DEMONETIZATION AND ITS IMPACT: A STUDY ON INDIAN FMCG SECTOR
Bibliographic record
Abstract
Demonetization of all the Rs.500 and Rs.1000 denomination banknotes is an attempt to curb black money, fake notes and to achieve other ancillary objectives. Numerous debates have been held over this move and various pros and cons of demonetization have come into picture. Against these backdrops, in this paper it is tried to find out the immediate effect of demonetization on the FMCG sector. It is likely that immediate cash crunch arising out of demonetization is likely to impact the sales and other performance of FMCG Companies. Analysis is made on the quarterly performance on the selected FMCG companies and annual reports are thoroughly scrutinized to find out the views of the companies concerned on demonetization and its effect. The content analysis is made by searching for terms Like “demonetization”, cash-crunch cash shortage etc. The analysis reveals that most of the sample companies have made some disclosure in the annual report on demonetization. Our analysis reveals that for 7 companies there is absolute negative growth in sales and for 4 companies sales growth is lower as compared to sales growth of corresponding quarter of previous year in respect of December end quarter.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".