Does the Commodity Program Payments in impact the value of Planted acres in the United States?

By Carl Zulauf, David Orden, Jonathan Coppess, Gary Schnitkey, and Nick Paulson

The empirical findings presented in this article raise the question of whether a foundation principle of United States829X085 commodity policy is valid, which suggests that historical base acres payments are sufficiently disconnected from planting decisions. The statistical confidence of PLC payment being linked to the change in acres of large acreage program crops recognized by the USDA (U. S.) has been 99% since the 2014 Farm Bill. S. T he Department of Agriculture determines the cost of production. There is the most convincing empirical evidence for peanuts and rice. The importance of the question raised by this empirical analysis is not the only factor considered

What is the backstory of Prior Farmdoc Daily Articles?

The analysis started with the observation that the variation in planted acres is the most reliable indicator of a crop’s yield profitability. A crop’s productive acres must be used for profitable purposes, as per farmers. The return of private markets to production is a crucial factor in the change in planted acres, as per economic principles. The correlation between private market return and change in acres was investigated in the study Feb. 6,2025. Farmdoc Daily covered the period associated with the present crop commodity programs of the U S. T he percent change in the acres of USDA cost of production crops, including barley, cotton, oats, peanuts and rice, as well as sorghum, soybeans or wheat, was found to account for only 44% of the percentage change from 2012-2013 to 2023-2024.

The  Feb. 14,2025. Farmdoc Daily investigated the impact of the ongoing drought in Arizona, California, Colorado, Nevada, New Mexico, Utah, and Wyoming on acres across the Colorado River Basin. In contrast to the other states, acres have decreased significantly in these regions. The most likely reason is the persistent drought that has impacted water availability and affordability. The removal of acres from the total acres in the United States helped to decrease the impact of drought, but only to 50%. This implies that a more comprehensive explanation of changes in United States acres between 2012-2013 and 2023-2024 would need to take into account variables such as private market return and drought in the states in Colorado River Basin

In this article, we explore the impact of government commodity program payments on the alteration in acres. Due to the emphasis on commodity programs, upland cotton is not a part of this analysis. The crop years of 2014 to 2017 (data Note 1) did not contain any program crops. The estimated regression equation is not significantly impacted by the removal of cotton. Both the regression in Figure 1 and the one in Table 2, which uses data from this Farmdoc Daily, have explanatory power that is equivalent Feb. 14,2025. Upland cotton was featured in Farmdoc Daily

As rice is classified differently among the two main data sources used in this article, its classification will be adjusted based on the number of rows and columns. Agricultural Statistics: USDA, National Applied Statistics Service (NASS) reports long-grains, medium-gravity, and short-crunch rice. The classification of rice into different types, including long-grain, Temperate Japonica, and medium-short-grid, is not yet established in current commodity programs. The latter categories are utilized by the USDA and FSA to report data. Although not part of this analysis, California is one of the states in the Colorado River Basin that grow almost exclusively Japonica rice. In the United States, cultivates long-grain rice as the primary crop, accounting for 93% of acres planted. California rice and Temperate Japonica rice share a significant amount of similarities. The decision was made to use “rice ex CA” (California) in calculations involving acres, net return, and cost of production, “rice exc Mo” (U. S. D ollars) using FSA program data, or “ice ex Canada” using data from both sources

Commodity Payments have been in existence Since the 2014 Farm Bill

The 2014 Farm Bill was the first time to authorize commodity programs for the period of 2013-2024. The primary initiatives have been ARC-CO (Agriculture Risk Coverage) and PLC (Price Loss Coverages). In Figure 2, the relationship between the average ARC-CO payment per arc of CO and the typical total economic cost per planted acre of a crop is presented. The ratio is also presented when PLC payment is utilized. The proportion is computed over the crop years of 2014-2022.12, as well as the years between 2012-2013 and 2023-2024. The difference between PLC’s payment-to-cost ratio per acre is significantly greater. The PLC range is 13 percentage points, with peanuts accounting for 13% and soybeans for zero. ARC-CO falls within the 2 percentage point (3). 1% for sorghum minus 1.1% for soybeans)

The Explanatory Power of Commodity Program Payments is the focus of another Regression analysis

Peanuts, rice ex Japonica, and sorghum have the highest PLC ratio in Figure 2, but they are all above the regression line of Figure 1. Peanuts and rice ex Japonica are more likely to grow acres, while sorghum is less affected by the private market return of the crop. The ARC-CO payment-to-cost ratio for sorghum is the highest, with peanuts coming in third. The data indicates that commodity program payments, particularly PLC, may be statistically linked to the percent change in acres from 2012-2013 to 2023-2024.

