"Energy Security and Climate Change Policy in the OECD: the Political Economy of Carbon-energy Taxation"
Bibliographic record
Abstract
Why do countries tax the same fuels at widely different rates, even among similarly situated countries in the global political economy? Given the potentially destabilizing effects of climate change, and the political and economic risks associated with a reliance on geographically concentrated, finite fossil fuels, International Organizations and economists of all political stripes have consistently called for increasing tax rates on fossil-based energy. Despite much enthusiasm among policy experts, however, politicians concerned with distributional consequences, economic performance and competitiveness impacts continue to be wary of raising taxes on carbon-based fuels. In this context, this thesis investigates the political economy of tax rates affecting the price of fossil fuels in advanced capitalist democracies. Through an examination of the political limits of government capacity to implement stricter carbon-energy policy, as well as the identification of the correlates of higher carbon-based energy taxes, it throws new light on the conditions under which carbon-energy tax reform becomes politically possible. Based on recent data collected from the OECD, EEA and IEA, I develop an estimate of the relative size of implicit carbon taxes across OECD member countries on six carbon-based fuels and across the household and industrial sectors. I exploit large cross-national differences in these carbon-energy tax rates in order to identify the correlates of, and constraints on, carbon-energy tax reform. Applying multiple regression analysis to both cross-section and time-series cross-sectional (TSCS) data, this thesis leverages considerable empirical evidence to demonstrate how and why electoral systems matter for energy and environmental tax policy outcomes. In particular, I find considerable empirical evidence to support the claim that systems of proportional representation (PR), in addition to the partisan preferences of the electorate, work together to explain differential rates of carbon-energy taxation. By opening up the ideological space to a broader spectrum of “green” parties, I argue that PR systems create a favourable institutional context within which higher rates of carbon-energy taxation become politically possible. After specifying a key causal mechanism within different types of electoral systems – the seat-vote elasticity – I argue further that, voters in disproportional systems actually have more leverage over politicians, and that an increase in environmental voting can have an impact on rates of carbon energy taxation, even in the absence of PR. While the accession to power of green political parties in PR systems is more likely to lead to higher rates of carbon energy taxation, voting for green parties in highly disproportional systems creates incentives for other parties to adopt “green” policies, leading to a similar outcome. In this way, the effect of green votes and green seats will have the opposite effect on policy according to the type of electoral system in use.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".