Moderated by Brent Hueth, USDA Economic Research Service

Input Measurement in Agricultural Productivity: the Case of Seed Use in the United States (Paper 1)

Presentation by Richard Nehring, USDA Economic Research Service

Authors: Richard Nehring, Sam Bailey, Daniel Bonin and Laura Dodson, USDA Economic Research Service

Modern agricultural biotechnology has facilitated the development of biological innovations embodied in new seeds, contributing to sustained agricultural productivity growth and helping ensure an abundance of food and fiber (Fernandez-Cornejo, The Seed Industry in U.S. Agriculture, AIB 786, 2004). Genetically engineered (GE) varieties with pest management traits became commercially available for major crops (corn, soybeans, and cotton) in 1996. My presentation today outlines preliminary empirical results on the estimation of the pricing of seed traits for corn, cotton, and soybeans for 1948 to the present, breaking out the estimation process into three major changes in seed use. More precisely ERS has developed a revised seed input file for the national and state-level productivity accounts that incorporates quality-adjusted price and quantity indices for 1948 to 1970, 1971 to 1995, and 1996 to the present. The first period covers the introduction of hybrid corn into all major corn producing regions. The second period covers the introduction of three-way crosses in corn production. And, the third period covers the introduction of genetically modified organisms (GMOs) into not only corn production, but cotton and soybeans as well, now accounting for more than 90 percent of acres planted in all three crops.

Understanding Productivity Gaps in Kenya and East Africa (Paper 2)

Presentation by Timothy Njagi, Tegemeo Institute

The Global Agricultural Report shows that productivity gaps have been declining in East Africa despite critical investments by government and development partners. I will explain the trends in agricultural productivity, decomposing the drivers and sources of growth, use the Kenya cereal sector as a case study to explain the observed trends. The presentation shall draw lessons on what has worked, existing challenges, and opportunities for improving agricultural productivity.

Measuring Biological Capital Assets (Paper 3)

Presentation by Richard Perrin, University of Nebraska, Lincoln

Authors: Richard Perrin, Adauto Rocha and Lilyan Fulginiti

Although international accounting conventions call for countries to include accounts for farm biological capital (cows, orchards, etc) in their income, wealth and productivity accounts, the U.S. and most other countries do not do so. This is due to two important reasons: investment is not easy to track because the capital assets are produced within the farm sector itself; and the age-productivity profiles of these capital assets do not match the monotonically-decreasing profile implied by the perpetual inventory method employed to account for other capital assets. Both ERS and BEA have explored potential accounts for biological capital, resulting in an ERS cooperative agreement with the University of Nebraska to develop a complete set of biological capital accounts for possible inclusion in the official ERS accounts. In this paper we present our basic approach and describe capital accounts created for two disparate categories: dairy cows and oranges.

Valuing Irrigation Water in World Agriculture (Paper 4)

Presentation by Keith Fuglie, USDA Economic Research Service

The use of water for irrigation is an important environmental resource in agricultural production. However, for most countries, information on the quantities and especially values of irrigation water is incomplete. This work uses differences in land rental rates between irrigated and unirrigated cropland to derive estimates of the shadow value of water by country. Drawing on data from FAO and OECD, estimates of irrigated water volume and area constructed by country over 1987-2017. Estimates of the shadow value of water for irrigation is then estimated using productivity differences between irrigated and dryland agriculture. Growth in agricultural TFP has in many cases raised the value of water used for irrigation. By 2017, the world-wide shadow value of irrigation water was about $140 billion per year, or $48 per cubic meter, with large differences by country.

Discussant for Papers 1-2: GianCarlo Moschini, Iowa State University

Discussant for Paper 3: Rachel Soloveichik, Bureau of Economic Analysis

Discussant for Paper 4: Jon Samuels, Bureau of Economic Analysis

Moderated by Michael Roberts, University of Hawai’i at Mānoa

Extreme Weather Events and Agricultural Total Factor Productivity Growth (Paper 1)

Presentation by Wei Zhang, Virginia Tech

Studies of the impacts of climate change on agriculture have so far disproportionately focused on the effects of changes in average seasonal temperature and precipitation on crop yields and production. These studies are limited in terms of evaluating the overall agricultural performance under a changing climate. We use a dynamic panel data model to estimate the impacts of extreme weather events on agricultural TFP growth rate. Our preliminary estimates show that extreme weather events have on average a negative and statistically significant impact on agricultural TFP growth rate. The estimated impacts are all negative across different event types and are statistically significant for storms and droughts. The long-run effects of extreme weather events on TFP growth rate are slightly smaller. Our estimates are robust to an alternative instrumental variable approach and across different subsamples.

Past and Future Climatic Impacts on U.S. Agricultural Productivity Growth (Paper 2)

Presentation by Ruixin Yang, George Mason University

Authors: Ruixin Yang, Sun Ling Wang, Qian Liu, and Mengfei Xin

Climate change is influencing our natural and social worlds in many ways. Higher temperature and the changing precipitation pattern have also affected the agricultural productivity. This study investigated the climate impacts on U.S. agricultural productivity growth using the historical climate data derived from NClimDiv database, the projected climate data from USGS, a panel of total factor productivity estimates for 48 contiguous states from Wang et al. (2022), and yields of selected crops from NASS. We apply both stepwise linear regression (SLR) with nonlinear (quadratic) terms and nonlinear regression tree models in our model building. A commonly used training and validating procedure in machine learning was applied to choose the “optimal” models with tuned hyperparameters. The preliminary results show that the climate change generally would reduce the growth rates of TFP and other major crop yields. As expected, the impacts are not uniform spatially, and crop type changes could also remedy the negative climate impacts due to heterogeneous impacts observed in the tentative results.

Climate-induced Productivity Changes and Agricultural Trade Impacts (Paper 3)

Presentation by Maros Ivanic, USDA Economic Research Service 

Authors: Jayson Beckman and Maros Ivanic, USDA Economic Research Service

We analyze the implications of the forecasted changes in the climate for the shifts in the land types across countries, and the associated changes in yields due to the change in temperature and precipitations. We simulate the changes in the countries' agricultural yields in the GTAP model, to evaluate the implications of the climate change for future trade patterns, and the additional market impacts. We find that climate change is likely to have heterogenous impact on countries' agricultural production, resulting in some countries, such as the United States, to expand their exports, while other countries’ production shrinks.

Productivity and climate change in long-term scenarios of global agriculture (Paper 4)

Presentation by Ron Sands, USDA Economic Research Service

Long-term analysis of climate change impacts on agriculture requires use of climate, crop, and economic simulation models. The economic representation of agricultural productivity becomes important in at least two ways: future productivity growth may differ from historical patterns, and output from crop models does not translate directly into economic models. Retrospective analysis of productivity change should inform the structure and parameters used in long-term economic models. Crop models provide a point estimate of change in crop yield with climate change, but economic models allow substitution among inputs and crop yield is endogenous. Future research on climate change impacts on agriculture will benefit from comparing perspectives across econometric analysis, the structure of long-term economic simulation models, and the structure of crop simulation models.

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).

Moderated by Spiro Stefanou, USDA Economic Research Service

Panelists:

Robert Chambers, University of Maryland - Agricultural TFP and the Environment: Accounting or Adjusting?

Chris O'Donnell, University of Queensland - Sustainable productivity change in the U.S. dairy sector

Ben Henderson, OECD - Can we measure sustainable productivity growth with a single indicator?

Sun Ling Wang, USDA Economic Research Service - Accounting for environmental factors in U.S. agricultural productivity measurement

Robin Sickles, Rice University - General Discussion