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MAST

Management, Analysis & Strategic Thinking

Kevin C. Dhuyvetter Terry L. Kastens Alicia Goheen Department of Agricultural Economics Kansas State University

What is MAST?

· Innovative farm and risk management educational program combining face-to-face workshops with distance learning · Offers depth not available in typical one- to two-day programs · On-campus sessions and distance modules

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Development of MAST

· Master of Agribusiness

­ Distance education degree for agribusiness professionals

· MAST at Kansas State University

­ First cohort 2002 ­ Ninety-eight participants have finished program

The MAST Target

· Audience

­ Progressive farm managers ­ Agricultural professionals supporting agriculture

· · · · Lenders Agricultural agents Farm managers Accountants

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The MAST Target

· Participant needs

­ Geographically isolated ­ Desire for more information than traditional extension program ­ Peer interaction

The MAST Target

· Participant Locations through Kansas

­ Also included: Indiana and Illinois

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The MAST Target

Principal occupation of MAST participants from 2002-2004

The MAST Target

· Reasons for participation

­ ­ ­ ­ ­ ­ ­ Better management skills Networking New tools Increased profits Strategic planning Generational transition planning Other

4

How MAST Works

· Eleven faculty members with various specialties · One program coordinator · Campus-wide support resources · Future-minded participants

How MAST Works

· Current cost: $850 (initially $750) · Partial to full scholarships available from FCS (Kansas Corn Commission first year) · Three hours undergraduate credit available

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How MAST Works

· Technology ­ Tegrity Software

­ Combining PowerPoint presentations with video and audio of instructor ­ Uploaded to website and burned on CD

How MAST Works

· Components

­ On-campus sessions ­ Distance learning modules

· PowerPoint presentations · Tegrity lectures

­ ­ ­ ­

Chat sessions Message boards E-mails Phone calls

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On-Campus Session One

· · · · · · Two-day introduction to the MAST program Train in distance education technology Introduce Excel spreadsheets Business Planning Goal Setting Build relationships among participants

Building Relationships

· Wildcat Farms Case Study

­ Team presentations ­ Preview tools and decision-making skills to come ­ Facilitates discussion between faculty and participants

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Modules

· Approximately 37 hours of video teaching · Approximately 1350 content slides · Updated as necessary by faculty to reflect current trends and new research information

Module One

· Land Ownership and Leasing (5.56 hrs)

­ ­ ­ ­ ­ ­ Introduction Land Values and Rent Land Investment Buying Land Agricultural Land Leasing Spreadsheets / Homework

8

· Today's value of a stream of future rents:

PVR = R1 R2 RT + + ,..., + 1 2 T (1 + i ) (1 + i ) (1 + i )

· Future rents based on growing today's rent:

PVR = R0 (1 + g )

1

(1 + i )

1

+

R0 (1 + g )

2

(1 + i )

2

+ ,..., +

R0 (1 + g )

T

(1 + i )

T

· Rents need adjusted for property tax and income tax; interest rate needs adjusted for income tax:

PVR =

( R0 - Ptx 0 ) ( 1 - Itx ) ( 1 + g )1 ( R 0 - Ptx 0 ) ( 1 - Itx ) ( 1 + g )2 + + , ..., 1 2 [1 + i ( 1 - Itx )] [1 + i ( 1 - Itx )]

+

( R 0 - Ptx 0 ) ( 1 - Itx ) ( 1 + g )T T [1 + i ( 1 - Itx )]

Returns to non-irrigated cropland by state 1951-2003

avg: non-ag growth= 1.6%; ag growth= 4.6%; rent= 5.3%; total= 11.5%

14% stock = 12.7% (9.1% gain, 3.6% div) 12% land = 11.5% 10% after-prop-tax rent percent 8% 6% 4% 2% 0% non-ag growth ag growth

39 states ranked by total returns to land

TX UT NM PA OK CA AZ KS IL OH NV NY MI LA FL WV IA SC VA OR NC IN NE WA ID WI CO AR MN MT SD KY ND TN WY MO AL MS GA

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Portion of Land Value Attributed to Agricultural (production and government payments)

Source: Kastens and Dhuyvetter

Percentage of Agricultural Value Attributed to Government Program Payments

Source: Kastens and Dhuyvetter

10

Estimated Reduction in Land Value with the Elimination of Government Programs

Source: Kastens and Dhuyvetter

Module Two

· Machinery Ownership and Leasing (4.95)

­ ­ ­ ­ ­ ­ ­ Introduction Projecting Machinery Costs Evaluating Machinery Investments Lease versus Purchase Decisions Economies of Size Machinery Cost Analysis Spreadsheets / Homework

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How important are farm machinery costs for Kansas farmers?

