Accounting for Growth from A to Z: Review Article on Information Technology and the American Growth Resurgence
Bibliographic record
Abstract
The author reviews the book Information Technology and the American Growth Resurgence by Dale Jorgenson, Mun Ho, and Kevin Stiroh, which provides a detailed analysis of the remarkable rebound in productivity and output growth in the last decade. He notes that the book can be considered a “Users’ Guide” to growth accounting and is highly recommended in this regard. The author reviews in an even-handed manner the critiques that have been put forward of the growth accounting methodology presented by Jorgenson et al. His bottom line is that while many of the critiques make valuable points, there is currently no alternative methodology to growth accounting that offers such a comprehensive framework for assessing the sources of economic growth. He also reviews the story put forward by Jorgenson et al. where in the mid-1990s the constant-quality prices of semiconductors fell substantially, leading to rapid declines in the price of Information Technology (IT) capital goods. Firms responded by substituting capital purchases toward IT capital, resulting in a surge in IT capital deepening and labour productivity growth. One limitation of the book is that it provides no analysis of the post-2000 US productivity growth acceleration, which has taken place in a period when rapid IT capital deepening was not occurring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".