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The University of Texas at Austin

Lyndon B. Johnson School of Public Affairs

Jay Zarnikau

Adjunct Professor of Public Affairs 2007 - 2008

Contact Info:
Phone: 512-372-8778 ext:103
Email: Wed. 6pm-7pm & please call to confirm appt.
Office: SRH 3.344




Jay Zarnikau is the president of Frontier Associates. He provides consulting
assistance to clients in the energy industry on issues related to energy
conservation, the restructuring of electricity markets, energy pricing, and
resource planning. His consulting work involves market research, statistical
modeling, economic analysis, and expert witness testimony.

Dr. Zarnikau has published over twenty articles in refereed academic
journals, including the Energy Journal; Energy Economics; Energy Policy;
Resources and Energy; and IEEE Transactions on Power Systems. His research
interests include statistical model selection, Bayesian statistical
techniques, the pricing of electricity and water, pollution taxes, and the
measurement of energy efficiency achievements.

Zarnikau, who has a Ph.D. in economics from The University of Texas at
Austin, formerly served as the Director of Electric Utility Regulation at
the Public Utility Commission of Texas and as a Program Manager at the UT
College of Engineering's Center for Energy Studies. He has taught
quantitative courses at the LBJ School of Public Affairs since 2003.

Education

Current Positions

Previous Positions

Courses

SemesterCourse
Spring 2010P A 397C - Advanced Empirical Methods for Policy Analysis: Advanced Applied Regression
Fall 2009P A 397 - Introduction to Quantitative Analysis
Spring 2009P A 397C - Advanced Empirical Methods for Policy Analysis: Advanced Applied Regression
Fall 2008P A 397C - Advanced Empirical Methods for Policy Analysis: Advanced Applied Regression
Spring 2008P A 397C - Advanced Empirical Methods for Policy Analysis: Advanced Applied Regression
Fall 2007P A 397 - Introduction to Quantitative Analysis
Spring 2007P A 397 - Introduction to Quantitative Analysis
Fall 2006P A 397 - Introduction to Quantitative Analysis
Spring 2005P A 397 - Applied Quantitative Analysis I