Cloud Adoption and Firm Performance: Evidence from Labor Demand

65 Pages Posted: 26 Apr 2022 Last revised: 20 Feb 2024

See all articles by Wang Jin

Wang Jin

Stanford Digital Economy Lab

John (Jianqiu) Bai

Northeastern University - D’Amore-McKim School of Business

Date Written: July 25, 2022

Abstract

Using novel measures that capture investment in cloud technologies based on firms’ labor demand, we show that cloud adoption is associated with significant productivity gains for a large sample of US public firms in the last decade. This finding is robust to a range of cloud-related measures, samples, and specifications controlling for time-varying industry and firm-level transitory shocks. Various methods including control function, dynamic panel, and instrumental variable are further employed to address potential endogenous choices of cloud-related labor demand. Robust results from these methods suggest that the identified productivity-enhancing effect is likely causal. More importantly, by employing the newly developed Difference-in-Differences (DiD) estimator for the staggered roll-out and heterogeneous effects of treatment, we show that the adoption of cloud is associated with about 6.9% higher sales in the long run. This effect is statistically significant, economically large, and increases over time, indicating potential organizational learning and complementary investment. This study is thus among the first to provide large-scale firm-level evidence concerning both short-term and long-term effects of cloud technologies on firm performance.

Keywords: Cloud Adoption, Labor Demand, Firm Productivity, Difference-in- Differences (DiD), Aggregate Group-Time Average Treatment Effects

JEL Classification: L2, M2, D22, D24, O33

Suggested Citation

Jin, Wang and Bai, John (Jianqiu), Cloud Adoption and Firm Performance: Evidence from Labor Demand (July 25, 2022). Available at SSRN: https://ssrn.com/abstract=4082436 or http://dx.doi.org/10.2139/ssrn.4082436

Wang Jin (Contact Author)

Stanford Digital Economy Lab ( email )

Stanford, CA 94305
United States

John (Jianqiu) Bai

Northeastern University - D’Amore-McKim School of Business ( email )

360 Huntington Ave.
Boston, MA 02115
United States

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