How Does State-Level Carbon Pricing in the United States Affect Industrial Competitiveness?
June 2020
Working Paper Number:
CES-20-21
Abstract
Pricing carbon emissions from an individual jurisdiction may harm the competitiveness of local firms, causing the leakage of emissions and economic activity to other regions. Past research concentrates on national carbon prices, but the impacts of subnational carbon prices could be more severe due to the openness of regional economies. We specify a flexible model to capture competition between a plant in a state with electric sector carbon pricing and plants in other states or countries without such pricing. Treating energy prices as a proxy for carbon prices, we estimate model parameters using confidential plant-level Census data, 1982'2011. We simulate the effects on manufacturing output and employment of carbon prices covering the Regional Greenhouse Gas Initiative (RGGI) in the Northeast and Mid-Atlantic regions. A carbon price of $10 per metric ton on electricity output reduces employment in the regulated region by 2.7 percent, and raises employment in nearby states by 0.8 percent, although these estimates do not account for revenue recycling in the RGGI region that could mitigate these employment changes. The effects on output are broadly similar. National employment falls just 0.1 percent, suggesting that domestic plants in other states as opposed to foreign facilities are the principal winners from state or regional carbon pricing.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
demand,
market,
econometric,
macroeconomic,
cost,
price,
state,
regional,
expenditure,
regulatory,
country,
pricing,
revenue,
subsidy,
emission,
energy prices,
regional economic,
region,
electricity prices
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Census of Manufactures,
Annual Survey of Manufactures,
Standard Industrial Classification,
Bureau of Economic Analysis,
Energy Information Administration,
County Business Patterns,
University of Maryland,
Longitudinal Business Database,
Census of Manufacturing Firms,
North American Industry Classification System,
Individual Characteristics File,
Commodity Flow Survey,
Federal Statistical Research Data Center
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'How Does State-Level Carbon Pricing in the United States Affect Industrial Competitiveness?' are listed below in order of similarity.
-
Working PaperThe U.S. Manufacturing Sector's Response to Higher Electricity Prices: Evidence from State-Level Renewable Portfolio Standards🔥
October 2022
Working Paper Number:
CES-22-47
While several papers examine the effects of renewable portfolio standards (RPS) on electricity prices, they mainly rely on state-level data and there has been little research on how RPS policies affect manufacturing activity via their effect on electricity prices. Using plant-level data for the entire U.S. manufacturing sector and all electric utilities from 1992 ' 2015, we jointly estimate the effect of RPS adoption and stringency on plant-level electricity prices and production decisions. To ensure that our results are not sensitive to possible pre-existing differences across manufacturing plants in RPS and non-RPS states, we implement coarsened exact covariate matching. Our results suggest that electricity prices for plants in RPS states averaged about 2% higher than in non-RPS states, notably lower than prior estimates based on state-level data. In response to these higher electricity prices, we estimate that plant electricity usage declined by 1.2% for all plants and 1.8% for energy-intensive plants, broadly consistent with published estimates of the elasticity of electricity demand for industrial users. We find smaller declines in output, employment, and hours worked (relative to the decline in electricity use). Finally, several key RPS policy design features that vary substantially from state-to-state produce heterogeneous effects on plant-level electricity prices.View Full Paper PDF
-
Working PaperTechnology Lock-In and Costs of Delayed Climate Policy
July 2023
Working Paper Number:
CES-23-33
This paper studies the implications of current energy prices for future energy efficiency and climate policy. Using U.S. Census microdata and quasi-experimental variation in energy prices, we first show that manufacturing plants that open when electricity prices are low consume more energy throughout their lifetime, regardless of current electricity prices. We then estimate that a persistent bias of technological change toward energy can explain the long-term effects of entry-year electricity prices on energy intensity. Overall, this 'technology lock-in' implies that increasing entry-year electricity prices by 10% would decrease a plant's energy intensity of production by 3% throughout its lifetime.View Full Paper PDF
-
Working PaperRelative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry
