Bibliographic record
Abstract
The paper examines the interest rate pass through of the policy interest rate to the market interest rate in Nepal. The span of the empirical exercise covers the phase of interest rate liberalization commencing from the first quarter of 1989/1990 to the final quarter of 2008/2009. The result suggests that there is a significant long run elasticity coefficient of the policy rate (taken to be the bank rate) to the different market rates (e.g. 1 yr fixed deposit, lending rate and saving rate), but there is only one error correcting relationship between the bank rate and the lending rate in the short run. However, the speed of adjustment, i.e. the adaptation coefficient, indicates a weaker adjustment of the short-term dynamics to the long run equilibrium. Looking at the sub-sample, which coincides with the promulgation of the NRB Act 2002, the period starting from the third quarter of 2001/2002 to the final quarter of 2008/2009, suggests that there is insignificant elasticity coefficient between the policy rate and two of the above-mentioned market rates. Paradoxically, while the elasticity coefficient between the policy rate and lending rate is found to be significant, it is negative! Overall, the situation indicates that at present, the bank rate in Nepal is ineffective in influencing the market rates and suggests that there are other factors at play. The paper ends by recommending introduction of a more effective indicator of monetary stance, greater awareness of external factors when making monetary policy, and enhancing and guiding the development of the domestic financial sector for equitable financial development and growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".