Kansas Farm Management Association Enterprise Analysis Nonirrigated Crops -- State Averages, 2001-2003

Corn 105 328 Sorghum 194 318 Wheat 327 585 Soybean 170 327 Alfalfa 57 103

Number of Farms Average Acres Costs, $ per Acre Seed Fertilizer Herb-Ins Crop Ins Machinery Other Land Interest Total Cost Machinery, %

Total Ac 1,660 Wtd Avg $13.62 17.57 13.61 3.59 60.30 17.17 24.94 13.78 $164.59 36.6%

$26.07 32.42 22.35 5.05 68.90 19.15 35.40 17.90 $227.24 30.3%

$8.76 20.12 18.78 3.08 53.39 15.90 17.39 12.52 $149.93 35.6%

$5.75 17.08 4.55 3.45 54.88 15.68 20.50 11.17 $133.05 41.2%

$21.69 3.86 16.93 3.98 62.21 17.93 25.31 14.83 $166.74 37.3%

$8.15 8.75 10.73 0.16 79.03 20.84 39.05 16.06 $182.76 43.2%

Note ­ A portion of interest cost should also be allocated to machinery costs Costs reflect operator's costs on owned and rented land

Machinery costs are highly variable across farms ...

Kansas Farm Management Association Enterprise Analysis Nonirrigated Crops -- State Averages, 2001-2003

Corn 105 481 306 196 Sorghum 194 432 313 208 Wheat 327 692 679 382 Soybean 170 443 310 228 Alfalfa 57 112 130 66 Total Ac 2,160 1,739 1,080 Wtd Avg $54.32 $60.73 $91.65 -$37.33 -40.7% $42.85 $51.68 $65.61 -$22.76 -34.7% $47.58 $49.26 $67.79 -$20.21 -29.8% $50.04 $60.38 $76.19 -$26.16 -34.3% $61.30 $76.77 $99.00 -$37.70 -38.1% $49.35 $55.76 $75.38 -$26.03 -34.5%

Number of Farms Average Acres High profit farms Mid profit farms Low profit farms Machinery Costs, $/acre High profit farms Mid profit farms Low profit farms High less low, $ High less low, %

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Relative custom rate ratio

2.5

Average = 1.306 (range -- 0.55 to 2.47)

2.0 Relative Custom Rate Ratio

Percent less than 1.0 = 23.6%

1.5

1.0

0.5

0.0 Farm Observation (n=182)

Machinery Decision Tools at www.agmanager.info

OwnCombine.xls

OwnBaler.xls

OwnSpray.xls

KSU-MachCost.xls

OwnTractor.xls

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Cost for whole baling operation, various balers

baler = var; wrap = var; purage = 0; purbales = 0; tradfreq = 1; T/year = var; mph = 6.50 swath = 29.0; T/acre/cut = 1.20; tractor:baler hrs ratio = 1.75; labor:tractor hrs ratio = 2.00

25 4x4 square 20 3x4 square 15 $/ton 10

5

round net wrap round twine

0 1000 2000 3000 4000 5000 6000 7000 Tons of hay baled per year

Matches approximately with custom rates in the 1500-2000 T/year range.

Module Three

· Financial Analysis (3.17 hrs)

­ ­ ­ ­ Enterprise Budgeting Financial Statements Financial Ratios Financial Planning

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Module Four

· Labor Economics and Management (2.78 hrs)

­ ­ ­ ­ ­ ­ Introduction Hard Communication Recruitment and Selection Orientation and Training Family Workforce Management Understanding the Legal Environment

Module Five

· Tax Management and Policy (4.20 hrs)

­ ­ ­ ­ ­ Current Farm Issues Special Issues Affecting Farmers Limited Liability Companies US Ag Policy Legal Issues in Leasing

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Module Six

· Risk Management (6.62 hrs)

­ ­ ­ ­ ­ ­ Basic Risk Concepts Measuring Risk Risk-Return Concepts Risk Analysis Tools Financial Risk Risk Transfer

available at www.agmanager.info

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Risk and Profit for basic insurance strategies, $/acre

brackets: {premium, profit}

noLDP noinsur LDP; noinsur CAT MPCI-65 MPCI-75 MPCI-85 RA-65 RA-75 RA-85 CRC-65 CRC-75 CRC-85 ($70) ($60) ($50) ($40) ($30) ($20) $/acre ($10) $0 worst yr in 10 avg year

{$0.00 $0.00} {$0.00 $2.16} {$0.00 $2.81} {$1.36 $4.12} {$2.65 $5.40} {$6.04 $5.86} {$1.62 $4.50} {$3.15 $6.01} {$7.14 $6.54} {$1.88 $4.86} {$3.65 $6.63} {$8.29 $7.25}

$10 $20

$30

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Risk and Profit for pricing & insurance strategies, $/acre

brackets: {premium, profit}

CRC-75 hedge 25 hedge 50 hedge 75 contract 25 contract 50 contract 75 puts 25 puts 50 puts 75 minpric 25 minpric 50 minpric 75 ($70) ($60) ($50) ($40) ($30) ($20) $/acre ($10) $0

{$3.65 $6.63} {$3.65 $6.40} {$3.65 $6.18} {$3.65 $5.95} {$3.65 $6.18}

worst yr in 10 avg year

{$3.65 $5.73} {$3.65 $5.28} {$3.65 $6.40} {$3.65 $6.18} {$3.65 $5.95} {$3.65 $5.95} {$3.65 $5.28} {$3.65 $4.60}

