Экономическая политика, качество институтов и механизмы "ресурсного проклятия"
Bibliographic record
Abstract
Sachs, Warner (1995) were among the first to claim that «resource curse» is real and that resource abundant economies do indeed grow more slowly than the others. Hundreds of papers were published since then supporting the «resource curse» thesis and offering new explanations of mechanisms and effects that may inhibit growth in resource rich economies. Several recent papers, however (Alexeev, Conrad, 2005; Stijns, 2005; Brunnschweiler, 2006) question the mere existence of the «resource curse» and make it necessary to reconsider the hypotheses about the impact of resource abundance on economic growth.\n\nThis paper compares various theories of «resource curse» with a special focus on models allowing for the varying — positive or negative — impact of resources on development depending on the quality of institutions and economic policies. Several mechanisms leading to a potentially inefficient use of resources are being examined; it is demonstrated that each of these mechanism is associated with market imperfections and can be «corrected» with appropriate government policies.\n\nEmpirical evidence seems to suggest that resource abundant countries have on average lower budget deficits and inflation, higher foreign exchange reserves and higher inflows of FDI. Besides, lower domestic fuel prices that are typical for resource rich countries, have a positive effect on long term growth even though they are associated with losses resulting from higher energy intensity. On top of that resource abundance allows to reduce income inequalities. So, on balance, resource wealth turns out to be conducive to growth, especially in countries with strong institutions. However, resource abundance makes democratic political regimes very unstable — they tend to gravitate towards authoritarianism. A game theoretical model is developed to show that democracy in resource abundant countries is inherently unstable and the empirical evidence on the stability of resource democracies is provided.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".