Data for: Substitution elasticities between GHG-polluting and nonpolluting inputs in agricultural production: A meta-regression

Abstract of associated article: This paper reports meta-regressions of substitution elasticities between greenhouse gas (GHG) polluting and nonpolluting inputs in agricultural production, which is the main feedstock source for biofuel in the U.S. We treat energy, fertilizer, and manure collectively as the “polluting input” and labor, land, and capital as nonpolluting inputs. We estimate meta-regressions for samples of Morishima substitution elasticities for labor, land, and capital vs. the polluting input. Much of the heterogeneity of Morishima elasticities can be explained by type of primal or dual function, functional form, type and observational level of data, input categories, number of outputs, type of output, time period, and country categories. Each estimated long-run elasticity for the reference case, which is most relevant for assessing GHG emissions through life-cycle analysis, is greater than 1.0 and significantly different from zero. Most predicted long-run elasticities remain significantly different from zero at the data means. These findings imply that life-cycle analysis based on fixed proportion production functions could provide grossly inaccurate measures of GHG of biofuel.关联论文摘要：本文针对农业生产中温室气体（GHG）污染性投入与非污染性投入之间的替代弹性开展元回归（meta-regressions）分析——美国生物燃料的核心原料来源正是农业生产。本文将能源、化肥与畜禽粪便统一归类为“污染性投入”，将劳动力、土地与资本归类为非污染性投入。针对劳动力、土地、资本与污染性投入之间的莫希玛（Morishima）替代弹性样本，本文进行了元回归估计。莫希玛替代弹性的大量异质性可由以下因素解释：原函数或对偶函数类型、函数形式、数据类型与观测层级、投入类别、产出数量、产出类型、时间周期以及国家类别。针对通过生命周期分析评估温室气体排放最为相关的基准情形，所有估计得到的长期弹性均大于1.0，且在统计上显著异于0。在样本数据均值处，绝大多数预测得到的长期弹性仍在统计上显著异于0。上述研究结果表明，基于固定比例生产函数开展的生命周期分析，可能会得到与实际偏差极大的生物燃料温室气体排放测算结果。