Using Cellulosic Ethanol to ‘Go Green’: What Price for Carbon?

The revised Renewable Fuels Standard (RFS2) mandates that cellulosic biofuels be part of the liquid transportation fuel mix and contribute to reducing our carbon footprint. Unfortunately, since no commercial cellulosic biorefinery exists and cellulosic biomass production is typically smaller scale than conventional crop production, limited knowledge exists of the actual costs of producing cellulosic biomass and converting it to cellulosic ethanol. Understanding of the implications of RFS2 requires a better understanding of the economics of producing cellulosic ethanol. We use the Biofuel Breakeven model (BIOBREAK), a simple long run breakeven model that represents the feedstock supply system and biofuel refining process, along with estimates of the potential reduction in carbon emissions from biofuels relative to conventional fuels, to derive the implicit carbon price (or carbon credit) needed to sustain a biomass market and cellulosic ethanol industry. We evaluate BIOBREAK under different oil prices, the RFS2 mandate, and with and without other biofuel incentives.Environmental Economics and Policy, Resource /Energy Economics and Policy, Biofuels, Biomass, Cellulosic Ethanol, RFS2, Carbon,

Essays concerning the cellulosic biofuel industry

Despite market-based incentives and mandated production, the U.S. cellulosic biofuel industry has been slow to develop. This dissertation explores the economic factors that have limited industry development along with important economic tradeoffs that will be encountered with commercial-scale production. The first essay provides an overview of the policies, potential, and challenges of the biofuel industry, with a focus on cellulosic biofuel. The second essay considers the economics of cellulosic biofuel production. Breakeven models of the local feedstock supply system and biofuel refining process are constructed to develop the Biofuel Breakeven (BioBreak) program, a stochastic, Excel-based program that evaluates the feasibility of local biofuel and biomass markets under various policy and market scenarios. An application of the BioBreak program is presented using expected market conditions for 14 local cellulosic biofuel markets that vary by feedstock and location. The economic costs of biofuel production identified from the BioBreak application are higher than frequently anticipated and raise questions about the potential of cellulosic ethanol as a sustainable and economical substitute for conventional fuels. Program results also are extended using life-cycle analysis to evaluate the cost of reducing GHG emissions by substituting cellulosic ethanol for conventional fuel. The third essay takes a closer look at the economic trade-offs within the biorefinery industry and feedstock production processes. A long-run biomass production through bioenergy conversion cost model is developed that incorporates heterogeneity of biomass suppliers within and between local markets. The model builds on previous literature by treating biomass as a non-commoditized feedstock and relaxes the common assumption of fixed biomass density and price within local markets. An empirical application is provided for switchgrass-based ethanol production within U.S. crop reporting districts (CRDs). Incorporating location-specific biomass supply conditions creates unique and important economic tradeoffs within each CRD that have important impacts on the potential supply and distribution of U.S. cellulosic biofuel production

Factors Influencing Corn Fungicide Treatment Decisions

Fungal disease management in U.S. corn production has undergone a major shift in the last 2 decades. The decision to apply fungicide, a management practice that was once rarely considered, is now contemplated annually by many U.S. corn producers. We investigate potential factors underlying the fungicide treatment decision. We use economics, agronomy, and plant pathology literature to develop a conceptual model of the fungicide treatment decision and test the model using a survey of Midwest corn producers. We find the treatment decision is positively related to perceived economic gains, but heuristic factors also have a strong influence

An Economic Evaluation of US Biofuel Expansion Using the Biofuel Breakeven Program with GHG Accounting

We present results from an application of the Biofuel Breakeven program (BioBreak) to 14 US cellulosic ethanol markets that vary by feedstock and location. BioBreak estimates the economic costs of cellulosic biofuel production for each market and identifies the necessary conditions to sustain long-run markets. Based on current market conditions, our results suggest that long-run cellulosic ethanol production is not sustainable without significant government intervention or high long-run oil prices ($135-170 per barrel). Using life-cycle analysis for cellulosic ethanol and conventional gasoline, we extend the BioBreak program results to derive an implicit value of reduced greenhouse gas emissions embodied in cellulosic ethanol. For the markets considered in our analysis, sustaining cellulosic ethanol production is equivalent to valuing the reduction in CO2 equivalents between$141 and $282 per metric ton.This research was supported (in part) by Iowa State University's Biobased Industry Center (BIC)

An economic breakeven model of cellulosic feedstock production and ethanol conversion with implied carbon pricing

The objectives of this paper include: 1) developing an economic framework to estimate long run equilibrium breakeven prices that cellulosic ethanol processors can pay for the marginal or last unit of biomass feedstock they purchase and still breakeven and that cellulosic feedstock producers need to receive for supplying the last unit of feedstock delivered to a commercial-scale plant; 2) estimating the gap or difference between the biorefinery’s willingness to pay (WTP) or derived demand for the last unit of cellulosic feedstock and the suppliers’ willingness to accept (WTA) or marginal cost (MC) of supplying the last unit of feedstock; 3) completing a life-cycle analysis (LCA) of each feedstock alternative or a “well-to-wheels” accounting of the potential greenhouse gas (GHG) savings associated with feedstock-specific ethanol relative to gasoline; and 4) calculating the carbon price or credit necessary for a biofuel market to exist in the long run. The model is designed to address various policy issues related to cellulosic biofuel production, including cellulosic biofuel production costs, the cost of cellulosic feedstock production when accounting for all costs incurred, government intervention costs either through tax credits and other incentives needed to sustain biofuel markets or through mandates to achieve the revised Renewable Fuels Standard (RFS.2), and finally, the implicit price or credit for CO2e embodied in cellulosic biofuel

