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Farm-Level Data Use in Individual and Group Extension Settings. 2005 AAEA Organized Symposium Michael Langemeier Professor Kansas State University. Presentation Focus.
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Farm-Level Data Use in Individual and Group Extension Settings • 2005 AAEA Organized Symposium • Michael Langemeier • Professor • Kansas State University
Presentation Focus • This presentation will focus on the use of farm management association panel data for extension, teaching, and research purposes. • Farm management association data is used by farm management association members, farm management association economists, and in extension, teaching, and research programs.
Outline of Presentation • Individual Farm Level Use • Financial Performance Benchmarks • Applied Analysis • Competitive Advantage • Productivity
Individual Farm Level Use • Summary of annual data • Trend analysis • Three year summary of key production and financial variables • Five year summary of key financial performance benchmarks
Financial Performance Benchmarks • Key Measures • Profit Margin • Asset Turnover Ratio • Economic Total Expense Ratio • Labor and Asset Utilization
Kansas Farm Management Association (KFMA) Data • Farms with continuous data (924 farms) • 1995 to 2004 • 10-Year Averages: • VFP: 211,355 • NFI: 43,496 • Total Assets: 733,429
Profitability • Operating Profit Margin Ratio • (Net Farm Income + Interest – Unpaid Labor) / (Value of Farm Production) • Average: • (43,496 + 14,874 – 35,321 / (211,355) = 0.1091 • Top quartile: • OPMR = 0.2160
Financial Efficiency • Asset Turnover Ratio • (Value of Farm Production) / (Average Total Assets) • Measures the effectiveness of the farm in utilizing assets. • Average: • (211,355) / (733,429) = 0.288 • Top quartile: • ATR = 0.383
Financial Efficiency • Total Expense Ratio • Includes cash expenses and depreciation. • Economic Total Expense Ratio • Includes cash expenses, depreciation, and opportunity charges on unpaid labor and owned assets. • Average = 1.114 • Top Quartile = 0.955
Applied Analysis • Competitive Advantage • Productivity • Technical and Cost Efficiency • Financial Stress • Credit Rating • Crop Insurance
Applied Analysis: Competitive Advantage • Paper presented at the 2003 SAEA Meetings • Jeffery Morgan • Agricultural Loan Officer, Clyde, Kansas • Michael Langemeier • Professor, Kansas State University
Introduction • Neoclassical Theory • Profit opportunities are short-lived because it is easy to imitate other firms. • Firms are homogeneous except for scale. • Resource-Based Theory • Heterogeneity of resources. • Imperfect mobility of resources. • Some firms consistently earn above average profits.
Objective of Study • Examine sustained competitive advantage for a sample of Kansas farms. • Variability in per unit cost: • Weather • Managerial Ability
Methods • Nonparametric Efficiency Approach • Farm’s efficiency in each year is measured relative to the efficiency of other farms in that particular year. • Overall Efficiency • Technical Efficiency • Allocative Efficiency • Scale Efficiency
Methods • Overall Efficiency Categories • Above Average • Insignificant • Below Average • Farm Characteristics • Farm Size • Farm Type • Expense Ratios and Profitability
Methods • If uncontrollable factors such as weather are the primary factors that explain differences in the cost of production between farms, there will be very few farms with above average overall efficiency levels. • Resource based theory suggests that it is possible for a relatively large proportion of the farms to have a competitive advantage or disadvantage.
Kansas Farm Management Data • 224 Farms • Continuous data from 1982 to 2001 • Average gross farm income = $252,626 • 43 farms had a gross farm income below $100,000 • 16 farms had a gross farm income above $500,000
Kansas Farm Management Data • Inputs • Labor • Purchased Inputs • Capital • Outputs • Beef • Milk • Swine • Crops • Hay and Forage • Miscellaneous Income
Kansas Farm Management Data • Farm Characteristics • Gross Farm Income • Farm Type • Economic Total Expense Ratio • Profit Margin Ratio
Results • Overall Efficiency • Above Average: 0.7800 • Below Average: 0.4752 • Farm Type • Farms in top category had significantly higher proportions of income coming from dairy and swine production.
Results • Gross Farm Income • Above Average: $395,650 • Below Average: $147,103 • Only 2 of the 43 farms with GFI less than $100,000 were in the top category. • 10 of the 16 farms with GFI greater than $500,000 were in the top category.
Results • Economic Total Expense Ratio • Above Average: 1.0206 • Below Average: 1.2964 • Profit Margin Ratio • Above Average: 0.1864 • Below Average: -0.0260
Summary • 27% of the farms had a sustained competitive advantage • 34% of the farms had a sustained competitive disadvantage
Applied Analysis: Productivity • Work in Progress • Paul Clark • Graduate Student, Kansas State University • Michael Langemeier • Professor, Kansas State University
Introduction • Productivity measures are used to monitor individual firm and industry performance over time. • Panel data is needed to examine productivity differences among firms.
Objectives of Study • Examine productivity of individual Kansas farms. • Relate individual farm productivity to farm size. • Examine output and input bias.
Methods • Malmquist Productivity Indices • Productivity can be decomposed into technical change and efficiency change. • Technical change can be further decomposed into output bias, input bias, and the magnitude component.
Kansas Farm Management Data • 195 Farms • Continuous data from 1984-2003 • Focus on crop, beef, and crop/beef farms • Average gross farm income = $232,236 • 30 farms had a gross farm income below $100,000 • 10 farms had a gross farm income above $500,000
Kansas Farm Management Data • Inputs • Labor • Purchased Inputs • Capital • Outputs • Wheat • Feed Grains • Oilseeds • All Hay and Forage • Beef • Other Income
Results • On average, most of the productivity change was due to technical change rather than efficiency change. • Inefficient firms often do not “catch up” to efficient firms. • Productivity and Farm Size • Small Farms 1.0213 • Large Farms 1.0328
Results • Technical Change and Output Mix • Technical change was positively related to feed grain production. • Technical Change and Input Mix • Technical change was negatively related to labor use. • Technical change was positively related to purchased input and capital use.
Contact Information • Departmental Publications: • www.agmanager.info • E-mail: • mlange@agecon.ksu.edu
Financial Stress • Definition of Financial Stress • Negative Return on Equity • Net farm income minus unpaid labor is negative. • High Debt to Asset Ratio • Debt to asset ratio greater than 0.70.
Financial Stress, KFMA(1995 to 2004) • Percentage of Farms (10-Year Averages) • Negative Return on Equity = 52.90% • High Debt = 10.85% • Financially Stressed = 7.40%
Financial Stress, KFMA(1995 to 2004) • Percentage of Farms • No Financial Stress = 78.90% • Financially Stressed over 50% of Time = 4.44% • Financially Stressed every Year = 0.43% • No Debt = 3.25%
Labor Use and Efficiency • KFMA Data • Farms with continuous data (924 farms) • 1995 to 2004 • 10-Year Averages: • Number of Workers = 1.46 • Total Acres = 1,739 • VFP = 211,355 • VFP per Worker = 144,964