Investing in an emerging market: evidence from US firms investing in India
Bibliographic record
Abstract
Purpose To look at investor reactions to US investments made in India. Specifically, the authors look at the stock price reaction when US firms invest in the Indian market. Design/methodology/approach The authors look at investor reactions to US investments made in India, using event study methodology. Findings The authors' results indicate that there is a variation in market's reaction across firms belonging to different industries. They find mixed investor response to investments in India. The firms experience both positive and negative abnormal returns. There are also number of firms for which they do not get any significant results. Also, possible reasons for why there were no significant results for some firms: small investment by US firms in comparison to total investments, and most of the investments studied were sequential and not the first investment by a firm to Indian market. They also carry out a regression analysis, where they regress abnormal returns on important firm level characteristics, such as firm size, cash flows, and research and development expenditure. The authors find firm size has a significant positive impact on abnormal returns. Research limitations/implications There is a need to carry out this study for a larger sample size over a larger time period, such that one can distinguish between first time investment and sequential investments. On average for their sample, investment in India by the US firms is small relative to their overall investment. This explains the lack of investor reaction for some cases. For future studies, it would be useful to look at high‐investment sectors in India. Practical implications Multinational network hypothesis, in line with internalization theory argue that due to differential degree of economic development between USA and developing countries, US firms' investments in these countries will enhance their multinational network. The multinational expansion will in turn substantially enhance firms' ability to internalize its foreign operations profitably, increasing shareholders' wealth. The authors do find these for some US firms. Originality/value There are no studies to the best of our knowledge on the Indian market.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".