Impacts of COVID-19 on Energy Expenditures of Local Self-Government Units in Poland
Bibliographic record
Abstract
Measures taken by the public administration to prevent the spread of the COVID-19 pandemic have led to drastic consequences for the economy. The full identification of its effects is hindered due to the delay in publishing the results of public statistics. The use of financial reports prepared by self-government authorities of all municipalities in Poland made it possible to obtain preemptive information in relation to the public statistics regarding the impact of COVID-19-related limitations on the energy expenditures incurred by local government units (LGUs), as well as an assessment of to what extent the LGUs had rationalized the energy consumption. By contrast, data from reports of energy companies made it possible to determine the impact of restrictions arising from the pandemic on the amount of energy sold and revenues from sales made by these companies. The analyses use indexes of the dynamics of changes in energy prices as well as indexes of the dynamics of changes in energy expenditures incurred by LGUs. Additionally, distributions of these indexes for the populations of municipalities are analyzed. To assess the effect of economic activity on energy expenditures incurred by LGUs, classification trees are utilized. It is established that the total production and sales of energy in Poland, in volume, in each quarter of 2020 were lower than in the corresponding period of the preceding year. However, as a result of an increase in energy prices by approximately 25%, the sales of electric power generating companies, in amounts, were higher in 2020 than in 2019. The increase in energy prices was also a cause of slightly increased total expenditures for purchasing energy in LGUs in Poland, which increased by 2.15% in 2020 compared to 2019. However, a substantial diversity in expenditure indexes was observed. That concerned both total expenditures and expenditures within individual sections of the budgets of municipalities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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 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".