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University of Rhode Island — Environmental & Natural Resource Economics

EEC 576 – Econometrics
Course Information

Professor: Dr. Corey Lang
Semester: Fall
Credits: 3
Prerequisites: ECN 575 or equivalent, or STA 308 or equivalent, or permission of instructor

Catalog Description: Application of statistics and mathematics to economic analysis. Implication of assumption required by statistical methods for testing economic hypotheses. Current econometric methods examined and discussed

Course Goals & Outcomes

Ragnar Frisch as founding editor of Econometrica defines “econometrics” in the inaugural issue (1933):

“Econometrics is by no means the same as economic statistics. Nor is it identical with what we call general economic theory, although a considerable portion of this theory has a definitely quantitative character. Nor should econometrics be taken as synonymous with the application of mathematics to economics. Experience has shown that each of these three view-points, that of statistics, economic theory, and mathematics, is a necessary, but not by itself a sufficient, condition for a real understanding of the quantitative relations in modern economic life. It is the unification of all three that is powerful. And it is this unification that constitutes econometrics.”

The primary objective of this course is to provide you with the necessary foundation in the econometric theory that can be used for research and policy design.

By the end of the semester students will be able to:

• Recognize and apply the major tools used by the econometrician in estimating and evaluating the coefficients of the linear models
• Recognize the major problems encountered when applying least square estimators to models and data which violate the Gauss-Markov assumptions
• Read and understand journal articles which employ these econometric techniques
Course Syllabus

Class topics:

• Why is Econometrics necessary?
• Random variables
• Expected values
• Estimating the eman and the variance
• Derivatives
• Matrix algebra
• Inference when sigma square is known
• Inference when sigma square is unknown
• Regression: summation notation
• Regression: matrix notation
• Properties of OLS
• Variances and Monte Carlo
• Basic OLS derivations
• Interval estimation
• Prediction
• Goodness of fit
• Alternative functional forms
• General Linear Model estimation
• Model misspecification
• Testing single coefficient
• Testing combinations of coefficients
• Testing functional forms
• Testing General Linear hypotheses
• Dummy variables
• Collinearity
• Experimental design
• Heteroskedasticity
• Generalized Least Squares
• Autocorrelation
• Large Sample theory
• Measurement errors and IV estimation
• Simultaneous equations
• Identification
• Two & Three Stage Least Squares

Dr. Corey Lang
Assistant Professor
Department of Environmental and Natural Resource Economics
207 Kingston Coastal Institute
Office: 401.874.4568
Fax: 401.782.4766
Email: cory@uri.edu

Reasons To Take This Course

The vast majority of resource economics research, published or un-published, contains from traces to large amounts of econometric information. Thus, possessing some knowledge of this field of study is not only desirable but also necessary in pursuing a graduate degree in resource economics and/or choosing a career in research or academia.

This course is a requirement for the environmental and natural resource economics graduate programs and a prerequisite for several other upper level graduate courses.