4th Quarter 2011 | 26(4)
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Eric Wailes, Eddie Chavez, Diana Danforth, Bruce Ahrendsen, and Bruce Dixon
JEL Classification Code: Q12, Q18
Keywords: Adjusted Gross Income, Commodity Payments, Eligibility, Means Test
U.S. government farm commodity program funding is being targeted for reduction to help decrease the federal budget deficit. While commodity program payments are mandatory, program funding can be altered annually through the fiscal year appropriations. Toward that end, Congress has initiated a review of the current legislation which will expire in 2012 (Harwood, 2009). Currently, forces influencing the review include the burgeoning federal budget deficit, historically high but volatile farm commodity prices, and agricultural trade agreements which seek to reduce trade distortions (Chavez and Wailes, 2011). To help reduce government expenditures, capping eligibility using a means test for commodity program payments was used in both the 2002 and 2008 farm bills and may be one of the items Congress looks at to reduce farm commodity program expenditures. This paper examines the impact of limiting eligibility to recipients who have an Adjusted Gross Income (AGI) of more than $250,000.
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Adjusted Gross Income and Government Program Payments
In the United States, government farm program payments are an important component of income for farm businesses. For the period 2000-2009, the government spent an average of $10.84 billion annually on various commodity support programs such as commodity payments, marketing loans, counter-cyclical payments, ACRE payments and crop market loss assistance (FAPRI-MU, 2010). Means testing income for eligibility for farm program payments became effective with the passage of the 2002 Farm Security and Rural Investment Act. Eligibility was to be denied to an individual taxable entity with average adjusted gross income (AGI) over $2.5 million for the previous three taxable years, with an exception granted for operations with 75% or more of the average AGI from farming, ranching or forestry. The Food, Conservation and Energy Act of 2008 further tightened eligibility limits. First, it separated AGI into two components—farm AGI and nonfarm AGI. The eligibility limit on farm AGI is $750 thousand and on nonfarm AGI, $500 thousand. Congress may seek to lower the current income eligibility cap for commodity program payments to reduce federal expenditures. Using 2004 IRS tax data and Agricultural and Resource Management Survey (ARMS) data, Durst (2007) analyzed the effects of a $200,000 AGI eligibility cap on 2004 farm program payments. His results indicated that a $200,000 AGI cap on eligibility would have affected an estimated 1.5% of all farm operator households. Qiu and Goodwin (2011) analyzed separate limits for farm AGI and non-farm AGI at $200,000 and reported results by commodity and region. They found that current limits and the $200,000 limits had the most significant impact on rice and cotton as percentages of number of producers and acreage affected. Total impact, however, was found to be greatest on corn, soybean and wheat producers because of the much larger acreages planted to these crops.
Imposing a $250,000 Cap on AGI
The present study focuses on analyzing the impact on recipients of government farm program payments that results from imposing a $250,000 cap on combined farm and non-farm AGI. This proposed cap failed as an amendment to the Fiscal Year 2012 House Agriculture Appropriations Bill submitted by Rep. Flake (R-AZ) (House Appropriations Committee, 2011). While the amendment failed, efforts to reduce the federal budget deficit will persist, including reduction of farm program spending through means testing.
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For this study, data were obtained for the three-year period 2007-2009 from the ARMS, conducted by USDA’s Economic Research Service, (ERS) and National Agricultural Statistics Service, (NASS). A limit of $250,000 or less in AGI was used as the eligibility criterion for receiving commodity program payments.
AGI is defined as net farm income plus off-farm income with capital gains minus adjustments. Adjustments are allowable deductions, including health and dental insurance costs, out-of-pocket health/medical expenses, contribution to retirement/pension plans, and other contributions such as alimony, child support, and charitable donations. Commodity program payments are defined as direct government payments minus conservation payments. Thus, the full farm population is divided into two groups based on AGI: 1) Those with AGI equal to or less than $250,000, and 2) those with AGI greater than $250,000. Because IRS tax data was not available, the estimates of this study are upper limits, since we have assumed the term “farm operator” to be an individual taxable entity.
