气候变化领域集成服务门户(CCPortal): The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation

CCPortal

DOI	10.1007/s11069-020-04484-w
	The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation
	Dundas S.J.; von Haefen R.H.
发表日期	2021
ISSN	0921030X
起始页码	2053
结束页码	2075
卷号	107 期号:3
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.
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
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206199
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
推荐引用方式 GB/T 7714	Dundas S.J.,von Haefen R.H.. The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation[J],2021,107(3).
APA	Dundas S.J.,&von Haefen R.H..(2021).The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation.Natural Hazards,107(3).
MLA	Dundas S.J.,et al."The importance of data structure and nonlinearities in estimating climate impacts on outdoor recreation".Natural Hazards 107.3(2021).