Economic Analysis of Telecommunications Markets and Policy
Bibliographic record
Abstract
My dissertation consists of two essays on the economics of telecommunications. The first chapter studies the implications of the Canadian Radio-television and Telecommunications Commission's (CRTC's) Third-Party ISP Access (TPIA) regulation, which requires internet-service providers (ISPs) to sell access to their network to third-party providers (TPPs) at wholesale prices. We estimate household preferences over internet plans using novel subscription and usage data and then calibrate a model of entry by TPPs to match the observed market structure. Our estimates characterize the regulator's trade-off: reducing the wholesale price increases TPP entry and consumer welfare, but decreases ISP revenues and the incentive to invest in networks. We then calculate the optimal wholesale price for different regulator objectives. Chapter 2 describes current levels of household demand for wireline broadband data using recent detailed data from a North American Internet Service Provider. Additionally, we examine application-level data demand to identify which types of internet applications use the most bandwidth. Our calculations show that, conservatively, 85\% of households on average would need to spend less than five extra hours per month to use the same amount of data if their download speed were throttled to 50 Mbps (for households who choose plans faster than 50 Mbps). The households most affected by the throttling are those that more frequently download large files. Our results suggest that many current wireline broadband subsidy policies across North America and Western Europe over-weight the welfare importance of access to speeds over 100/10 Mbps.
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 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) | 0.000 | 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 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".