- School of Economics
Juan Moreno-Cruz is an Assistant Professor in the School of Economics. He has a Ph.D. in Economics from the University of Calgary and a B.S. and M.S. in Electrical Engineering from the University of Los Andes in Bogota, Colombia. Moreno-Cruz’s research focuses on the interaction of energy systems, technological change, and climate policy. Moreno-Cruz has investigated how technologies designed to modify the climate affect the strategic interaction among nations. Currently, he is developing a new set of theoretical and empirical tools to study energy-system transitions in order to inform energy and environmental policy. Moreno-Cruz's work is at the intersection between applied theory and public policy.
- Ph.D., University of Calgary
- M.S., Universidad de Los Andes
- B.S., Universidad de Los Andes
- Economic Growth and Institutions
- Economic History
- Energy Economics
- Environmental Economics
- International Trade
- Natural Resource Economics
- Policy Analysis
- Technological Change
- Uncertainty and Decision-Making
- Urban Economics
- ECON-4321: Tech & Entrepreneurship
- ECON-6106: Microeconomic Analysis
- ECON-6160: Econometric Analysis
- ECON-6380: Economic of Environment
- ECON-6440: Economics of Technology
- ECON-7032: Macro of Innovation
- ECON-7102: Environmental Econ I
- Regional Energy Rebound Effect: The Impact of Economy-Wide and Sector Level Energy Efficiency Improvement in Georgia, USA
Rebound effect is defined as the lost part of ceteris paribus energy savings from improvements on energy efficiency. In this paper, we investigate economy-wide energy rebound effects by developing a computable general equilibrium (CGE) model for Georgia, USA. The model adopts a highly disaggregated sector profile and highlights the substitution possibilities between different energy sources in the production structure. These two features allow us to better characterize the change in energy use in face of an efficiency shock, and to explore in detail how a sector-level shock propagates throughout the economic structure to generate aggregate impacts. We find that with economy-wide energy efficiency improvement on the production side, economy-wide rebound is moderate. Energy price levels fall very slightly, yet sectors respond to these changing prices quite differently in terms of local production and demand. Energy efficiency improvements in particular sectors (epicenters) induce quite different economy-wide impacts. In general, we expect large rebound if the epicenter sector is an energy production sector, a direct upstream/downstream sector of energy production sectors, a transportation sector or a sector with high production elasticity. Our analysis offers valuable insights for policy makers aiming to achieve energy conservation through increasing energy efficiency.
- A New Approach for Optimal Electricity Planning and Dispatching with Hourly TIme-Scale Air Quality and Health Considerations
The production of electricity from coal, natural gas, petroleum, and biomass releases air pollutants with significant impacts on ecosystems and human health. Pollutant exposure depends not only on the pollutant source emissions rate and the relative location of the power plant to population centers but also on temperature, wind velocity, and other atmospheric conditions, all of which vary by hour, day, and season. We have developed a method to evaluate fluctuating pollutant formation from source emissions, which we integrate within an electricity production model. In a case study of the state of Georgia from 2004 to 2011, we show how to reduce air pollutants and health impacts by shifting production among plants during a select number of hourly periods.
- Do Atlanta Residents Value MARTA? Selecting an Autoregressive Model to Recover Willingness to Pay
Understanding homeowners’ marginal willingness-to-pay (MWTP) for proximity to public transportation infrastructure is important for planning and policy. Naïve estimates of MWTP, however, may be biased as a result of spatial dependence, spatial correlation, and/or spatially endogenous variables. In this paper we discuss a class of spatial autoregressive models that control for these spatial effects, and apply them to sample data collected for the Atlanta, Georgia housing market. We provide evidence that a general-to-specific model selection methodology that relies on the generality of the spatial Durbin model (SDM) should be preferred to the classical specific-to-general methodology that begins with an assumption of no spatial effects. We show that applying the SDM raises the estimate of MWTP for transit proximity in Atlanta but also widens its confidence interval, relative to ordinary linear regression. This finding may have implications for risk estimations in land value capture forecasts and transportation policy decisions.
