The potential cost of methane and nitrous oxide emissions regulation in U.S. agriculture

Most studies on the impacts of agriculture on the environment have devoted efforts to measure the environmental impacts of the sector rather than to assess its ability to reduce or mitigate such impacts. Some have addressed the environmental efficiency of the sector (Reinhard, et al., 1999, Ball et al., 1994 and 2004; Rezek and Perrin, 2004 and Serra et al., 2011) but only few have examined greenhouse gas emissions (Njuki and Bravo-Ureta, 2015; Dakpo, Jeanneaux and Latruffe, 2016) from the sector. This paper analyzes the agricultural performance of states in the U.S. in terms of their ability to reduce emissions of methane and nitrous oxide, two major greenhouse gases (GHGs) with important global warming potential. The analysis evaluates Färe’s PAC (pollution abatement cost) for each state and year, a measure of the opportunity costs of subjecting the sector to GHG emissions regulation. Using both hyperbolic and directional distance functions to specify the technology with good and bad outputs, we find that such regulations might reduce output by an average of about 2%, though the results for individual states vary quite widely

The increasing opportunity cost of sequestering CO2 in the Brazilian Amazon forest.

Bush fires raged across the Brazilian Amazon in 2019. The CO2 that was sequestered in those forests is now in the atmosphere, adding to the rate of global warming. The burned-over land will likely be converted to agriculture. Possible contributors to these events include climate change itself, creating hotter, drier conditions, and what is reportedly a reduction in the vigor of forest preservation efforts under a new government. But here we explore a third possible contributor: technical change may have been increasing the incentives to convert forests to agriculture. We examine the nature of technical change from 2003 to 2015, across 287 municipalities within Brazil’s “arc of deforestation”. We consider grains, livestock and timber as agricultural outputs and CO2 emission from deforestation as an undesirable output. On average across the region, we estimate the annual rate of technical change in agriculture over this period to have been 4.9%, with a significant bias toward agricultural outputs and away from CO2 emissions, meaning that it has been increasingly attractive to convert these forests to agriculture. This technological incentive for deforestation has thus been building up during the early part of this century, but actual deforestation was held in check somewhat by forest preservation policies until recently, when a more relaxed policy environment has allowed the increased technological incentive for deforestation to be more fully expressed. These changes have added to climate change as contributors to the recent burst in Amazon forest destruction

An expected value of sample information (EVSI) approach for estimating the payoff from a variable rate technology.

This paper examines the payoff to variable rate technology (VRT) using a Bayesian approach following literature on the expected value of sample information (EVSI). In each cell within a field, we compare the expected payoff from an optimal variable rate conditioned on a signal from that cell, with the expected payoff from a uniform rate technology (URT) that is optimal for all cells in the field. This comparison, when evaluated across the theoretical distribution of signals, provides an estimate of the expected gross benefit from VRT relative to URT. Under plausible assumptions, a closed-form algebraic solution relates this expected benefit to field and nitrogen response characteristics. We apply our approach to data from on-farm field-level experiments conducted by the Data-Intensive Farm Management Project (DIFM) (Bullock, et al. 2019), which examined nitrogen (N) response across cells for which soil electroconductivity (EC) served as the signal related to nitrogen response. We calculate the expected gross benefits to be about $1.81/ac, insufficient to support costs of VRT implementation. Our model provides quantitative estimates of the extent to which this poor outcome could be improved by a higher correlation between the EC signal and the state of nature of interest, by higher variability of the state of nature across cells, and by a sharper curvature of yield response to N

Dual technological development in Botswana agriculture: A Stochastic input distance function approach

To improve the welfare of the rural poor and keep them in the countryside, the government of Botswana has been spending 40% of the value of agricultural GDP on agricultural support services. But can investment make smallholder agriculture prosperous in such adverse conditions? This paper derives an answer by applying a two-output six-input stochastic translog distance function, with inefficiency effects and biased technical change to panel data for the 18 districts and the commercial agricultural sector, from 1979 to 1996 This model demonstrates that herds are the most important input, followed by draft power. land and seeds. Multilateral indices for technical change, technical efficiency and total factor productivity (TFP) show that the technology level of the commercial agricultural sector is more than six times that of traditional agriculture and that the gap has been increasing, due to technological regression in traditional agriculture and modest progress in commercial agriculture. Since the levels of efficiency are similar, the same patient is repeated by the TFP indices. This result highlights the policy dilemma of the trade-off between efficiency and equity objectives