April 2018
Working Paper Number:
CES-18-16
This paper addresses the relative effectiveness of market vs program based climate policies. We compute the carbon price resulting in an equivalent reduction in energy from programs that eliminate the efficiency gap. A reduced-form stochastic frontier energy demand analysis of plant level electricity and fuel data, from energy-intensive chemical sectors, jointly estimates the distribution of energy efficiency and underlying price elasticities. The analysis controls for plant level price endogeneity and heterogeneity to obtain a decomposition of efficiency into persistent (PE) and time-varying (TVE) components. Total inefficiency is relatively small and price elasticities are relatively high. If all plants performed at the 90th percentile of their efficiency distribution, the reduction in energy is between 4% and 13%. A modest carbon price of between $9.48/ton and $14.01/ton CO2 would achieve reductions in energy use equivalent to all manufacturing plants making improvements to close the efficiency gap.View Full Paper PDF
-
Working PaperMeasuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.View Full Paper PDF
-
Working PaperThe Effects of Environmental Regulation on the Competiveness of U.S. Manufacturing
January 2011
Working Paper Number:
CES-11-03
Whether and to what extent environmental regulations influence the competitiveness of firms remains a hotly debated issue. Using detailed production data from tens of thousands of U.S. manufacturing plants drawn from Annual Survey of Manufactures, we estimate the effects of environmental regulations'captured by the Clean Air Act Amendments' division of counties into pollutant-specific nonattainment and attainment categories'on manufacturing plants' total factor productivity (TFP) levels. We find that among surviving polluting plants, a nonattainment designation is associated with a roughly 2.6 percent decline in TFP. The regulations governing ozone have particularly discernable effects on productivity, though effects are also seen among particulates and sulfur dioxide emitters. Carbon monoxide nonattainment, on the other hand, appears to increase measured TFP, though this appears to be concentrated among refineries. When we apply corrections for two likely sources of positive bias in these estimates (price mismeasurement and sample selection on survival), we estimate that the total TFP loss for polluting plants in nonattaining counties is 4.8 percent. This corresponds to an annual lost output in the manufacturing sector of roughly $14.7 billion in 1987 dollars ($24.4 billion in 2009 dollars). These costs have important implications for both the intensity and location of firm expansions.View Full Paper PDF
-
Working PaperENVIRONMENTAL REGULATION AND INDUSTRY EMPLOYMENT: A REASSESSMENT
July 2013
Working Paper Number:
CES-13-36
This paper examines the impact of environmental regulation on industry employment, using a structural model based on data from the Census Bureau's Pollution Abatement Costs and Expenditures Survey. This model was developed in an earlier paper (Morgenstern, Pizer, and Shih (2002) - MPS). We extend MPS by examining additional industries and additional years. We find widely varying estimates across industries, including many implausibly large positive employment effects. We explore several possible explanations for these results, without reaching a satisfactory conclusion. Our results call into question the frequent use of the average impacts estimated by MPS as a basis for calculating the quantitative impacts of new environmental regulations on employment.View Full Paper PDF
-
Working PaperEmpirical Distribution of the Plant-Level Components of Energy and Carbon Intensity at the Six-digit NAICS Level Using a Modified KAYA Identity
September 2024
Working Paper Number:
CES-24-46
Three basic pillars of industry-level decarbonization are energy efficiency, decarbonization of energy sources, and electrification. This paper provides estimates of a decomposition of these three components of carbon emissions by industry: energy intensity, carbon intensity of energy, and energy (fuel) mix. These estimates are constructed at the six-digit NAICS level from non-public, plant-level data collected by the Census Bureau. Four quintiles of the distribution of each of the three components are constructed, using multiple imputation (MI) to deal with non-reported energy variables in the Census data. MI allows the estimates to avoid non-reporting bias. MI also allows more six-digit NAICS to be estimated under Census non-disclosure rules, since dropping non-reported observations may have reduced the sample sizes unnecessarily. The estimates show wide variation in each of these three components of emissions (intensity) and provide a first empirical look into the plant-level variation that underlies carbon emissions.View Full Paper PDF
