SOME DETERMINANTS AND MECHANICS OF ECONOMIC GROWTH IN MIDDLE-INCOME COUNTRIES: THE ROLE OF ICT INFRASTRUCTURE DEVELOPMENT, TAXATION AND OTHER MACROECONOMIC VARIABLES
Bibliographic record
Abstract
This study examines key factors in the economic growth of middle-income countries over the period 1970–2017. The variables considered are ICT infrastructure development, taxation revenue, government expenditure, gross capital formation, foreign direct investment, and inflation. This study considers interlinkages between the macroeconomic variables noted above. The purpose of this study is to determine: (1) if there is causality between the variables and (2) the direction of any causality. Using a panel vector error-correction model, we find both short-run and long-run relationships between the variables. In each specification, we find that ICT infrastructure development, taxation revenue and the four macroeconomic variables all stimulate economic growth in the long run. This suggests that policymakers should curate an integrated and holistic policy framework pertaining to taxation, ICT infrastructure development and other macroeconomic policies to create a vibrant national economic ecosystem that would ensure the sustained economic growth of middle-income countries.
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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 | 0.001 | 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 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".