The Economics of Maintenance for Real Estate Investments
Bibliographic record
Abstract
We propose a theory of urban decay. Following a negative real estate demand shock, property managers optimally suspend maintenance and the probability that they ever restart can be modest. Because maintenance expenditures are proportionately less risky than are the incremental building profits they generate, managers impose a more demanding profit standard on maintenance than on the initial investment. This differential in profit standards means that rather than maintain existing investments, property managers favor new investments, which, if marginally acceptable, they also leave unmaintained. Contractually required maintenance (e.g., for publicly subsidized real estate investments), increases the minimum profit for the initial investment acceptance and discourages subsidized real estate investments in favor of unsubsidized investments. However, the required profit for acceptance of a permanently maintained investment is below the profit boundary for maintenance if maintenance is not contractually required. Consequently, the subsidy that induces the investment is least expensive if maintenance is not required, more expensive if maintenance is permanently required and most expensive if maintenance is induced immediately after initial construction but thereafter is at the discretion of the manager. All of our findings are strongest for poorer quality properties.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".