Stochastic model of economic cycles and its econometric application
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
<p>In this paper, I demonstrate the adequacy of economic systems to the basic provisions of synergetics, which makes the latter eligible for macroeconomic analysis. In justifying this statement, a synergetic approach to the development of a model of economic cycles was considered. The novelty of this model was related to the probabilistic description of the investment function and the perception of the economic system as a material object with certain properties. According to the model, the income oscillations are induced by both exogenous (investment fluctuations) and endogenous (system elasticity) causes. The cycle's amplitudes correlate with the intensity of investment fluctuations as well as the efficiency of the economic system. The duration of the economic cycle is determined by the inclusive wealth of the system and its dynamic factor, which characterizes the ability of the system to withstand investment fluctuations and eliminates their consequences. Thus, the economic cycle is interpreted as the "natural noise" accompanying the functioning of market economics.</p><p>The proposed model creates a mathematical basis for the numerical analysis of empirical economic data. An example of possible econometric applications of the model was considered using the current cyclic contraction in US incomes.</p>
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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