In this study, the appropriations bill amendment offered by Rep. Flake of Arizona is interpreted to mean that those farm operators with AGI greater than $250,000 would be considered ineligible for commodity farm program payments. These payments are described in section 1001D(b)(1)(C) of the Food Security Act of 1985 (7 U.S.C. 1308-3a(b)(1)(C)). The program payment eligibility criterion for the current crop year is established based on the annual average of the three-year period AGI preceding the previous crop year. The three-year annual average criterion is similar to the means test formulation currently in effect as mandated by the 2002 and 2008 Farm Bills. For example, the eligibility for 2011 is based on the annual average AGI for the three-year period 2007-2009. Since the latest ARMS data available to the authors are for 2009, it is not possible to compare our results with actual payments for 2011. Thus, the annual average payments for the three-year period 2007-2009 are used to estimate the 2011 payments for ineligible farm operators, which become the estimated potential government savings for 2011.
The results are presented in Tables 1 through 4. Table 1 shows the average number of farm operators by AGI group for the three-year period of 2007-2009—which is used to establish payment limit eligibility for crop year 2011—by production specialty. Production specialty in the ARMS data set is determined by the dominant crop or livestock enterprise by income source. Table 2 shows the commodity payments received by U.S. farm operators with government program payments by AGI group for the three-year eligibility period of 2007-2009 by production specialty. Tables 3 and 4 show the same information for average farm numbers and average payments received by state. All farm numbers and commodity payment levels are estimates based on the ARMS data and the expansion factors provided in the ARMS data set. To preserve clarity, we do not preface each number below with “estimated” but the figures are estimates.
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For the three-year period 2007-2009, Table 1 shows that an annual average of 840,178 U.S. farm operators received government farm program payments of which 763,592—or 90.9%—had average annual AGI equal to or less than $250,000 and 76,586—or 9.1%—had average annual AGI greater than $250,000.
Of the annual average number of farms receiving government farm program payments over the same period, 560,478 were crop farms—66.7%—and 279,700 were livestock farms—33.3%. For crops, 58,903—10.5%—had AGI greater than $250,000 while for livestock, 17,682—6.3%—had AGI greater than $250,000.
On the basis of production specialty, Table 1 shows that the largest percent shares of farm operators with AGI greater than $250,000 were rice—27.7%, cotton—24.4%, hogs—21.6%, corn—18.8%, and general cash grain—15.8%. The lowest value was for tobacco at 3.8%. If the $250,000 eligibility AGI cap had been implemented for 2011, 9.1% of all farm operators would be affected.
Table 2 shows that the annual average commodity program payments for all farm operators with AGI equal to or less than $250,000 was $5.45 billion—70.7%—while the annual average commodity program payments for farm operators with AGI greater than $250,000 totaled $2.26 billion—29.3%. By production specialty, the largest annual average percent shares of commodity program payments for farms with AGI greater than $250,000 were to farms dominated by cotton—46.6%, hogs—41.5%, corn—39.2%, poultry—37.6%, and general cash grain—36.7%. The lowest value was for farms with mostly beef cattle—13.7%. The top dollar recipients of commodity program payments for farms with AGI over $250,000 were to those dominated by corn—$628.0 million, general cash grain—$402.3 million, general crops—$206.0 million, cotton—$191.4 million, and wheat—$134.1 million.
Ignoring tobacco because of the buyout program, the top dollar recipients of commodity program payments per farm operator with AGI over $250,000, were farms with large portions of cotton—$107,104, peanuts—$86,113, rice—$70,475, and grain sorghum—$53,151. If the $250,000 eligibility cap had been implemented for 2011, the potential government savings for crop year 2011 would have been $2.26 billion from all farm operators—of which $1.90 billion—84.2%—would come from crop farms, and $355.6 million—15.8%—would come from livestock farms.
The average numbers of farms by state by AGI group are shown in Table 3. The percent of farm operators with AGI greater than $250,000 was highest for California—22.6%, Arizona—15.1%, South Dakota—15.1%, Illinois—14.6%, and Nebraska—13.7%. Alabama had the lowest value, at 3.2%.
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Table 4 presents the commodity program payments received by state by AGI group. On an annual average basis, the top ten recipient states of commodity program payments for farms with AGI over $250,000 were Texas—$199.0 million, Iowa—$178.0 million, Illinois—$161.7 million, North Dakota—$146.1 million, Minnesota—$131.6 million, Nebraska—$106.7 million, North Carolina—$103.3 million, Arkansas—$100.2 million, California—$97.9 million, and Indiana—$87.6 million. If these payments were eliminated, these ten states would account for 58.1% of the potential government commodity program savings.
