<b>Research Note</b>—Does Technological Progress Alter the Nature of Information Technology as a Production Input? New Evidence and New Results
Bibliographic record
Abstract
Prior research at the firm level finds information technology (IT) to be a net substitute for both labor and non-IT capital inputs. However, it is unclear whether these results hold, given recent IT innovations and continued price declines. In this study we extend prior research to examine whether these input relationships have evolved over time. First, we introduce new price indexes to account for varying technological progress across different types of IT hardware. Second, we use the rental price methodology to measure capital in terms of the flow of services provided. Finally, we use hedonic methods to extend our IT measures to 1998, enabling analysis spanning the emergence of the Internet. Analyzing approximately 9,800 observations from over 800 Fortune 1,000 firms for the years 1987–1998, we find firm demand for IT to be elastic for decentralized IT and inelastic for centralized IT. Moreover, Allen Elasticity of Substitution estimates confirm that through labor substitution, the increasing factor share of IT comes at the expense of labor. Last, we identify a complementary relationship between IT and ordinary capital, suggesting an evolution in this relationship as firms have shifted to more decentralized organizational forms. We discuss these results in terms of prior research, suggest areas of future research, and discuss managerial implications. *This paper is dedicated to the memory of Paul Chwelos, respected colleague and dear friend.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".