About

I'm a computational economist specializing in economic modeling of energy, environmental, and infrastructure policy.

At The Brattle Group, I lead the firm’s economic impact assessment work and develop large-scale modeling frameworks to evaluate the effects of economic shocks. My work combines computable general equilibrium (CGE) modeling with electricity market and power sector analysis to assess how regulatory changes, market design, technology adoption, and investment decisions affect economic activity and long-term planning outcomes. I lead the development of BEYOND, Brattle’s economic impact assessment model, as well Brattle's power sector capacity expansion model, gridSIM. 

I am also part of the teaching faculty in the Department of Economics at University of Maryland, College Park, where I teach Microeconomics for the Applied Economics program.   

In my academic research, I research optimal climate policies using dynamic programming and numerical optimization. Below I summarize my current research and model development: 

Economic Impact of the E-Rate Program (Link)
For the Schools, Health & Libraries Broadband Coalition (SHLB), we assessed the economy-wide impacts of reducing or eliminating federal E-Rate support for broadband connectivity and internal network infrastructure used by schools and libraries. Using the BEYOND model, the study estimated effects on national, regional, and state GDP, real wages, and tax revenues under scenarios eliminating all E-Rate support or only Category 2 infrastructure support. The analysis found that eliminating approximately $2.6 billion in annual E-Rate support would reduce U.S. real GDP by about $4.2 billion, real wages by $2.8 billion, and tax revenues by $1.5 billion annually, with losses distributed broadly across states. The results highlight that because broadband is an essential educational input, reducing E-Rate support forces schools and libraries to devote more of their constrained budgets to connectivity, reducing other educational activity and generating broader economic losses.

Economic Impacts of Large Load Growth in New York State
For National Grid, we assessed the economy-wide impacts of emerging large-load growth, including data centers, manufacturing facilities, and other industrial customers. Using the BEYOND model, the study estimated the economic activity associated with each MW of new load and evaluated impacts on state GDP, household income, and tax revenues under alternative load-composition scenarios. The analysis found that economic outcomes depend both on the mix of new load and on the extent to which complementary data-services activities localize within New York, highlighting the importance of broader digital-services ecosystem development in determining the economic benefits associated with data center growth.

Economic Impacts of Commercial Automobile Tort Costs (Link)
For the Institute of Legal Reform of the US Chamber of Commerce, we performed economic analysis to show how much economic growth could result from cutting back on commercial transportation lawsuits. Using the BEYOND model, the study analyzed what would happen if all states reduced their commercial auto tort costs to the levels experienced in the lowest-cost states (as a proportion of revenue), and found that: every additional $1 million in tort costs in this space, US GDP would decline by about $2 million; and that over a 10-year period, such a change would increase GDP by an average of $52.3 billion per year, through avoided litigation costs and increased economic activity. 

Economic Impacts of Inflation Reduction Act’s Clean-Energy Tax Credits (Link)
For ConservAmerica, we performed an economic analysis of clean energy tax credits and their effects on US investment, electricity rates, economic growth, and jobs through 2035. Brattle’s analysis explored the economic implications if, within this context, the available Clean Electricity Production Tax Credits (§45Y) and Clean Electricity Investment Tax Credits (§48E) were to be discontinued by Congress. The study used an integrated modeling framework that couples two tools developed by Brattle: BEYOND was used to capture economy-wide impacts of increased electricity prices, and changes in power sector investment and gridSIM, a detailed power sector capacity expansion model, was used to project the tax credits’ impacts on the generation resource mix across the US economy. 

Economic Impacts of New York’s Cap and Invest Program (NYCI) 

NYCI is a transformative policy aimed to reduce greenhouse gas emissions through a declining economy-wide emissions cap. The cap is set so that the state achieves the emissions reduction goals set forth in the Climate Leadership and Community Protection Act (CLCPA); the program’s emissions allowance auction is used to price emissions based on the supply (equal to the cap) and economy-wide demand for emissions allowances; the revenue generated through allowance auctions is invested to facilitate the state’s decarbonization efforts in an equitable way. Our study for Environmental Defense Fund examines the power sector and economy-wide impacts of NYCI. Using an integrated modeling framework that couples Brattle’s electricity capacity expansion model and macroeconomic model of the US, we study the interdependencies between carbon pricing, electricity generation, energy consumption and macroeconomic growth. The report can be found here: Link

How Learning Helps Mitigate the Worst When the Downside of Climate Change is Extreme (Link)

Deep uncertainty in equilibrium climate sensitivity (ECS), the eventual temperature increase in response to changes in GHG concentrations, has persistently been a critical issue in determining an effective yet feasible hedging strategy against low-probability, high-consequence climate outcomes. We examine how learning efforts to reduce uncertainty in ECS affects the optimal policy when the downside of climate change is catastrophic. Using stochastic dynamic programming, we investigate the role of learning under a “triple worst-case” scenario, in which climate damages are catastrophic at high temperatures; the true ECS, unknown to the world, exceeds the range of current scientific beliefs; and negative emissions technologies do not materialize at scale for deployment. We find that learning primarily contributes to welfare improvements through mid-course corrections in short-run emission abatement and long-run capital investment decisions.