Comparison of Farm Program and Expected Yields for Ohio Corn Farmers

Similar documents
Price vs. Revenue Farm Safety Net Carl Zulauf, Professor, Department of Agricultural, Environmental and Development Economics; August 2012

Competitiveness of U.S. Wheat: the Role of Productivity

Fall Crop Outlook Webinar

1979 WHEAT AND FEED GRAIN SET ASIDE PROGRAM:

Summary and Benefits of ACRE. University of Illinois

ARC or PLC: an example for wheat

November variable Yield can


The Revenue Program Option in the 2008 U.S. Farm Bill: Evaluating Performance Characteristics of the ACRE Program

2008 FARM BILL: WITH FOCUS ON ACRE AND SURE

PRICE AND PROFIT: INVESTIGATING A CONUNDRUM. Carl R. Zulauf, Gary Schnitkey, and Carl T. Norden*

Comparing Current and 1970 Farm Prosperity: Production Response Overview: Analysis: World Production Response:

Crops Marketing and Management Update

FARM ECONOMICS Facts & Opinions

USDA Acreage & Stocks Report

Outline of Presentation

An Analysis of 1999 Gross Returns for Small Grains in North Dakota

Commodity Market Outlook

Self-Propelled Spraying: Machinery Ownership versus Custom Hire Michael Langemeier, Associate Director, Center for Commercial Agriculture

Illinois Crop Yield Database

Contracting Corn Silage Acres

1998 Double Crop Soybean Costs and Returns

AGRONOMY 375 EXAM II. November 7, There are 15 questions (plus a bonus question) worth a total of up to 100 points possible. Please be concise.

September 12, USDA World Supply and Demand Estimates

Full Season Soybeans Enterprise 1998 Costs and Returns

ACRE Sign-up Deadline June 1, 2010 Jim Hilker, Roger Betz, Dave Schweikhardt and Roy Black Michigan State University Extension May 13, 2010

Costs to Produce Corn and Soybeans in Illinois 2017

Corn and Soybean Stocks, Acreage, and Balance Sheet Implications

2007 U.S CORN PRODUCTION RISKS: WHAT DOES HISTORY TEACH US? Darrel Good and Scott Irwin May 17, 2007 MOBR 07-01

June 12, USDA World Supply and Demand Estimates

January 12, USDA World Supply and Demand Estimates

TRI-STATE FERTILIZER UPDATE

Result Demonstration Report

SOYBEANS: LARGE SUPPLIES CONFIRMED, BUT WHAT ABOUT 2005 PRODUCTION?

Empowering growth across the agriculture industry for 30 years. North Dakota Wheat Analysis 2018 prepared with

Ag Outlook Webinar. Chris Hurt, Professor, Department of Agricultural Economics

Emerging Issues: Uncertainty in U.S. Ag Policy and Trade. Ohio Soybean Association- August 29, 2018 Ben Brown

HAS PRICE BEHAVIOR OF MAJOR FARM PROGRAM CROPS CHANGED SINCE FAIR? Carl R. Zulauf, Matthew C. Roberts, and Abigail G. Boor* January 2005

Wheat Pricing Guide. David Kenyon and Katie Lucas

Analysis of the October 2010 USDA Crop Production & WASDE Reports

August 10, USDA World Supply and Demand Estimates

Key Findings. CAUV Value Projections for 2018

TOTAL $ PURCHASED INPUTS PRICE SEED $ LBS $45.00 $45.00 MANURE $ TON $21.60 $21.60 LIVESTOCK FAC & EQUIP $5.00 $5.

Kentucky Farm Business Management Program. Annual Summary Data

Economic Comparison of SDI and Center Pivots for Various Field Sizes

2009 Corn Yield Prospects Continue to Improve. Scott Irwin, Darrel Good, and Mike Tannura August 13, 2009 MOBR 09-04

IN-FIELD PROFITABILITY ASSESSMENT. Analyses & Tools to Aid Profitable In-Field Outcomes Suzanne Fey Data Analyst

Managing Your Farm in Challenging Times

Oral Statement before the United States Senate Committee on Agriculture, Nutrition, and Forestry. Hearing on the trade section of the farm bill

May 10, USDA World Supply and Demand Estimates

A Tax Incentive for Certified Seed: An Assessment

Profitability analysis of the experimental data By Marvin Batte

FDACS Contract No Deliverable Report #3: Corn Fertility Trials Report. January 12, 2016

ADVERSE IMPACTS OF DROUGHT ON CROPS AND CROP PRODUCERS IN THE WEST

Washington County Agriculture Profile

CHS. Midwest Cooperatives. Pre-Harvest Marketing Plan

Nutrient Use Efficiency: A Midwest Perspective

Diversified versus Specialized Swine and Grain Operations

Focus. Analyzing the Impact of Drought Conditions on Texas High Plains Agriculture

DELINEATION OF HIGH RISK FIELD AREAS FOR VARIABLE SOURCE N FERTILIZER APPLICATIONS TO OPTIMIZE CROP N USE EFFICIENCY

Crops Marketing and Management Update

Key Questions You Should Be Asking About Crop Program Decisions Carl Zulauf, Ohio State University, November 2014

Agricultural Policy Effects on Land Allocation. Allen M. Featherstone Terry L. Kastens Kansas State University

Post Harvest Marketing

An Analysis of Markets for High Oil Corn

CORN: PRODUCTION EXCEEDS EXPECTATIONS

BACKGROUND INFORMATION AND RESEARCH PROBLEM

2017 Ohio Farm Business Summary

2018 Illinois Society of Professional Farm Managers and Rural Appraisers Mid-Year Survey

c) What optimality condition defines the profit maximizing amount of the input to use? (Be brief and to the point.)

