Technology adoption as climate adaptation: evidence from US air conditioning and implications for energy systems

Seminar, Agricultural & Applied Economics Departmenthttps://windc.wisc.edu/Sue-Wing-4-5-2019.pdfOthe

The Synthesis of Bottom-Up and Top-Down Approaches to Climate Policy Modeling: Electric Power Technologies and the Cost of Limiting U.S. CO2 Emissions

In the U.S., the bulk of CO2 abatement induced by carbon taxes comes from electric power. This paper incorporates technology detail into the electricity sector of a computable general equilibrium model of the U.S. economy to characterize electric power’s technological margins of adjustment to carbon taxes and to elucidate their general equilibrium effects. Compared to the top-down production function representation of the electricity sector, the technology-rich bottom-up specification produces less abatement at a higher welfare cost, suggesting that bottom-up models do not necessarily generate lower costs of abatement than top-down models. This result is shown to be sensitive to the elasticity with which technologies’ generating capacities adjust to relative prices

Capital Malleability and the Macroeconomic Costs of Climate Policy

This paper argues for introducing the role of capital malleability into the analysis of environmental policies. The issue is explored by means of a theoretical model, a numerical analysis and a computable general equilibrium (CGE) model. Considering the three approaches together is fundamental in obtaining theory-compatible policy-relevant results. The model outcomes reveal differences between results under separate assumptions regarding the malleability of capital. When capital is imperfectly malleable a carbon policy is less effective than under the assumption of perfect malleability of capital. Therefore, it is important that, especially for the analysis of short-term environmental regulations, the issue of capital malleability is taken into consideration.General Equilibrium, CGE Models, Climate Change Policy

Technology strategies for low-carbon economic growth: a general equilibrium assessment

This paper investigates the potential for developing countries to mitigate greenhouse gas emissions without slowing their expected economic growth. A theoretical frame- work is developed that unifies bottom-up marginal abatement cost curves and partial equilibrium techno-economic simulation modeling with computational general equilibrium (CGE) modeling. The framework is then applied to engineering assessments of energy efficiency technology deployments in Armenia and Georgia. The results facilitate incorporation of bottom-up technology detail on energy-efficiency improvements into a CGE simulation of the economy-wide economic costs and mitigation benefits of technology deployment policies. Low-carbon growth trajectories are feasible in both countries, enabling reductions of up to 4 percent of baseline emissions while generating slight increases in GDP (1 percent in Armenia and 0.2 percent in Georgia). The results demonstrate how MAC curves can paint a misleading picture of the true potential for both abatement and economic growth when technological improvements operate within a system of general equilibrium interactions, but also highlight how using their underlying data to identify technology options with high opportunity cost elasticities of productivity improvement can lead to more accurate assessments of the macroeconomic consequences of technology strategies for low-carbon growth.http://documents.worldbank.org/curated/en/279241468256026769/Technology-strategies-for-low-carbon-economic-growth-a-general-equilibrium-assessmentPublished versio

The macroeconomic cost of catastrophic pollinator declines

We develop a computable general equilibrium (CGE) approach to assess the macroeconomic impacts of productivity shocks due to catastrophic losses of pollination ecosystem services at global and regional scales. In most regions, producers of pollinator dependent crops end up benefiting because direct output losses are outweighed by increased prices, while non-agricultural sectors experience large adverse indirect impacts, resulting in overall losses whose magnitudes vary substantially. By comparison, partial equilibrium analyses tend to overstate the costs to agricultural producers, understate aggregate economy-wide losses, and overstate the impacts on consumers' welfare. Our results suggest an upper bound on global willingness to pay for agricultural pollination services of $127–$152 billion

Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships

Emissions of CO2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO2 emitted by US road transport at a resolution of 1 km annually for 1980-2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO2 emissions and population density at broad spatial/temporal scales, with total on-road CO2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE's bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities' dual importance as sources of CO2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales.https://doi.org/10.1073/pnas.1421723112Published versio

Absolute vs. intensity-based emission caps

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).Cap-and-trade systems limit emissions to some pre-specified absolute quantity. Intensity-based limits, that restrict emissions to some pre-specified rate relative to input or output, are much more widely used in environmental regulation and have gained attention recently within the context of greenhouse gas (GHG) emissions trading. In this paper we provide a non-technical introduction to the differences between these two forms of emission limits. Our aim is not to advocate either form, but to elucidate the properties of each in a world where future emissions and GDP are not known with certainty. We argue that the two forms have identical effects in a world where future emissions and economic output (i.e., GDP) are known with certainty, and show that outcomes for marginal costs, abatement, emissions and welfare diverge only because of the variance of actual future GDP relative to its forecast expectation

