Associate Professor, Financial Economics Carnegie Mellon University
Chris Telmer's research includes the effect of government subsidies on the financing of renewable energy assets.
CMU News online
2025-07-11
Carnegie Mellon University experts are developing practical solutions for a fast-changing energy system.
"Rapid AI-driven electricity demand is reshaping the power sector. Financing new generation will be challenging in a world of uncertain demand forecasts, with safeguards needed to avoid passing the costs of overbuilding onto consumers, says Chris Telmer, Associate Professor, Financial Economics. "At the same time, the grid is shifting from centralized plants and long-distance transmission to a decentralized model, with power increasingly co-located with major users like data centers and factories."
PV Magazine online
2019-04-22
“A key aspect of the analysis is novel,” said Carnegie Mellon University (CMU) finance professor Chris Telmer, who together with CMU professor Jay Apt supervised the seven Carnegie Mellon MBA students who conducted the analysis. “The students got data on what hundreds of mid-merit NGCC plants are doing and then specified solar+storage assets in order to replicate the NGCC ‘jobs being done.’”
1 min
Carnegie Mellon University experts are developing practical solutions for a fast-changing energy system. Their work modernizes infrastructure, accelerates innovation and harnesses AI for a more efficient and resilient future at a moment when the stakes for national competitiveness and public well-being have never been higher. Learn what CMU experts have to say about their Work That Matters.
2001
1995
Ph.D.
Economics
1991
M.A.
Economics
1989
B.A.
Economics
1986
2020
We provide a series of variance decompositions based on a panel data set of international goods prices. The panel spans 301 goods and services across 123 cities from 78 countries over the years 1990-2015. We analyze good-by-good deviations from the Law of One Price (LOP) for all bilateral city pairs and time periods. Our main finding is that variation within the LOP distribution is large relative to how the distribution itself moves over time.
2015
We propose a new methodology for measuring intergenerational mobility in economic well-being. Our method is based on the joint distribution of surnames and economic outcomes. It circumvents the need for intergenerational panel data, a long-standing stumbling block for understanding mobility.
