Foreign Capital Inflows and Growth of Employment In India: An Empirical Evidence from Public and Private Sector
Bibliographic record
Abstract
The role of foreign capital in economic growth has been a burning topic of debate in countries world over including India. It is not possible for a developing country like India to grow without sufficient foreign capital inflow, technology and employment generation. The Indian government has taken many initiatives to attract foreign investment to boost the Indian economy since the liberalization process started in 1991. As a result, India has received Foreign Direct Investment (FDI) to the tune of US $ 380215 million by the end of June 2015. This study has assessed the growth of employment in public and private sector by the flow of foreign capital, comprising of Foreign Direct Investment, Foreign Portfolio Investment (FPI), External Commercial Borrowings (ECBs), and NRI Deposits in India during the period 1991 to 2012. The study has also analyzed the trends of employment in public and private sectors of Indian economy. We find that overall foreign capital inflows, except for the FPI and NRI deposits, have a significant positive impact on the growth of private sector employment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".