By incorporating the ARC-CO payment into private market return as an explanatory variable, the extrinsic power increases from 50% to 57% (regression 2, Table 1) and is dependent on PEG income. The statistical confidence level for this significant increase is significantly less than 75% based on an F-test (refer to Data Note 2). The explanatory power of private market return is increased to 83% by including PLC payment, as shown in regression 3, Table 1. The rise is substantial with 95% statistical confidence determined by an F-test (observe Data Note 2). The statistical confidence level of PLC payment and private market return is 99% positive for both. The correlation between increased private market return and higher PLC payment is found in the number of planted and prevent plant acres of crop in 2023-2024 compared to the 2012-2013 period. Two additional regressions estimated to add context to the regression results in Table 1 are presented in Data Note 3.

Policy Discussion

The conventional policy argument is supported by the fact that there is no statistically significant connection between ARC-CO payment and the change in acres from 2012-2013 to 2023-2024. The payment of less than 100% of production on historical base acres, as per regulations like ARC-CO and PLC, will have an adverse impact on the planted acres that are paid more than the current acres planted to the crop. The payment for a crop’s commodity is determined by historical base acres, which means that farmers will receive the same payment regardless of the type of crop they planted on the base acre in the current year. Farmers will make a rational decision to plant the crop with the highest private market return, which they would do in the absence of commodity payment

PLC payment is statistically correlated with the change in acres from 2012-2013 to 2023-2024 with 99% accuracy, unlike ARC-C O. T he small sample size may make this finding a statistical anomaly. The statistical significance of PLC payment is noteworthy. Furthermore, even after removing the peanuts (which are obviously an outlier observation), PLC is close to being significant at 89% statistical confidence (see Data Note 3). It is important to be cautious about dismissing empirical findings without delay

This warning is backed up by three additional points. Initially, the 2014 Farm Bill made it evident that peanuts and long-grain rice could receive more PLC payments on an ongoing basis than other program crops. The PLC statutory reference price for peanuts and long-grain rice was 4% and 3%, respectively, exceeding the Olympic average market year price from 2009 to 2013 (with the high price removed) (refer to Figure 3). The reference price for medium/short grain rice was 7% less than the Olympic average, making it the next highest. Only barley had a statutory reference price that was less than 17% of its Olympic average market price. From 2014-2020 (USDA, FSA), peanuts and long-grain rice were subject to a PLC payment for eight of the nine years. It took seven years for medium/short grain rice to receive payment. Wheat, six years later, was the second highest crop

The 2014 Farm Bill’s commodity programs saw a 49% increase in base acres and prevent plant acres for peanuts, as well as rice ex CA by 84% and more than the 2012-13 season. The increase in acres for two crops during the years 2012-2013 to 2023-2024 could have been due to the base acres not planted to that crop

Farmers may consider the return from planting a crop on acre basis to be the private market return and the payment from the commodity program, particularly when such payments are expected regularly. Figure 2 illustrates how the average PLC payment per base acre for peanuts, which is 13%, can result in a +7% return on investment. Peanuts ranks as the second most profitable crop, not the fourth (refer to first and third panels in Figure 5). The change transformed rice ex CA from runner up to most profitable crop, quadrupling its return. Rice ex CA and soybeans yield similar combined returns, but the ARC-CO payment did not affect crop profitability rank order

The modification in crop profitability ranking is significant because the aim of this examination is to clarify the change in acres observed since 2013. The analysis revealed that two of the three crops analyzed, peanuts and rice ex CA, had more acres in 2023-2024 than in 2012-2013. The third most profitable crop in the private market was soybeans

Figure 5 shows a regression relationship between the percent change in acres and the private market return plus PLC payment. The statistical confidence of the summed return coefficient, as shown in Figure 6, is 99% and holds great significance. In contrast to Figure 1, the explanatory power of private market return is higher at 72% (72%) compared to 50% (48%) and lower at 84% (83%) when considering PLC payment and private returns as independent variables (regression 3, Table 1)

Policy Implications

The most accurate gauge of a crop’s profitability is the variation in acres. The economic principles dictate that any change in acres must be linked to the private market return to produce the crop. The private market return is statistically significant, but it only accounts for approximately 50% of the change in acres of large acreage field crops since the current crop commodity programs were authorized

The statistical significance of change in acres and PLC payment per base acre is linked to this period. Based on this discovery, is there a correlation between the decision to plant and PLC payment?

