Product market regulation and productivity convergence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article we investigate the effect of product market regulation on the international diffusion of productivity shocks. The results indicate that regulations that restrict competition slow the process of adjustment through which best practice production techniques diffuse across borders and new technologies are incorporated into the production process. This effect is reflected in cross-country differences in ICT investment and speeds of catch up of sectoral productivity, which are significantly influenced by differences in product market regulation. Thus, persisting cross-country differences in product market regulation can partially explain the recent observed divergence of labour productivity in OECD countries, given the emergence of new general purpose technologies over the 1990s. In the case of Canada, the results suggest that remaining regulatory barriers to competition in a few key non-manufacturing sectors may have prevented the economy from benefiting to the full extent from high productivity growth rates in the United States and other productivity leaders. ONE OF THE ECONOMIC PARADOXES of the past decade was that GDP per capita diverged across OECD countries even as policies con-verged in many areas, such as macroeconomic stabilization and product market regulation. The paradox was particularly striking in pro-ductivity performance across countries, the major driver of divergence in GDP per capita. Spectacular productivity growth acceleration in some countries, in primis the United States, was matched by continued stagnation or even decel-eration in many continental EU countries. Yet, product market policies, which are thought to affect productivity growth, became increasingly market-oriented everywhere, with privatiza-tion and liberalization spreading throughout the OECD area. How can this be reconciled with the idea that institutional change and produc t marke t r e fo rms sh ou ld l ead to improved productivity performance? This article argues that it is not only institu-tions and policies per se that mattered for explaining the productivity episodes from the late-1990s, but also the relationship between the
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 0.001 |
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 it