Energy market dynamics and the role of fiscal policy in oil‐exporting countries: a TVAR approach
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
Abstract While realising the macroeconomic significance of oil price fluctuations, this research examines the role of fiscal policy under changing dynamics of energy market for selected oil‐exporting countries. We specify a non‐linear threshold structural vector autoregression model which constitutes policy variables such as general government expenditures and primary fiscal balance and macroeconomic indicators such as real GDP growth and the inflation rate. To capture the energy market dynamics, this research selects Brent crude oil price as threshold variable and segregates the sample period 1991‐2019 as ‘high’ and ‘low’ oil price regimes. While using non‐linear generalised impulse response functions, we find that under higher oil price regime, an increase in government expenditures and reduction in fiscal deficit have larger multiplier effect to enhance output growth in most of the sampled countries. In addition, this research identifies larger inflationary effects of an increase in government expenditures and fiscal deficit under higher oil price regime for all countries except Canada. However, under a higher oil price regime, a fiscal deficit induced output growth, and under a lower oil price regime, a reduction in government expenditure brings inflation in Saudi Arabia. Furthermore, this research provides an alternative measure of threshold crude oil price for the sampled countries to their accounting‐based concept of fiscal break‐even price.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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