The Impact of key Macroeconomic factors on Economic Growth of Bangladesh: a VAR Co-integration Analysis
Bibliographic record
Abstract
This study analyzes the impact of key macroeconomic factors on economic growth of Bangladesh from the period of 1988 to 2012.The key macroeconomic factors studied are market capitalization, foreign direct investment and real interest rate. This study also examines the long run and short run relationship between the economic growth and capital market, foreign direct investment, and real interest rate by using vector autoregressive (VAR) model. The VAR results suggest that the market capitalization, foreign direct investment and real interest rate have impact on economic growth in the long run, but in short run it does not have any predictable behavior. The variance decomposition results also conclude the same result as VAR model. All variables have the long run effects on economic growth but it does not have in short run, and the effects increases with time. Based on the finding, this study suggests that the government should come out with the appropriate macroeconomic plan and policy to draw more inward foreign direct investment, increase market capitalization and stabilize real interest rate in order to faster the economic growth in future. As finding of this study shows that these factors do not have significant impact on economic growth in Bangladesh in the short run
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".