DOI: 10.1007/s11069-020-04484-w
论文题名: The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation
作者: Dundas S.J. ; von Haefen R.H.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期: 3 起始页码: 2053
结束页码: 2075
语种: 英语
中文关键词: Climate change
; Cross-sectional
; Extreme heat
; Nonlinear effects
; Panel
; Recreation demand
英文关键词: angling
; climate change
; economic impact
; environmental quality
; estimation method
; extreme event
; future prospect
; nonlinearity
; panel data
; recreational activity
; United States
英文摘要: Credible empirical estimation of the economic impacts of climate change is dependent on data structure (e.g., cross sectional, panel) and the functional relationship between weather data and behavioral outcomes. We show here how these modeling decisions lead to significantly different results when estimating the effects of weather and simulating the potential welfare impacts of climate change on outdoor recreation. Using participation data from 1.6 million households in the United States from 2004 to 2009, we estimate the impact of temperature and precipitation on participation decisions for marine shoreline recreational fishing. Results from linear models suggest temperature positively impacts participation and, by implication, climate change is likely to improve welfare associated with outdoor recreation in all regions of our study area. Conversely, nonlinear specifications suggest more days with extreme heat reduce participation and lead to significant declines in welfare under future climate scenarios. Differences in the treatment of how weather enters recreation participation decisions change both the sign and magnitude of welfare effects by nearly $1 billion annually. Differences in data structure, however, only affect the magnitude of welfare impacts but not the sign. Disaggregation of welfare estimates suggests warmer baseline climates are more susceptible to these choices. Our results demonstrate the critical nature of modeling decisions about data structure and the use of weather data to assess the future impacts of climate change, especially with nonmarket goods where value is related to environmental quality such as outdoor recreation. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168998
Appears in Collections: 气候变化与战略
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作者单位: Department of Applied Economics, Oregon State University, Corvallis, OR, United States; Coastal Oregon Marine Experiment Station, Oregon State University, Newport, OR, United States; Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, NC, United States
Recommended Citation:
Dundas S.J.,von Haefen R.H.. The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation[J]. Natural Hazards,2021-01-01,107(3)