Nursing home choice, family bargaining, and optimal policy in a Hotelling economy
Bibliographic record
Abstract
Abstract We develop a model of family bargaining to study the impact of the distribution of bargaining power within the family on the choice of nursing homes by families, and on the locations and prices chosen by nursing homes in a Hotelling economy. In the baseline (static) model, where the dependent parent cares only about the location of the nursing home, the markup of nursing homes is increasing in the bargaining power of the dependent parent, and nursing homes are located at the extreme periphery. We compare the laissez‐faire with the social optimum (which involves more central locations of nursing homes), and examine its decentralization in first‐best and second‐best settings. We explore the robustness of our results to introducing a bequest motive in a dynamic overlapping generations model, which allows us to study the joint dynamics of wealth accumulation and nursing home prices. If the bequest motive is strong, the markup is decreasing in the bargaining power of the dependent. However, wealth accumulation, by reducing interest rates, raises markup rates and nursing homes prices.
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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 | 0.003 | 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 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".