Macroeconomic developments and policies since 2000
Bibliographic record
Abstract
The first section provides a brief review of developments in key macroeconomic variables since 2000. These include the usual target variables of economic growth, inflation, external balance and employment as well as intermediate target variables of fiscal balance, savings and investment. Section II considers some of the major exogenous shocks experienced in the last 24 years and how well (or badly) India's policies coped with them. The shocks include the foreign capital surge of 2006-8, the global financial crisis (GFC) of 2008-9 and the Covid pandemic that hit India in 2020. Section III considers some of the key macro challenges that lie ahead. These include; the worsened international economic environment produced by undermining of the rules- based, liberal, world trading order by the first four months of second Trump administration in the US through steep tariffs on major trading partners (China, EU, Canada and Mexico) as well as higher tariffs on nearly all other trading nations; the need to raise India's aggregate investment, savings and exports through an array of economic policy reforms in foreign trade, factor markets, taxation and deregulation to raise the rate of economic growth from 6-6.5 percent to above 8 percent; and ensure a more employment-intensive pattern of development, while maintaining external and domestic macro balance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".