On a per farm operator basis, the top recipients of commodity program payments for farms with AGI over $250,000 were in Arizona—$113,677, North Carolina—$93,391, Arkansas—$91,104, Florida—$60,502, California—$51,608, and Texas—$50,928. Nevada and Utah received the lowest average payments of $11,738.
If the $250,000 AGI limit were effective, the percent loss of program payments would be highest for North Dakota—44.8%, followed by Arkansas—40.6%, California—39.3%, Indiana—39.1%, and North Carolina—36.2%.
During the FY 2012 agricultural appropriations markup an attempt was made to restrict commodity program payment eligibility even more than under the law existing at that time. A 2012 appropriations bill amendment which came very close to being adopted would have made an individual or taxable entity with a combined AGI greater than $250 thousand ineligible for commodity program payments. This study estimates the upper limit of the potential budget savings and distributional impacts by state and commodity had this more restrictive eligibility means test been applied in 2011. Since access to actual tax returns used to determine cap eligibility was not available this upper limit was used. Based on the ARMS data set, an estimated 9.1% of all farms—10.5% of crop farms, and 6.3% of livestock farms—would have been ineligible to receive commodity program payments under the proposal. Estimated budget savings in 2011 would be $2.3 billion from all farms. Corn farms would account for the largest annual savings of $628 million. Ten states would account for 58% of savings in 2011. The percent loss of total commodity program payments to farmers by state would have been largest for North Dakota—44.8% and Arkansas—40.6% and smallest for Nevada/Utah—about 10%.
This analysis shows that $2.3 billion in annual expenditure savings could be achieved potentially by lowering the eligibility cap on current commodity program payments to $250,000 of AGI. However, the distribution of these impacts is far from uniform when viewed by crop and by State. Some states and commodities will experience disproportional reductions in payments. As the debate continues on how best to reduce the federal deficit by reformulating farm policy, distributional impacts of proposed policy changes as presented here need to be considered.
For More Information
Chavez, Eddie C. and Eric J. Wailes. 2011. Analysis of U.S. rice policy in a global stochastic framework. Paper presented at the Southern Agricultural Economics Association Annual Meeting, Corpus Christi, TX, February 5-8. Available at: http://ageconsearch.umn.edu
Durst, Ron L. 2007. Effects of reducing the income cap on eligibility for farm program payments. EIB-27. U.S. Dept. of Agriculture, Econ. Res. Serv. September 2007. Available at: http://ageconsearch.umn.edu/bitstream/59027/2/eib27.pdf
FAPRI-MU. 2010. Crop insurance: background statistics on participation and results. FAPRI-MU report #10-10. Available at: http://www.fapri.missouri.edu/outreach/publications/2010/FAPRI_MU_Report_10_10.pdf
Food Security Act of 1985 (7 U.S.C. 1308-3a(b)(1)(C)). Section 1001D(b)(1)(C).
Harwood, Joy. 2009. An overview of the U.S. agricultural economy and the 2008 farm bill. Agricultural and Resource Economics Review 38(1) 8-17.
House Appropriations Committee. 2011. Summary: fiscal year 2012 agriculture appropriations bill. June 13, 2011. Available at: http://appropriations.house.gov/UploadedFiles/6.13.11_FY_12_Agriculture_Conference_Summary.pdf
Qiu, Feng and Barry K. Goodwin. 2011. The implications of binding farm program payment limits associated with income means testing. Poster presented at the Agricultural and Applied Economics Association Annual Meeting, Pittsburgh, PA, July 24-26. Available at: http://ageconsearch.umn.edu/bitstream/103733/2/AAEAPoster_MeansTest_201107.pdf
U.S.Department of Agriculture, Farm Service Agency. 2009. fact sheet. average adjusted gross income 2009 and subsequent crop years. March 2009.
Eric Wailes (email@example.com) is Distinguished Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, Arkansas. Eddie Chavez (firstname.lastname@example.org) is Program Associate, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, Arkansas. Diana Danforth (email@example.com, is a Senior Program Associate, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, Arkansas. Bruce Ahrendsen (firstname.lastname@example.org) is Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, Arkansas. Bruce Dixon (email@example.com) is Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, Arkansas. This study was funded in part by the Arkansas Rice Research and Promotion Board, the Arkansas Soybean Research Board, AgHeritage Farm Credit Services, and Farm Credit Midsouth
The views expressed are those of the authors and do not necessarily reflect the positions of the Federal Reserve Bank of Kansas City, the Federal Reserve System, or Purdue University.
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