Select one of the options below:
Upon successful completion of this course students should be able to:
1. use computer software to estimate a linear regression.
2. interpret the economic meaning of the estimated linear regression coefficients.
3. test hypotheses and construct confidence intervals for regression coefficients.
4. make predictions using the estimated regression.
5. test and correct for heteroskedasticity.
6. estimate and interpret binary dependent variable models (e.g. probit and logit regressions).
(ECON 204) and (STAT 201 or STAT 204 or STAT 301 or STAT 307 or STAT 311 or STAT 315) and (MATH 141 or MATH 155 or MATH 160). Credit not allowed for both AREC 335 and ECON 335
9704910821 | anita.pena@colostate.edu
Dr. Anita Alves Pena is an associate professor of economics at Colorado State University. Her research interests are in public sector economics, labor economics, and economic development, and her current research relates to undocumented and documented immigration, public policy, poverty, and agricultural labor markets. Dr. Pena received her Ph.D. in economics from Stanford University in 2007, M.A. in economics from Stanford University in 2004, and B.A. in economics from the Johns Hopkins University in 2001. She currently teaches Microeconomic Theory, Public Economics, and Microeconomics of Development at the graduate level, as well as undergraduate Intermediate Microeconomics, Introduction to Econometrics, and Economics of Public Finance.