Microbehavioral Econometric Methods and Environmental Studies uses microeconometric methods to model the behavior of individuals, then demonstrates the modelling approaches in addressing policy needs. It links theory and methods with applications, and it incorporates data to connect individual choices and global environmental issues. This extension of traditional environmental economics presents modeling strategies and methodological techniques, then applies them to hands-on examples. Throughout the book, readers can access chapter summaries, problem sets, multiple household survey data with regard to agricultural and natural resources in Sub-Saharan Africa, South America, and India, and empirical results and solutions from the SAS software.
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Professor S. Niggol Seo is a natural resource economist who specializes in the study of global warming. He received his PhD in Environmental and Natural Resource Economics from Yale University in 2006 with a dissertation on microbehavioral models of global warming. Since 2003, he has worked with the World Bank on various climate change projects in Africa, Latin America, and Asia. He held professor positions in the United Kingdom, Spain, and Australia from 2006 to 2015. Since September 2015, he is Professor of Environmental & Natural Resource Economics at the Muaebak Institute of Global Warming Studies in Seoul, South Korea. Prof. Seo has published six books and over 50 international journal articles on the economics of global warming.
Microbehavioral Econometric Methods and Environmental Studies uses microeconometric methods to model the behavior of individuals, then demonstrates the modelling approaches in addressing policy needs. It links theory and methods with applications, and it incorporates data to connect individual choices and global environmental issues. This extension of traditional environmental economics presents modeling strategies and methodological techniques, then applies them to hands-on examples.Throughout the book, readers can access chapter summaries, problem sets, multiple household survey data with regard to agricultural and natural resources in Sub-Saharan Africa, South America, and India, and empirical results and solutions from the SAS software.
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