The Impact of Macroeconomic Indicators on the Balance of Payments: Empirical Evidence from Afghanistan
Bibliographic record
Abstract
This study aims to empirically investigate the impact of a set of macroeconomic variables including balance of trade, FDI, exchange rate, and inflation on the balance of payments (BOP) of Afghanistan using quarterly data from the second quarter of 2004 to the fourth quarter of 2020 (2004Q2 to 2020Q4). The paper uses the Vector Error Correction Model (VECM), and Johansen co-integration test for analysis to explore the BOP of Afghanistan and provides comparable literature to other least-developed and low-income developing countries. The findings reveal that balance of trade (BOT), foreign direct investment (FDI), and exchange rate are significant determinants of Afghanistan’s BOP in the long run. More specifically, BOT and FDI positively impact the BOP, whereas the effect of the exchange rate on the BOP is found negative. Yet, inflation has an insignificant impact on the BOP. Though all variables have an insignificant impact on the BOP in the short run, the relevant policy measures ought to consider improvement in BOT, promoting FDI, and exchange rate stability to ensure synchronized improved BOP and economic growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".