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Discrete choices in coastal environm...

Hindsley, Paul Robert.

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Discrete choices in coastal environments: Addressing confounding factors in random utility models.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Discrete choices in coastal environments: Addressing confounding factors in random utility models./
作者:	Hindsley, Paul Robert.
面頁冊數:	259 p.
附註:	Adviser: Craig Landry.
Contained By:	Dissertation Abstracts International69-04A.
標題:	Agriculture, Fisheries and Aquaculture. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3313052
ISBN:	9780549616191

Discrete choices in coastal environments: Addressing confounding factors in random utility models.
Hindsley, Paul Robert.

Discrete choices in coastal environments: Addressing confounding factors in random utility models. - 259 p.

Adviser: Craig Landry.

Thesis (Ph.D.)--East Carolina University, 2008.

Discrete choice methods, which model individuals' choices, provide coastal managers and policy makers a powerful tool in understanding and forecasting resource users' behavior. Among resource decisions, coastal recreation has proven to be an important component of coastal life. Recreation behavior gives considerable insight into people's preferences for environmental resources. However, many coastal recreational opportunities lack explicit markets. As a result, uncertainty looms over the value of environmental services associated with these opportunities. Resource policy makers and managers need tools which allow them to quantify the value of these services so they can develop meaningful management strategies. Discrete choice methods provide managers and policy makers one such tool.

ISBN: 9780549616191Subjects--Topical Terms:

1020913
Agriculture, Fisheries and Aquaculture.

Discrete choices in coastal environments: Addressing confounding factors in random utility models.
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500 $a Source: Dissertation Abstracts International, Volume: 69-04, Section: A, page: 1454.
502 $a Thesis (Ph.D.)--East Carolina University, 2008.
520 $a Discrete choice methods, which model individuals' choices, provide coastal managers and policy makers a powerful tool in understanding and forecasting resource users' behavior. Among resource decisions, coastal recreation has proven to be an important component of coastal life. Recreation behavior gives considerable insight into people's preferences for environmental resources. However, many coastal recreational opportunities lack explicit markets. As a result, uncertainty looms over the value of environmental services associated with these opportunities. Resource policy makers and managers need tools which allow them to quantify the value of these services so they can develop meaningful management strategies. Discrete choice methods provide managers and policy makers one such tool.
520 $a This dissertation evaluates recreational users' preferences utilizing observed behavior, methods commonly referred to as revealed preference models. One important facet of revealed preference models lies in data collection. This dissertation investigates common factors confounding statistical inference of recreation site choice models using data collected onsite. While onsite data collection allows managers to reduce sampling costs and observe rare events, it also inherently biases statistical inference. This dissertation develops methods which allow policy makers and managers the ability to collect onsite data while minimizing the subsequent biases. Chapters 5 and 6 focus specifically on the biases through an evaluation of recreational saltwater anglers. Chapter 5 first identifies how these biases manifest themselves and then develops a novel approach to address these biases by combining two existing weighting methods, Weighted Exogenous Stratified Maximum Likelihood (WESMLE) and propensity score methods. This method is termed balanced WESMLE. Using data from the National Marine Fisheries Services' (NMFS) Marine Recreation Fishing Statistics Survey (MRFSS) for the Southeast Atlantic and Gulf states, this study uses an auxiliary sample of coastal recreational anglers to "quasi-randomize" data collected onsite so it appears to have been collected at random. Results indicate that failure to address both endogenous stratification and size-biased sampling leads to significant biases in welfare estimates.
520 $a Chapter 6, which is titled "Evaluating the Role of Variable and Model Selection in Propensity Score Estimation", extends the results of chapter 5 to investigate the role of model and variable selection in the estimation of balanced WESMLE methods. Again using data from the NMFS' MRFSS for the Southeast Atlantic and Gulf states, results indicate that variable selection for propensity score based weight estimation can play an important role in minimizing non-random sample selection bias. Weight misspecification may compound bias.
520 $a Chapter 7 of this dissertation develops an approach to address congestion in site choice models using observed congestion levels sampled onsite. Few studies address congestion in site choice models. When studies of site choice fail to incorporate some form of congestion, coefficients for variables which are correlated with congestion tend to absorb the subsequent congestion effects. However, site choice and observed congestion measures are simultaneously determined, leading to upward bias in the RUM congestion coefficient. Also, when recreational users are observed onsite, congestion is often observed for chosen sites, but not alternative sites. This chapter addresses these obstacles by generating exogenous proxies for rationally expected congestion. In a study of North Carolina beach site choice, results indicate that recreation beach users exhibit a negative but heterogeneous response to congestion.
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650 4 $a Economics, General. $3 1017424
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