Moderated by Robert Chambers, University of Maryland

Environmental stress, biotechnology, and agricultural productivity (Paper 1)

Presentation by Guanming Shi, University of Wisconsin-Madison

Biotechnology has potential to help adapt to changes in the environment and as a means to improve agricultural productivity. While biotech crops have spread rapidly across the United States, relatively little is known about the interaction between biotechnology and environmental changes. A prominent example is climate change, which has direct and indirect impacts on agricultural productivity. This paper uses observational data to investigate whether biotechnology affects crops' ability to deal with environmental stressors, including ground-level ozone. Using U.S. county-level agricultural production data, paired with remotely sensed ozone estimates, over the period 2003-2020, we estimate a fix effects model with instrumental variable for local ozone concentration. Our results suggest that biotech crops may have a disadvantage in dealing with ozone pollution. Yet, biotech adoption reduces yield distribution risks. Our results highlight the importance of breeding efforts that consider environmental stress, especially those climate change sensitive factors such as ozone pollution.

Impacts of undesirable inputs and output on state agricultural productivity (Paper 2)

Presentation by Roberto Mosheim, USDA Economic Research Service

Authors: Roberto Mosheim and Sun Ling Wang

Crop and livestock operations produce a large amount of excess nutrients and greenhouse gases. The interaction between fertilizer uses and subsequent benefits and costs is complex. On the one hand, crop plants require inorganic nutrients such as nitrogen, potash, and phosphate for crop production. On the other hand, excessive application of nutrients can damage air and water resources through soil erosion, runoff, volatilization, and leaching. According to EPA agriculture accounted for 11.2 percent of U.S. greenhouse in 2020. ERS notes that climate change has the potential to adversely impact agricultural productivity at the local and regional scale.

We use a production function augmented with four environmental variables with various panel data models both spatial and non-spatial. We employ data for spatial N, P, K from the fertilizer institute and State GHG Emissions and Removals data from EPA as well as a panel of multilateral outputs and inputs data at the U.S. state-level from USDA in the analysis.

Productivity and environmental sustainability growth (Paper 3)

Presentation by Ben Henderson, OECD

Increasing agricultural productivity growth sustainably is necessary to provide sufficient affordable and nutritious food for a growing global population, while supporting sector livelihoods and improving environmental outcomes. Innovations to grow agricultural total factor productivity (TFP) are often touted as a solution for simultaneously deliver on all these dimensions. This study compares and examines TFP and agri-environmental indictor (AEI) data to shed some light on the veracity of these claims. Following this an initial attempt is made to construct an environmentally-adjusted measure of TFP.

Accounting for environmental factors in measuring TFP (Paper 4)

Presentation by Robin Sickles, Rice University

We will explore how the directional distance function method can be modified to analyze productivity growth and to explicitly evaluate the role that undesirable outputs of the economy, such as carbon dioxide and other greenhouse gases, have on the frontier production process. We decompose productivity growth into efficiency change (catching up) and technology change (innovation) and explore implications of environmental accounting on the total factor productivity of OECD and Asian economies (Jeon, and Sickles, 2004). We also discuss a more disaggregated method utilized by Mosheim and Sickles (2020) to allow for environmental spillovers based on spatial econometric methods.  The theoretical underpinnings of the methods are discussed in detail in Sickles and Zelenyuk (2019).