Cash Rental Rates for Iowa 2016 Survey

Using Enterprise Budgets to Compute Crop Breakeven Prices Michael Langemeier, Associate Director, Center for Commercial Agriculture

Commodity Market Outlook

Crops Marketing and Management Update

Testing for Yield Persistency: Is It Skill or is It Luck?

THE CURRENT STATE OF THE U.S. AGRICULTURAL ECONOMY

SOYBEANS: AN EARLY WEATHER MARKET

Crop Economics Outlook Gary Schnitkey University of Illinois

Crops Marketing and Management Update

LATE PLANTING DECISIONS WITH CROP INSURANCE: DECISION GUIDELINES FOR MICHIGAN FARMERS IN SPRING 2011

Appendix I Whole Farm Analysis Procedures and Measures

Commodity Market Outlook

Objectives: Background:

Ag Business Climate Outlook for 2017

Nitrogen Rate Recommendation System for Iowa Corn Production

AFPC. Climate Change Project Texas Representative Feedgrain Farms. Research Report 14-1 February Agricultural and Food Policy Center

2008 Farm Bill: Doug Yoder, Illinois Farm Bureau

Ohio Agricultural Production and Rural Infrastructure

SOYBEANS: SURPLUS GROWS, ACREAGE TO DECLINE

December 12, USDA World Supply and Demand Estimates

2004 ANNUAL REPORT Missouri Sustainable Agriculture Demonstration Award

IJF(Jv POLICY WORKING PAPER. EFFECTS OF DEBT AND FREEZING TARGET PRICES AFfER 1990 ON ECONOMIC VIABILITY OF REPRESENTATIVE CROP FARMS IN TEXAS

Soil Amendment and Foliar Application Trial 2016 Full Report

SplitN.AgClimate4U.org

Content. Introduction. Farm Decision-making: Simulation and Decision Tree Approach

EASTERN CORN BELT DELAYS CONTINUE, MORE FARM PROGRAM DETAILS

SOYBEANS: SMALLER STOCKS, MORE ACRES, AND EARLY WEATHER WORRIES

U.S. Farm Sector Profits

January 12, USDA World Supply and Demand Estimates

INSTRUCTIONS Farmer GAME Thanks for playing our challenge. Please read the following in order to understand the gameplay.

Transcription:

ESO 1954 f, ; ' l t ;. :, -'.) :,_;;cs L:)GY Comparison of Farm Program and Expected Yields for Ohio Corn Farmers. ;' -~ - by Sharon Thayer, Carl Zulauf, Gary Schnitkey and Lynn Forster* June 1992 * Research Associate, Associate Professor, Assistant Professor, and Professor; Department of Agricultural Economics and Rural Sociology, The Ohio State University. The authors appreciate the insightful comments of Dwight Harris and Luther Tweeten on an earlier draft of this paper.

I COMPARISON OF FARM PROGRAM AND EXPECTED YIELDS FOR omo CORN FARMERS Since 1986, the yields which determine government income deficiency payments to farmers have been frozen at 1981-1985 levels. Farm groups argue that these yields, usually referred to as program or Agricultural Stabilization and Conservation Service (ASCS) yields, should be updated to reflect the increase in yields since the early 1980's. On the other hand, concern exists that updating ASCS yields could significantly increase the cost of farm programs. To provide insights into these policy arguments, ASCS yields for com are compared with expected average com yields for a sample of Ohio farmers. Calculation of ASCS Yield Presently a farm's ASCS yield is calculated by averaging program yields for the years 1981 through 1985, after first eliminating the high and low program yields. The program yield for each year between 1981 and 1985 equals the average of the farm's proven or assigned yields for the five previous crop years. For example, the program yield for 1981 equals the average of the farm's proven or assigned yields for the 1976 through 1980 crops. Proven yield is based on a farm's actual yield as documented by grain slips, measured bins, and c~rtified or determined acres. If yields can not be documented (which is the usual

