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On the correlation between GDP and energy consumption in macroeconomic development

2021· article· en· W3199656984 on OpenAlexaff
Danylo Cherevatskyi, Roman G. Smirnov

Bibliographic record

VenueEconomy of Industry · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEconomicsGross domestic productConsumption (sociology)MacroeconomicsEnergy consumptionPurchasing power parityEnergy intensityReal gross domestic productEconomyEconometrics

Abstract

fetched live from OpenAlex

There is substantial literature devoted to the study of the dependence between energy production and economic development. At the same time, the long-standing discussion of the relationship between the gross domestic product and consumption of primary energy resources, numbering thousands of publications, eventually degenerated into a dispute about econometric methods but did not give final results, which caused the need to resort to other approaches. This paper is an attempt to find a solution to this problem by the methods of theoretical mechanics and regression analysis of the relationship between GDP and energy production in macroeconomic development. Our case studies include the economies of Germany, France, Italy, Japan, Russia, Turkey, and Ukraine. In each case, we characterize the gross domestic product, recalculated at purchasing power parity in 2017 prices, and the consumption of primary energy resources (coal, oil, natural gas, hydro and nuclear energy, energy from renewable sources). Within the framework of the study, it was assumed that the development of any national economy over time is its path in the economic space, and the consumption of primary energy resources is due to dynamic characteristics inherent in macroeconomics, in particular, "mass", which serves as a measure of the inertia of the country's economic complex, the presence of an informal sector, etc. The path, traversed by macroeconomics in the economic space, is the gross domestic product accumulated over time. The observation period is from 1990 to 2019, that is – 30 years. The use of the theory of classical mechanics, in particular – kinematics and dynamics, is justified by the fact that macroeconomics in its development requires the expenditure of energy resources, and this likens it to a machine that moves in a certain space that models a given economyсs. The article introduces methodological approaches to defining the conventional mass of macroeconomics, accelerating its movement, expenditure of energy resources for the functioning of the formal sector of the national economy, the efficiency of energy use in the formal sector.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.032
GPT teacher head0.201
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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