Financial Stability of Romanian Households in Light of the COVID-19 Pandemic Shocks
Bibliographic record
Abstract
The present paper examines the effects of the Covid-19 pandemic on the financial situation of Romanian Households, using a simple random sampling without replacement. For a larger investigation of the survey results, that offers a new perception in looking at issues of financial stability, a binary logistic regression model was applied in order to econometrically quantify the relationship between determinants and respondents' behavior regarding the use of savings to pay bills and credits commitment during the coronavirus pandemic. The results of the model show that the respondents’ household with four members and over used 2.75 times more savings to pay bills and credits commitment than those consisting of three or fewer members. It should be mention that, among the respondents participating in the research, slightly over 28 percent of the respondents have no emergency savings at all. In addition, less than a quarter of the responses (16.5 percent) indicate that staple foods were purchased with borrowed money in order to meet the basic consumption needs. The analysis of households’ resilience to shocks is significant in the epidemic context, as the ability of households to cope with the shock determines how much consumption will decrease and whether debtors will register outstanding debts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".