Towards an energy theory of value? A critical assessment of the correlation between flows of primary, net, and useful energy flows and monetary indicators for Canada, 1961-2022
Bibliographic record
Abstract
My thesis examines the relationships between indicators of biophysical quality of energy sources and associated monetary indicators, taking Canada as a case-study for the period from 1961 to 2022. I test the hypothesis of a statistically significant relationship between the caloric value of energy sources (measured in joules) used in the Canadian economy and various associated monetary indicators of value (measured in constant Canadian dollars). I use three different measures of energy to test the impact of energy quality on monetary indicators: one measure not corrected for quality (primary and secondary energy flows) and two measures corrected for quality (net-energy ratios and exergy flows). I use four monetary indicators to examine the connections between biophysical quality and monetary value: price, cost of production, profitability and monetary output. I test the hypothesis at two different scales. I first test the correlation between the disaggregated standard Energy Return on Energy Invested (EROIst) of oil sands-derived crude produced in open-pit mining facilities and their associated spot prices, cost of production and profitability from 1997 to 2016 in the province of Alberta, Canada, using original data. I test the correlation between the each EROIst series and the prices, costs of production and profitability of each crude stream independently, using a simple econometric model using first differences in the variables. The regressions for both crude streams fail to find any statistically significant correlation between monetary and biophysical indicators. I reiterate the test at a macroeconomic level. Using the theoretical framework of aggregate production functions (APF), I build 11 multivariate regression models of the Canadian economy measuring the correlation between output production measured in Canadian dollars and labor, capital and energy flows for Canada from 1961 to 2022 using several measures of energy to correct for quality. To assess the methodological validity of the models, I review the history of production functions and their critique by post-Keynesian and ecological economists. The first series of models (1-8) uses provincially disaggregated data on output regressed over primary and secondary energy flows of energy, labor and capital from 1997 to 2022. The models find labor and energy-use to be statistically significant, with the former bearing more impact on output growth over the latter. These models display a slightly higher predictive power over a standard, 2-inputs model. The price of energy is more statistically significant than energy-use in energy-producing provinces. The second series of models (9-10) uses original data on the net-energy ratio of primary energy consumed and the EROIst of primary energy produced in Canada from 1961 to 2022. Neither are statistically significant when regressed over output production. The model testing for EROIst displays a higher Adjusted R^2 over the model testing for net-energy ratios of energy consumed and flows of primary and secondary energy. The validity of the two models is circumscribed provided the number of negative coefficients yielded. One last model estimates the correlation between inputs and output of the Canadian economy using an exergy-based production function, where flows of labor and capital are modeled as sub-function of the flows of muscle work, mechanical work and heat empowering their economic use. Flows of capital modeled as a sub-function of mechanical work and heat are found to be statistically significant predictors of output growth, meaning Biophysical Production Functions are useful modelling devices. However, their validity is limited by their dependence on monetary figures to aggregate flows of capital
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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 | 0.006 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.016 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".