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Title:Relationship between socioeconomic status and hunting/fishing license sales in Cook County, IL
Author(s):Zhang, Xiaohan
Advisor(s):Miller, Craig A.
Department / Program:Natural Res & Env Sci
Discipline:Natural Res & Env Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Socioeconomic Index
Hunting License Sales
Fishing License Sales
Spatial Analysis
Abstract:Enhanced management of hunting/fishing activities could be attained by understanding factors influencing license sales. Previous studies suggest socioeconomic status significantly influences participation in recreational activities and license sales. However, few of these studies connect socioeconomic status and license sales on an aggregated community level or spatial context. This study aims to examine the relationship between socioeconomic factors and license sales in Cook County, Illinois. An index, aggregating census tract socioeconomic indicators in the dimension of economic status, occupation, education, ethnic groups, household and age structure, was created by principle component analysis and used to measure the overall socioeconomic context at the census tract level. Three components were extracted and an index system with three sub-indices (Socioeconomic Status, Household Mobility and Age Index) was created. License sales was measured in terms of license holder density by dividing the number of license holders over the population size within an individual census tract. Spatial and statistical analyses were applied to the indices and density of license sales to achieve the study objective. Cluster maps of license sales and socioeconomic indices presents the positive spatial relationship between the hunting license sales and all the three indices, and between the fishing license sales and Household Mobility. There is no clear spatial correlation between the fishing license sales and the other two indices. Linear regression and multinomial logistic regression were applied to the dataset respectively. Compared with linear regression, the multinomial logistic regression produced more accurate predictions, but there were still spatial factors not included in the model (i.e. the residuals were spatially correlated). Both models predicted that all the three indices positively influenced the hunting license sales, and Household Mobility and Age Index positively influenced the fishing license sales as well. However, the two models differed in the relationship between the Socioeconomic Status and fishing license sales. Linear model predicted a linear negative correlation, whereas the multinomial logistic regression predicted a non-monotonic correlation. Combining the cluster maps and the regression results helps to detect the possible “hot spots” that may require further studies. One of the three indices is likely to prevail over the others, or factors other than the indices need to be explored to explain the local license sales in areas of the hot spots. Better understanding of the special cases in hot spots is probably cable to guide the local license promotion.
Issue Date:2015-01-21
Rights Information:Copyright 2014 Xiaohan Zhang
Date Available in IDEALS:2015-01-21
Date Deposited:2014-12

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