-
Working PaperThe Energy Efficiency Gap and Energy Price Responsiveness in Food Processing
June 2020
Working Paper Number:
CES-20-18
This paper estimates stochastic frontier energy demand functions with non-public, plant-level data from the U.S. Census Bureau to measure the energy efficiency gap and energy price elasticities in the food processing industry. The estimates are for electricity and fuel use in 4 food processing sectors, based on the disaggregation of this industry used by the National Energy Modeling System Industrial Demand Module. The estimated demand functions control for plant inputs and output, energy prices, and other observables including 6-digit NAICS industry designations. Own price elasticities range from 0.6 to -0.9 with little evidence of fuel/electricity substitution. The magnitude of the efficiency estimates is sensitive to the assumptions but consistently reveal that few plants achieve 100% efficiency. Defining a 'practical level of energy efficiency' as the 95th percentile of the efficiency distributions and averaging across all the models result in a ~20% efficiency gap. However, most of the potential reductions in energy use from closing this efficiency gap are from plants that are 'low hanging fruit'; 13% of the 20% potential reduction in the efficiency gap can be obtained by bringing the lower half of the efficiency distribution up to just the median level of observed performance. New plants do exhibit higher energy efficiency than existing plants which is statistically significant, but the difference is small for most of the industry; ranging from a low of 0.4% to a high of 5.7%.View Full Paper PDF
-
Working PaperElectricity Pricing to U.S. Manufacturing Plants, 1963-2000
October 2007
Working Paper Number:
CES-07-28
We construct a large customer-level database and use it to study electricity pricing patterns from 1963 to 2000. The data show tremendous cross-sectional dispersion in the electricity prices paid by manufacturing plants, reflecting spatial price differences and quantity discounts. Price dispersion declined sharply between 1967 and 1977 because of erosion in quantity discounts. To estimate the role of cost factors and markups in quantity discounts, we exploit differences among utilities in the purchases distribution of their customers. The estimation results reveal that supply costs per watt-hour decline by more than half over the range of customer-level purchases in the data, regardless of time period. Prior to the mid 1970s, marginal price and marginal cost schedules with respect to annual purchase quantity are remarkably similar, in line with efficient pricing. In later years, marginal supply costs exceed marginal prices for smaller manufacturing customers by 10% or more. The evidence provides no support for a standard Ramsey-pricing interpretation of quantity discounts on the margin we study. Spatial dispersion in retail electricity prices among states, counties and utility service territories is large, rises over time for smaller purchasers, and does not diminish as wholesale power markets expand in the 1990s.View Full Paper PDF
-
Working PaperThe Impact of Industrial Opt-Out from Utility Sponsored Energy Efficiency Programs
October 2023
Working Paper Number:
CES-23-52
Industry accounts for one-third of energy consumption in the US. Studies suggest that energy efficiency opportunities represent a potential energy resource for regulated utilities and have resulted in rate of return regulated demand-side management (DSM) and energy efficiency (EE) programs. However, many large customers are allowed to self-direct or opt-out. In the Carolinas (NC and SC), over half of industrial and large commercial customers have selected to opt out. Although these customers claim they invest in EE improvements when it is economic and cost-effective to do so, there is no mechanism to validate whether they actually achieved energy savings. This project examines the industrial energy efficiency between the program participants and non participants in the Carolinas by utilizing the non-public Census of Manufacturing data and the public list of firms that have chosen to opt out. We compare the relative energy efficiency between the stay-in and opt-out plants. The t-test results suggest opt-out plants are less efficient. However, the opt-out decisions are not random; large plants or plants belonging to large firms are more likely to opt out, possibly because they have more information and resources. We conduct a propensity score matching method to account for factors that could affect the opt-out decisions. We find that the opt-out plants perform at least as well or slightly better than the stay-in plants. The relative performance of the opt-out firms suggest that they may not need utility program resources to obtain similar levels of efficiency from the stay-in group.View Full Paper PDF
