Solow's Productivity Paradox and Technologically Induced System-Maintenance Effort

This working paper develops a falsifiable theoretical and methodological model for interpreting Solow’s productivity paradox as a net-balance problem of technological complexity. The starting point is the observation that digital technologies, automation, artificial intelligence, and information systems are increasingly visible across modern economies, while aggregate productivity statistics often fail to show proportional gains. Instead of treating this gap solely as a measurement, diffusion, or implementation problem, the paper proposes an explicit distinction between the gross technological benefit of innovation and the systemic maintenance effort required to operate, control, integrate, secure, document, and regulate the complexity generated by that innovation. The central model extends a conventional production-function framework by introducing a net technology factor. Technological gross benefit is modeled as a function of system complexity, while technologically induced system-maintenance effort is treated as an absorptive factor that may reduce observable net productivity. The model distinguishes technical maintenance effort from regulatory and organizational maintenance effort and provides a formal structure for forward calculation, backward inference, proxy development, and falsification. The paper does not claim to provide a completed empirical proof. Instead, it offers a reproducible research framework and validation protocol. It identifies measurable variables and proxies, discusses test cases from production, banking, healthcare, construction-permitting processes, and regulatory absorption, and formulates conditions under which the model would be supported, weakened, or falsified. The contribution of the paper is the formalization of a system-theoretical mechanism that may help explain why technological progress can be locally effective while appearing only weakly in aggregate productivity measures: part of the gross benefit of technology may be absorbed by the effort required to maintain the complexity it creates. This version is intended as a working-paper release for discussion, critique, and further empirical validation.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-29
DOI
https://doi.org/10.5281/zenodo.20450554
Primary Topic
Digital Platforms and Economics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Solow's Productivity Paradox and Technologically Induced System-Maintenance Effort

Rudolf Schaefer
Zenodo (CERN European Organization for Nuclear Research)
Digital Platforms and Economics
preprint

Solow's Productivity Paradox and Technologically Induced System-Maintenance Effort

Rudolf Schaefer
preprint en

Abstract

This working paper develops a falsifiable theoretical and methodological model for interpreting Solow’s productivity paradox as a net-balance problem of technological complexity. The starting point is the observation that digital technologies, automation, artificial intelligence, and information systems are increasingly visible across modern economies, while aggregate productivity statistics often fail to show proportional gains. Instead of treating this gap solely as a measurement, diffusion, or implementation problem, the paper proposes an explicit distinction between the gross technological benefit of innovation and the systemic maintenance effort required to operate, control, integrate, secure, document, and regulate the complexity generated by that innovation. The central model extends a conventional production-function framework by introducing a net technology factor. Technological gross benefit is modeled as a function of system complexity, while technologically induced system-maintenance effort is treated as an absorptive factor that may reduce observable net productivity. The model distinguishes technical maintenance effort from regulatory and organizational maintenance effort and provides a formal structure for forward calculation, backward inference, proxy development, and falsification. The paper does not claim to provide a completed empirical proof. Instead, it offers a reproducible research framework and validation protocol. It identifies measurable variables and proxies, discusses test cases from production, banking, healthcare, construction-permitting processes, and regulatory absorption, and formulates conditions under which the model would be supported, weakened, or falsified. The contribution of the paper is the formalization of a system-theoretical mechanism that may help explain why technological progress can be locally effective while appearing only weakly in aggregate productivity measures: part of the gross benefit of technology may be absorbed by the effort required to maintain the complexity it creates. This version is intended as a working-paper release for discussion, critique, and further empirical validation.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Digital Platforms and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.