$10 $20

$30

Kansas Farm Management Association 2000 to 2700 farms 1973-1998

· · · · average ROA was 5.09% average interest rate was 10.9% std. dev. of the interest rate was 2.86% Correlation between ROA & int was -0.3

· a KFMA subsample: the most profitable half of the largest third (about 350-400 farms)

­ average ROA was 13.52% ­ std. dev. of ROA was 8.66%

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Risk and profit with leverage

Debt-to Average Asset Return on Ratio Equity Base Case: ROA = 13.52% std = 8.66% interest = 10.9% 0% 13.52% 20% 14.18% 40% 15.27% 60% 17.45% 80% 24.00%

ROE =

ROA - I +I 1 - D/A

Risk and profit with leverage

Debt-to Average Standard Asset Return on Deviation Ratio Equity of ROE Base Case: ROA = 13.52% std = 8.66% interest = 10.9% 0% 13.52% 8.66% 20% 14.18% 11.06% 40% 15.27% 15.12% 60% 17.45% 23.30% 80% 24.00% 47.99%

2

std(ROE) = var(ROE)

1 2 var(ROE) = var(ROA) + L var(I) - 2 L cov(ROA,I) 1- L

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Risk and profit with leverage

Probability of a Return on Equity Below Debt-to Average Standard 0% -5% -10% -25% Asset Return on Deviation Ratio Equity of ROE Base Case: ROA = 13.52% std = 8.66% interest = 10.9% 13.5% 8.7% 5.92% 1.62% 0.33% 0.00% 0% 13.52% 8.66% 14.2% 11.1% 10.00% 4.15% 1.44% 0.02% 20% 14.18% 11.06% 15.3% 15.1% 15.62% 9.00% 4.73% 0.39% 40% 15.27% 15.12% 17.5% 23.3% 22.69% 16.76% 11.94% 3.42% 60% 17.45% 23.30% 24.0% 48.0% 30.85% 27.28% 23.93% 15.36% 80% 24.00% 47.99%

Normal Distribution

Given a mean and standard deviation, and assuming a normal distribution, we can assign probabilities to various levels of return.

-2Std

68%

95%

Mean

30% 25% 20% 15% 10% 5% 0%

Expected profit (ROE) and risk (prob of -10% ROE) ROA is 13.52% profit risk

0%

20%

40%

60%

80%

Leverage (Debt/Assets ratio)

+2Std

+Std

-Std

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Expected profit (ROE) and risk (prob of -10% ROE) ROA is 5.09%

60% 50% 40% 30% 20% 10% 0% -10% -20% 0% 20% 40% 60% 80% Leverage (Debt/Assets ratio)

profit risk

Module Seven

· Marketing (4.87 hrs)

­ ­ ­ ­ ­ ­ ­ Introduction Futures and Options Grain Marketing Drivers Economics of Storage Value Based Marketing Alternative Products and Niche Marketing Marketing Plans

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Optional Module

· Analytical Tools (4.60 hrs)

­ ­ ­ ­ ­ ­ Overview and background for modeling Fitting lines to data (linear vs. quadratic model) Determining optimums (calculus vs. solver) Binary variables and interaction terms More regression examples Modeling issues and wrap-up

On Campus Session Two

· · · · Two-day, capstone event Participants begin using the concepts taught Envision and plan for the future Content

­ Opportunity Scoping ­ Strategic Thinking ­ Business Plan Development

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MAST Evaluation

· 98% participants recommend MAST to others · 100% participants believe MAST will have a positive effect on their bottom line

MAST Evaluation

· · · · Overall content 4.49 Overall quality of program 4.54. Worth the time invested in program 4.53 Worth the dollars invested in program 4.38 Helped to better understand competition 4.15 · Make more profitable decisions for business 4.44 · Make better risk management decisions 4.26

Scale: 1- Strongly Disagree 3- Neutral 5- Strongly Agree

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Participant Comments

"The importance of the distance learning format compared to an on-site class or local meeting can't be overstated. This style of learning for today's manager is convenient and timely. The real dividends will come in the future as I employ the tools I learned in the program and review the modules when needed." - Marvin Tischhauser Morris County, Kansas

Participant Comments

"If you're interested in better positioning your business, this program is for you. All the modules offered information that has been valuable to me and my customers. I would not hesitate to recommend the MAST program for all those associated with agriculture." - Hamilton Bock Wabaunsee County, Kansas

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Participant Comments

"The ability to learn at my own pace in my own home, is a favorable environment, as well as being able to research and explore other information in relation to the modules easily. The message board and chat room sessions were also very valuable for information sharing and peer interaction." - Justin Miller New Paris, Indiana

What We've Learned

· · · · · · Time commitment is an issue Technology challenges continue to exist Message board / chat room "voyeurs" No such things as a "typical student" Demand for college credit has been very low Distance education has been quite effective, but face-to-face interaction is also important

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Future of MAST...

· Expand to broader geographical region · Target other groups for cohorts (e.g., lenders) · Offer more additional "stand alone" modules (e.g., livestock specific issues) · Take the "show on the road"?

Questions?

http://www.agecon.ksu.edu/MAST/default.htm

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