Inflation and Economic Growth: Evidence from Pakistan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study empirically explores the nexus between inflation and economic growth in the context of Pakistan economy. Annual data for the period of 1960-2006 has been used. According to the results of the study, inflation is positively related with economic growth in Pakistan and vice versa. As for as, the concern of causality between these two variables, it is found to be uni-directed. In other words, inflation is causing growth but not vice versa. To examine the extent to which economic growth is related to inflation and vice versa, Error Correction Models (ECM) have been employed. With the help of this procedure, it is possible to examine the short-run and long-run relationship between two variables. The Error Correction Model (ECM) test is essential to see whether an economy is converging towards equilibrium in the short- run or not. According to the outcome of the study, inflation is away from its equilibrium value. For instance, the error correction term -0.49 implies that 49 percent of the adjustments towards the short-run equilibrium relation for Pakistan occur within a year through changes in growth rates. On the other hand, 58 percent (error correction term -0.58) of the deviation of the inflation from its short-run equilibrium level is corrected each year. Furthermore, the estimated threshold model suggest that 9 percent threshold level (i.e. structural break point) of inflation above which inflation starts to lower the economic growth in Pakistan. Pakistan must need inflation but in single digit for growth because too fast a growth rate may also accelerate the inflation rate.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it