THREE CHAPTERS ON THE ECONOMICS OF LAND CONSERVATION
Notice bibliographique
Résumé
In this dissertation, I investigate the distributional impacts of land conservation on households of varying race and ethnicity, tenure, and income as well as household decisions to locate near conserved lands based on characteristics such as partisan affiliation. While land conservation is considered a public good by most, answering who benefits from conservation, and who chooses to live near conservation are valuable insights for policy makers looking to both provide adequate conservation and ensure that conservation policy is equitable and achievable.\nIn Manuscript 1, I quantify the benefits from newly conserved lands to homeowners in Massachusetts using a hedonic pricing model with fine-scale spatial fixed effects. I find that on average, a 10 acre increase in conserved open space within a quarter mile increases property values by 0.18% or $659. After establishing that properties receive a premium from new conservation, I calculate the dollar gains that each household in Massachusetts received from conservation between 1998 and 2016. Then, I use a descriptive analysis to estimate how the capitalized benefits from conservation are distributed among households of different income, race, or ethnicity. In general, I show that White and wealthier homeowners receive disproportionately more dollar benefits than lower income or minority homeowners, and this pattern holds at both a local and national scale.\nIn Manuscript 2, I estimate the potential financial impacts to renters from housing price responses from gains in conservation at the block group level. I use census and conservation data for the entire coterminous U.S. to show how housing prices responded to newly conserved lands between 2000 and 2014. I implement a propensity score matching approach to match block groups that experienced conservation during this period to characteristically similar areas that did not. I model both home and rental price responses using a first difference model with a series of spatial fixed effects, state-level interactions, and base controls. Results suggest that while homeowner property values increased in response to gains in conservation during this period, rental prices did not respond. These results hold under an expansive set of robustness checks and model extensions.\nIn the final manuscript I study the location decisions of households and the value they place on proximity to conserved land in their home choices based on partisan affiliation. Specifically, I test whether Democrats, Republicans, or Unaffiliated households have a different willingness to pay (WTP) for open space proximity using a residential sorting model in three distinct cities. While partisan groups seem to diverge in behavior at the ballot box, our results indicate that there is no statistical difference in WTP between partisan groups when it comes to sorting across space.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».