A team of economists found that the U.S. Department of Agriculture has been underestimating the role that unusual weather plays in agricultural productivity, thus overestimating the effectiveness of some agricultural policies.
In the first study of agricultural total factor productivity (TFP) that reports net weather effects and measures how ignoring weather distorts interpretations of productivity, the researchers looked at weather from 1960 to 2004, and farm productivity in 16 major agricultural states from 1964 to 2004. In 12 of the 16 states, researchers found that unusual weather increased the average total factor productivity by 11.4% — an additional source of growth that officials were partly attributing to policy, when it was in fact due to factors such as above-average rainfall.
Across all 16 states in the study period, when the researchers filtered out weather effects, growth was about 14% slower than calculations from USDA indexes.
"A portion of the [total factor productivity] change measured by USDA is due to weather shocks that are not influenced and cannot be controlled by economic or agricultural policies," said Alejandro Plastina, the lead author of the study, which was published March 15 in Agricultural Economics. "We need to remove that portion of TFP change due to weather shocks before using the data for economic analyses."
Plastina, an associate professor of economics at Iowa State University, told The Academic Times that "most previous studies simply measure TFP change, ignoring weather effects" entirely. But these effects could become even more pertinent as climate change leads to more extreme weather. Plastina and his colleagues developed a method to filter out the effect of weather shocks on measurements of productivity, and "future researchers can use the weather-filtered TFP to explore the drivers of weather-filtered TFP," he said.
For this study, Plastina and his co-authors calculated average weather from 1960 to 2004, using data on monthly precipitation and daily temperatures for areas of four square kilometers, aggregated at the state level. The researchers looked at 16 major agricultural states: California, Oregon, Washington, Iowa, Illinois, Indiana, Michigan, Missouri, Minnesota, Ohio, Wisconsin, Arkansas, Louisiana, Mississippi, Oklahoma and Texas. Whenever the rainfall and temperatures varied from the predicted weather based on the calculated averages, their model captured that information.
What they found was that "agricultural policies were less effective than previously thought," Plastina said. "In the economic literature, there is a long-term discussion about the rates of return to public investments in the agricultural sector, where the dominant view is that returns are extremely high, and much higher than public investments in other sectors of the economy."
Taking weather into consideration "would simply change the magnitude of the return on investment" when it comes to funding priorities such as international market development for agricultural products, research at land-grant universities and rural infrastructure, Plastina said.
As he and his co-authors wrote, "Given the importance of weather in production risk, and the fact that the vast majority of studies performing TFP decompositions do so without accounting for weather, this question seems particularly relevant and timely."
The study, "How weather affects the decomposition of total factor productivity in U.S. agriculture," published March 15 in Agricultural Economics, was authored by Alejandro Plastina and Sergio H. Lence, Iowa State University; and Ariel Ortiz‐Bobea, Cornell University.