Climate Change Economics

This paper analyzes changes in U.S. energy-intensive, trade-exposed (EITE) manufacturing over the past decade, through the lens of previously proposed climate policy measures. The American Clean Energy and Security Act of 2009 defined measures and thresholds for EITE eligibility and proposed compensatory allowances designed to reduce negative competitive impacts to domestic industry and to prevent emissions leakage. We undertook a retrospective analysis of the 2009 eligibility criteria, using the same methods with more recent data to examine trends over the 2004–2017 period. We find that energy intensity, emissions intensity, output, and emissions have fluctuated with economic conditions, and defining measures and thresholds that remain informative is challenging. Had ACES been enacted as written and not revised, the number of sectors qualifying for rebates would have decreased from 39 to 26, after adjustment for the changes in North American Industry Classification System definitions. Emissions from the eligible sectors fell 26% across the three periods of analysis, while emissions from manufacturing as a whole fell 5%. We decompose the changes in emissions into scale and intensity measures based on a hybrid measure derived from Grossman and Krueger [(1993). Environmental impacts of a North American free trade agreement. In The US-Mexico Free Trade Agreement, PM Garber (ed.). Cambridge, MA: MIT Press] and Kaya and Yokoburi [(1997). Environment, Energy, and Economy: Strategies for Sustainability. Tokyo: United Nations University Press]. As an alternative, we perform the same analyses using the EPA’s Greenhouse Gas Reporting Program data. These data, not available when ACES was written, offer annual greenhouse gas estimates for facilities that emit more than 25,000 tons CO₂e annually. Finally, we draw some recommendations for future policy including (1) using measures that make price level adjustments straightforward or unnecessary, (2) keeping EITE policy focused on a small group of industries to minimize sectoral reclassification problems, (3) identifying industries prone to emissions leakage rather than just changes in output and (4) consider spatial heterogeneity of emissions and trade patterns.

We introduce solar geoengineering (SG) and carbon dioxide removal (CDR) into an integrated assessment model to analyze the trade-offs between mitigation, SG, and CDR. We propose a novel empirical parameterization of SG that disentangles its efficacy, calibrated with climate model results, from its direct impacts. We use a simple parameterization of CDR that decouples it from the scale of baseline emissions. We find that (a) SG optimally delays mitigation and lowers the use of CDR, which is distinct from moral hazard; (b) SG is deployed prior to CDR while CDR drives the phasing out of SG in the far future; (c) SG deployment in the short term is relatively independent of discounting and of the long-term trade-off between SG and CDR over time; (d) small amounts of SG sharply reduce the cost of meeting a $2^{°}$C target and the costs of climate change, even with a conservative calibration for the efficacy of SG.

The study examines the impact of climate variables on wheat production in 10 major wheat-producing districts of Pakistan. In doing so, we apply the Driscoll–Kraay approach to estimate the panel data from 1981 to 2019. Our empirical analysis reveals that climate variables, including temperature, rainfall and humidity, follow a common correlation across districts. We find that wheat productivity and temperature, as well as rainfall, follow an inverted U-shaped relation. The response of the wheat productivity is quadratic rather than linear towards average temperature and rainfall during the specific time of cultivation, including planting, flowering and harvesting. Besides, fertilizer use promotes and humidity impedes wheat productivity. Our findings are robust considering heterogeneity, serial correlation and spatial dependency.

Climate change and emerging pests and diseases may negatively affect coffee yields and revenues in Ethiopian regions at low altitudes. Hence, the relocation of coffee farms to regions at higher altitudes has been suggested in order to assure sustainability and resilience for Ethiopian coffee production. In this paper, we study how sunk establishment costs, uncertain net returns and policy-induced incentives may affect the timing and value of a coffee farm relocation. This is done by developing a real-options model taking into account the relevant drivers of the farmer’s decision to relocate. We then present an empirical analysis examining a hypothetical relocation. We show that relocation is a rather attractive opportunity even though the presence of volatile net returns and relatively high establishment costs may induce its postponement. Thus, we determine the optimal amount of subsidy needed in order to foster the relocation process.