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Estimating the Recreational Value of Volcanic-Slope Agricultural Landscapes Using Avidity-Corrected Travel Cost Models

2026/05/29 by Evi Irawan, Syafika Rahma Bintari, Chunyu Ying · 1 voice
Economics, Econometrics and Finance · Environmental Science · Psychology · #Conservation, Biodiversity, and Resource Management #Economic and Environmental Valuation #Recreation, Leisure, Wilderness Management

paper · pdf · doi:10.59978/ar04020010

openalex created_date 2026/05/29 · openalex publication_date 2026/05/29 · openalex updated_date 2026/06/25

Abstract

Volcanic-slope agricultural landscapes provide both productive and recreational functions, yet their economic value remains underexamined, particularly in developing countries where many such areas operate as informal destinations. This study estimates recreation demand and consumer surplus for a volcanic-slope agricultural landscape in Indonesia, focusing on Selo and Cepogo on the saddle between Mount Merapi and Mount Merbabu. Using an on-site intercept survey of 100 visitors conducted in June–July 2024, annual visit frequency is modeled as a function of generalized travel cost, including time. To address the sampling problems inherent in on-site surveys, namely zero truncation and endogenous stratification, four count-data models are estimated: zero-truncated Poisson, negative binomial models, and their avidity-corrected counterparts. Across specifications, visitation declines with higher travel cost and increases strongly with perceived landscape attractiveness, while substitute sites reduce repeat visits, indicating a competitive regional recreation market. Correcting for avidity and overdispersion improves model fit and yields more conservative welfare estimates. Bootstrapped consumer surplus remains positive and substantial across specifications, with a preferred benchmark of approximately 435 thousand IDR per trip and 1,517 thousand IDR per individual annually. Although based on a modest sample, the findings show that volcanic-slope agroecosystems can generate measurable recreation benefits and that correcting on-site sampling bias is important for credible welfare estimation and local landscape governance.

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