Getting to Liquidity: Determining Hunting Lease Prices using Predictive Analytics

dc.contributor.advisor

Bachman, Joseph

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Christensen, Jamie

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2022-04-20T17:15:51Z

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2022-04-20T17:15:51Z

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2022-04-20

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Nicholas School of the Environment

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Land leasing for hunting has historically been conducted with little more than a handshake. In response, digital marketplaces provide tools and establish trust for landowners to connect with outdoor enthusiasts seeking hunting leases. In the early stages of these marketplaces, with limited land supply and use demand, establishing accurate pricing for the hunting leases is challenging. This project seeks to understand if a predictive land pricing capability can be developed for long-term hunting leases on land available in one such two-sided marketplace, Outdoor Access. Analysis of paid recreational leases on hunting listings from 2020 identified key attributes that contributed to the price of these leases. Using publicly available spatial data, a linear regression model was developed to assign predictive lease prices to hunting listings in 2021. While the model failed to predict accurate lease prices, it supported Outdoor Access negotiations of final lease prices with landowners and hunters.

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https://hdl.handle.net/10161/24844

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Hunting

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Land Leasing

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Outdoor Recreation

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Getting to Liquidity: Determining Hunting Lease Prices using Predictive Analytics

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Master's project

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0

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