- Mitigation and the Geoengineering Threat
Recent scientific advances have introduced the possibility of engineering the climate system to lower ambient temperatures without lowering greenhouse gas concentrations. This possibility has created an intense debate given the ethical, moral and scientific questions it raises. In this paper I examine the economic issues introduced when geoengineering becomes available in a standard two-period two-country model where strategic interaction leads to suboptimal mitigation. Geoengineering introduces the possibility of technical substitution away from mitigation, but it also affects the strategic interaction across countries: mitigation decisions made in the first period directly affect the geoengineering decisions made in the second period. With similar countries, I find the strategic effect creates greater incentives for free-riding on mitigation, but with asymmetric countries, the strategic effect that arises from the prospect of geoengineering can induce inefficiently high mitigation levels in equilibrium.
- Climate Policy under Uncertainty: A Case for Solar Geoengineering
Solar Radiation Management (SRM) has two characteristics that make it useful for managing climate risk: it is quick and it is cheap. SRM cannot, however, perfectly offset CO2-driven climate change, and its use introduces novel climate and environmental risks. We introduce SRM in a simple economic model of climate change that is designed to explore the interaction between uncertainty in the climate’s response to CO2 and the risks of SRM in the face of carbon-cycle inertia. The fact that SRM can be implemented quickly, reducing the effects of inertia, makes it a valuable tool to manage climate risks even if it is relatively ineffective at compensating for CO2-driven climate change or if its costs are large compared to traditional abatement strategies. Uncertainty about SRM is high, and decision makers must decide whether or not to commit to research that might reduce this uncertainty. We find that even modest reductions in uncertainty about the side-effects of SRM can reduce the overall costs of climate change in the order of 10%.
- The Intergenerational Transfer of Solar Radiation Management Capabilities and Atmospheric Carbon Stocks
Solar radiation management (SRM) technologies are considered one of the likeliest forms of geoengineering. If developed, a future generation could deploy them to limit the damages caused by the atmospheric carbon stock inherited from the current generation, despite their negative side effects. Should the current generation develop these geoengineering capabilities for a future generation? And how would a decision to develop SRM impact on the current generation’s abatement efforts? Natural scientists, ethicists, and other scholars argue that future generations could be more sanguine about the side effects of SRM deployment than the current generation. In this paper, we add economic rigor to this important debate on the intergenerational transfer of technological capabilities and pollution stocks. We identify three conjectures that constitute potentially rational courses of action for current society, including a ban on the development of SRM. However, the same premises that underpin these conjectures also allow for a novel possibility: If the development of SRM capabilities is sufficiently cheap, the current generation may for reasons of intergenerational strategy decide not just to develop SRM technologies, but also to abate more than in the absence of SRM.
- Strategic Incentives for Climate Geoengineering Coalitions to Exclude Broad Participation
Solar geoengineering is the deliberate reduction in the absorption of incoming solar radiation by the Earth's climate system with the aim of reducing impacts of anthropogenic climate change. Climate model simulations project a diversity of regional outcomes that vary with the amount of solar geoengineering deployed. It is unlikely that a single small actor could implement and sustain global-scale geoengineering that harms much of the world without intervention from harmed world powers. However, a sufficiently powerful international coalition might be able to deploy solar geoengineering. Here, we show that regional differences in climate outcomes create strategic incentives to form coalitions that are as small as possible, while still powerful enough to deploy solar geoengineering. The characteristics of coalitions to geoengineer climate are modeled using a 'global thermostat setting game' based on climate model results. Coalition members have incentives to exclude non-members that would prevent implementation of solar geoengineering at a level that is optimal for the existing coalition. These incentives differ markedly from those that dominate international politics of greenhouse-gas emissions reduction, where the central challenge is to compel free riders to participate.
- A Simple Model to Account for Regional Inequalities in the Effectiveness of Solar Radiation Management
We present a simple model to account for the potential effectiveness of solar radiation management (SRM) in compensating for anthropogenic climate change. This method provides a parsimonious way to account for regional inequality in the assessment of SRM effectiveness and allows policy and decision makers to examine the linear climate response to different SRM configurations. To illustrate how the model works, we use data from an ensemble of modeling experiments conducted with a general circulation model (GCM). We find that an SRM scheme optimized to restore population-weighted temperature changes to their baseline compensates for 99% of these changes while an SRM scheme optimized for population-weighted precipitation changes compensates for 97% of these changes. Hence, while inequalities in the effectiveness of SRM are important, they may not be as severe as it is often assumed.