' case), a farmer's yield is assigned the average program yield for similar farms in the area as judged and established by the county ASCS committee. Data The data used for this study are taken from the 1990 Ohio Farm Longitudinal Household Survey. This survey collected information during the spring of 1991 from a randomly selected sample of approximately 1,000 Ohio farm households. The surveyed households were asked for the yields of their crops on a per acre basis, including (1) ASCS corn yield, (2) average corn yield expected for 1991, and (3) actual corn yield in 1990. Of the surveyed farm households, 461 harvested corn in 1990, provided information on expected yield, and reported that they had a corn base and yield established with ASCS. For these 461 farms, expected average yield in 1991 ranged from 60 to 210 bushels per acre, with an average of 123 bushels. In comparison, actual corn yield in 1990 for these farmers averaged 121 bushels per acre, the same as the average yield for the state of Ohio. ASCS com yield ranged from 68 to 165 bushels per acre, with an average of 110.8 bushels. According to the Ohio state ASCS office, the average ASCS yield for Ohio was 110.5 bushels in 1991. Thus, the averages for farmers analyzed in this study were similar to the comparable averages for Ohio. Two variables were calculated: (1) ASCS yield minus expected average yield in 1991 and (2) ASCS yield minus 1990 actual yield. Only the results for ASCS minus expected average yield are presented. This choice was made in part because the results are similar for the two calculated Y:anables. In addition, expected average yield is a more stable measure of production 2

I than actual yield because short run weather influences are removed. To illustrate this consideration, standard deviation, a measure of variation, was 24.8 bushels per acre for 1990 actual yield, but only 19.1 bushels per acre for 1991 expected yield. ASCS Versus Expected Yield Almost 60 percent of the farmers analyzed in this study had an ASCS yield which was at least five bushels lower than their expected yield (Graph 1). Included in this 60 percent were 16 percent who reported an ASCS yield at least 25 bushels below their expected yield. On the other hand, 19 percent of the farmers had an ASCS yield which exceeded expected yield by five or more bushels per acre. Thus, the difference between ASCS and expected yield varied substantially. Of the 461 farmers included in this study, 338 participated in the 1990 com program. If expected yield had been used instead of ASCS yield to determine 1990 income deficiency payments, 22.5% of the 338 farmers would have received lower payments while 66.6% would have received larger payments. Excluding consideration of payment limitations, average per farm payment would have increased from $8,025 to $8,768, or 9.3%. Who Wins? Who Loses? A key policy question is which farmers will win and which farmers will lose if ASCS yields are updated to reflect expected yields. Statistical analysis revealed that the answer to this question is strongly related to a farmer's expected yield. Specifically, for farms with an expected yi~ld less than 85 bushels per acre, ASCS yield averaged 20 bushels more than 3

' expected yield (Graph 2). In contrast, for farms with an expected yield which exceeded 145 bushels per acre, ASCS yield averaged 32 bushels less than expected yields. These yield differences imply that government payment per acre would increase 25. 6 percent for farms with expected yields greater than 145 bushels but would decrease 21.2 percent for farms with an expected yield less than 85 bushels. Two factors may explain the conclusion that farmers with higher expected yields would gain more from updating ASCS yields. First, farms with higher expected yields in 1991 may have experienced faster increases in their yields during the 1980s than farmers with lower expected yields. Second, the use of program yields on similar farms to establish ASCS yields if actual yields are not available may have created a more uniform set of ASCS yields than the actual yields of farms warrant. In other words, the use of yields other than actual yields may work to the advantage of farmers with lower yields but to the disadvantage of farmers with higher yields. Conclusions The majority of Ohio farmers in this study had an ASCS yield which was less than their expected yield, and thus would receive increased government income payments if ASCS yields were updated to reflect current yields. Not all Ohio farmers would benefit from updating ASCS yields. Approximately onefifth would experience a decline in their income deficiency payments. 4

The distributional impacts of updating ASCS yields vary significantly across farmers. Updating ASCS yields will benefit farmers with higher current yields, and hurt farmers with lower current yields. In the aggregate, updating ASCS yields to reflect current yields will increase deficiency payments to Ohio farmers by approximately 10 percent. This will translate into higher federal cost for farm programs. 5

GRAPH 1. DISTRIBUTION OF FARMERS BY DIFFERENCE BETWEEN ASCS AND EXPECTED YIELD ASCS MINUS EXPECTED OHIO, 19 9 1 YIELD (bu./ acre}-,------,------,----.---...-----.-------, greater than 15 5 lo 14 11.7% 4 to -4-5 lo -14 26.2% -15 lo -24 16.1 % -25 lo -34 less!hon -35 0 5 10 15 20 25 30 PERCENT OF FARMERS GRAPH 2. DIFFERENCE BETWEEN ASCS AND EXPECTED YIELD BY LEVEL OF EXPECTED YIELD.,,...... 0 0... :i.0 '-" 0...J 25 15 5 19.8 bu. 3.0 bu. OHIO, 1991 w ):: -5-+-------------,,-,:-.----- () -5.5 bu. w 0.. x w g:i -15 z Si: VJ ~-25-+------------------- <( -31.8 bu. -35-+---,-_-8-4--.--85 1_0_4...--10_5 1_25-,..-1-2-6---14-5-.---14_5_+ -; EXPECTED YIELD (bu./acre) 6