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A comparison of ordinary least squar...

Cui, Yue.

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A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida./
Author:	Cui, Yue.
Description:	238 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-01, Section: A, page: .
Contained By:	Dissertation Abstracts International72-01A.
Subject:	Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3435234
ISBN:	9781124329017

A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida.
Cui, Yue.

A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida. - 238 p.

Source: Dissertation Abstracts International, Volume: 72-01, Section: A, page: .

Thesis (Ph.D.)--Michigan State University, 2010.

Recreational boating continues to be one of the nation's most popular recreational activities and it contributes substantially to the United States' economic well-being. However, the future growth in boating is threatened by various factors, including changing demographics, the increasing cost of waterfront property for boating facilities and services, and the conversion of facilities that provide public boating access to other land uses and private access. Developing a better understanding of the current and expected relationship between the demand for and supply of recreational boating access in the context of social and demographic changes occurring in Florida, and better understanding of the relationship with the capacity of government and private businesses to develop and maintain boating access, is crucial for developing new boating opportunities and maximizing the returns, including boater and public benefits, from both private and public investments in boating access.

ISBN: 9781124329017Subjects--Topical Terms:

524010
Geography.

A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida.
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100 1 $a Cui, Yue. $3 1023465
245 1 2 $a A comparison of ordinary least square and spatial regression models for estimating recreational boat ownership in Florida.
300 $a 238 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-01, Section: A, page: .
500 $a Adviser: Ed. Mahoney.
502 $a Thesis (Ph.D.)--Michigan State University, 2010.
520 $a Recreational boating continues to be one of the nation's most popular recreational activities and it contributes substantially to the United States' economic well-being. However, the future growth in boating is threatened by various factors, including changing demographics, the increasing cost of waterfront property for boating facilities and services, and the conversion of facilities that provide public boating access to other land uses and private access. Developing a better understanding of the current and expected relationship between the demand for and supply of recreational boating access in the context of social and demographic changes occurring in Florida, and better understanding of the relationship with the capacity of government and private businesses to develop and maintain boating access, is crucial for developing new boating opportunities and maximizing the returns, including boater and public benefits, from both private and public investments in boating access.
520 $a Over the course of the last fifty years, researchers have utilized a variety of different methods and approaches for describing, analyzing and forecasting recreation demand, including the demand for recreational boating. The majority of recreational boating demand studies have focused on participation, travel cost, benefit and value. This research developed a zonal demand model to explore factors that affect boat ownership and to develop models for predicting boat demand in Florida. A primary purpose was to identify and test factors, including socioeconomic variables, urbanization and boating opportunities that affect the ownership of boats in general and of various types and sizes of boats at three different zonal levels. Zonal regression models were developed to estimate recreational boat ownership, simulate changes in boat ownership associated with demographic, economic, and policy changes, and predict trends in boat ownership at county, zip code and census tract levels. Based on OLS regression models, spatial regression models were subsequently developed to understand spatial effects on zonal models and improve the predictability of the models. The models demonstrated the importance of population-level socioeconomic factors, urbanization and boating opportunity predictors in explaining variation in boat ownership rates. The results show that population-level socioeconomics, urbanization and the availability of boating opportunities are important factors in determining boat ownership rates. In terms of R square and AIC, the county model has a better goodness-of-fit than either of the two smaller zonal units models: zip codes and census tracts. This supports the hypothesis that the large scale model predicts better than the small scale models.
520 $a This study also determined that employing a spatial regression model to improve model performance by partially removing the spatial effects. Spatial regression models, including spatial error, spatial lag model, SAR and CAR models, were developed with the same independent variable combinations as the corresponding OLS models (boat type, size and zonal unit). The spatial regression models resulted in an overall improvement of the original OLS models, and a removal, to some extent, of the spatial effects and associated heteroskedasticity.
590 $a School code: 0128.
650 4 $a Geography. $3 524010
650 4 $a Recreation. $3 535376
690 $a 0366
690 $a 0814
710 2 $a Michigan State University. $3 676168
773 0 $t Dissertation Abstracts International $g 72-01A.
790 1 0 $a Mahoney, Ed., $e advisor
790 $a 0128
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3435234