The EU-funded TechChange project aims to study this type of technological change, and especially how it affects the workforce in terms of employment and wage inequality. TechChange uses a model with highly heterogeneous firms and workers and decreasing returns to firm size and revisits past periods of technological change and related policy interventions to gain insights for the future.
Objective
Technological change in information technology has the potential of transforming the production process of firms. Some processes such as automation affect workers directly, while others such as the introduction of automated workflow and control tools simply allow firms to grow to bigger sizes. We call the latter Quantity-Biased Technological Change (QBTC).
The existing literature has done relatively little to understand the effects of such technological progress that affects the size and structure of firms and thereby indirectly the workforce. We aim to study this type of technological change, and especially how it affects the workforce in terms of employment and wage inequality.
We aim to explore this intuitive idea in a model with highly heterogeneous firms and workers and decreasing returns to firm size. When technology enables firms to manage more workers, productive firms are now less limited by size considerations and tend to expand, affecting the marginal product of the workers. A preliminary calibration that aims to explains changes in the firm size, wage, and profit distribution in Germany over the last 15 years shows evidence of quantitative importance of the channel and its interaction with other effects, such as Skill-Biased Technological Change (SBTC). Yet there remain many obstacles: accounting for worker heterogeneity within the firm, exploring issues of market power, micro-founding the source of QBTC, and possibly linking it to new innovations such as the rise of artificial intelligence in firm management.
In addition, we propose to revisit past periods of technological change and related policy interventions to gain insights for the future. To achieve this, we discuss how to analyze the past impact on regions with different industrial and occupational compositions. On top, we aim to explore a novel methodology to identify which and how many workers will be affected.
Fields of science
Programme(s)
Funding Scheme
ERC-COG - Consolidator GrantHost institution
1348 Louvain La Neuve
Belgium