Test of Linkage between Governance Style and National Economic Indices
Bibliographic record
Abstract
The relationship between the deliberate reinvention of the wheel, for macroeconomic indices such as interest rate, inflation, exchange rate, stock prices, index of industrial output within the electoral windows and the political parties’ (incumbent and opposition) ideology is the focus of this study. Monthly macroeconomic data for UK, USA, Japan, China, Hong Kong, Egypt, South Africa, Brazil, Nigeria, France and Germany from Morgan Stanley Capital International (MSCI) as well as World Bank for the period of 2000-2015 were used in the study. Employing majorly, the dynamic Genaralized Method of Moment (GMM) estimation technique, the study reveals that the coefficients of partisanship effects have the same negative signs and is significant for all the countries except Nigeria and Egypt. Also, the coefficients are similar in terms of size (US and China). Hence, the results show that party orientation does have significant impact on stock market returns of the selected countries with greater impact on Nigeria and Egypt. Strengthening the various regulatory agencies in charge of these macroeconomic policies is recommended to avoid this uncessary manoeuvring in governance. We are of the view that automation of capital markets activities will reduce the chances of manipulating capital market economic data.
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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 | 0.002 | 0.009 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".