This is a question, not an answer

The significance of PLC payment may be a statistical anomaly, particularly due to the limited number of observations in this analysis. The PLC payment may act as a proxy variable for variables that are not included in the analysis (see Data Note 4)

Nevertheless, PLC payment is significant with a statistical confidence of 99%. It is important to be cautious about dismissing empirical findings without delay

The matter of coupling is a crucial one. Farmer decisions can lead to a significant increase in program costs over time due to the increasing number of crops with higher yields. The Federal budget deficit is a significant concern, and this situation is not something to be concerned about. Commodity payments have crop-specific consequences that may impact reporting to the World Trade Organization

To sum up, it is necessary to conduct further research and evaluation on the compatibility of PLC payment with planting determinations

Policy options to decouple PLC payment from acreage decisions would include::

Eliminate PLC, leaving ARC-CO as the sole commodity program. According to the analysis, there is no statistical relationship between ARC-CO payment and change in acres. This finding aligns with the market-oriented setting of ARC-CO program parameters, which should theoretically reduce coupling

Importing crop-based adjustments to the PLC program would result in gradual downside flexibility. AP LC payment is applicable to a crop, as an illustration::

• Reduce the crop’s reference price by a percentage for the following year
• A certain percentage of the crop’s share of base acres that can be claimed as payment for next year should be decreased

To minimize the impact of PLC payments on planting decisions, a cap of one percent of the US per acre cost of production is recommended for all registered operators

Data Note 1: Cotton

The 2014 Farm Bill did not cover cotton as a covered commodity, largely due to Brazil’s successful lawsuit against US cotton support programs in retaliation. Starting with the 2018 crop year, Congress declared seed cotton as a program crop

Data Note 2: F-Ratios

The F-ratio of the increase in explanatory power of ARC-CO in regression 2 is 0.80. For a 75% statistical confidence, the F-ratio test level is 1.69. The F-ratio for the increase in PLC’s explanatory power is 10 in regression 3.11.95% statistical confidence is obtained when the F-ratio test shows a value of 6.61.

Data Note 3: Additional Regressions

The first regression in Table 2 relies solely on PLC as the explanation factor. Regression 4 Table 2 reveals that the percentage of PLC payment accounts for 47% of the percent change in acres. The private market return’s explanatory power is the only variable that can be explained, and it is nearly identical to Figure 1. Peanuts are excluded from regression 2 in Table 1. The objective is to determine the impact of peanuts on regression figures. Peanuts is the most distant from the regression line in Figure 1. The private market’s profitability is a crucial factor to consider (refer to Regression 5, Table 2). PLC’s statistical confidence drops to 89%, which is just below the lowest commonly-used test level of 90%. The explanatory power without peanuts is not as high as the 83% for regression 3, but it still reaches 78%

Generic Base units (Acres) are the focus of data Note 4.

The 2014 Farm Bill’s generic base program is a potential unaccounted variable. Due to cotton’s inability to receive payments under the commodity program, Congress changed upland cotton base acres to generic base acre acres. ARC-CO or PLC payments were made to farmers who chose to plant a program crop on generic base acres. Seed cotton was designated as a program crop by Congress for the 2018 crop year, ending the generic base for that year

The use of a generic base payment on planted acres has been linked to an increase in acres planted to program crops, particularly peanuts, during the 2014-2017 crop years April 13,2017.  and  May 18,2017.  Farmdoc Daily). The generic base program’s termination during the 2017 crop year and the payment made to base acres should have lessened the impact on planted acres by 2023. Nonetheless, there is a potential correlation that should be taken into account

Does the Commodity Program Payments in impact the value of Planted acres in the United States? Was originally published by Farmdoc