This course will provide an introduction to modern econometric techniques in general and spatial econometrics in particular. It is designed for senior and graduate students of geography department who may have relatively limited background in statistics, mathematics, and econometrics but are keen to learn this ‘difficult’ subject. This course will use the popular open source statistical computer language R. Its focus is on using statistical computing to produce analytical reports for real-world applications, research papers, and dissertations. Its aim is to enable students to develop the application of statistics to the study of economic geography, to understand how these techniques can help them comprehend the complex reality concerned and endow them with a fascination for spatial econometric methods. Through lectures, group work, and hands-on computer sessions, the class will enable students to explain when and why to use spatial econometrics and demonstrate how to apply spatial econometric methods. The class will help students develop ability to estimate and interpret spatial econometric models for analyzing socioeconomic relationships and human-environment interactions. The class will enable students to use spatial econometric tools in R effectively. (Integrated Geography)

Credits: 3
Grading Method: Regular

Course Offerings

    Fall 2017Instructor: Laixiang SunView: Syllabus
    Fall 2015Instructor: Laixiang SunView: Syllabus
    Fall 2014Instructor: Laixiang Sun