Occasional Empirical Environmental Group

This seminar will discuss results about what factors might help make carbon pricing more acceptable. The alternatives include revenue recycling, revenue earmarking, progressive refunding at the national and international levels. We will discuss results from three surveys – one in Sweden, one in 5 European countries and one in seven developing countries. The EU survey will be the main focus!

In recent years the analysis of US climate policy on the electricity sector has predominantly deployed electricity planning or capacity expansion models that use deterministic or equilibrium optimization methods. While uncertainty in key input assumptions is considered, it is usually restricted to scenario analysis. In this study we combine time-series econometric forecasting methods with an equilibrium electricity system-expansion model. The goal is to produce statistically rigorous distributions of outcomes, rather than rely upon individually selected scenarios. We apply these techniques to the case of the US Inflation Reduction Act (IRA) in the context of the western US electricity grid. Our results indicate that the impact of the IRA, in terms of additional investment in low-carbon resources, depends heavily on the realization of key exogenous variables. However, the net effect of the IRA is to sharply narrow the range of future carbon emissions, largely by eliminating states of the world where investment in natural gas resources would otherwise be optimal.

I study ownership and price-setting in the unregulated Swedish district heating market, which comprises 160 local natural monopolies out of which one third are private. Conditional on exogenous cost factors I find that private and public firms set the same unit price, but that the fixed yearly fee in private networks is about 30 percent higher, which is in line with economic theory of monopoly pricing and two-part tariffs. For a representative stand-alone household, this premium equals six percent (90 EUR) of the total yearly expenditures on district heating. Further, I find that the premium is higher fo foreign than domestically owned private firms.

This paper addresses the challenge of accurately modeling and estimating climate change damages. Time-series approaches rely on weather shocks, while cross-sectional analyses capture climatic differences but suffer from omitted variable bias. Climate is defined as the statistical pattern of weather over time, allowing for adaptation to predictable changes, unlike unpredictable weather realizations. To assess econometric approaches, I integrate forward-looking adaptation into a detailed, quantitative integrated assessment model of climate change. I analyze how adaptation affects observed damages under time-series and cross-sectional approaches and compare this information with the requirements for calculating the social costs. While neither approach fully captures climate change costs, time-series methods focusing on weather shocks outperform cross-sectional methods in several key respects.