Decomposing economic mobility transition matrices

The intergenerational mobility literature has consistently found that the distribution of adult economic outcomes differ markedly depending on parental economic status, yet much remains to be understood about the drivers or determinants of this relationship. Existing literature on potential drivers focuses primarily on mean effects. To help provide a more complete picture of the potential forces driving economic persistence, we propose a method to decompose transition matrices and related indices. Specifically, we decompose differences between an estimated transition matrix and a benchmark transition matrix into portions attributable to differences in characteristics between individuals from different households (a composition effect) and portions attributable to differing returns to these characteristics between individuals from different households (a structure effect). We also incorporate a detailed decomposition, based on copula theory, that decomposes the composition effect into portions attributable to specific covariates and their interactions. We illustrate our method using data on white men from the 1979 National Longitudinal Survey of Youth. Estimation is based on an extended Mincer equation that includes cognitive and non-cognitive measures. To address the potential endogeneity of education, we implement an IV strategy that allows us to estimate causal effects and investigate the role of unobserved ability

Decomposing Joint Distributions via Reweighting Functions: An Application to Intergenerational Economic Mobility

We propose a decomposition method that extends the traditional Oaxaca-Blinder decomposition to a continuous group membership setting that can be applied to any distributional measure of interest. This is achieved by reframing the problem as a decomposition of joint distributions: we decompose the difference between an empirical and a (hypothetical) independent joint distribution of membership index and an outcome of interest. Differences are divided into a composition effect and a structure effect. The method is based on the estimation of a counterfactual joint distribution via reweighting functions that can be caste into various distributional measures to investigate the drivers of the empirical relationship. We apply the method to U.S. intergenerational economic mobility and investigate multiple versions of the intergenerational elasticity of income (IGE): the traditional linear IGE, quantile regression counterparts, and a nonparametric IGE. Quantile results reveal a U-shaped effect which is primarily compositional in nature; nonparametric results indicate the composition effect is the main driver of the mean parental-offspring link at low levels of parental income while the structural effect is the main driver at high levels of parental income. Both of these effects are masked by the traditional IGE which implies an even 50-50 split between the composition and structure effect

Decomposing economic mobility transition matrices

The intergenerational mobility literature has consistently found that the distribution of adult economic outcomes differ markedly depending on parental economic status, yet much remains to be understood about the drivers or determinants of this relationship. Existing literature on potential drivers focuses primarily on mean effects. To help provide a more complete picture of the potential forces driving economic persistence, we propose a method to decompose transition matrices and related indices. Specifically, we decompose differences between an estimated transition matrix and a benchmark transition matrix into portions attributable to differences in characteristics between individuals from different households (a composition effect) and portions attributable to differing returns to these characteristics between individuals from different households (a structure effect). We also incorporate a detailed decomposition, based on copula theory, that decomposes the composition effect into portions attributable to specific covariates and their interactions. We illustrate our method using data on white men from the 1979 National Longitudinal Survey of Youth. Estimation is based on an extended Mincer equation that includes cognitive and non-cognitive measures. To address the potential endogeneity of education, we implement an IV strategy that allows us to estimate causal effects and investigate the role of unobserved ability

Understanding intergenerational economic mobility by decomposing joint distributions

We propose a simple and generalizable decomposition method to evaluate intergenerational economic mobility. The method decomposes the difference between the empirical parent-offspring joint distribution of incomes and a hypothetical independent parent-offspring joint distribution of incomes. The difference is attributed to (1) a portion due to a link between parental income and offspring characteristics (a composition effect) and (2) a portion due to a link between parental income and the returns to characteristics (a structure effect). The method is based on the estimation of counterfactual joint distributions consistent with (actual and counterfactual) conditional distributions estimated via distributional regression and (actual and counterfactual) distributions of covariates. The counterfactual joint distributions are then caste into common measures of mobility found in the literature: intergenerational elasticities of incomes and their quantile regression counterparts, transition matrices, summary indices of transition matrices, and upward mobility probabilities. These counterfactual measures are used to assign portions of measured (im)mobility to composition and structure effects. We apply the method to U.S. intergenerational economic mobility of white males born between 1957 and 1964. Across multiple mobility measures and using two different counterfactuals, we find that the composition effect (i.e., differences in the distribution of characteristics) generally accounts for about 60-70% of the measured mobility gap. Further, we find evidence of a safety-net effect of parental income which appears to be primarily compositional in nature

Understanding intergenerational economic mobility by decomposing joint distributions

We propose a simple and generalizable decomposition method to evaluate intergenerational economic mobility. The method decomposes the difference between the empirical parent-offspring joint distribution of incomes and a hypothetical independent parent-offspring joint distribution of incomes. The difference is attributed to (1) a portion due to a link between parental income and offspring characteristics (a composition effect) and (2) a portion due to a link between parental income and the returns to characteristics (a structure effect). The method is based on the estimation of counterfactual joint distributions consistent with (actual and counterfactual) conditional distributions estimated via distributional regression and (actual and counterfactual) distributions of covariates. The counterfactual joint distributions are then caste into common measures of mobility found in the literature: intergenerational elasticities of incomes and their quantile regression counterparts, transition matrices, summary indices of transition matrices, and upward mobility probabilities. These counterfactual measures are used to assign portions of measured (im)mobility to composition and structure effects. We apply the method to U.S. intergenerational economic mobility of white males born between 1957 and 1964. Across multiple mobility measures and using two different counterfactuals, we find that the composition effect (i.e., differences in the distribution of characteristics) generally accounts for about 60-70% of the measured mobility gap. Further, we find evidence of a safety-net effect of parental income which appears to be primarily compositional in nature