Explaining Long-Run Changes in the Energy Intensity of the U.S. Economy

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).Recent events have revived interest in explaining the long-run changes in the energy intensity of the U.S. economy. We use a KLEM dataset for 35 industries over 39 years to decompose changes in the aggregate energy-GDP ratio into shifts in sectoral composition (structural change) and adjustments in the energy demand of individual industries (intensity change). We find that although structural change offsets a rise in sectoral energy intensities from 1960 until the mid-1970s, after 1980 the change in the industrial mix has little impact and the average sectoral energy intensity experiences decline. Then, we use these data to econometrically estimate the influence on within-industry changes in energy intensity of price-induced substitution of variable inputs, shifts in the composition of capital and embodied and disembodied technical progress. Our results suggest that innovations embodied in information technology and electrical equipment capital stocks played a key role in energy intensityâs long-run decline.U.S. Department of Energy Office of Science (BER) Grant No. DE-FO2-02ER6348

Final Technical Report: "Representing Endogenous Technological Change in Climate Policy Models: General Equilibrium Approaches"

The research supported by this award pursued three lines of inquiry: (1) The construction of dynamic general equilibrium models to simulate the accumulation and substitution of knowledge, which has resulted in the preparation and submission of several papers: (a) A submitted pedagogic paper which clarifies the structure and operation of computable general equilibrium (CGE) models (C.2), and a review article in press which develops a taxonomy for understanding the representation of technical change in economic and engineering models for climate policy analysis (B.3). (b) A paper which models knowledge directly as a homogeneous factor, and demonstrates that inter-sectoral reallocation of knowledge is the key margin of adjustment which enables induced technical change to lower the costs of climate policy (C.1). (c) An empirical paper which estimates the contribution of embodied knowledge to aggregate energy intensity in the U.S. (C.3), followed by a companion article which embeds these results within a CGE model to understand the degree to which autonomous energy efficiency improvement (AEEI) is attributable to technical change as opposed to sub-sectoral shifts in industrial composition (C.4) (d) Finally, ongoing theoretical work to characterize the precursors and implications of the response of innovation to emission limits (E.2). (2) Data development and simulation modeling to understand how the characteristics of discrete energy supply technologies determine their succession in response to emission limits when they are embedded within a general equilibrium framework. This work has produced two peer-reviewed articles which are currently in press (B.1 and B.2). (3) Empirical investigation of trade as an avenue for the transmission of technological change to developing countries, and its implications for leakage, which has resulted in an econometric study which is being revised for submission to a journal (E.1). As work commenced on this topic, the U.S. withdrawal from Kyoto and the administration's announcement of a voluntary target based on emission intensity made it apparent that the degree of emission leakage to developing countries would depend on (i) the form of the emission limit set by developed countries and (ii) the incentives faced by developing nations to accede to an international climate regime. This realization led to synergistic research on the properties of intensity targets under uncertainty, which resulted in two theoretical studies, one which has been published (A.1) and the other which is currently in review (C.5)

Second-best instruments for near-term climate policy: Intensity targets vs. the safety valve

Current proposals for greenhouse gas emissions regulations in the United States mainly take the form of emissions caps with tradable permits. Since Weitzman's (1974) [3] study of prices vs. quantities, economic theory predicts that a price instrument is superior under uncertainty in the case of stock pollutants. Given the general belief in the political infeasibility of a carbon tax in the US, there has been recent interest in two other policy instrument designs: hybrid policies and intensity targets. We extend the Weitzman model to derive an analytical expression for the expected net benefits of a hybrid instrument under uncertainty. We compare this expression to one developed by Newell and Pizer (2006) [6] for an intensity target, and show the theoretical minimum correlation between GDP and emissions required for an intensity target to be preferred over a hybrid. In general, we show that unrealistically high correlations are required for the intensity target to be preferred to a hybrid, making a hybrid a more practical instrument in practice. We test the predictions by performing Monte Carlo simulation on a computable general equilibrium model of the US economy. The results are similar, and we show with the numerical model that when marginal abatement costs are non-linear, an even higher correlation is required for an intensity target to be preferred over a safety valve.Doris Duke Charitable Foundatio