Cars, Congestion and Costs: A New Approach to Evaluating Government Infrastructure Investment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The existing debate about the cost of traffic congestion in Canadian cities has been limited to estimating the value of time lost by people sitting in traffic. However, there are broader costs of congestion that should be taken into account. This Commentary offers a decision-making framework for governments seeking to include these broader, social welfare costs in selecting which infrastructure investments merit public subsidy, and which ones should be handled by the private sector. In general, the social returns from infrastructure can be substantial and governments are missing a large portion of the economic benefits of infrastructure when they do not estimate them. In particular, economic externalities – which arise when an individual’s use of infrastructure affects someone else – can be quite large. Governments should assess the full range of social costs and benefits of externalities and include them in building a consistent economic case for investment. With regard to transportation in particular, this report provides a new way of estimating the cost of congestion. To date, governments have made the case for transportation investment based on the estimated economic cost of time lost due to congestion. In the Greater Toronto and Hamilton Area, the commonly used estimate is that congestion costs the economy about $6 billion per year. However, the existing studies provide underestimates of the costs of congestion. The reason: they ignore the positive effects of relationships among firms and people that are among the main benefits of urban living. These urban agglomeration benefits range from people accessing jobs that better match their skills, sharing knowledge face-to-face, and creating demand for more business, entertainment and cultural opportunities which, in turn, benefit other people. When congestion makes urban interactions too costly to pursue, these benefits are foregone, adding significantly to the net costs of congestion. For the Greater Toronto and Hamilton Area this report estimates the additional costs to be at least $1.5 billion and as much as $5 billion per year. For Canadian governments, the framework for comparing the private and social returns of investments can apply to a wide range of investments, ranging from transportation to education to health and much more. In cases in which there is a substantial private return, the economically efficient option is for pure private provision. With such a framework in hand, Canadian governments can make better choices about their investment needs.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it