Evaluation of the Hypothesis of Nonlinear Relationship between Finance and Energy Investment
Bibliographic record
Abstract
Abstract Because of the consequences of changes in inflation, which affect the behavior of economic agents, the banking system, and the size of investments, high inflation provokes investors to withdraw funds from long-term projects and invest them in the banking sector. This effect reduces potential economic growth. In turn, the low level of inflation, which persists for a sufficient time interval of several years, indicates the stability of the national economy and attracts external and internal investors, contributes to economic growth. Based on this, it can be assumed that the presence of this relationship will be observed when analyzing data from national economies. Therefore, we can distinguish several hypotheses: inflation has a certain relationship with the indicator of financial development (h1); Inflation and financial development have a nonlinear relationship (h2); monetary policy implemented in the state can have a positive impact on the indicators of financial development, which will affect the dynamics of economic growth (h3). For this purpose, a sample was made from five countries: Germany, United States, Canada, China, Japan, and also Russia was selected in addition to them. This group of countries describes different aspects of the financial sector, as well as the level of economic development, so it will allow you to test hypotheses on a sufficient number of examples. The set of macroeconomic indicators of these countries is sufficiently studied, so it was easily amenable to econometric analysis.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".